Handbook of Cultural Economics [3 ed.] 2019954483, 9781788975803, 9781788975797

Table of contents :
Front Matter
Copyright
Contents
List of contributors
Preface
Introduction
1 Application of welfare economics to the arts
2 Art auctions
3 Art dealers
4 Artificial intelligence
5 Artists’ labour markets
6 Artists’ resale rights
7 Artists’ rights
8 Broadcasting
9 Business models
10 Contingent valuation
11 Contract theory and information goods
12 Copyright
13 Cost of production
14 Creative industries
15 Creativity
16 Criticism
17 Crowdfunding
18 Cultural capital
19 Cultural districts
20 Cultural diversity
21 Cultural entrepreneurship
22 Cultural statistics
23 Cultural value
24 Demand
25 Digital piracy
26 Digitization in the cultural industries
27 Economic impact of the arts
28 Event cinema
29 Festivals
30 Google Trends data
31 Heritage
32 Information goods
33 Intangible cultural heritage
34 Intermediaries
35 International trade
36 Marketing the arts
37 Media economics and regulation
38 Motion-picture industry
39 Museums
40 Music industry
41 Music publishing
42 Non-profit organizations
43 Orchestras
44 Participation
45 Performance indicators
46 Performing arts
47 Platforms
48 Political economy
49 Pricing the arts
50 Public support
51 Publishing
52 Ratings, reviews and recommendations
53 Regulation of heritage
54 Superstars
55 Tax concessions
56 Theatre
57 Video game industry
58 Welfare economics
Index

Citation preview

HANDBOOK OF CULTURAL ECONOMICS, THIRD EDITION

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Handbook of Cultural Economics, Third Edition

Edited by

Ruth Towse Professor of Economics of Creative Industries, CIPPM, Bournemouth University and CREATe Fellow in Cultural Economics, University of Glasgow, UK

Trilce Navarrete Hernández Lecturer in Cultural Economics, Erasmus University Rotterdam, the Netherlands

Cheltenham, UK • Northampton, MA, USA

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© Ruth Towse and Trilce Navarrete Hernández 2020 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Chapter 19 (‘Cultural districts’/Mariangela Lavanga) is Open Access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Published by Edward Elgar Publishing Limited The Lypiatts 15 Lansdown Road Cheltenham Glos GL50 2JA UK Edward Elgar Publishing, Inc. William Pratt House 9 Dewey Court Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library Library of Congress Control Number: 2019954483 This book is available electronically in the Economics subject collection DOI 10.4337/9781788975803

ISBN 978 1 78897 579 7 (cased) ISBN 978 1 78897 580 3 (eBook) Typeset by Servis Filmsetting Ltd, Stockport, Cheshire

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Contents List of contributorsix Prefacexi Introduction1 Ruth Towse and Trilce Navarrete Hernández  1 Application of welfare economics to the arts William J. Baumol

9

 2 Art auctions Orley Ashenfelter and Kathryn Graddy

19

 3 Art dealers Olav Velthuis

29

 4 Artificial intelligence Joëlle Farchy and Juliette Denis

38

 5 Artists’ labour markets Trine Bille

46

 6 Artists’ resale rights Victor Ginsburgh and Clare McAndrew

56

 7 Artists’ rights Michael Rushton

66

 8 Broadcasting72 Glenn Withers  9 Business models Pierre-Jean Benghozi

82

10 Contingent valuation Tiziana Cuccia

95

11 Contract theory and information goods Richard Watt

106

12 Copyright116 William M. Landes 13 Cost of production Víctor Fernández-Blanco and Juan Prieto-Rodríguez

129

14 Creative industries Ruth Towse

137

v

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vi  Handbook of cultural economics 15 Creativity145 Karol Jan Borowiecki 16 Criticism154 Samuel Cameron 17 Crowdfunding158 Carolina Dalla Chiesa and Christian Handke 18 Cultural capital David Throsby

168

19 Cultural districts Mariangela Lavanga

174

20 Cultural diversity Heritiana Ranaivoson

183

21 Cultural entrepreneurship Mark Blaug and Ruth Towse

192

22 Cultural statistics David Throsby

197

23 Cultural value Jen D. Snowball

206

24 Demand216 Jordi McKenzie and Sunny Y. Shin 25 Digital piracy Jordi McKenzie

228

26 Digitization in the cultural industries Joel Waldfogel

235

27 Economic impact of the arts Bruce A. Seaman

241

28 Event cinema Allègre L. Hadida

254

29 Festivals262 Bruno S. Frey 30 Google Trends data Olivier Gergaud and Victor Ginsburgh

266

31 Heritage279 Françoise Benhamou 32 Information goods Michael Hutter

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287

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Contents  vii 33 Intangible cultural heritage Tiziana Cuccia

294

34 Intermediaries304 Paolo Di Caro, Luigi Di Gaetano and Isidoro Mazza 35 International trade Günther G. Schulze

311

36 Marketing the arts François Colbert

320

37 Media economics and regulation Gillian Doyle

329

38 Motion-picture industry Darlene C. Chisholm and Yu-Hsi Liu

339

39 Museums349 Víctor Fernández-Blanco and Juan Prieto-Rodríguez 40 Music industry Christian Handke

358

41 Music publishing Ruth Towse

371

42 Non-profit organizations Dick Netzer (updated by Bruce A. Seaman)

379

43 Orchestras392 Luis César Herrero-Prieto and Mafalda Gómez-Vega 44 Participation399 Victoria Ateca-Amestoy 45 Performance indicators Trilce Navarrete Hernández

408

46 Performing arts Ruth Towse

415

47 Platforms421 Maya Bacache-Beauvallet and Marc Bourreau 48 Political economy Isidoro Mazza

430

49 Pricing the arts Michael Rushton

441

50 Public support Bruno S. Frey

449

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viii  Handbook of cultural economics 51 Publishing457 Trilce Navarrete Hernández 52 Ratings, reviews and recommendations Paul Belleflamme and Martin Peitz

466

53 Regulation of heritage Ilde Rizzo

474

54 Superstars485 Günther G. Schulze 55 Tax concessions John W. O’Hagan

494

56 Theatre503 Marta Zieba 57 Video game industry Tylor Orme

514

58 Welfare economics Mark Blaug

520

Index527

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Contributors Orley Ashenfelter, Princeton University and NBER, USA. Victoria Ateca-Amestoy, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Spain. Maya Bacache-Beauvallet, Institut Polytechnique de Paris, France. William J. Baumol (deceased), formerly with New York University and Princeton University, USA. Paul Belleflamme, Université catholique de Louvain, Belgium. Pierre-Jean Benghozi, CNRS-Polytechnique, Paris, France and GSEM, University of Geneva, Switzerland. Françoise Benhamou, Université Paris 13, France. Trine Bille, Copenhagen Business School, Denmark. Mark Blaug (deceased), formerly University of Amsterdam, the Netherlands. Karol Jan Borowiecki, University of Southern Denmark, Denmark. Marc Bourreau, Institut Polytechnique de Paris, France. Samuel Cameron, formerly of the University of Bradford, UK. Darlene C. Chisholm, Suffolk University, USA. François Colbert, HEC Montréal, Canada. Tiziana Cuccia, University of Catania, Italy. Carolina Dalla Chiesa, Erasmus University Rotterdam, the Netherlands. Juliette Denis, University of Paris 1 Panthéon Sorbonne, Paris. Paolo Di Caro, Italian Ministry of Economy and Finance, Italy. Luigi Di Gaetano, Italian Competition Authority, Rome, Italy. Gillian Doyle, University of Glasgow, Scotland. Joëlle Farchy, University of Paris 1 Panthéon Sorbonne, Paris. Víctor Fernández-Blanco, Universidad de Oviedo, Spain. Bruno S. Frey, University of Basel and CREMA, Zurich, Switzerland. Olivier Gergaud, Kedge Business School, France. Victor Ginsburgh, ECARES, Université libre de Bruxelles, Belgium. Mafalda Gómez-Vega, Universidad de Valladolid, Spain. ix

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x  Handbook of cultural economics Kathryn Graddy, Brandeis University and CEPR, USA. Allègre L. Hadida, University of Cambridge, UK. Christian Handke, Erasmus University Rotterdam, the Netherlands. Luis César Herrero-Prieto, Universidad de Valladolid, Spain. Michael Hutter, WZB Berlin Social Science Center, Germany. William M. Landes, University of Chicago, USA. Mariangela Lavanga, Erasmus University Rotterdam, the Netherlands. Yu-Hsi Liu, Shih-Hsin University, Taiwan. Isidoro Mazza, University of Catania, Italy. Clare McAndrew, Arts Economics, Ireland. Jordi McKenzie, Macquarie University, Australia. Trilce Navarrete Hernández, Erasmus University Rotterdam, the Netherlands. Dick Netzer (deceased), formerly New York University, USA. John W. O’Hagan, Trinity College Dublin, Ireland. Tylor Orme, Emerson College, USA. Martin Peitz, University of Mannheim, Germany. Juan Prieto-Rodríguez, Universidad de Oviedo, Spain. Heritiana Ranaivoson, Vrije Universiteit Brussel, Belgium. Ilde Rizzo, University of Catania, Italy. Michael Rushton, Indiana University, USA. Günther G. Schulze, University of Freiburg, Germany. Bruce A. Seaman, Georgia State University, USA. Sunny Y. Shin, Macquarie University, Australia. Jen D. Snowball, Rhodes University, South Africa. David Throsby, Macquarie University, Australia. Ruth Towse, Bournemouth University, UK. Olav Velthuis, University of Amsterdam, the Netherlands. Joel Waldfogel, University of Minnesota, USA. Richard Watt, University of Canterbury, New Zealand. Glenn Withers, Australian National University and University of New South Wales Canberra, Australia. Marta Zieba, University of Limerick, Ireland.

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Preface A new edition of a book such as this is a time also to take stock of changes in the content. What is now apparent that was already present but not yet fully absorbed into cultural economics in 2010 when the second edition was being assembled is the full impact of digitisation in the creative industries, ranging from art markets to the performing arts, video games to museums. Its effects are found in participation, demand, business models and new modes of supply. Relatively few of the underlying goods have changed, but access and pricing have. These changes are, however, part of a wider change in the economic theory adopted to analyse them. What is now named platform economics has invaded the cultural sector with two implications for this book: one is that many authors have embraced these changes in cultural economics; the other is that economists who may previously not have been especially interested in cultural economics now apply the theory to the creative industries. This expands the outlook of cultural economics and emphasises its integration with mainstream economics. This edition has been edited jointly and reflects our shared interests in the effects of digitisation and of its implications for copyright, cultural policy and management in the creative industries. As editors, we see grasping these as fundamental for both the viability of the traditional arts and heritage and for newer art forms. The growth, for instance, of the video game industry has led to employment for creative artists on a probably unprecedented level: look at the website of any video game company and (at the time of writing) almost all of them has an advertisement for artists with computer skills. We perceive increasing overlap between art forms and artists’ labour markets, calling for multi-skilled and talented creators. Some industries have been more alert than others in adapting to the required changes, as the content of this volume demonstrates. As editors, we encouraged authors of former chapters to take some of this into account when revising, and our choice of new authors reflects our perceptions of these issues. As ever, we are most grateful for the contributions of all the authors and their willingness to take part in what is a collaborative venture. As in previous editions, the book is laid out encyclopedia style by alphabetic order of the rather cryptic titles we have imposed on the chapters (and their authors). All chapters except three have been revised or are newly written; the exceptions are the ‘classic’ Chapters 1 and 58 on welfare economics by Baumol and Blaug, respectively, which have been carried over from the second edition, and Chapter 42 by Netzer, on non-profit organisations, which has been most generously revised by Bruce A. Seaman. All chapters have recommendations for further reading and the editors have cross-referenced chapters within the book.

xi

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Introduction

Ruth Towse and Trilce Navarrete Hernández

Over the past sixty or so years, cultural economics has established itself as a field of study that is relevant to arts organisations, creative industries, cultural policy and, increasingly, to economic policy for growth and development. It began modestly in the 1960s with an interest in the economic analysis of the finance of museums and the live performing arts, and has spread and evolved into a broader analysis of the cultural or creative industries and their role in the creative economy. This economy is now dominated by the digital revolution in the use of knowledge and information, and its distribution via the Internet; it is shaped by the need to foster creativity and to understand the production and consumption of creative goods and services. While some economists hold that the digital economy does not call for a new kind of economics, nevertheless, new concepts have been adopted with the title ‘platform economics’ and extended universally. Cultural economics has long wrestled with topics to which ordinary economics did not seem fully applicable (for instance, understanding economic incentives for artists and other creators) and has accordingly developed an understanding of public policy issues concerning the development and support of the creative industries. Cultural economics now offers expertise in the analysis of markets for a wide range of creative products, ranging from art to digital television, which were reflected in the topics covered in the second edition of this Handbook. The third edition now takes matters a step further, with a good proportion of the chapters dealing with the economic theory and its application in the digital economy. However, there are timeless topics in cultural economics. Research on the economic characteristics of production and consumption of the performing arts, museums and built heritage on topics such as such as demand, elasticity, pricing, costs, market structure, finance and regulation continue to attract cultural economists. Some of these art forms – even the most traditional such as opera and museums – have been able to embrace new technologies, not so much on the production side (though that too) as in facilitating their ability to reach wider audiences. In addition, there has been an increased amount of economic research on the cultural industries (broadcasting, film, publishing and sound recording, and video games) and on the impact of the creative industries on economic development in cities and districts, including through festivals and cultural tourism. In addition to the public finance of the older arts, regulation by governments continues to play an important role in the creative economy in relation to heritage and the media, and through copyright law and artists’ rights legislation. This book covers all these topics.

ECONOMIC CHARACTERISTICS OF CULTURAL GOODS AND SERVICES What all creative goods and services have in common is that they contain a creative or artistic element. Cultural goods may be capital or durable consumer goods – a picture in 1

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2  Handbook of cultural economics a museum, a DVD – and they yield a flow of services over their lifetime; others, especially the performing arts, exist only for a particular time span. Cultural goods are tangible objects, such as an artwork or a book; others are intangible services, such as a musical performance or a visit to a museum. Some are final goods and services that are supplied to consumers. Others are intermediate goods and services that go into the production of other cultural products or into non-cultural output; for example, a sound recording may be sold to the consumer, played on the radio as an input to a broadcast, played in a shopping mall or sports hall, or split into tracks and downloaded on or streamed to an iPlayer or mobile phone. In addition to this cultural element, what creative goods have in common with all other goods and services is that their production utilises resources of land, labour and capital, and other inputs, particularly human ingenuity (entrepreneurship and human capital). These resources have other uses and therefore have an opportunity cost and a price. Even when they are supplied free, the costs producing them have to be borne by someone. Museum entry may be free for the visitor, but the cost of the visit is paid for by the funding organisation, that is, the state or other sponsor. When cultural products are supplied or financed by the government, they are paid for out of taxes that are levied on all taxpayers, not just those who visit cultural facilities, and therefore there is a redistribution of income from non-participants to those who participate (who are typically financially better off). Increasingly, services such as television and radio programmes and music are supplied free to listeners and, as they are financed by advertising, they are ultimately paid for by sales to consumers who buy the advertised goods and services. These are the two- or multi-sided markets in which private for-profit firms finance the supply of creative services. This differs from sponsorship, where the firm finances a specific arts organisation or project, often to publicise its own brand name. One more characteristic of cultural goods and services is that they typically require considerable investment in the fixed cost of producing the first unit, while the marginal cost of producing further units is relatively low. The ratio of fixed to marginal costs varies, however. In the performing arts, there is a high fixed cost of preparing and rehearsing a performance but then each live performance also requires the presence of the performers and back-stage support staff, thus creating marginal costs. By contrast, if the performance is recorded, copies can be distributed for very little cost. In the case of digitally produced material, fixed costs are lower and distribution costs are virtually zero. Even the performing arts, such as opera and ballet, have come to be widely accessible through what has known as event cinema – the showing of live performances broadcast from building-based performance in real time to cinemas large and small.

ECONOMIC THEORY AND CULTURAL ECONOMICS Cultural economics uses economic theory and empirical testing in order to explain these many aspects of the creative economy. Microeconomics, welfare economics, public choice economics and macroeconomics may be used, and economists choose one or another of these bodies of theory as appropriate to analyse the topics they seek to explain. Sometimes, this can seem confusing but it is not inconsistent and the theories are not incompatible; they just tackle things at different levels. Microeconomics, as its name

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Introduction  3 s­ uggests, is concerned with individual decisions concerning the consumption and production of specific goods and services, and deals with their supply, demand and pricing. So, for example, microeconomics can be applied to understanding how theatre-goers respond to changes in prices. Microeconomics is also involved in industrial economics – the study of the structure of firms in an industry – and in platform economics, the study of the economic strategies and pricing decisions of online intermediaries resulting from economic interactions between distinct groups of consumers or users who benefit from the resulting network effects. By contrast, macroeconomics analyses broad aggregates at the level of the whole economy, looking at employment, economic growth and development. Examples are the impact of a new cultural facility on a city or the contribution to national or regional income generated by the creative industries. The term creative industries is now widely used to cover the whole arts and cultural sector (the performing arts including live music, theatre, opera and dance; heritage, that is, museums and built heritage; and the cultural and media industries, including sound recording, film, software and video games, publishing and broadcasting), and includes industries, such as fashion and advertising, that so far have had little attention in cultural economics. National governments and supra national organisations, such as the European Union, routinely measure the size and growth of the whole creative industries sector. Over the past decade or so, the quality and use of statistics on production and consumption in the creative economy have greatly improved, though labour market data still present problems. Welfare economics takes as its theme the economic well-being of a whole society and it offers an analytical framework for assessing the effect of changes in, for example, technological developments, laws and social attitudes on welfare. It lays down theoretical criteria for increased social efficiency and it forms the basis for cost–benefit analysis, which is widely used by government to evaluate new projects. Although welfare economics looks at aggregate welfare, its analytical methods are founded in microeconomics. Cultural economics has made great use of welfare economics in evaluating government policies for financing and regulating cultural institutions, including in relation to copyright law. Less use has so far been made of the theory of political economy, which applies economic analysis to political decision-making and takes into account the self-interest of policymakers and administrators. Another area of economics that is widely used in cultural economics is public finance. Public finance is the term used for the study of taxation and expenditure at the national, regional and local levels of government. It analyses the efficiency and equity effects of taxes and subsidies; the former is concerned with incentives to consumers and taxpayers, and the latter deals with topics such as the redistribution of income. Public finance is closely connected to government policy; however, although economists are frequently involved in the positive aspects of policy-making, for instance, estimating the costs and benefits of a particular programme or project, they have little professional competence in the normative side of policy formation. An important contribution by economists in analysing cultural policy-making has been the recognition that it often seeks to achieve multiple objectives that are in conflict (for example, raising quality and spreading access to the arts and heritage) and that require different policy measures and incentive structures. Performance indicators have been developed and utilised in situations in which financial data cannot be used to evaluate efficiency in the achievement of objectives, whether at the

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4  Handbook of cultural economics macro level or the micro level. A museum, for example, is a multi-product firm, offering research and conservation services as well as education and entertainment for visitors. A lump-sum grant would not distinguish priorities of government policy, for instance, if a publicly funded museum is expected to target participation by new audiences, and such a grant, therefore, would not necessarily provide the right incentive to achieve the desired policy outcome. Since almost all subsidy to the arts and heritage is channelled via the supply side, public expenditure given to arts organisations needs to be targeted and its success in achieving policy objectives monitored. The focus of public finance is almost entirely on the supply of goods and services by public and private organisations. Chapters in this book explain all these topics. Applying the Theories An example of how different theories and economic research can be used in combination is presented by the well-known economic analysis of the performing arts by Baumol and Bowen (1966). Initially, the authors gathered a mass of microeconomic data on theatre, opera, ballet and orchestras on employment, prices, revenues and audiences in the USA and UK, and looked at trends over a period of time. They then developed the theory that is now called Baumol’s cost disease, using a macroeconomic framework to compare growth in two sectors in the economy, manufacturing (the dynamic sector) and the performing arts (the stagnant sector), to explain why costs and prices were rising faster in the performing arts than in manufacturing. They employed microeconomics to analyse consumers’ responses to price rises, and predicted the possible consequences for arts organisations of a financial deficit. Evoking market-failure arguments from welfare economics, they argued that external and unpriced benefits would be lost if the performing arts were left to market forces alone and that the presence of these externalities and other spillover effects made the case for welfare-improving government intervention via direct subsidy or tax breaks. In methodological terms, the cost disease theory is a mixture of positive and normative approaches. Data gathering and analysis is a positive research activity in that measures of labour productivity and cost inflation utilise standard macroeconomic tools and are objective, while welfare economics is normative in that it seeks to achieve the norm of social welfare improvement. Positive and Normative Economics The distinction between positive and normative is very important in economics because it is a way of legitimising the scientific contribution of economic thinking and distinguishing it from controversial opinion and belief. This distinction does not always appear sound and there are even dangers from being overconfident in the power of the distinction but, to economists, it is important to try to be objective and to respect individual choice. Thus, to return to the example of Baumol’s cost disease, establishing the real increase in prices and costs (that is, increases after allowing for inflation) and in audience figures is not controversial, though there may be some statistical errors in predicting future revenues. However, we cannot go from those facts to argue that the government ought to subsidise the arts, without making normative claims. That case had to be made, for the policy goal

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Introduction  5 of maintaining a certain level of arts provision, by showing that without financial support from other sources, revenues from ticket sales would be unlikely to cover the cost of producing the same level and quality of performing arts and that those levels of output could not be achieved. Baumol and Bowen (1966) were very clear on this distinction. If that is the case, you might reasonably ask why some economists did not accept the theory of the cost disease. The reasons are that Baumol made the following assumptions: first, that the arts are a stagnant sector unable to benefit from technological progress, whereas the manufacturing sector does do so and therefore can produce goods more cheaply; secondly, that performing arts organisations, such as theatre companies and orchestras, cannot change their artistic component labour; thirdly, that rates of pay in the performing arts would rise at the same rate as those in the economy as a whole (that the labour market is integrated). It is these assumptions that have been criticised as unrealistic and incorrect, but not the logic of increasing costs. Moreover, it is not only the cultural sector that is prone to this disease; it has manifested itself in a range of public sector services. Latterly, Baumol accepted that digital distribution would enable arts organisations to reach far greater audiences at almost zero marginal cost, while maintaining that the fixed cost of creating the good in the first place would remain subject to the same strictures as in the pre-digital economy.

PUBLIC FINANCE One of the earliest topics that concerned cultural economists was the case for public finance – either direct finance or subsidy, or tax measures to encourage private donation – of the arts and heritage. The type of intervention adopted varies considerably from country to country but it is possible to identify broad trends. In mainland Europe, many countries have what are tantamount to state-owned and state-managed arts and heritage organisations; central, regional or local government owns the buildings and contents, employs the people working in them and is responsible for managing the organisation. That has changed over the years with a move to privatising the management, but much of the finance remains part of the public sector and is provided out of taxation; revenues from ticket sales may revert to the government office responsible. At one time, broadcasting was also a state monopoly in most countries. Changes have been made to both ownership and management structures in some countries in all areas of the cultural sector, but direct finance is still the norm, at least for museums and the traditional performing arts. An exception to this model is built heritage where many significant items are in private ownership, and therefore regulation, often combined with subsidy, is used to achieve policy objectives. By contrast, the model in the USA and other countries, one being Japan, has been of private finance through revenues from ticket sales and other enterprises and state encouragement of private giving through the tax system (such as the use of tax waivers) to privately constituted, typically non-profit, arts and heritage organisations. The intermediate model adopted in the UK, Australia, New Zealand and Ireland, among others, is the arm’s length principle of public finance, whereby private, non-profit organisations (often constituted as charities) are granted sums of money from general taxation for a specific period of time and are expected to raise a considerable proportion of their incomes from

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6  Handbook of cultural economics sales and donations, increasingly helped to some extent by the tax system. In practice, these models overlap but differing attitudes about the responsibility of the state and public finance still frame the debates and practices of cultural policy. By contrast, the cultural industries are private, for-profit businesses that rarely receive public finance (the exception being public service broadcasting), though they are regulated by the state for monopoly (anti-trust) abuses and, more significantly, by copyright and other intellectual property law.

PUBLIC GOODS The main economic rationale for public finance for the arts is that they have public-goods characteristics, and so the extent to which that is the case has been debated for a long time in cultural economics. Pure public goods have the characteristics of being both non-rival and non-excludable, meaning that one person’s consumption of them does not reduce what is available to others and, equally, they are available to all-comers. Over-the-air broadcasting is an example of a service with strong public-good characteristics. There are several implications of these features: an entrepreneur seeking to make a profit or a nonprofit organisation seeking to cover its costs with revenues from sales would not be able to fully capture those revenues as consumers would likely free-ride on the expenditures of others – once a sufficient amount to get the good or service supplied were raised, everyone could ‘cash in’ and get access to the good or service. The result is that the good would not be supplied except through some form of collective finance – for instance, taxation – and the allocation of resources via the price mechanism would not produce the socially desirable output of goods and services. Many goods and services in digital form are effectively public goods, and this has given rise to new business models and a great deal of piracy. Cultural goods and services vary as to the extent of their public-goods characteristics. For example, visits to the theatre or to a museum have a private benefit (utility) to the visitor, for which they are prepared to pay and for which entry can be excluded for those who do not pay; however, visiting a beautiful city provides utility for which a price cannot be charged for by entry ticket. Even excludable goods and services may have some external (or spillover) benefits; an element of non-rivalry is present since consumption by paying audiences and visitors benefits the public welfare by reinforcing a sense of national or local identity and by increasing understanding of other people and cultures. Just the existence of a theatre or a museum may also produce social benefits, and contingent valuation studies have shown that people who do not participate in the arts and heritage are willing to pay something to provide these facilities, either to ensure that they exist for others or as an option for their own future consumption. Markets therefore do not take their full value into account through prices, and this argues for some form of public finance. A second argument for public finance of the arts and heritage is that consumer demand does not reflect the full value of these goods because they are experience goods; consumers’ tastes are not fully formed and they cannot have full information about cultural goods. Moreover, cultural value is elusive and is not fully recognised in price. Information problems mean that expert judgement has to be relied on to ensure quality and that leads to supplier-induced demand. This easily results in the domination of expert opinion, often supported by state finance, with consumers and taxpayers being unable

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Introduction  7 to assert their preferences. An alternative but similar concept used to justify replacing consumer sovereignty with collective provision is that of merit goods, the term used by economists for goods that are held, usually by experts, to have inherent value for society. It is worth noting that the above arguments for government intervention are not confined to the arts but are made also in relation to health, the environment and education. The logic of these arguments has, however, not been extended to the creative goods and services produced by the private enterprise cultural industries, the exception being public service broadcasting.

CREATIVE INDUSTRIES AND THE DIGITAL REVOLUTION The growth of the service sector and the decline of manufacturing in developed economies have focused interest in the creative or knowledge economy and this, in turn, has led to considerable interest in the creative industries, emphasising their role as the main force for growth in the creative economy. The impact of this paradigm change is reflected in the content of this third edition of the Handbook with both new and some revised chapters demonstrating the significant impact that the digital revolution has had. The digital technological revolution has had profound effects on the production, consumption, distribution and marketing of creative goods and services, on their costs and pricing, and on their content. Digitisation has enabled producers to transform many cultural goods into intangible services for delivery via the Internet and to market other goods that way. It has transformed items that previously would have been classified as goods into services; e-books, newspapers and photographs are some examples. In electronic form, these items can be personalised, reused and retransmitted in ways that were not possible in the form of tangible goods. This transformation has meant that pricing policies have changed significantly; instead of buying a good for a fixed amount of money (the price) that you can keep for as long as you like or give away to someone else, when you obtain them now as electronic services you pay a licence fee for a specific selection of services for a specific period of time. Digitisation has also meant that these services become akin to public goods since it is trivially easy to share digital files between users without payment and that has produced an upheaval in the creative industries that produce digital material – recorded music, games, film, and so on. Although copyright law exists to prevent such free-riding, digitisation has called into question its ability to enable creators and the creative industries to fully appropriate revenues in these markets. Copyright law protects technological protection measures, and digital rights management is used to prevent unauthorised distribution, but the scale of copying has made it an insuperable task to enforce it fully. Copyright law has to find a balance between the demands of producers and users in the digital world – fundamental to the success of the creative economy.

EMPIRICAL RESEARCH ON THE CREATIVE INDUSTRIES One of the main contributions economics can make to all the topics mentioned above is to provide empirical evidence. That can range from the collection of basic data (for example,

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8  Handbook of cultural economics the value-added of the creative industries) to testing theories of incentives. In the past, lack of data, especially of official statistics on the cultural sector, has been a barrier to good empirical research, but that has now changed in part owing to the emphasis on the economic role of the creative industries in the creative economy as well as to past efforts by cultural economists. As with other branches of economics, good statistical analysis and theoretical development are vital to the success of cultural economics.

ABOUT THIS EDITION This Introduction has shown that cultural economics has a body of knowledge that provides common approaches to production and consumption in all the creative industries. The third edition of this Handbook shows how much the subject has progressed since 2011. As in previous editions, the titles of the chapters have been kept short to make the book easy to use and chapters are cross-referenced to guide the reader to related topics together with suggestions for further reading, which in almost all cases have been provided by the chapter authors. Also as previously, it is assumed that readers have a basic knowledge of economic theory. The books listed at the end of this Introduction explain the theories used in cultural economics.

REFERENCES Baumol, W.J. and W.G. Bowen (1966), Performing Arts: The Economic Dilemma, New York: Twentieth Century Fund. Caves, R. (2000), Creative Industries: Contracts Between Art and Commerce, Cambridge, MA and London: Harvard University Press. Throsby, D. (2010), The Economics of Cultural Policy, Cambridge: Cambridge University Press. Towse, R. (2019), A Textbook of Cultural Economics, 2nd edn, Cambridge: Cambridge University Press.

FURTHER READING Richard Caves’s (2000) book is a detailed analysis of the structure of the creative industries based on the contracts between the artist or original creator and the firm; this provides a wealth of material covering the whole cultural sector. David Throsby’s (2010) book demonstrates the relevance of economics to all aspects of cultural policy for the arts and cultural industries by an author who is one of the best-known cultural economists. A Textbook of Cultural Economics (Towse 2019) provides an introductory account of the whole field of cultural economics along with explanations of the economic theory necessary to understand it, updated to take account of the digital revolution in the creative industries.

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1.  Application of welfare economics to the arts William J. Baumol

There are some very agreeable and beautiful talents of which the possession commands a certain sort of admiration; but of which the exercise for the sake of gain is considered, whether from reason or prejudice, as a sort of public prostitution. The pecuniary recompense, therefore, of those who exercise them in this manner, must be sufficient, not only to pay for the time, labour, and expense of acquiring the talents, but for the discredit which attends the employment of them as a means of subsistence. The exorbitant rewards of players, opera-singers, opera-dancers, &c. are founded upon those two principles; the rarity and beauty of the talents, and the discredit of employing them in this manner . . . Such talents, though far from being common, are by no means so rare as is imagined. Many people possess them in great perfection, who disdain to make this use of them; and many more are capable of acquiring them, if anything could be made honourably by them. (Smith 1776 [1904], bk I, ch. X, pt 1, pp. 108–9)

WELFARE ANALYSIS AND RATIONALE FOR PUBLIC FUNDING OF THE ARTS Welfare economists seem not to have devoted much systematic attention to the arts. The connection, rather, grew from the other direction – the arts seeking justification in the analysis of welfare theory, not for themselves, but for the public funding on which they often rely. The problem is that, for a number of reasons, the arts have found it difficult to support themselves in the marketplace. There are obvious exceptions, such as commercial theatre and painters who have achieved popularity and wealth. However, much of artistic activity historically has depended on the voluntary patronage of royal princes and, later, merchant princes. As democracy took over the world’s wealthier economies, government support often replaced that of the patrons. However, this gave rise to a troubling issue: why, in a society whose government ostensibly acted so as to contribute to the welfare of its citizens, should products, such as paintings, and services, such as opera performances, be singled out for financial support, when the bulk of the goods and services generated by the economy are left to their own devices to sink or swim in the marketplace? The answer to some, few of them economists, seems obvious. The arts are among the most desirable products of civilization – indeed, they are among the most worthy of the outputs of the economy. However then, we must ask, if they are so worthy, why is this not matched by their demand? The answer is that their limited audience simply reflects inadequate education of the consuming public, and the consequently undeveloped ability to appreciate the finer things is all too easily attacked by those who question the credentials of the self-appointed arbiters of taste. The difficulties of those who advocate public support for the arts are compounded by the well-documented fact that their audience is typically composed of individ­ uals whose incomes, wealth and education are well above those of the population as a whole. This means that devotion of general taxation to support of the arts invites condemnation as a reversal of Robin Hood practice, taking from the poor to give to the rich. 9

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10  Handbook of cultural economics Economists with interest in the arts have been led to employ the tools of welfare economics to construct a more solid foundation for public funding. They have proposed a number of arguments in support of this approach – among them equality of opportunity, the external benefits of education, the public-good properties of the product, the infant organization argument and investment for the future. In addition, economists have returned to the merit-goods argument, the judgement that the arts merit public support simply because of the superiority of their inherent worthiness.1 Equality of Opportunity There can be little doubt that, on average, consumers of the arts have incomes above those of members of society in aggregate. However, alternatively, the less affluent often do not get the opportunity to experience the arts and to discover the attraction of cultural activity for themselves. This problem is exacerbated by the high admission fees made necessary by high costs of live performance, museum operation and other cultural activities. So, if equality of opportunity is included in the calculation of social welfare, this can be taken as one justification for public support. Beneficial Externalities It is a standard argument of welfare economics that if an activity generates beneficial externalities, public subsidy of that enterprise may well enhance welfare. The externalities of artistic activity are, however, not entirely clear. There is the likelihood that one artistic undertaking can inspire others and, thereby, facilitate further creative endeavours. It has also been claimed that persons with interest in the arts are generally better members of society, increasing the benefits to others from their presence. However, these claims are not easy to prove or even to make explicit. Culture as Public Good There can be little doubt that cultural activities often possess public-good properties. A half-empty theatre or a sparsely attended museum is perfectly analogous to the uncrowded bridge (in the example provided by Dupuit 1844 [1952]) – since the true cost of an additional user is zero, if any non-zero price prevents anyone from using the facilities the result is a net social loss. This problem is particularly acute in the case of mass media, such as broadcasting, because there is no practical limit to the number of listeners who can be served without depletion of supply to others. Here too, however, a zero price is impossible without subsidy. Infant Cultural Enterprise The financial difficulties of new art forms and even new arts organizations are well known, and the starving unrecognized artist has become a cliché. The notion that new enterprises merit public assistance and that society benefits from such aid in the long run is an ancient argument, and has elicited much scepticism from economists.

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Application of welfare economics to the arts  11 Cultural Reputation and Investment for the Future It is often claimed that, even if a society does not value the arts for itself sufficiently to provide the requisite support through the market, it may want to do so for other reasons. For example, it may want to avoid the reputation of being a society of Philistines, or it may feel that future cultural activity justifies current preservation of the arts. This attitude is parallel to that of that King of Naples who reportedly supported the opera on condition that he never be asked to attend. Merit Goods It seems generally to be felt among economists – even among those most personally supportive of the arts (see, for example, Peacock 1969 [1997]) – that, while these arguments have some validity, they do not by themselves constitute an overwhelming case for extensive support of the arts. The basic objection is that, while cultural activity undoubtedly offers such benefits, so do other human activities, and it is not clear on the grounds so far noted that the arts deserve to be singled out for special support. In response, it can be argued that subsidies are provided to many other activities, some with little in demonstrable benefits other than those they provide directly to their purchasers. However, few if any of these activities have made a convincing case for public support. Ultimately, at least some of the economists (and others) who advocate generous subvention to the arts fall back on Professor Musgrave’s device: the merit-goods argument (see, for example, Scitovsky 1976), which proposes that the arts deserve support simply because they are significantly worthy. That is, the arts deserve public funding because they are good. If asked why, or how one tests the proposition, the implied answer is that it is self-evident. Whether or not this is accepted as convincing, it must be recognized to be an honest reply. This completes the brief survey of the issue that is surely central to the welfare economics of the arts. It must be admitted that its protracted investigation by analysts of the highest calibre has not carried the discussion much further from where it stood some decades ago. The discussion turns now to a second critical issue for which welfare theory is pertinent: the role of instruments, such as copyright, in ensuring compensation of the suppliers of cultural products. This issue is hardly new, but recent economic developments have made the matter more acute, and analysis has contributed greatly to our insights on the subject.2

CULTURAL OUTPUT: COMPENSATION, THE NEED FOR REPEATED SUNK COSTS, PUBLIC-GOOD PROPERTIES AND MEASURES TO PROTECT INTELLECTUAL PROPERTY The Basic Problems Many art forms are characterized by public-good properties: they are not depletable, meaning that the number of consumers of a cultural product can increase without having to reduce consumption by anyone else, and exclusion may be difficult, meaning that individuals may be able to consume such a product without the permission of the supplier.

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12  Handbook of cultural economics These two attributes, in turn, raise two issues: how can suppliers be compensated for their efforts (something desired not only as a matter of equity, but also in order to elicit their continued supply) and, if compensation is to be obtained through the market mechanism, what price, if any, should be charged for the products? These are not new issues for the arts. A half-empty theatre raises all of these problems, but recent technological change has greatly increased their significance. The availability of the mass media and, especially, the Internet has magnified the size of the audience that can be provided for without depleting the provision to others. Moreover, these new transmission modes have made it more difficult to collect whatever compensation the supplier may consider appropriate. As Dupuit (1844 [1952]) and Samuelson (1954) made clear, a key dilemma here is the desirability of charging consumers anything at all. If the price mechanism is the means used to compensate suppliers, a zero price cannot be optimal socially because artistic activity is not costless and, particularly where the activity is carried out for profit, a zero price will not elicit the socially optimal supply. Indeed, with such a product price, the output of commercial suppliers can be expected to be zero. However, zero output of such desirable products patently cannot be optimal. Any non-zero price cannot be optimal either, for, if additional consumers can, for all practical purposes, be supplied at zero marginal cost, the exclusion of any consumer by a non-zero price must entail a social loss – preventing a benefit to a consumer whose cost to society would be zero. This is only the beginning of the puzzles. Suppose that this dilemma is ignored as an unsolvable theoretical problem, and non-zero prices are the norm. What second-best price is consistent with maximal welfare benefits? The textbook conclusion does not suffice because price equal to marginal cost will generally not allow recoupment by the suppliers. The problem is traceable to the character of sunk cost that is common in artistic activity. Standard theory tells us that sunk costs do not matter, that their magnitude should not affect optimal price. As a piece of ancient history that cannot be changed by any current or future pricing decision, these are simply irrelevant, but in the arts, sunk costs are not just historical data. The problem is that sunk outlays, characteristically, must be incurred again and again. For example, the production costs of a newly mounted drama are indeed a sunk cost, and if an acting company were to present that drama and no other for the indefinite future, the sunk cost would be irrelevant. It would not matter whether the future performances rewarded the investors handsomely or failed to return any of their outlays. However, that is patently not how an acting company carries on its activities. New productions must be brought to the stage, normally at fairly frequent intervals, so that sunk outlays take the form of an inter-temporal stream of periodic and relatively large expenditures, rather than a once-and-for-all occurrence. Also, future sunk costs are still variable, not sunk, in the present. To induce investors to keep providing the necessary resources, past recoupment history must be such as to promise the possibility or even the likelihood of recovery of future sunk investments. This is true not only of stage productions, but also of the training required for singers or dancers. Trained performers have a very limited working life, and the sunk outlays entailed in their training must be repeated constantly if the activities in their fields are not to come to an end. These difficulties have a near perfect analogue in the ‘new economy’, in which innovation has become the prime weapon of competition in much of industry. The proprietary

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Application of welfare economics to the arts  13 knowledge that emerges from inventive activity is well known to have significant publicgood properties, and competition forces firms to repeat constantly the sunk outlays that are entailed in the innovation process. Not only are these problems in the performing arts and the innovation process the same, but it is arguable that the pricing principles that are applicable to either are also pertinent to the other. Government Buyout of Intellectual Property and the Public-Good Problem The analogy with the economics of innovation immediately offers one way of dealing with the problem that contributes further justification for government support. In the case of innovation, patents constitute the most direct analogue to copyright, in the arts. Both of these raise the public-good problem; they are designed to reward the creator of intellectual property by enhancing that person’s ability to exclude unauthorized users, thereby making it prospectively possible for the creator to extract a price for its use. However, that nonzero price runs into the Dupuit–Samuelson dilemma: why exclude anyone from the benefit of costless usage of a product? There is a considerable literature (see, for example, Kremer 1998, for an excellent discussion and citations of other writings) that suggests a way to cut this Gordian knot: patent buyouts. This entails outright purchase of the property by government, with the creators thereby offered appropriate rewards, in return for which they give up any right to charge for use of their creations. Kremer provides a dramatic example: In 1839 the government of France combined elements of the patent system and of direct government support of research by buying out the patent for Daguerreotype photography and placing the technique in the public domain. After the patent was bought out, Daguerreotype photography was rapidly adopted worldwide and was subject to myriad technical improvements. (Kremer 1998, p. 1138)

This goes a good part of the way towards providing a solution to the problem, as it provides the desired incentive for creative activity, while not precluding socially costless access to others. Such an approach is possible in the arts, but it must be recognized that it does not completely solve the problem. First, as Ramsey analysis shows (see below), the government subvention, and the resources it provides to recipients, must come from somewhere. This, in turn, must entail non-zero taxes, which themselves unavoidably distort decisions and therefore entail welfare costs. Second, there remains the unsolved theoretical problem of determining an optimal buyout price, particularly in light of a patent or copyright is a (deliberate) granting possible monopoly power to the creator of the intellectual property, who may well seek to extract a monopoly profit via the price. Finally, there is the problem of reality. While governments are often willing to supply part of such a subvention, they may not be prepared to provide enough to permit the activities to remain solvent with a non-zero price for their use, a problem exacerbated by the arts’ ever-rising real costs. Solvency Generally Requires Price Discrimination Cultural products, then, are generally supplied at non-zero prices, even when they are produced with substantial government support. Moreover, the process is often characterized

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14  Handbook of cultural economics by considerable price discrimination – student and senior discounts, reduced subscription prices, lower group prices, arrangements with schools, churches, and trade unions, and a variety of other such arrangements. This is done, at least in part, for reasons of equity – to prevent exclusion of the impecunious. Part of the purpose, however, as in subscription pricing, is to help in dealing with the financial needs of the enterprise. Economics teaches us that the need for this approach may be more pressing than practitioners recognize. It has already been noted here that marginal cost pricing is incompatible with survival of firms that need to incur substantial sunk costs repeatedly. Nor will even absolute freedom of competitive entry at zero entry cost drive prices down to the uncompensatory marginal cost level, in such circumstances. This is because entry can be expected to occur only if prices in the field offer the prospect of enabling an entrant to cover all of its prospective sunk costs. So any prices above marginal costs, but insufficient to cover sunk costs, will elicit no entry. Entry will only occur and drive down prices if at least some of those prices are sufficiently above marginal costs to recoup the sunk outlays. However, it has been known, at least since the writings of Dupuit in the mid-nineteenth century (see also the illuminating recent discussions by Hausman and Mackie-Mason 1988 and Varian 2000), that price discrimination helps the firm with fixed costs to recover its outlays. Indeed, recovery is sometimes unachievable without this. Here I go one step further and demonstrate that solvency generally is impossible without recourse to discriminatory prices, although this is not true in every case. Moreover, I show that effective competition in the form of totally unimpeded entry, at least into commercial cultural activity, not only does not prevent the adoption of such prices in those circumstances where it is required to prevent insolvency, but instead, these competitive pressures tend to make price discrimination mandatory. Socially Optimal Discriminatory Prices The full story follows from the observation that full ease of entry not only ensures that the incumbent firm’s profits will be driven down to the competitive level, but goes beyond that. In such a market, entry and the threat of entry ensure that the incumbent, in the long run, cannot expect to earn more than competitive returns, no matter what prices it chooses to adopt for its products. Then our result follows: 1.  Among the prices more than very temporarily available to the incumbent, those that maximize its profit will yield exactly the competitive rate of return. 2.  If that maximum is unique, any other prices adopted by the incumbent will yield a rate of return below the competitive level, that is, a rate of return that is not viable financially. 3.  Since differential prices are not subject to the constraint that all purchases must be provided at the same price, the profits attainable under discriminatory prices will generally be higher, and certainly no lower, than those offered by any uniform price. Consequently, the unique profit-maximizing prices that the firm is required to charge in order to break even normally will be discriminatory, with the firm that adopts them occupying the position of discriminatory price taker. The competitive model, as a guide to socially optimal pricing, then suggests that not only financial viability, but also static optimality, requires the prices for cultural products to be

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Application of welfare economics to the arts  15 discriminatory. However, there is a more direct way to see that. Ramsey theory addresses itself directly to the determination of second-best prices in the presence of recoupment shortfall, if prices were set at marginal costs (see Ramsey 1927, and, for a simpler description, Baumol and Bradford 1970). Moreover, the well-known Ramsey formula clearly calls for discriminatory pricing, with the differences between prices and marginal costs determined by demand elasticities. Given the solvency constraint, the prices that emerge are precisely those that, in the past, were referred to as charging what the traffic will bear. However, the zero economic profit constraint means that these prices constitute no exercise of monopoly power. This is one of the key implications of the discussion of this section. Licensing of Copyright for Commercial Reuse Ramsey theory constitutes the foundation of welfare analysis of the pricing of cultural products. In the world of mass media, however, this is not the end of the story. Once copyright becomes an instrument for the extraction of compensation, a new issue arises. Others engaged in cultural activities will want access to the material covered by copyright for its reuse in their own pursuit of profit. For example, films and recorded television programmes often are re-broadcast by others not their proprietors, and recordings of music are played by broadcasters. In some cases, the users are direct competitors of the copyright owners. The question is whether or not there exists an economically efficient price for this access to the material covered by copyright. I show next that there is such an efficient price. There are levels of the access price that are materially too high or substantially too low for a social optimum. Prohibitively high licensing fees are equivalent to outright refusal to give a licence to anyone, while inadequate fees, which can easily occur if licensing is compulsory, constitute a strong disincentive for investment in the creative activity that yielded the product. Fees that are excessively low can also lead to use of the product by some inefficient firms at the expense of others better qualified to do so. The theory of price regulation provides a pricing principle that can be used in finding an efficient copyright-licensing fee. This principle has been referred to as the efficient component-pricing rule (ECPR) or as the parity principle. The efficiency property of the parity-pricing rule is the attribute that, when charged the parity licence fee, a renter of the copyrighted material will be able, viably, to charge consumers a lower price than the copyright owner’s only if the former is the more efficient of the two in the process of transmitting the item to consumers. The logic of the proof that the parity-pricing formula (given below) satisfies this requirement is not difficult to understand. For this purpose, it is helpful to think of the item covered by copyright as one of the inputs to the final product provided to consumers. Then, the purchaser of access to the material under copyright (the renter) is engaged in the transmission of this material to customers. Thus, the latter is clearly not placed under an inefficient competitive handicap by the licence fee if, when the renter’s remaining input cost of supplying (transmitting) the final product to consumers is X pounds per unit of final-product output lower than the copyright owner’s, the renter can just afford to provide the final product exactly X pounds cheaper than the copyright owner can. This has been called the level playing field theorem.

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16  Handbook of cultural economics All this can be described formally, giving an explicit formula for an efficient licence fee. We use the following notation: Pf,i 5 the copyright owner, I’s, given price per unit of final product; minPf,c 5 the competitor, C’s, minimum viable price of final product; Pi 5 the price charged for a licence to use the copyright, per unit of final product; ICr,i 5 the incremental cost to the copyright owner of the remaining final-product inputs, per unit of final product; ICr,c 5 the corresponding figure for the competitor; and ICi 5 the incremental cost to the copyright owner of use of the copyright by itself or by others. As will be demonstrated, ECPR requires that the licensing price satisfy the following rule: Pi 5 Pf,i 2 ICr,i . (licence price 5 I’s final-product price – I’s IC of remaining inputs)(1.1) Equation (1.1) tells us that ECPR establishes a tight link between the price, Pf,i, that the copyright owner charges for its final product and the price, Pi, it charges its rivals for the licence to use the copyright. If incremental production costs do not change, efficiency requires that a rise in one of these prices must be matched, pound for pound, by a rise in the other. Then our task is to prove the level playing-field theorem. The parity price, as given by equation (1.1), for use of material covered by copyright is both necessary and sufficient for the playing field to be level. This means that the maximum difference between the remunerative prices of the perfect substitute final products of the two firms, the copyright owner (I), and its final-product competitor (C), is exactly equal to the difference in the firms’ remaining incremental costs (other than the licence fees). Proof: The level playing field is defined by

minPf,c 2 Pf,i 5 ICr,c 2 ICr,i .

(1.2)

That is, the lowest compensatory price the competitor can afford to charge should differ from the copyright owner’s exactly by the amount (positive or negative) that the former’s remaining costs are below the latter’s. The lowest price that is financially viable for the competitor clearly is given by:

minPf, c 5 Pi 1 ICr,c .

(1.3)

That is, the price must cover the copyright licensing cost plus the remaining cost of supplying the final product (including the normal profit on the required capital). Comparing the two equations, we see at once that the level playing-field condition (1.2) will be satisfied if and only if:

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Pi 5 Pf, i 2 ICr,i .(1.4)

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Application of welfare economics to the arts  17 However, this is the parity-pricing formula (1.1). Thus, parity pricing is both necessary and sufficient for a level playing field. QED. This completes our proof that parity pricing of a copyright licence is necessary for economic efficiency in the provision of final product by its competing suppliers. For, if the rule is violated, a less efficient supplier of the remaining inputs can win the competition for the business of supplying those inputs, instead of the task going to its more efficient rival. That is, violation of equation (1.1) permits the less efficient supplier of the remaining inputs, such as transmission, to under-price its more efficient competitors.3 The proof is readily extended to cases with three or more competing firms.

OTHER ISSUES AND CONCLUDING REMARKS There seems, so far, to be no systematic literature that can be deemed to constitute a welfare economics of the arts and culture. Yet it has been possible to show here that these arenas do give rise to issues that are definitely within the scope of welfare theory and that require such theory for their analysis. I have noted some appropriate analytic methods, but the topics discussed here qualify primarily as illustrations. There are many other topics related to culture that appear to demand welfare analysis. For example, the issue of cultural heritage, and its valuation, is a significant and fascinating topic that calls for study in terms of welfare analysis. In addition, communication of the products of artistic activity naturally gives rise to such issues as network externalities and compatibility of the instruments of communication. In summary, much remains to be done in the field. However, the promise of such an undertaking is underscored by the analytic tools already available in other areas of applied economics, which means that a good part of the requisite work already has been carried out.

NOTES 1. For two excellent compendia of pertinent discussions, see Blaug (1992) and Towse (1997, vol. 2, pts V–VII). For other discussions with significant additional insights, see Frey and Pommerehne (1989) and Throsby (1994). For a sceptical view, see Grampp 1986, also in Towse (1997, pp. 669–73). 2. Much valuable information on the subject and much insight has been provided in Towse (2001). 3. Here, we should pause to admit that, where scale economies mean that marginal cost pricing is not feasible, theory calls for adoption of a Ramsey price for the licence, as well as for final product, and that Ramsey price can violate ECPR. It should be noted, however, that a frequent complaint against ECPR in regulatory arenas, such as telecommunications and electricity, is that it yields bottleneck input prices that are disturbingly high. Yet, the Ramsey-adjusted ECPR prices can be expected to be even higher. Specifically, as long as any rents are left to a competitor of the owner of an essential facility, such as a patent or a copyright, the rival’s demand for the essential facility will be inelastic. Thus, the Ramsey rule requires the price of access to the facility to be raised until all such rents accrue to the facility’s owner, while ECPR leaves competitors’ efficiency rents to them.

SEE ALSO: Chapter 46: Performing arts; Chapter 49: Pricing the arts; Chapter 50: Public support; Chapter 58: Welfare economics.

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18  Handbook of cultural economics

REFERENCES Baumol, W.J. (2005), ‘Intellectual property: how the right to keep it to yourself promotes dissemination’, Review of Economic Research on Copyright Issues, 2 (2), 17–23. Baumol, W.J. and D. Bradford (1970), ‘Optimal departures from marginal cost pricing’, American Economic Review, 60 (June), 265–83. Blaug, M. (ed.) (1992), The Economics of the Arts, Aldershot: Gregg Revivals. Dupuit, J. (1844), ‘Del la de l’Utilité des travaux publics’, Annales des ponts et Chaussées: Memoires et Documents, 2nd ser., 8 (2), 332–75, repr. 1933 in M. de Bernardi (ed.), De l’utilité de la Mesure, Turin, trans. R.H. Barback (1952), International Economic Papers, no. 2, 83–110. Frey, B.S. and W.W. Pommerehne (1989), Muses and Markets: Explorations in the Economics of the Arts, Oxford: Basil Blackwell. Grampp, W.D. (1986), ‘Should the arts support themselves?’ Economic Affairs, 7 (2), 41–3. Hausman, J.A. and J.K. Mackie-Mason (1988), ‘Price discrimination and patent policy’, RAND Journal of Economics, 19 (Summer), 253–65. Kremer, M. (1998), ‘Patent buyouts: a mechanism for encouraging innovation’, Quarterly Journal of Economics, 113 (4), 1137–67. Musgrave, R. (1959), The Theory of Public Finance, New York: McGraw-Hill. Peacock, A.T. (1969), ‘Welfare economics and public subsidies to the arts’, Manchester School of Economic and Social Studies, 37 (4), 323–35, repr. 1997 in R. Towse, Cultural Economics: The Arts, the Heritage and the Media Industries, Cheltenham, UK and Lyme, NH, USA: Edward Elgar, pp. 501–13. Ramsey, F. (1927), ‘A contribution to the theory of taxation’, Economic Journal, 37 (March), 47–61. Samuelson, P.A. (1954), ‘The pure theory of public expenditure’, Review of Economics and Statistics, 36 (November), 387–9. Scitovsky, T. (1976), ‘What’s wrong with the arts is what’s wrong with society’, in M. Blaug (ed.), The Economics of the Arts, Aldershot: Gregg Revivals, pp. 58–69. Smith, A. (1776), An Inquiry into the Nature and Causes of the Wealth of Nations, repr. 1904, E. Cannan (ed.), London: Methuen & Co. Throsby, D. (1994), ‘Production and consumption of the arts: a view of cultural economics’, Journal of Economic Literature, 32 (1), 1–20, also in R. Towse (1997), Cultural Economics, the Arts, the Heritage and the Media Industries, vol. 1, Cheltenham, UK and Lyme, NH, USA: Edward Elgar, pp. 51–85. Towse, R. (1997), Cultural Economics: The Arts, the Heritage and the Media Industries, 2 vols, Cheltenham, UK and Lyme, NH, USA: Edward Elgar. Towse, R. (2001), Creativity, Incentive and Reward, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Varian, H. (2000), ‘Differential pricing and efficiency’, First Monday, 23 October, 1–16.

FURTHER READING For a general overview of the economic issues raised by the arts, there can be no better source than the superb collection put together by Ruth Towse (1997). Though an older volume, the work by Blaug (1992) lays out the subject very effectively. On the issue of public funding, opinions range from Scitovsky (1976), who was an enthusiastic supporter of government financing, to Grampp (1986), who is at the opposite end of the spectrum, with careful intermediate positions taken by Peacock (1969 [1997]) and Frey and Pommerehne (1989). The classical exposition of the issues raised by public finance and the ‘public goods’ issue, in particular, can be found in Musgrave (1959). For more on the optimal pricing of permission to use material covered by copyright, see Baumol (2005).

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2.  Art auctions

Orley Ashenfelter and Kathryn Graddy

Works of art and culture are sold by many means. These include transactions between dealers and their customers, auctions with open outcry, Internet auctions, and even, occasionally, sealed-bid auctions. However, the standard procedure for establishing art valuations for the most expensive works is still most commonly the English auction, where prices ascend in open bidding.

HOW ‘ENGLISH AUCTIONS’ REALLY WORK Many people think they understand the rules of an English auction because they are so commonly used.1 Sotheby’s, Christie’s, Phillips and the other English auction houses have invented and refined these rules over two centuries, and they are now common in many other parts of the world. It is well known that in an English auction the bidding begins low and edges upward as bidders escalate their bids. When the bidding stops, the item for sale is said to be knocked down or hammered down. The price at which an item is knocked down or hammered down is called the hammer price. What is not so well understood is that the items knocked down have not necessarily been sold. Here is the reason. The seller will generally set a reserve price, and if the bidding does not reach this level the item will go unsold. Auctioneers say that an unsold item has been bought in. (This terminology is misleading since the auction house rarely buys unsold items.) An item that has been bought in may be put up for sale at a later auction, sold elsewhere or taken off the market. In auctions of Impressionist paintings, about one-third of the paintings put up for sale will not find buyers in a normal period. In wine auctions, however, the typical buy-in rate ranges from 5 per cent to 10 per cent. The typical buy-in rates for other auction items – European paintings, silver, furniture and jewellery – usually, but not always, fall between these extremes. Table 2.1 shows sale rates (equal to one minus the buy-in rate) in different departments at Christie’s in London from a typical two-year period together with average value of a lot sold. As can be seen from the table, 96 per cent of items put up for sale in auctions of arms and armour were sold, 89 per cent of wine at auction was sold, and 71 per cent of impressionist and modern art items were sold. Although prices have increased over time, sale rates are surprisingly stable across different time periods. Ashenfelter and Graddy (2011) showed that over the 27-year period from 1980 to 2007 the average sale rate for Impressionist art was 69.8 per cent. Auctioneers are very secretive about whether and at what level a reserve price may have been set, and there is an auctioneer’s art in getting the bidding started on each item without revealing the reserve price. For example, the auctioneer may have to accept and announce fictitious bids ‘off the wall’ or ‘from the chandelier’ to start the real bidding. Bids from off the wall are legally being placed on behalf of the seller. Sellers are forbidden 19

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20  Handbook of cultural economics Table 2.1  Average sale rates by department Department

Impressionist Old Master drawings Contemporary British pictures Old Master pictures Continental pictures Clocks Jewellery Furniture Silver Sculpture Modern British pictures Victorian pictures British drawings &  watercolours Rugs & carpets Topographical pictures Islamic Cars Chinese works of art Books & manuscripts Russian works of art Japanese Musical instruments Watches Prints – old modern and  contemporary Miniatures Antiquities Porcelain & glass Tribal art Photographica Modern guns Garden statuary Arms & armour Frames Stamps Wine

Average sold lot value (£) 1996

1995

122 820   50 670   36 820   29 710   29 180   21 810   14 340   12 190   11 670   11 080   11 070   10 340 9460 9160

135 430   29 210   36 840   23 560 6 560   10 450 5130 6750 8220 5910 6340 7190 8400 3400

9160 8640 6670 5750 5640 5220 4490 4410 3960 3870 3850 3350 3260 2700 2650 2580 2510 2120 1890 1800 830 690

No. of auctions in sample

Sale rate (% of lots sold)

% sold by value

Mean

Std dev.

Mean Std dev.

 8  4  7  7 11  7  4  8 25 10  5  9  6 14

71 77 79 78 73 72 88 86 85 87 78 70 66 72

(0.11) (0.09) (0.04) (0.14) (0.15) (0.11) (0.03) (0.05) (0.09) (0.11) (0.21) (0.05) (0.13) (0.14)

80 89 87 83 82 79 89 89 92 92 81 81 75 87

(0.10) (0.08) (0.06) (0.17) (0.15) (0.10) (0.07) (0.04) (0.06) (0.07) (0.20) (0.05) (0.11) (0.10)

3700 8010 6950 7610 6400 4270 5480 2840 4110 2190 4230

 8  2  5  6  8 15  4  5  5  6  8

80 68 68 71 70 81 64 72 77 71 81

(0.17) (0.13) (0.22) (0.16) (0.19) (0.12) (0.14) (0.04) (0.05) (0.09) (0.12)

85 81 82 65 79 86 69 76 76 81 92

(0.14) (0.00) (0.12) (0.22) (0.16) (0.09) (0.15) (0.05) (0.16) (0.11) (0.09)

3260 3640 2600 2090 1660 3620 1540 2400 2260 650 580

 2  3 14  3  3  5  4  4  4 22 37

82 57 76 67 61 93 91 96 81 78 89

(0.05) (0.08) (0.12) (0.08) (0.27) (0.06) (0.10) (0.03) (0.15) (0.13) (0.09)

92 66 85 75 79 94 91 99 85 82 91

(0.07) (0.13) (0.10) (0.19) (0.08) (0.04) (0.11) (0.01) (0.14) (0.12) (0.08)

by contract with the auctioneer from bidding in the auction. This is the protection that the auctioneer offers to prospective buyers to ensure that they are not being artificially bid up. If you sit through an auction you will find that every item is hammered down and treated as if it were sold.2 Only after the auction does the auctioneer reveal whether and

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Art auctions  21 at what price an item may have actually been sold. That is, the auctioneers do not reveal the reserve price and they make it as difficult as they can for bidders to infer it. Although the above description outlines commonly accepted practice in auctions, many people describe them differently. For example, one prominent economist states, ‘the auctioneer begins with the lowest acceptable price – the reserve price – and proceeds to solicit successively higher bids from the customers until no one will increase the bid. Then the item is ‘“knocked down” (sold) to the highest bidder’ (Milgrom 1989, p. 8). Real auctioneers do not reveal the reserve price in this way, and many knocked-down items may be unsold. In another example, Graham and Marshall (1987, p. 1221) state that, ‘when the bidding stops, the auctioneer will generate a false or phantom higher bid if he feels that the high bidder is “good for another bump”’. However, inventing fictitious bids above the reserve price is certainly unethical and probably illegal. Since the auctioneer’s rules are known to an entire array of personnel who often move on to become bidders or their agents, it is difficult for an auction house to engage systematically in the generation of fictitious bids above the reserve price over long periods. Indeed, the litigation by the US Department of Justice over price-fixing engaged in by Sotheby’s and Christie’s, where the chairman of Sotheby’s was convicted, demonstrates how difficult it can be to avoid the detection of collusion. Any auction house that values its reputation – and the long-run profits its reputation secures – has an incentive to avoid this practice.3 Secret reserve prices and high buy-in rates have some interesting implications for the theoretical study of auctions. In the optimal auctions model of Riley and Samuelson (1981), for example, the reserve price serves to extract a slightly higher price from the bidder with the highest valuation of the item on offer.4 The reason for this is that in an English auction the seller only receives an amount equal to the second highest valuation placed on the object among the bidders. By setting a reserve price the seller takes a chance on extracting part of the valuation gap between the two bidders with the highest valuations in exchange for the risk of losing the sale altogether. However, this optimal auctions model is probably not of much help in understanding how reserve prices are set in most auctions. First, since it is a dominant strategy for each bidder in an English auction to bid up to their true valuation of the object, the optimal reserve price is identical no matter whether it is kept secret or not. This model therefore offers no explanation of why the reserve price should be secret. Second, in the optimal auctions model the reserve price is independent of the number of bidders. It follows that the probability that an item will be sold increases with the number of bidders. However, buy-in rates are very high for some types of items despite a large number of bidders. Moreover, buy-in rates differ systematically across types of items in a manner that is almost certainly not related to the number of bidders in these auctions. It seems very unlikely that actual buy-in rates can be explained primarily by the considerations important in the optimal auctions literature. A likely explanation for the secrecy surrounding reserve prices is that it serves to thwart rings.5 There is always random variation in the interest and turnout of bidders; when the turnout is low, some sellers may prefer that their goods be bought in and offered for sale at a later date rather than risk a collusive ring bidding to depress the item’s price. The auctioneer may also engage in other practices that weaken rings. For example, the auctioneer typically does not reveal the identity of the purchaser, if there was one, and

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22  Handbook of cultural economics this creates strong incentives for the ring members to bid privately in opposition to the interests of the ring. An explanation for the key determinants of the seller’s reserve price may be found in models of search (Mortensen 1970), where the seller may expect to offer the item at auction more than once, or even to sell it privately to a dealer as an alternative. The highest observed price in a particular auction may be thought of as a job offer which will be accepted only if it exceeds the reserve price. In these models there is a natural rate of unemployment that may well be related to the normal buy-in rate that characterizes auction markets.

COMPETITION AMONG AUCTION HOUSES It is sometimes said that the auctioneers at Christie’s (now owned by a French company) are gentlemen who try to act like businessmen, while the auctioneers at Sotheby’s (now owned by Americans) are businessmen who try to act like gentlemen. There is no doubt an element of truth to this characterization of the style of these two auction houses. The competition among auctioneers is more than a matter of style, however. The auction business is an interesting example of an industry where the cost of building a reputation may act as a significant entry barrier to new competitors. Surprisingly little attention has been paid in the literature about auctions to the role of the auctioneer. In principle the auctioneer acts on behalf of the seller, but the auction house typically receives compensation from both the buyer and the seller for items that are sold. The buyer’s premium is a percentage of the sale price paid to the auctioneer by the buyer. For many years, the buyer’s premium varied from 10 to 25 per cent of the sale price, typically being a lower fraction of higher-valued sales. However, houses have increased buyer’s premiums in that the lower bound for art (other than for Internetonly sales) at most locations is now 13.5 per cent at Christie’s and 13.9 per cent at Sotheby’s. This use of a sliding scale by value for the buyer’s premium is a recent innovation. It seems likely that competitive pressures among the major auction houses resulted in this change in the scale, as it is more likely to represent the real selling costs of an item. However, it is almost certainly also because more of the auction houses’ revenues have, in recent years, derived from the buyer’s side of the market. Table 2.2 lists the buyer’s premium for Christie’s and Sotheby’s in March 2019. The amount is generally not negotiable. Interestingly, Sotheby’s experimented with no buyers’ commissions for online sales in late 2017 in order to establish dominance in the highly competitive Internet market, but brought back commissions for online sales less than six months later. The seller’s commission is a percentage of the sale price paid to the auctioneer by the seller. It varies with the type, and importance, of the item being sold, ranging from 15 per cent for wine to as little as 5 per cent or less for some types of paintings. Furthermore, auction houses operate a sliding scale for commission rates, based on total annual sales. Thus, with a buyer’s commission of 25 per cent and a seller’s commission of 5 per cent, if a painting is sold at an auction for a hammer price of $100 the buyer will pay $125 to the auctioneer, and the seller will receive $95 from the auctioneer, giving the auctioneer a gross revenue of $30.

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Art auctions  23 Table 2.2  Buyer’s commissions for selected locations at Christie’s (C) and Sotheby’s (S) auction houses (effective 1 February 2019 for Christie’s and effective 25 February 2019 for Sotheby’s) Amount of Hammer Price

Buyer’s Commission (%)

London

Up to £225 000 Above £225 000–£3 million Above £3 million

(London wine)

All amounts

Paris

Up to €200 000* Above €200 000–€2.5 million* Above €2.5 million

New York

Up to US$300 000** Above US$300 000–US$4 million** Above US$4 million

(New York wine)

All amounts

Hong Kong

Up to HK$2.5 million*** Above HK$2.5 million–HK$30 million*** Above HK$30 million (C) Above HK$31 million (S)

25.0 20.0 13.5 (C) 13.9 (S) 22.5 (C) 21 (S) 25.0 20.0 13.5 (C) 13.9 (S) 25.0 20.0 13.5 (C) 13.9 (S) 25.0 (C) 24.0 (S) 25.0 20.0 13.5 (C) 13.9 (S)

Notes: * The cut-off at Sotheby’s is €250 000 rather than €200 000. ** The cut-off at Sotheby’s is US$400 000 rather than US$300 000. *** The cut-off at Sotheby’s is HK$3.5 million rather than HK$2.5 million.

If an item goes unsold, the auctioneer will receive neither a buyer’s premium nor a seller’s commission. To make sure the seller bears some of the cost of auctioning but not selling an item, auctioneers usually charge the seller a fee on unsold items. This fee is often a percentage of the reserve price set by the seller, which obviously gives the seller an incentive to keep the reserve price low. In addition, some auction houses will not allow a seller to put up an easily recognized item for resale until some time has passed. Sometimes it is claimed that when an advertised item goes unsold, its future value will be affected. Such items are said to have been burned. Beggs and Graddy (2008) find that paintings that have failed between sales return about 30 per cent less than other paintings. Whether failure at auction causes the lower price is still open to debate. While paintings may sell for less after they fail at auction, it is not at all clear that the failure caused the lower price. Changes in the seller’s reserve price – perhaps owing to a previous failure – can cause final observed prices to be either higher or lower after an item fails to sell, in which case observed price changes are not caused directly by failure, but result from sample selection. Lower prices may also be observed owing to downward price trends when an artist falls out of fashion, or for other idiosyncratic reasons.

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24  Handbook of cultural economics When bidders have independent private valuations of the items on offer, as in Riley and Samuelson (1981), the failure of an item to sell should not influence its future saleability either at auction or privately. However, in models where bidder valuations are correlated, as in Milgrom and Weber (1982), the failure of an item to sell is informative about the value it might achieve in another sale. If an object can be burned, the assumption of correlated valuations becomes more appropriate. It is not clear whether paintings really are burned – that is, whether their failure to sell has caused a price decrease – or whether this is a fiction invented to encourage sellers to be satisfied with lower reserve prices. Most auction houses now collect a much larger part of their revenues from the buyer’s premium than was true in the past. The most commonly given reason is that auction houses have been increasingly forced to bargain down the size of the seller’s commission when they deal with large consignors. Since it is far more difficult for a large number of small buyers to bargain effectively, the buyer’s premium has provided a new source of revenue. This suggests that real bargaining costs have changed in recent years. Since Christie’s and Sotheby’s operate much as a duopoly in respect of the sale of major works of art, there is a strong incentive for them to collude in the setting of sellers’ commissions. Evidence of their collusion emerged in the major criminal trial of Alfred Taubman, chairman of Sotheby’s, in New York City, who was found guilty of price-fixing in 2001. (Price-fixing is a criminal offence in the United States, and penalties may include both incarceration and monetary fines.) Testimony in the trial by the former president of Sotheby’s indicated that executives anticipated higher profits as a result of collusion that were in the tens of millions of dollars. Ashenfelter and Graddy (2005) provide an economic analysis of this price-fixing scandal. With or without collusion, this duopoly is very much as alive today as it was over 20 years ago. According to The Art Newspaper, Christie’s and Sotheby’s together sell more than 80 per cent of art priced over $1 million at auction (Gammon 2018).

THE DECLINING PRICE ANOMALY The empirical study of auctions has led to findings that have challenged some theories of auction behaviour and also led to new theoretical work. One of the most prominent examples is the discovery of what is now called the declining price anomaly in wine auctions by Ashenfelter (1989). The existence of this anomaly has now been found in the sale of many other items, including paintings (Beggs and Graddy 1997), condominiums (Ashenfelter and Genesove 1992) and cattle (Engelbrecht-Wiggans and Kahn 1992). Although not much discussed, it seems to be common knowledge among auctioneers that, when identical lots of wine are sold in a single auction, prices are more likely to decline than to increase with later lots. This does not mean that price declines always occur, but they are far more common than would be expected by chance alone. Most auctioneers are aware that later bidders on similar items are more likely to pay lower prices, but they are uncomfortable about revealing this information to uninformed bidders. Apparently most bidders, similar to economists, expect to see identical items sold at identical prices. When inexperienced bidders see exceptions to this rule they may think something unethical is going on. As a result, auctions are

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Art auctions  25 set up to disguise this regularity. For example, the auctioneer will ­usually offer smaller lots of the same item before larger lots. Since most bidders see nothing anomalous in quantity discounts, declining per unit prices seem more acceptable. Auctioneers have another device for limiting the extent to which bidders are likely to see price declines for identical items. When a series of lots of identical items is offered, the winning bidder on the first lot has the option of immediately taking all the subsequent lots at the same price.6 This rule has two effects. For a bidder who wants some (but not all) of the items on offer, it increases the risk of waiting for the lower prices that may materialize with later lots. Risk-averse buyers are thus forced to pay a real price for any attempt to exploit the typical pattern of price declines: they may lose the opportunity to buy any of the lots they want. Thus this rule increases the seller’s revenue as long as there are risk-averse buyers. In addition, since the option to purchase several lots is often exercised, bidders will in this case see a uniform price for all items. These results suggest that risk aversion or quantity constraints play a significant role in real auction markets. Indeed, assuming bidders are risk averse may simply be a convenient analytical device for dealing with the fact that many bidders at auctions are buying to fill orders and are effectively quantity constrained. The mechanism used in practice by the auctioneers that gives the first buyer the option to purchase subsequent lots at an identical price is clearly related to the optimal auction design suggested by Maskin and Riley (1984) when there are risk-averse bidders. Since the first discussion of the declining price anomaly in Ashenfelter (1989), over 30 papers have been published on this subject, trying to explain the anomaly and documenting the anomaly in other auction markets.

AUCTIONEERS AND ACCURATE INFORMATION The theoretical literature about auctions emphasizes that there are good reasons for auctioneers to provide truthful information about the items being sold (Milgrom and Weber 1982). The idea is that revealing information tends to remove uncertainty and make low bidders more aggressive; this puts upward pressure on the bidding of others, which is in the interest of the auctioneer. It may seem surprising to some, but auctioneers do appear to act consistently with this prediction. For example, auction houses typically go to considerable effort to estimate the price that an item offered for sale will fetch. Predicting the price at which a unique item will sell requires considerable expertise, so it is of some interest to see just how good these predictions are. The usual practice is for the auctioneer to provide a high estimate and a low estimate in an auction catalogue. Ashenfelter’s (1989) results generally show that auction houses are truthful; the average of the auctioneer’s high and low estimates is very highly correlated with the price actually received. Furthermore, Abowd and Ashenfelter (1988) find that auctioneer’s price estimates are far better predictors of prices fetched than hedonic price functions. The details of the arrangements for price fixing revealed by Diana Brooks, the chief executive officer of Sotheby’s, during the Christie’s–Sotheby’s price-fixing trial provide further insight into the role of experts at auction houses. Brooks reported that at one point her boss, Chairman Alfred Taubman, proposed that the auction houses collude in providing clients with similar estimates of the value of their art. Brooks reported that this was

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26  Handbook of cultural economics impossible because she could not simply tell Christie’s departmental experts, who produce the estimates, to do a dishonest job without causing a breakdown in the conspiracy. Since Abowd and Ashenfelter (1988) was published, many papers have looked at the issue of whether presale estimates are truly unbiased. Some of this research has found systematic over- and under-valuation, based on various characteristics of the items being sold. However, in most of these papers the biases are small and appear unintentional. The one exception to this body of work is Mei and Moses (2005), who conclude that estimates for expensive paintings are intentionally biased upwards in order to increase revenue. More recently, however, McAndrew et al. (2012) have found that once unsold items are taken into account, the auction house estimates are unbiased. In summary, auctioneers do seem to provide genuine expertise in predicting prices. Perhaps honesty is an auctioneer’s most profitable policy rule.

ANCHORING EFFECTS IN ART AUCTIONS Suppose two Matisse paintings with identical characteristics were put up for sale, but one of the paintings had previously been sold in a hot market for a high price and the other had been sold in a cold market for a low price. Would the painting that previously sold in the hot market fetch a higher price at auction? The anchoring effect, classically described by Amos Tversky and Daniel Kahneman (1974), is one of the most powerful and well-established biases in laboratory experiments. Beggs and Graddy (2009) show that this effect also occurs in art markets. Using data on both Impressionist and contemporary art, Beggs and Graddy’s (2009) work finds that the current price is influenced by the previous price. In an auction environment, this implies that bidders are anchoring their bids (either on the previous price or the presale estimate). The evidence does not, however, confirm whether sellers and auctioneers are also anchoring or are simply responding to anchoring on the part of the bidders.

THE INFORMATION IN AUCTION RESULTS: AN EXTERNALITY Some of the most fascinating stories about auctions involve the surprising discovery of a highly valued artwork in an auction where prices were expected to be very low. This type of story illustrates one way that regular auctions confer information benefits that are typically not captured by the profits of the auctioneer. In effect, the presence of an auction system provides a way for an uninformed seller to obtain approximately the market value for the items they own without the necessity of becoming informed. As long as there are two well-informed buyers in the room who do not collude, the price the object attains will be the same as if the seller was well informed in the first instance. The value of a public auction system as protection for uninformed sellers has long been understood in Europe, but it is not widely appreciated in the United States. In both Sweden and Austria, for example, auction houses have sometimes been run as state-owned

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Art auctions  27 monopolies. The major auction houses in both the United States and England are not state-owned, but they are watched with care by institutions such as the Metropolitan Museum of Art, which disposes of its property only through public auctions. As described in this chapter, data and prices from art auctions can also be used to study and understand the intricacies of auctions and competition. Furthermore, data from art auctions, combined with econometric techniques, can be used to answer questions about art. For example, both Graddy (2013) and Ginsburgh and Weyers (2008) have used auction data to determine whether the rankings of the art critic, Roger de Piles, have withstood the test of time. More recently, Graddy and Lieberman (2018) have used data from art auctions to determine whether or not prices are significantly higher or lower for works created after the artist experiences the death of a family or friend, compared with works produced at other times during the artist’s life. Data from art auctions, combined with methodology from the field of economics, provide a rich and unusual method for answering many questions, in both economics and the arts. The main problem is that the public auction system provides a valuable method for setting and determining values, but these values can also be used for determining prices in transactions outside the auction system. That is, the auction system allows traders to make private transactions outside the auction system, but if everyone traded in this way there would be no auctions in the first place. It is probable that the inability of auctioneers to capture a significant part of the benefits of the information they produce leads to less use of the auction system than is optimal for society.

NOTES 1. What is called an English auction is actually Roman. The word auction comes from the Latin auctio, which means to ascend. 2. There are exceptions to this rule. In New York City the auctioneer is legally required to state whether an item has been sold at the conclusion of the bidding. When an item goes unsold, the auctioneer announces that the item has been passed by. This rule was promulgated after it was revealed publicly that an auction in the early 1980s consisted primarily of unsold paintings and a lawsuit was filed by their owner against Christie’s. The New York auctioneers did not reveal this information before this rule was promulgated, and they usually do not reveal this information in other locations except where required by law. 3. It should be appreciated that an auctioneer faces a real trade-off in deciding whether to follow the standard ethical auction practices. If the auctioneer gains a reputation for following these practices, he receives the benefit that buyers will reveal their true valuations of the items put up for sale and this results in higher prices for the buyers (and higher commissions for the auctioneers). Many sellers try to give the impression that they follow standard auction practices even when they do not, apparently because they believe that it increases their sale prices to uninformed buyers. Some of the most amusing examples of this practice are depicted by the home-shopping clubs broadcast on late-night cable television. This kind of cheating seems to be endemic to any kind of economic activity where reputations are valuable. 4. The term reserve price is an unfortunate choice of words in this context. In reality virtually every seller has some price below which they would not agree to sell an object; the theory of optimal auctions indicates why, for strategic reasons, a seller should set a reserve price that is strictly higher than the minimum price for which they would sell the object. 5. Merriam-Webster Dictionary defines a ring as ‘An exclusive combination of persons for a selfish, and often corrupt, purpose, as to control the market’. 6. Since the buyer must exercise this option immediately, this rule does not establish an option value for risk-neutral traders which could be used to explain the price decline anomaly. Here is the reason. Since the option expires as soon as it is purchased, it is only of value if it is exercised. If it is exercised, however, there will be no price decline. Thus the existence of an option value is not consistent with the price declines.

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28  Handbook of cultural economics

SEE ALSO: Chapter 3: Art dealers; Chapter 34: Intermediaries; Chapter 49: Pricing the arts.

REFERENCES Abowd, J. and O. Ashenfelter (1988), ‘Art auctions: price indices and sale rates for Impressionist and contemporary pictures’, mimeo, Department of Economics, Princeton University. Ashenfelter, O. (1989), ‘How auctions work for wine and art’, Journal of Economic Perspectives, 3 (3), 23–36. Ashenfelter, O. and D. Genesove (1992), ‘Testing for price anomalies in real-estate auctions’, American Economic Review, 82 (2), 501–5. Ashenfelter, O. and K. Graddy (2003), ‘Auctions and the price of art’, Journal of Economic Literature, 41 (3), 763–87. Ashenfelter, O. and K. Graddy (2005), ‘Anatomy of the rise and fall of a price-fixing conspiracy: auctions at Sotheby’s and Christie’s’, Journal of Competition law and Economics, 1 (1), 3–20. Ashenfelter, O. and K. Graddy (2011), ‘Sale rates and price movements in art auctions’, American Economic Review Papers and Proceedings, 101 (3), 212–16. Beggs, A. and K. Graddy (1997), ‘Declining values and the afternoon effect: evidence from art auctions’, Rand Journal of Economics, 28 (3), 544–65. Beggs, A. and K. Graddy (2008), ‘Failure to meet the reserve price: the impact on the returns to art’, Journal of Cultural Economics, 32 (4), 301–20. Beggs, A. and K. Graddy (2009), ‘Anchoring effects: evidence from art auctions’, American Economic Review, 99 (3), 1027–39. Engelbrecht-Wiggans, R. and C. Kahn (1992), ‘An empirical analysis of dairy cattle auctions’, mimeo, University of Illinois. Gammon, M. (2018), ‘Why the Christie’s and Sotheby’s duopoly is impregnable’, The Art Newspaper, 22 November. Ginsburgh, V. and S. Weyers (2008), ‘On the contemporaneousness of Roger de Piles’ Balance des Peintres’, in S.E. Cullenberg, J.W. Childers and J. Amariglio (eds), Sublime Economy: On the Intersection of Art and Economics, London: Routledge, pp. 112‒23. Graddy, K. (2013), ‘Taste endures! The rankings of Roger de Piles (1709) and three centuries of art prices’, Journal of Economic History, 73 (September), 765–90. Graddy, K. and C. Lieberman (2018), ‘Death, bereavement, and creativity’, Management Science, 64 (10), 4505–14. Graham, D.A. and R.C. Marshall (1987), ‘Collusive bidder behavior at single-object second-price and English auctions’, Journal of Political Economy, December, 95 (December), 1217–39. Maskin, E. and J. Riley (1984), ‘Optimal auction with risk averse buyers’, Econometrica, 52 (November), 1473–518. McAndrew, C., J.L. Smith and R. Thompson (2012), ‘The impact of reservation prices on the perceived bias of expert appraisals of fine art’, Journal of Applied Econometrics, 27 (2), 235–52. Mei, J. and M. Moses (2005), ‘Vested interest and biased price estimates: evidence from an auction market’, Journal of Finance, 60 (5), 2409–36. Milgrom, P.R. (1989), ‘Auctions and bidding: a primer’, Journal of Economic Perspectives, 3 (3), 3–22 Milgrom, P.R. and R.J. Weber (1982), ‘A theory of auctions and competitive bidding’, Econometrica, 50 (September), 1089–122. Mortensen, D.T. (1970), ‘Job search, the duration of unemployment, and the Phillips curve’, American Economic Review, 60 (December), 847–62. Riley, J.C. and W.F. Samuelson (1981), ‘Optimal auctions’, American Economic Review, 71 (June), 381–92. Tversky, A. and D. Kahneman (1974), ‘Judgment under uncertainty: huristics and biases’, Science, 185 (4157), 1124–31.

FURTHER READING Ashenfelter (1989) and Ashenfelter and Graddy (2003, 2011) are recommended further reading.

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3.  Art dealers

Olav Velthuis

In 2018, the size of the art market was estimated to be US$67.4 billion worldwide. This number includes fine art as well as decorative arts and antiques. Geographically, the art market is dominated by the United States (44 per cent of all sales), followed by the United Kingdom (21 per cent) and China, an art market which was almost non-existent until the new millennium but now accounts for 19 per cent of global sales (McAndrew 2019). Art dealers mediate supply and demand on art markets. According to estimates, around 300 000 art dealers are active around the globe. Most of them are small-scale enterprises employing only few people, with a single owner who also operates as managing director. However, some of the dealers are medium-sized enterprises, with branches all over the world and over 100 people on the payroll. Apart from labour costs, the main expenses art dealers incur are rent and the inventory they may have in case they sell from stock (Shubik 2003). Given their private nature and the absence of public listings, little is known with certainty regarding art dealers’ revenue and profit rates, but surveys suggest that many of them are financially weak. Forty-three per cent of all dealers worldwide have annual sales of less than 500 000 dollars, and only 2 per cent sales of more than US$50 million (McAndrew 2019; see also Benhamou et al. 2002). While sales have increased for dealers with high turnovers (over $1 million), those of smaller dealers have shrunk dramatically, suggesting a winner-take-all trend.

COMPETITION AMONG ART DEALERS The market for dealers is highly competitive. In major art capitals such as New York, London or Berlin, several hundred dealers are active. Barriers of entry tend to be low: in most countries, no special licences or diplomas need to be obtained for an art dealer to start a business, while start-up costs are relatively low as well. Some private dealers simply work out of their own homes. Competition in art markets is rarely on price, but instead focuses on product. This means that dealers permanently seek to get access to valuable works of art; information about the whereabouts of these works and the willingness of their owners to part with them is a key asset of any dealer. Dealers also compete over potential clients. They permanently try to create loyalty and trust relationships with these clients in order to ensure that they repeatedly buy art with them. Cultural economics has focused on financial motives for buying art (for example, art as an investment, a store of wealth or as a hedge against inflation) but at least two other motivational categories can be distinguished: motivations related to the work of art itself (for example, its artistic or aesthetic value) and social motivations (Moulin 1967 [1987]). By buying art, people may, for instance, try to gain access to a social circle, such as a group of collectors who regularly buy at the same art gallery and meet each other at art world events (Hutter et al. 2007). Buying art may also contribute to creating individual 29

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30  Handbook of cultural economics and group identities or may generate status. In that respect, art is a form of conspicuous consumption, as Veblen (1899 [1994]) stated. Properties that are extrinsic to the work of art, such as its high price or the exclusive venue where it is bought, can make a work of art all the more attractive for such status-orientated buyers. At the lower end of the market, however, art dealers may cater to the demand of a relatively anonymous group of buyers who are interested in acquiring a piece for decorative reasons or, for example, as a souvenir of a tourist trip. Although these three sets of motives can be distinguished in theory, in practice, a mixture of all three tends to be relevant for acquiring art. The lower return on paintings compared with other financial assets, has been interpreted as evidence of motives other than the merely financial: the lesser financial return is compensated by the artistic, decorative, aesthetic or status value which buyers derive from buying a work of art. The specific motivation of buyers is one of the key factors shaping competition on art markets. At one extreme, for a buyer who seeks to build up or complete a collection focusing on, for example, one specific artist or time period, few substitutes exist. He or she may be exclusively interested in one particular piece of art made by an artist of their liking, executed in a specific style and depicting a specific subject matter. The supply curve is in this case fully inelastic. The same holds for a status-orientated buyer who wants to own a well-known trophy work by a celebrity artist such as Jeff Koons or Damien Hirst (Graw 2009). This may be one of the explanations for stardom phenomena within the art market, suggesting that variations in talent coincide with more than proportional variations in income (Adler 1985; Candela et al. 2016). That is, the art market should not be seen as a single market but as a large set of monopolistic or, in the case of few interested buyers, monopsonistic markets (see, for example, Moulin 1967 [1987]). At the other extreme, substitutability may be almost perfect in wholesale markets for art where, generally, mass-produced, anonymous paintings and multiples are exchanged between parties such as hotel chains or tourist retail stores and art production companies (Fitz Gibbon 1987). In those companies, which frequently have their production facilities in China, art is produced in an assembly-line fashion, with many employees working on the same pieces of art, according to a strict division of labour in order to increase productivity. The wholesale trade of these paintings frequently takes place through the Internet or on specialized annual trade fairs. In between both extremes, different levels of substitutability can be found within art markets: a collector may, for instance, be interested in owning a work by Andy Warhol, without a strong preference for one work in particular. Substitutability may be more extensive for a buyer who is merely interested in art for decorative purposes. He or she will consider buying work made by a variety of artists, as long as the subject matter is pleasing to them and the colours ‘go with the couch’. Likewise, a starting collector may not have a fully developed taste or may have only decided that he or she will be buying contemporary rather than modern or pre-modern art, without a strong preference for specific works or specific artists.

SEGMENTING ART MARKETS Art markets can be segmented in different ways. First, on the basis of the type of art that is sold: commercial versus non-commercial, traditional versus avant-garde, official versus

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Art dealers  31 informal, bourgeois versus intellectual art, or, as the French sociologist Pierre Bourdieu calls it, the ‘immediate, temporary success of best-sellers’ versus ‘deferred, lasting success of “classics”’ (Bourdieu 1993). Secondly, art dealers can be active in the primary and/or the secondary markets for art (Zorloni 2013). On the primary market, new works of art created by living artists are sold. Dealers tend to represent a limited number of artists, usually 10–30, on a long-term basis. In 2018, 63 per cent of sales of primary market dealers were generated by their top three artists and 43 per cent by their single most successful artist (McAndrew 2019). Profits generated by these artists are frequently used to cross-subsidize the careers of other artists the dealer represents. Dealers on the primary market usually work on a consignment basis: the artist does not sell his or her work to the gallery but consigns it for a solo or group exhibition. In the event that the work is sold, the proceeds are divided according to a pre-established ratio. For starting artists, this ratio tends to be 50:50, but once the artist becomes successful he or she may bargain his or her share up. If the work remains unsold, the dealer can either keep it in his or her inventory, without transfer of property rights, or the artist can take the work back. In these consignment relationships, risk, which is high given the uncertain economic value of art, is shared between artist and dealer. As Richard Caves (2000, p. 39) puts it, the relationship between an artist and a dealer resembles a joint venture more than a principal–agent relationship. A second advantage for a dealer to sell art on the basis of consignments relates to capital intensity: since the dealer does not need to buy the works he or she offers for sale, the dealer does not tie up capital in inventory. Access to capital is one of the main problems dealers face, given that banks are usually unwilling to finance them because of the (perceived) high risks (McAndrew 2019). Although standard, legally binding contracts exist for consignment relationships, these are often conducted without them. The reason is that complete terms cannot be stated in a contract. First, an artist cannot be contractually enforced to continue producing valuable works of art in the future. Second, if a contract were written up, it is difficult for one party to monitor the other and ensure that all terms of the contract are complied with. Third, litigation is expensive if there is a breach of contract and may damage the reputation of both artist and gallerist. Transaction costs involved in developing a contract, monitoring and litigation are high for consignments (Velthuis 2005). Finally, it is questionable if a dealer can expect financial compensation from successful litigation. In the absence of complete contracts, dealers often try to engage in long-term trust relationships with their artists. As Caves (2000, p. 41) argues: ‘The infeasibility of explicit contracting leads the parties into the language of moral obligation, with reputation the insurance of reasonable performance in the absence of legally binding obligations.’ Apart from using consignments, dealers in the primary market have occasionally employed artists to make copies of a popular original image. In the history of art, we also find courts and patrons employing artists. Currently, employment relationships are only observed at the lower end of the market, for junk art (Zorloni 2013), where art is sold by art gallery chains or art wholesalers. The artists they employ produce standardized artworks in semi-mass production. Dealers may also acquire works directly from artists. After property rights are transferred, it is at the dealers’ discretion when and for how much they sell the work. For instance, the dealer may decide to keep artworks in his or her inventory if he or she wants to speculate on future rises in the price of an artist’s work, as many

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32  Handbook of cultural economics dealers did in the past (Fitzgerald 1995). Some well-capitalized dealers still buy works directly from artists if they consider the market for these works to be firmly established. On the secondary market, works of art are re-sold. Given that only a small percentage of living artists has an active secondary market, on this market segment works predominantly by deceased artists are traded. On the secondary or resale market, dealers take works on consignment from private collectors, companies or, in some rare cases, from museums. Once the work is sold, the dealer receives a commission. Alternatively, the dealer buys these pieces and subsequently tries to sell them at a profit. In all these instances, the dealer’s profit ultimately relies on informational advantages regarding the value of the work involved in a transaction, the whereabouts of specific works of art, the willingness of potential buyers to pay, or the need of collectors to sell (parts of) their collection owing to what market participants refer to as the three Ds – debt, divorce or death. On the secondary market, dealers compete with auction houses. Sales at public auctions account for 43 per cent of the global market (McAndrew 2019); most cultural economic studies of art markets have focused exclusively on the auction market owing to the availability of auction price data (see, for example, Frey and Eichenberger 1995; Goetzmann et al. 2010; Mei and Moses 2002). Especially after the financial crisis of 2008, auction houses have expanded their business and competed more directly with dealers by engaging in private sales, in which works are not sold publicly, but the auction house privately brokers deals between buyers and sellers. A third way in which art markets are segmented is by geographical scope. At one extreme, markets are generally locally orientated, with local artists catering for the demand of local buyers. The characteristics of the art traded within these markets may be influenced by trends in national or global markets, but is hardly noticed or recognized by the latter (Plattner 1996). At the other extreme are global markets that tend to be concentrated in art capitals such as New York, Berlin or London. Galleries within these capitals often represent artists from many different countries and their clientele may likewise be dispersed geographically. The most important art auctions, which traditionally take place at Christie’s and Sotheby’s in New York in May and November, are similarly marketed globally. The trade in art has always crossed borders. In the sixteenth and seventeenth centuries, artists such as Peter Paul Rubens were travelling through Europe to cater to the demand at courts in France, England and Spain. In the early twentieth century, works made by Italian Renaissance painters and French impressionists were sold to American collectors. In the 1980s, the newly rich Japanese middle class took an interest in Impressionism. Since the late 1990s, however, art markets have become global to an unprecedented extent; they now encompass many more regions than in the past and cross-border flows have expanded (Horowitz 2011). New collectors from Latin America, the former Soviet Union and Asia have entered the art market, while artists from, among others, Mexico, India and China have been sold at international auctions and have been acquired by well-known Western museums and private collectors. Also, market participants now operate more globally than ever before. Auction houses, for instance, have started organizing sales in emerging markets such as Dubai and Hong Kong, while globally operating art dealers have opened up branches or organized exhibitions in those regions.

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Art dealers  33

CREATING DEMAND In whichever market segment (commercial or non-commercial, local or global or primary or secondary) dealers operate, the role of art dealers is to some extent always more complicated than just matching supply and demand. Dealers also function as market-makers, in that they are actively engaged in creating the demand for the works they are offering. While textbook neoclassical economics tends to assume that preferences are fixed, most approaches to art markets assume that appreciating art is an acquired taste and that preferences are shaped socially. This role of dealers in shaping preferences is most prominent on the primary market, when artists have just left the art academy, their work is unknown and usually has little economic value. In order to create this value, art dealers need to promote artists (Velthuis 2005). To do so they regularly organize exhibitions in their exhibition spaces, which usually last six to eight weeks. They bring the work of artists to the attention of art critics and cultural institutions, such as museums, in the hope that these will lend creditability to the artist by acquiring their work, writing about it favourably and exhibiting it in museum shows. From its inception in nineteenth-century France, the modern art market has been a dealer-critic market (White and White 1965). The reason for this is that the value of art cannot be determined objectively and individually, but relies to a large extent on the credibility of the experts involved in the collective evaluation processes which take place within art worlds. Changing tastes and fashions can radically increase or diminish the artistic and economic value of objects within art markets (Bonus and Ronte 1997; Schönfeld and Reinstaller 2007). In sociological terms, the value of art is socially constructed (Velthuis 2003), or, as the French sociologist Pierre Bourdieu (1993) stated, it is a market which is based on the production of belief. In economic terms, expert opinions and judgements serve to reduce information and search costs for economic agents on the market; a collector may economize on these costs if he or she wants to acquire art by taking the judgement of cultural institutions into account. Several empirical studies indicate that the cultural judgement of museum curators and art critics, on the one hand, and the economic judgement of the art market, on the other, are correlated (see, for example, Frey and Pommerehne 1989; Galenson 2000). This can be interpreted in different ways: either collectors derive extra utility from consuming artworks that cultural institutions deem important; or the taste of collectors is directly influenced by the choices of cultural institutions. According to some, this so-called dealer-critic model is increasingly under pressure in art markets. They claim that the role of the (public) expert has been gradually replaced by the (private) collector. In Europe and the United States super-wealthy collectors such as Charles Saatchi or François-Henri Pinault would now determine artistic credibility and reputations through the acquisitions they make (Horowitz 2011; Lind and Velthuis 2012). As a result, the dealer-critic model would be replaced by what Graw (2009) calls a dealer-collector system or what Nachoem Wijnberg and Gerda Gemser (2000) call a market selection system. Within the new regime, expert judgement has less impact on the market. Economic values would determine artistic reputations, instead of the other way around. Unsurprisingly, experts themselves have lamented this (Graw 2009), but so far, no systematic empirical studies have demonstrated that such a shift has indeed taken place.

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34  Handbook of cultural economics

ANOMALIES OF THE MARKET In a number of other respects, art markets deviate dramatically from textbook theory of perfect markets, and demonstrate a number of striking anomalies (Santagata 1995). First, transaction costs are high (David et al. 2013). For instance, at auction, buyers and sellers of works of art may have to pay up to 20 per cent of the sale price as commission. These transaction costs render art less attractive as a financial asset class (as do insurance and storage costs related to art investments). Secondly, if the art market is considered as a financial market, its lack of liquidity is striking. A collector who wants to sell his or her work, owing to an urgent need for cash, may have to wait several months before a dealer is able to broker a sale or before an auction will take place in which the work fits. Art dealers keep works for months, years and, in some cases, decades in inventory before they finally sell it. Also, unlike assets on financial markets, works of art are hardly divisible. Although some attempts have been made to securitize art (Velthuis and Coslor 2012) and artworks are regularly bought by consortia of dealers and investors, it is generally impossible to buy, for example, a one-hundredth share in a painting by Rembrandt. Thirdly, the art market is characterized by a lack of transparency. Information regarding the quality of the art supplied or the willingness to pay on the part of buyers is incomplete, difficult and often expensive to gather. Prices for which art dealers sell works of art are frequently unknown. For instance, of the ten, allegedly, most expensive painting ever sold, only three were sold at auction; the other seven were sold privately. This means that sales prices have not been disclosed officially. Similarly, sales prices at contemporary art galleries are difficult to obtain, and frequently deviate from listed prices owing to the habit of awarding discounts (Velthuis 2005). As a result of the lack of transparency, information asymmetries abound on the art market. Some participants may, for instance, have better knowledge about the authorship, authenticity or provenance of a work of art than do their competitors, which enables them to make excess returns. For instance, a work may be sold at auction as a work painted by a member of Rembrandt’s studio, while some parties may have information indicating that the work has been painted by Rembrandt himself. The New York art dealer Duveen made handsome profits on the trade of Italian Renaissance artists in the early twentieth century through his famous partnership with art historian Bernard Berenson. Duveen would buy works cheaply and sell them dearly after Berenson had confirmed the authenticity of important Renaissance works or re-attributed them to more famous masters. The widespread existence of information asymmetries provides ample opportunities for fraud and deceit. Forgeries have been created of many old and modern masters; moulds used for sculptures which were promised to be made in an edition of five or ten, have been reused to make more copies, as has happened with other multiples such as etchings. In all these instances, the art market is akin to a market for lemons (Akerlof 1970), where the quality of the work is known to the seller but not to the buyer. Realizing this, interested parties may refrain from buying works of art altogether. In order to prevent this from happening, dealers award certificates of authenticity or hire the services of art experts who should assure buyers of the quality of the works involved. Other forms of fraud, albeit not related to the quality of the work, may, for example, occur if artists sell works out of their studio without paying a commission to a dealer who represents them and who is contractually entitled to a pre-negotiated percentage of each sale. In order

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Art dealers  35 to handle these information asymmetries and the opportunities for deceit they entail, economic interaction on the art market is, unlike the economics textbook’s assumptions, far from anonymous. Participants develop long-term trust relationships which reduce the incentives for mutual deceit (Caves 2000). Finally, it is important to note that in the digital era, the transparency of the art market has been improved considerably by companies that specialize in providing market information such as auction price data (for example, artprice.com or artnet.com). Buyers and sellers may now know instantly what the economic value of a specific artwork is.

CHANGING INFRASTRUCTURE OF THE ART MARKET In many cultural industries, the rise of digital technologies has revolutionized market infrastructures. In particular, platformization and disintermediation have diminished the importance of middlemen and instead allowed for direct exchange between producers and consumers of cultural products (Kenney and Zysman 2016). So far, the impact of disintermediation on art dealers has been relatively weak. Online sales of art now amount to US$6 billion globally, which amounts to 9 per cent of total global sales, and an increase of almost 100 per cent within five years (McAndrew 2019). However, a large part of these sales is conducted through the websites of the art market’s traditional intermediaries, that is, dealers and auction houses. Although platforms such as Artsy have contributed to facilitating discovery for consumers and reducing search costs, they direct clients to dealers’ websites for sales. Several reasons for this limited impact of online sales have been proposed (Khaire 2015). One reason is that the difficulties for consumers in understanding or judging the value of an artwork require physical proximity with the work and dense interactions with the intermediary who seeks to create this value by explaining its meaning and embedding it in art historical narratives. Another reason is that consumers are likely to value buying art as a social and leisure activity in itself. That is, they not only derive utility from the acquisition itself, but also from acquiring the work, and being part of the social scene including vernissages, exclusive dinner parties, and visits to the artist’s studio which the acquisition gives access to. Online platforms have little to offer in that respect. The rise of art fairs has had a more profound impact on the art market and on dealers’ strategies (Baia-Curioni 2012). Currently, hundreds of art fairs are organized around the globe on an annual basis. Up to several hundred art dealers participate in each fair. Dealers rent a booth where they exhibit their highest-quality or best-selling objects to the thousands of potential buyers who pass by over a period of less than a week. Although local fairs do exist, where participants generally have the same nationality, art fairs tend to have an international character. Fairs enable both buyers and collectors to economize on search and information costs; while it would be time-consuming and thus costly for a wealthy collector with high opportunity costs to regularly visit all art galleries in his hometown, let alone in his or her home country or all over the world, the fair brings a large selection of these galleries together. With their many parties, talk shows and busy crowds which allow for celebrity spotting, fairs create a social experience as much as an artistic experience (Moeran and Strandgaard Pedersen 2009). For dealers, art fairs are an important venue to meet new collectors. The share of sales conducted at the fairs has increased from almost non-existent in the early 1990s to 46 per cent of the average

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36  Handbook of cultural economics dealer’s annual revenue currently (McAndrew 2019). Participation in fairs, in particular the most prestigious ones such as Art Basel or the TEFAF in Maastricht, also functions as a reputation or quality signal for dealers (Zorloni 2013). However, fairs are costly, especially for smaller dealers. They frequently incur losses at fairs, and predominantly continue participating because of the signalling and marketing function. In this respect, fairs exacerbate inequality among dealers; while the costs of participating (that is, booth rental, travel, transportation, marketing and insurance costs) are comparable for small, starting and large, established galleries, the revenues of megadealers at the fair tend to be multiple. A steady stream of galleries in the lower and middle segment has closed its doors in the art capitals of Europe and the United States, citing the fair-squeeze as one of the main reasons (McAndrew 2018). Moreover, rents in art capitals have been steeply rising, at a time when, owing to the success of fairs, fewer people still come to visit commercial gallery spaces. It should therefore not come as a surprise that in 2017, more galleries closed than opened worldwide (McAndrew 2018). That year, the number of new entrants to the market was 87 per cent lower than a decade before. Although these trends have been seen as a sign that the art market’s current infrastructure and business models of art dealers have become obsolete, so far no clear alternatives have emerged.

SEE ALSO: Chapter 2: Art auctions; Chapter 34: Intermediaries; Chapter 49: Pricing the arts.

REFERENCES Adler, M. (1985), ‘Stardom and talent’, American Economic Review, 75 (1), 208–12. Akerlof, G.A. (1970), ‘The market for “lemons”: quality uncertainty and the market mechanism’, Quarterly Journal of Economics, 84 (3), 488–500. Baia-Curioni, S. (2012), ‘A fairy tale: the art system globalisation and the fair movement’, in M. Lind and O. Velthuis (eds), Contemporary Art and its Commercial Markets: A Report on Current Conditions and Future Scenarios, Berlin: Sternberg Press, pp. 115–51. Benhamou, F., N. Moureau and D. Sagot-Duvauroux (2002), ‘Opening the Black Box of the White Cube: A survey of French contemporary art galleries at the turn of the Millenium’, Poetics, 30 (4), 263–80, doi:https:// doi.org/10.1016/S0304-422X(02)00024-4. Bonus, H. and D. Ronte (1997), ‘Credibility and economic value in the visual arts’, Journal of Cultural Economics, 21 (2), 103–18. Bourdieu, P. (1993), The Field of Cultural Production: Essays on Art and Literature, Cambridge: Polity Press. Candela, G., M. Castellani, P. Pattitoni and F.M.L. Di Lascio (2016), ‘On Rosen’s and Adler’s Hypotheses in the modern and contemporary visual art market’, Empirical Economics, 51 (1), 415–37. Caves, R. (2000), The Creative Industries, Cambridge, MA: Harvard University Press. David, G., K. Oosterlinck and A. Szafarz (2013), ‘Art market inefficiency’, Economic Letters, 121 (1), 23–5, doi:https://doi.org/10.1016/j.econlet.2013.06.033. Fitz Gibbon, H.M. (1987), ‘From prints to posters: the production of artistic value in a popular world’, Symbolic Interaction, 10 (1), 111–28. Fitzgerald, M.C. (1995), Making Modernism: Picasso and the Creation of the Market for Twentieth-Century Art, New York: Farrar, Straus and Giroux. Frey, B.S. and R. Eichenberger (1995), ‘On the return of art investment return analyses’, Journal of Cultural Economics, 19 (3), 207–20. Frey, B.S. and W.W. Pommerehne (1989), Muses and Markets: Explorations in the Economics of the Arts, Oxford: Blackwell.

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Art dealers  37 Galenson, D.W. (2000), ‘The careers of modern artists’, Journal of Cultural Economics, 24 (2), 87–112. Goetzmann, W., L. Renneboog, and C. Spaenjers (2010), ‘Art and money’, American Economic Review, 101 (3), 222–6. Graw, I. (2009), High Price: Art between the Market and Celebrity Culture, Berlin: Sternberg Press. Horowitz, N. (2011), Art of the Deal: Contemporary Art in a Global Financial Market, Princeton, NJ: Princeton University Press. Hutter, M., Ch. Knebel, G. Pietzner and M. Schäfer (2007), ‘Two games in town: a comparison of dealer and auction prices in contemporary visual arts markets’, Journal of Cultural Economics, 31 (4), 247–61. Kenney, M. and J. Zysman (2016), ‘The Rise of the platform economy’, Issues in Science and Technology, 32 (3), 61–9. Khaire, M. (2015), ‘Art without borders? Online firms and the global art market’, in O. Velthuis and S. Baia Curioni (eds), Cosmopolitan Canvases: The Globalization of Markets for Contemporary Art, Oxford: Oxford University Press, pp. 102–26. Lind, M. and O. Velthuis (eds) (2012), Contemporary Art and its Commercial Markets: A Report on Current Conditions and Future Scenarios, Berlin: Sternberg Press. McAndrew, C. (2018), The Art Market 2018, Basel and Zurich: Art Basel and UBS. McAndrew, C. (2019), The Art Market 2019, Basel and Zurich: Art Basel and UBS. Mei, J. and M. Moses (2002), ‘Art as an Investment and the underperformance of masterpieces’, American Economic Review, 92 (5), 1656–68. Moeran, B. and J. Strandgaard Pedersen (2009), Fairs and Festivals: Negotiating Values in the Creative Industries, Copenhagen: Copenhagen Business School. Moulin, R. (1967), Marché de la peinture en France, 1987 trans. A. Goldhammer, The French Art Market: A Sociological View, New Brunswick, NJ: Rutgers University Press. Plattner, S. (1996), High Art Down Home: An Economic Ethnography of a Local Art Market, Chicago, IL: Chicago University Press. Quemin, A. (2006), ‘Globalization and mixing in the visual arts: an empirical survey of “high culture” and globalization’, International Sociology, 21 (4), 522–50. Santagata, W. (1995), ‘Institutional anomalies in the contemporary art market’, Journal of Cultural Economics, 19 (2), 187–97 Schönfeld, S. and A. Reinstaller (2007), ‘The effects of gallery and artist reputation on prices in the primary market for art: a note’, Journal of Cultural Economics, 31 (2), 143–53. Shubik, M. (2003), ‘Dealers in art’, in R. Towse (ed.), A Handbook of Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 194–200. Veblen, T. (1899), The Theory of the Leisure Class, repr. 1994, New York: Dover. Velthuis, O. (2003), ‘Symbolic meanings of prices: constructing the value of contemporary art in Amsterdam and New York galleries’, Theory and Society, 32 (2), 181–215. Velthuis, O. (2005), Talking Prices: Symbolic Meanings of Prices on the Market for Contemporary Art, Princeton, NJ: Princeton University Press. Velthuis, O. and E. Coslor (2012), ‘Financialization of art markets’, in K. Knorr Cetina and A. Preda (eds), Handbook of the Sociology of Finance, Oxford: Oxford University Press, pp. 369–78. Velthuis, O. and S. Baia Curioni (eds) (2015), Cosmopolitan Canvases: The Globalization of Markets for Contemporary Art, Oxford: Oxford University Press. White, H.C. and C.A. White (1965), Canvases and Careers: Institutional Change in the French Painting World, New York: John Wiley & Sons. Wijnberg, N.M. and G. Gemser (2000), ‘Adding value to innovation: impressionism and the transformation of the selection system in visual arts’, Organization Science, 11 (3), 323–9. Zorloni, A. (2013), The Economics of Contemporary Art, Heidelberg: Springer.

FURTHER READING On the relationship between the primary and the secondary market, see Hutter et al. (2007) and Zorloni (2013). For globalization of art markets, see Quemin (2006) and Velthuis and Baia Curioni (2015). For sociological studies of art dealers and the market, see Moulin (1967 [1987]), Plattner (1996), Velthuis (2005) and White and White (1965). On legal and organizational aspects of the art market, see Caves (2000).

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4.  Artificial intelligence

Joëlle Farchy and Juliette Denis

Artificial intelligence (AI) is a topical issue that is the subject of public debate. While some see it as the promise of a super-humanity, capable of resisting disease and death, or even conquering other planets and bringing human life to them, others predict the mass destruction of jobs or the ruin of a Europe crushed by competition. Research in AI has experienced an unprecedented growth since the 2010s, owing to the combined effects of the rise in computing capacity and the increase of varied and relevant data available for learning. Machine learning is the main way in which AI is developed today, and its performance is directly linked to the data collected. While it generates as many fantasies as concerns, AI is a concept whose very definition is the subject of debate. Artificial intelligence refers to all forms of algorithmic processing which seek to understand how human cognition works and how to reproduce it. It is increasingly being used in a wide range of sectors; for example, tax, national security, media, education, health, insurance, banking, justice, transport and labour. Advances in algorithms and AI, the widespread use of the Internet and connected objects, and the colossal circulation of data of all types have an increasing influence on our lives and our economy. Having experienced early dematerialization, cultural industries and the media are seen as laboratories for emerging business models. Thus, models built around algorithms and large corpuses of data that feed them have multiplied within these sectors. First, this chapter specifies the categories of data used in the cultural sector and the associated regulation issues. Throughout the value chain, there are three main applications of AI: upstream in the creative process; at the consumption level in recommending certain works to users; and at the production level, in order to know the market and predict or provoke success. It is this last point that we develop in a second step because it is at this level that academic work in economics is most numerous. Finally, examples from the field of music, the art market and the audio-visual sector illustrate the different expectations of each sector.

DATA AND DATA REGULATION In the cultural sector, AI mobilizes data in two ways: ● ●

The AI feeds on data to run the algorithms. The AI automatically generates data.

One of the great promises of machine learning is the extraction and processing of large amounts of unstructured data and the production of new data. In particular, natural language processing (NLP), which refers both to a better understanding of natural language 38

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Artificial intelligence  39 and to better rendering of results in natural language, has been greatly improved by AI. On the one hand, on social networks, for example, natural language data analysis makes it possible to track not only the volume of discussions about content, but also the sentiments expressed in those discussions. On the other hand, the automatic generation of simple texts in natural language (Natural-Language Generation) aims to develop computer programmes capable of generating texts from data or text in a language understandable by humans. Three types of data are used: ●

The artworks themselves can be considered as data. Users’ data (demographic characteristics of the user, behaviour such as highlighted passages in a book, and favourite genres of music) allow us to analyse everyone’s tastes and habits. ● In addition to users’ data, which, as in all sectors, allows the personalization of the services offered, content metadata plays a major role in the new services offered. Metadata is information describing a specific piece or creator (duration of the work, rights holder, lyrics of a song, rhythm of a piece of music, texture of a painting, language used in a book, and so on). This metadata, which is sometimes produced internally by the platforms, is also the subject of intense activity by specialized actors in order to check its quality and to enrich it.

●●

In each of the above cases, the questions raised for the regulator are not always the same. For Works, the Question of Intellectual Property From a legal standpoint, intellectual property is at the heart of discussions on the creative economy because it acts as an incentive to produce new works. In the case of creation associated with AI, two new questions are asked. Upstream, AI cannot function without the massive amounts of data that feeds it. Artificial intelligence operators indiscriminately pick data or information that is sometimes protected works or more often than not pieces, parts or extracts whose protection is in question. Owing to the volumes to be processed, the transaction costs of the rights holders’ authorizations are often out of proportion to the prospects of gain. This is why pragmatic and comprehensive solutions to facilitate authorizations for rights holders in the case of mass use are to be sought. Downstream, the algorithm produces new works (output) which are the result of human–machine collaboration, and we can therefore wonder what is the share of creativity of the machine, if this final realization can be qualified as a work of the mind by law and, in this case, who is the author and who is the owner of the rights. For Users’ Data, the Question of Personal Data The European General Data Protection Regulation (GDPR), which came into force on 25 May 2018, reinforces individual protection and makes companies aware of their responsibilities. The intimate nature of the data harvested in the cultural sector means that they should be handled with special care.

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40  Handbook of cultural economics For Metadata and Users’ Data, the Question of Sharing Data The blockages and asymmetries of information in the access to data create new balances of power within the cultural sectors, in favour of the downstream which alone controls the fineness of the knowledge of the customers. Since the most important consumption of cultural contents is now online consumption, it is possible to know everything, but only the downstream of the value chain has these data available – especially platforms. To match supply and demand, to personalize their advertising, to make predictions, recommendations and so on, they need to know precisely how their customers behave. That is why one of the goals of regulation is to prevent and to limit asymmetry of information inside the value chain. Creating metadata on content with algorithms requires access to a database (of songs, movies or artwork). The players in possession of commercial databases, such as major distributors or streaming platforms, therefore have a huge advantage. Given the blockages and asymmetries of information, many voices advocate for a better policy of access, sharing and circulation of data. Should the companies be encouraged to share and gather data in the spirit of entrepreneurial freedom? Should we create sectoral data of general interest or essential facilities? In balance with regard to protections, protection for firms’ investments, protection of privacy and protection of public liberty for citizens, the role of regulation is to support new services and new business models that need to access and share data.

THE ROLE OF ARTIFICIAL INTELLIGENCE IN MAKING APPROPRIATE DECISIONS As the cultural economy is a prototype economy, where uncertainty about demand is particularly high, identifying decision-making tools to limit risk has always been a key focus. A small number of productions attract most of the demand according to the welldocumented model of the superstar economy (Rosen 1981; Benhamou 2002; Anderson 2004). The exploitation of data thanks to algorithms gives new impetus to the ambition to make the appropriate investment decisions, and to support, or even replace the usual human intuitions and expertise by presumably objective analyses of the determinants of the success of a work or an artist. In addition to analysing market trends, one of the promises of AI is to compare, on the basis of the exploitation of historical data, successful content with that in production in order to analyse the keys to success, and possibly to anticipate it. The models can be applied according to the availability of data at various stages of the production process. Before the content is placed on the market, forecasting systems are established based on the intrinsic characteristics of it, particularly in the audio-visual industry, where production risks are high. At the time of marketing, additional data are available such as Internet users’ reactions on social networks or the first consumption data. In academic work, the term predictive, used in many papers, can be confusing. It mixes models in which the objective is to acquire a causal understanding (Hennig-Thurau and Houston 2019), highlighting variables that explain success, and models in which the only

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Artificial intelligence  41 objective is to improve the accuracy of success prediction, without seeking to understand the reasons (Ren and Kauffman 2017). Two very different data analysis techniques are used: ●

Economists have long used quantitative data analysis techniques such as econometrics for explanatory purposes. These techniques involve a priori modelling where the data validate hypotheses or intuitions. ● With machine learning, the purpose is no longer explanatory but performative. The break with traditional quantitative techniques is based on the fact that the modelling is based on the data itself. The performance of the model is not due to its explicability of the results but to its ability to provide a rapid and effective response to the problem at hand. These treatments, based on machine learning, are inherently conservative; they do not anticipate evolutions but reproduce the past in the present or the future to provide results, trends or estimates. It should be noted that, increasingly, more efforts are being devoted to explaining the results obtained with machine learning, instead of seeking the best accuracy at all costs. This is particularly true within the film industry, where it is very important to understand which variables explain a film’s success in order to support long-term decisions.

MUSIC, AUDIO-VISUAL AND ART MARKET: DIFFERENT OBJECTIVES Examples from three sectors illustrate the different objectives that can be pursued. Music: Promoting Future Success by Integrating Users’ Data Analysing musical pieces on the basis of their objective characteristics, using machinelearning algorithms, has become a field of scientific research in its own right with the development of music information retrieval (MIR) systems. Predicting success based on these intrinsic characteristics of content is referred to as ‘Hit song science’ (Pachet 2012), on which various studies have been conducted (Herremans et al. 2014; Pham et al. 2016; Interiano et al. 2018). Since the creation of The Echo Nest and The Million Song Database, researchers, especially those not specialized in music research, have had access to a range of data on musical characteristics (audio, duration, year, artist, genre, and so on) as well as more abstract metadata such as danceability or energy. The Echo Nest’s metadata, calculated by algorithm, is the largest collection of metadata on musical content to date, even if it is not always reliable. In addition, deep learning algorithms outperform manually annotated models to improve forecast performance by allowing automatic extraction of audio characteristics (Choi et al. 2016; Yang et al. 2017). Compared with other applications (especially for recommendation), however, the use of MIR algorithms to predict or detect success characteristics before pieces are released to the market remains relatively unexplored (Herremans et al. 2014). Despite progress, there is no commercial application mature enough to predict with certainty a probable success based solely on the analysis of a piece’s own characteristics. Those who have tried the ‘tube

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42  Handbook of cultural economics factory’ have not succeeded. This is why other researchers or professionals try to predict the success of a song by no longer relying solely on intrinsic metadata, but by including, at the time of release, the first user’s data in order to anticipate a possible success, support it, especially on social networks, and make it last. The way in which these users’ data are produced and made accessible is therefore important. However, the major streaming platforms have a decisive competitive advantage in this field compared with other participants. It is not the millions of songs available in their catalogue but the way they allow their listeners to discover music and transform a track into a hit that constitutes their added value, and a competitive differentiating factor. The users’ data they hold and analyse enable streaming platforms to anticipate success and then amplify it by observing the performance of a title from playlist to playlist, and then promoting it to those with the largest number of subscribers. Thus, being visible on these playlists is fundamental for artists, and the profession of playlist pitcher has emerged in labels with the objective of showing their artists on it. Audio-Visual: Limiting the Risks of Production by Analysing Scenarios In the audio-visual sector, there is a great deal of academic work on predicting success, and on the commercial applications (for example, Scriptbook, Vault and Storyfit) of evaluating the potential of a scenario. In academic work, econometrics was initially favoured for its explanatory power. Following Litman’s (1983) pioneering work on factors that explain film success, publications have increased (Litman and Kohl 1989; Prag and Casavant 1994; De Vany and Walls 1999; Basuroy et al. 2003; Elberse 2007; Nelson and Glotfelty 2012). Among the most frequently selected explanatory variables are those related to the characteristics of the content (genre of the film, subject, presence of star actors, duration, type of scenario, and so on), those corresponding to the conditions of release (number of cinemas in which the film is distributed, how long, release date, advertising, and so on) and variables concerning the reactions of the first audience (first broadcast data and word-of-mouth data). Since the predictive accuracy of econometric models is lower than that of machinelearning algorithms, other tools have been developed, particularly based on the precise analysis of the scenario. When the film is still in a phase where relatively little money has been invested, producers are tempted to evaluate the commercial potential of a new scenario by taking as a reference the box office performance of films deemed similar (Eliashberg et al. 2014). Traditionally, there are rules, more or less intuitive, to determine this potential. Artificial intelligence makes it possible to divide the scenario according to its strengths and weaknesses. Automatic extraction and analysis of metadata has been greatly improved by NLP, which provides guidance for the qualification and more or less automated classification of a scenario, whereas these classifications were usually attained by tedious manual annotations. On the basis of these qualifications, successful film scenarios are compared with those awaiting production. Recent work uses advances in natural language analysis to solve, through machine learning, more surprising questions, such as the anticipation of the classification of a scenario’s degree of violence by supervisory authorities (Martinez et al. 2019). The outcome of the scenario analysis appears to be mixed. The undeniable progress in natural language analysis has led to an increase in the number of commercial offers

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Artificial intelligence  43 whose objective is to automatically (semi-)analyse a scenario on the basis of metadata alone; however, the quality of the results provided has not given rise to sound scientific assessments. In addition, many professionals are reluctant to see the growth of these new tools, fearing the formatting of their work. In the short term, it seems more promising to use data modelling – not to analyse the quality of the scenario itself, but to determine whether there is an audience for a specific scenario by integrating users’ data. Marketing expenses and social media are much more reliable indicators of box office success, although they may come too late to change a movie. The use of AI has been widely adopted by distributors to support marketing and distribution decisions. Systems that make it possible to evaluate the best release dates in cinemas or to customize advertising have proven to be valuable tools, providing granular audience trends. The basic idea is that films with similar intrinsic metadata will attract a similar audience. The Art Market: Improving Price Forecasts to Better Buy or Invest The growth of the art market and the arrival of new collectors have accelerated the demand for transparent and organized information, including at the international level, leading to a proliferation of rankings and other indicators (Moureau 2018). The establishment of the first organized price databases has helped to increase the number of potential investors (Coslor and Spaenjers 2013). The use of this data, in academic work or by specialized companies, opens up the possibility of using automatic learning to evaluate the best investment opportunities. Since Baumol’s pioneering work in 1986, many academic studies have sought to explain, estimate or predict the prices of works, based on statistical or econometric methods. The two methodologies commonly used by researchers to construct price indices are those of repeated sales (Goetzmann 1993; Pesando 1993) and the hedonic regression initiated by Rosen in 1974. After using classic quantitative techniques to analyse prices, research now includes machine learning. More recent work has thus begun to construct indicators on the basis of a larger and more qualitative number of data, extracted automatically. Filipiak et al. (2015), for example, incorporate a semantic approach to automatically extract descriptions that accompany works sold at auction from auction houses’ websites. Since this data is provided in natural language, researchers use annotation and enrichment tools to extract information (signing a table, edition number, and so on). The processing of the visual characteristics of the image (colour, style and composition) also provides solutions for collecting data from the works themselves, which complement the usual metadata. A first study thus proposes to estimate the value of a painting using a machine-learning algorithm (Hosny et al. 2014) that automatically extracts data on the work itself (colour, contrast, presence of a face, and so on); the objective is to integrate the visual characteristics of the work into the price determinants. Several commercial applications also use machine learning to estimate the price of works. The price of the works is the result of a large number of variables that can be integrated into the algorithms. The issue will not so much be the creation of the technology as the collection of data, particularly from the primary market.

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44  Handbook of cultural economics

CONCLUSION In all sectors, beyond the largely unreachable dream of perfectly modelling the keys to success, more prosaic algorithms are already widely used to: identify market trends; facilitate the decision-making of a publisher, producer or collector; or even specify the commercial strategy of a distributor in order to target the audience, expand the potential audience, or optimize the presence of a work or an artist according to the distribution media. As complementary indicators of professional experience, machine-learning algorithms help to better position a project or anticipate public reactions.

SEE ALSO: Chapter 26: Digitization in the cultural industries; Chapter 34: Intermediaries; Chapter 47: Platforms.

REFERENCES Ahlers, M., L. Grünewald-Schukalla, M. Lücke and M. Rauch (2019), Big Data und Musik, Jahrbuch für Musikwirtschafts- und Musikkulturforschung 1/2018 (Big Data and Music, Yearbook for Music Economics and Music Culture Research 1/2018), Wiesbaden: VS Verlag für Sozialwissenschaften. Anderson, C. (2004), ‘The long tail’, Wired Magazine, 1 October, accessed 28 October 2019 at https://www. wired.com/2004/10/tail/. Basuroy, S., S. Chatterjee and S.A. Ravid (2003), ‘How critical are critical reviews? The box office effects of film critics, star power, and budgets’, Journal of Marketing, 67 (4), 103–17. Baumol, W. (1986), ‘Productivity growth, convergence, and welfare: what the long-run data show’, American Economic Review, 76 (5), 1072–85. Benhamou, F. (2002), L’économie du star system (The Star-System Economy), Paris: Éditions Odile Jacob. Choi, K., G. Fazekas and M. Sandler (2016), ‘Automatic tagging using deep convolutional neural networks’, in J. Devaney, M.I. Mande, D. Turnbull and G. Tzanetakis (eds), Proceedings of International Society for Music Information Retrieval (ISMIR), 7–11 August, New York University and Columbia University, New-York: International Society for Music Information Retrieval, pp. 805–11. Coslor, E. and C. Spaenjers (2016), ‘Organizational and epistemic change: the growth of the art investment field’, Accounting, Organizations and Society, 55 (September), 48–62. De Vany, A. and W.D. Walls (1999), ‘Uncertainty in the movie industry: does star power reduce the terror of the box office?’, Journal of Cultural Economics, 23 (4), 285–318. Del Vecchio, M., A. Kharlamov, G. Parry and P. Ganna (2018), ‘The data science of Hollywood: using emotional arcs of movies to drive business model innovation in entertainment industries’, July, accessed 12 May 2019 at https://arxiv.org/abs/1807.02221. Elberse, A. (2007), ‘The power of stars: do star actors drive the success of movies?’, Journal of Marketing, 71 (4), 102–20. Eliashberg, J., K.S. Hui and Z.J. Zhang (2014), ‘Assessing box office performance using movie scripts: a kernelbased approach’, IEEE Transactions on Knowledge and Data Engineering, 26 (11), 2639–48. Farchy, J. and J. Denis (2020), La culture des données: Intelligence artificielle et algorithmes dans les industries culturelles (Data Culture: Artificial Intelligence and Algorithms in Creative Industries), Paris: Presses des Mines. Filipiak, D. and A. Filipowska (2016), ‘Towards data-oriented analysis of the art market: survey and outlook’, Financial Internet Quarterly ‘e-Finanse’, 12 (1), 21–31. Filipiak, D., K. Węcel and A. Filipowska (2015), ‘Semantic annotation to support description of the art market’, in A. Filipowska, R. Verborgh and A. Polleres (eds), Proceedings of the 11th International Conference on Semantic Systems, SEMANTICS 2015, Vienna, Austria, September 15–17, 2015, New York: ACM, pp. 51–4. Goetzmann, W.N. (1993), ‘Accounting for taste: art and the financial markets over three centuries’, American Economic Review, 83 (5), 1370–76. Hennig-Thurau, T. and M.B. Houston (2019), Entertainment Science, Data Analytics and Practical Theory for Movies, Games, Books, and Music, Cham: Springer International.

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Artificial intelligence  45 Herremans, D., D. Martens and K. Sörensen (2014), ‘Dance hit song prediction’, Journal of New Music Research, 43 (3), 291–302. Hosny, A., J. Huang and Y. Wang (2014), ‘The green canvas: art evaluation analytics’, Data Science CS109 Final Project, Fall, accessed 18 March 2019 at http://ahmedhosny.github.io/theGreenCanvas/. Interiano, M., K. Kazemi, L. Wang, J. Yang, Z. Yu and N.L. Komarova (2018), ‘Musical trends and predictability of success in contemporary songs in and out of the top charts’, Royal Society Open Science, 5 (5), accessed 28 October 2019 at https://royalsocietypublishing.org/doi/full/10.1098/rsos.171274. Litman, B.R. (1983), ‘Predicting success of theatrical movies: an empirical study’, Journal of Popular Culture, 16 (4), 159–75. Litman, B.R. and L.S. Kohl (1989), ‘Predicting financial success of motion pictures: the ’80s experience’, Journal of Media Economics, 2 (2), 35–50. Martinez, V.R., K. Somandepalli, K. Singla, A. Ramakrishna, Y.T. Uhls and S. Narayanan (2019), ‘Violence rating prediction from movie scripts’, in Proceedings of the Thirty-Third International AAAI Conference, Honolulu, 27 January–1 February, Palo Alto, CA: AAAI Press. Moureau, N. (2018), ‘Magic index on the wall, who is the most valuable artist of them all?’, in A. Glauser, P. Holder, T. Mazzurana, O. Moeschler, V. Rolle and F. Schultheis (eds), Art & Market, Basingstoke: Palgrave Macmillan. Nelson, R.A. and R. Glotfelty (2012), ‘Movie stars and box office revenues: an empirical analysis’, Journal of Cultural Economics, 36 (2), 141–66. Pachet, F. (2012), ‘Hit song science’, in T. Li, M. Ogihara and G. Tzanetakis (eds), Music Data Mining, New York: Chapman & Hall/CRC Press, pp. 305–26. Pesando, J. (1993), ‘Art as an investment: the market for modern prints’, American Economic Review, 83 (5), 1075–89. Pham, J., E. Kyauk and E. Park (2016), ‘Predicting song popularity’, accessed 11 March 2019 at http://cs229. stanford.edu/proj2015/140_report.pdf. Prag, J. and J. Casavant (1994), ‘An empirical study of the determinants of revenues and marketing expenditures in the motion picture industry’, Journal of Cultural Economics, 18 (3), 217–35. Ren, J. and R.J. Kauffman (2017), ‘Understanding music track popularity in a social network’, in Proceedings of the 25th European Conference on Information Systems ECIS, Guimarães, Portugal, Association for Information System, 5–10 June, pp. 374–88. Rosen, S. (1974), ‘Hedonic prices and implicit markets: product differentiation in pure competition’, Journal of Political Economy, 82 (1), 34–55. Rosen, S. (1981), ‘The economics of superstars’, American Economic Review, 71 (5), 845–58. Yang, L.-C., S.-Y. Chou, J.-Y. Liu, Y.-H. Yang and Y.-A. Chen (2017), ‘Revisiting the problem of audio-based hit song prediction using convolutional neural networks’, in Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New-Orleans, LA, 5–9 March, pp. 621–5.

FURTHER READING For more detailed discussion, see Farchy and Denis (2020), Ahlers et al. (2019) on ‘Big Data’ and music, Del Vecchio et al. (2018) on business models in Hollywood and Filipiak and Filipowska (2016) on the art market.

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5.  Artists’ labour markets Trine Bille

Artists’ earnings and labour market behaviour have been studied for a long time in cultural economics. Early work includes Felton (1980) and Towse (1993). The research has mainly been concentrated around artists’ income conditions, how artists behave on the labour market and the structural conditions in this particular labour market. While the starving-artist image might be exaggerated, most of the literature has shown evidence that many artists do their work under poor income conditions, even though they could probably earn more and have a more comfortable life if they took a non-arts job. The most important questions are the following: is the artists’ labour market different from other labour markets? How is it different? Why is it different? Furthermore, the research is also closely related to policy measures, as another important issue is what policy can do to improve artists’ labour market conditions (if this is a political goal). The following sections give an overview of the literature and the questions the literature has addressed.1 First, the important and difficult question of how to define an artist is discussed, as the answer to this question has implications for the empirical results in any given research study. The following four sections investigate these important themes in the research: the average income of artists, the distribution of income among artists, the impact of education on artists’ income and working conditions. These sections include empirical research as well as theoretical contributions. Finally, policy measures concerning artists’ labour markets are discussed.

DEFINITION OF ARTISTS In order to describe and analyse artists’ labour markets, we need a definition of who should be considered to be an artist. It is clear, that artists constitute an extremely heterogeneous group and, as a consequence, artists are often imperfect substitutes for one another. The theoretical discussion of this topic is closely connected to the question of where to draw the line between professional artists and amateur artists (Becker 1982). The answer is not clear, and the problem is contentious. At the empirical level, the definition of an artist is not straightforward, as there is no single criterion for defining an artist, as is the case, for instance, with a lawyer, a doctor or a teacher. Many artists have multiple jobs – usually related to the arts – and the quality of the artwork (which is difficult to conceptualize, let alone measure; Eliassen et al. 2018) may or may not have an impact on the definition of being an artist. Can a person who spends a lot of time painting be considered an artist, even though he or she cannot make a living from it and is not recognized as an artist among his or her peers? Frey and Pommerehne (1989) have suggested several criteria for defining artists: 46

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Artists’ labour markets  47 ●

the amount of time spent on artistic work; the amount of income derived from artistic activities; ●● the reputation as an artist among the general public; ●● recognition among other artists; ●● the quality of the artistic work produced; ●● membership of a professional artists’ groups or associations; ●● a professional qualification (education) in the arts; or ● the subjective self-evaluation of being an artist. ●●

While some of these criteria are objective and easy to apply and operationalize, others are very subjective and difficult to use for empirical purposes. However, this does not mean that the objective criteria are the valid criteria. In a study, based on a rich data-set for the 3028 visual artists in Denmark, consisting of a combination of register data from Statistics Denmark and data collected in a survey, Baldin and Bille (2018) segmented artists into six classes by using a finite mixture model. The six classes are: professional artists (21 per cent), subsidized artists (14 per cent), aspiring artists (11 per cent), workers related to arts (12 per cent), arts as a hobby (16 per cent) and seniors (26 per cent). These classes combine several variables and reveal different types of artists with particular working and living conditions. Another discussion relates to which art forms to include in the artists group when studies are made on an aggregate level to describe, for example, the general income conditions for artists. The question is relevant, as expanding the definition of artists may change the average artists’ income and other results of the research. A common list includes: actors and directors, announcers, architects, authors, dancers, designers, musicians and ­composers, painters and sculptors, craft artists and photographers (Alper and Wassall 2006; Bille 2012). Up for discussion is whether or not others, for example, announcers and perhaps architects, should be included in the group of artists, and evidence on earnings would show that the labour market conditions, for example, for a visual artist compared with an announcer, differ greatly. While some of these groups are employed and earn a salary in a company (a television station or an architectural firm), many, such as visual artists, are self-employed without any stable job or income.

LOW AVERAGE INCOME AND THE WORK PREFERENCE MODEL Artists’ income and earnings have been studied widely (Throsby 2001). The data for these studies has been census data (mainly in the US and UK, where examples include Filer 1986; O’Brien and Feist 1995; Alper and Wassall 2006), surveys (as in Throsby and Petetskaya 2017) or register data from official statistical sources such as tax authorities, mainly in Scandinavia and the Nordic countries (for example, Karttunen 2001; Bille 2012), often combined and merged with surveys based on a personal identification number (Bille et al. 2017). Register data also have the advantage that they give true panel data with possibilities to study artists’ careers over a longer period of time (as in Bille and Jensen 2016). Independent of the data sources, one of the common conclusions across countries is that the average income of artists is very low, and lower than that for comparably educated

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48  Handbook of cultural economics groups. This has been demonstrated in many empirical studies (see, for example, Alper and Wassall 2006; Throsby and Petetskaya 2017). The important question is, why is it so? Is this income penalty caused by characteristics inherent in the nature of the artistic labour market? Some theoretical explanations can help understanding the phenomenon. The Work Preference Model The most widely applied explanation is the work preference model introduced by David Throsby (1994, 1997). The main hypothesis of the model is that artists are intrinsically driven to create, and therefore they will maximize the time spent working as an artist, subject to the constraint of earning enough income to survive. The utility the artist gets from the artistic work is included in the artist’s labour supply function together with income and leisure. Accordingly, we can talk about the psychic income the artist gets from his or her artistic occupation. Withers (1985) characterized this as the artists subsidizing the arts by accepting low incomes. The model has (in different versions) been subject to empirical testing. The common way to do so is to split the artists’ income into that coming from arts and that obtained in a non-artistic work (sometimes also arts-related work) and then to analyse the relative role of each in determining the artists’ labour supply. Although the argumentation and predictions of the model are widely used, there are only a few empirical tests (for example, Throsby 1994; Caserta and Cuccia 2001; Robinson and Montgomery 2002; Casacuberta and Gandelman 2012; Bille et al. 2017). Most studies have found the following crosselasticities between the arts wage and non-arts wage rates in accordance with the work preference model: 1.  When non-arts wage rates rise, the artists switch to arts work because they can afford to do so once their income constraint has been met; 2.  They also do more arts work when arts wages rise, since they are able to earn the basic income they need and do their chosen arts work. Therefore, if the wage rate in the artistic occupation is lower than that obtainable in a non-artistic job open to the artist and he or she still chooses to work in the arts, that difference in the rate of payment represents the opportunity cost of working in the arts, or the psychic income of the artist. The term wage rate is normally used to denote payment per hour. For artists this is the imputed wage rate, as many are not paid per hour, or do not even receive a wage. Other studies have directly tested artists’ job satisfaction compared with other groups. Studies by Bille et al. (2013) and Steiner and Schneider (2013) confirm that on average artists are found to be considerably more satisfied with their work than are non-artists, and non-pecuniary benefits are among the key arguments for preferring to be an artist. The Skewed Income Distribution and the Superstar Model Empirical studies similarly have found another important and special characteristic of the labour market for artists, namely, the highly skewed income distribution (Alper and Wassall 2006). For example, based on a representative sample of 1000 visual artists in

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Artists’ labour markets  49 Denmark, Bille et al. (2018) have shown that those 5 per cent of artists who earn the most together share 47 per cent of the total market, and the top 25 per cent shares 87 per cent, while the 50 per cent who earn the least only share 1 per cent of total market earnings. Forbes magazine publishes every year a list of highest-earning musicians showing the enormous sums these superstars are earning. In 2019 Taylor Swift earned the most with $185 million per year. Elton John was fifth on the list, earning $84 million per year, and Celine Dion earned $37.5 million and was number 38 on the list (Forbes 2019). Risk-Taking Among Artists Another theoretical explanation of the willingness to work in the arts is related to the sometimes extremely high rewards some artists can obtain from their work if they manage to become a superstar. That is, when deciding how much time to spend working in the arts sector, artists would consider not only the expected (average) wage, but the earnings they can obtain if they succeed in rising to the top of their professions. Skewed earnings’ distributions may play a role in artists’ choices, as a few extremely high wages may have a disproportionately great attractive force (Marshall 1930). Economic theory has established that declining absolute risk aversion requires a positive appreciation of skewness (Tsiang 1972). The relevance of skewness in choices under conditions of uncertainty has been demonstrated in several empirical studies on gambling and betting, for example, Garrett and Sobel (1999). Even if the chance of succeeding appears to be extremely small, the opportunity to earn a very high income coupled with risk-taking behaviour helps us to understand why some artists take the risk even if this entails accepting a very low income for a period of time. The Superstar Model As one of the important properties of the creative industries, Caves (2000) mentions the A-list/B-list property, where A-list artists are well known and successful. The superstar model introduced by Rosen (1981) and the literature on ‘winner-takes-all-markets’ (Cook and Frank 2010) show us that small differences in talent can be magnified in huge earnings differences. In a context of a consensus about talent, as Rosen (1981) has shown, there will be no substitute for a particular talent. Therefore, demand is highly inelastic, and prices could increase without leading to a decrease in demand. Furthermore, the size of the market determines the huge multiplication of relatively small differences in talent that result in the highly skewed income distribution. However, as Champarnaud (2014) has noted, depending on how demand reacts to prices, the superstars in Rosen’s model (1981) can turn out to be poor. An alternative explanation can be found on the demand side: the consumption of the majority of artistic products is concentrated on a relatively small group of superstar artists. Information costs can lead consumers to choose what other people have already selected, and some studies have shown that this will lead not only to a superstar phenomenon, but also to a random selection of talent (Adler 1985). Similarly, mechanisms such as the bandwagon effect (when people’s preference for a commodity increases as the number of people buying it increases) and conspicuous consumption (using consumption to show social status) can explain why consumers to a large extent prefer to consume

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50  Handbook of cultural economics the same product as other consumers. These features of consumption can explain the motives for preferring the works of superstars and in this way reinforce market demand and snowball their popularity, resulting in a very high income and a large market share for the superstars.

THE ROLE OF EDUCATION Arts education may provide artists with important skills. The economics of education is a field that is in general interested in understanding and explaining the role of education and training in determining workers’ income. Two main theories developed in the economics of education have been used to analyse the role of training and specialized higher education in artists’ earning profiles (Towse 2006). Human capital theory tells us that people can invest in themselves by means of education, training and experience, and build up a stock of knowledge and skills that they can use to increase their productivity and therefore earn a higher income. By contrast, sorting models refer to the role of a labour market in matching work and the supply of workers with employers and jobs. Education and training provide certification regarding workers and in this way, they make the labour market work more smoothly. Most of the empirical evidence shows no impact of education on artists’ income (Alper and Wassall 2006). Many artists are self-taught, and in artists’ labour markets indefinable features such as talent and artistic creativity apparently contribute more to success or higher rates of payment than education and training. This contradicts findings in many other professions. Similarly, in the labour market for artists, having certificates and diplomas plays a less important role than is the case in other labour markets, as experience and reputation have proved to be much more central. This is also why awards play an important role in the cultural sector (Frey and Gallus 2017). In the early empirical literature, earning functions on a cross-sectional sample were used to explore possible differences in the rewards to education, training and other labour market attributes comparing artists with a reference group. Results have shown that artists do not seem to fit the standard earnings model as well as other workers, and earning functions have poorer goodness-of-fit for artists (Alper and Wassall 2006). Artist’s education has little or no impact on the artist’s income. Self-educated artists have the same earnings and the same supply behaviour as those with a formal arts education, and the prestige of the arts college attended does not have long-lasting effects. Filer (1986, 1990), looking at artist occupations, found that measures of earnings inequality for occupations where individual talent and performance are important determinants of earnings tend to be similar to those for artists, making the arts similar to comparable occupations. In general, the empirical results of most studies show no, or very weak, correlation of education with artistic earnings, but a positive correlation with non-artistic earnings (Throsby 1994, 1996, 1997; Alper and Wassall 2006). Throsby (1996) differentiates between professional arts education and general education, expecting non-arts income to be affected by general education and income from arts-related work to be influenced by professional arts education. However, this elaboration still confirms the general results. While most of the early studies have been made on a cross-section sample of artists, there are very few studies based on true longitudinal data, making it possible to study

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Artists’ labour markets  51 artists’ income development and survival in their profession. It is well known that many (young) people have ‘given it a try’ in the arts and the creative industries, but few are able to turn it into a career. Less well researched is which exogenous factors have an impact on survival in the arts and the creative industries. An exception is Coulangeon et al. (2005), who found a much lower probability of disappearing in the first two years for musicians than for actors and dancers. Bille and Jensen (2016) have studied the impact of education on artists’ careers using a unique longitudinal data-set for five different groups of artists in Denmark. The data is national register data from Statistics Denmark, which make it possible to follow all individuals during the period 1996–2012. Using the Cox model to estimate survival functions and semi-parametric analysis, the results show, among other things, that an artistic education has a significant impact on artists’ careers in the arts for actors, musicians, writers and journalists. For visual artists and dancers, a relevant artistic education had no impact on staying in the profession, and other important industry differences are found. Even though talent is important, it is reasonable to expect than an artistic education can have a significant impact on artists’ careers owing to the importance of technical skills, networks and signalling effects, but with important industry differences.

ARTISTS’ WORKING CONDITIONS There is a whole literature on other special characteristics of artists’ labour markets, for example, multiple jobholding, the widespread use of part-time, short and temporary contracts, self-employment and cultural entrepreneurship (see, for example, Mathieu 2012), as these special working conditions are much more frequent among artists than in the general workforce (Benhamou 2000). Studies of artistic occupations show how artists are able to counter an unpredictable future through risk-spreading by combining different sources of income in order to manage their artistic careers (Menger 2006); therefore, multiple jobs are common among artists (Shishko and Rostker 1976). Many authors talk about boundaryless careers (for example, Eikhof et al. 2012). A related topic is the widespread use of part-time, short and temporary contracts, as explained by Caves (2000). Many jobs are short term and project based, especially in the movie industry and among musicians. This extended use of short time projects and contracts can also help us explain the weak importance of diplomas for careers, as reputational competition turns out to be important, when building a strong reputation from job to job is the best way to get a new contract (Caves 2000). For some artists, such as authors and visual artists, self-employment is almost the only option to organize their work, as there are few regular jobs. In classical music and at theatres, permanent jobs are more common. There is a growing literature on cultural entrepreneurship (see for example, Klamer 2011) but even though many artists are selfemployed, they do not see themselves as entrepreneurs (Bille et al. 2018). This can be related to the phenomenon described as the double economy in the field of arts (Menger 1999, 2006), implying that artistic success does not necessarily coincide with economic success. Bourdieu (1996), for instance, claims that artists are disposed to deny the economic aspects of life and that artistic work carried out in order to achieve monetary

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52  Handbook of cultural economics income can be considered inconsistent with the artistic ideal. According to Bourdieu, seeking monetary income can in itself even result in lower artistic valuation. In a more recent work, Alacovska and Bille (2019) argue that the informal labour practices and alternative economic activities represent a vital component of artistic portfolio careers and sustainable artistic livelihoods, which have been neglected in the literature. Using a mixed-method study of visual artists in Denmark, they map the spectrum of economic practices ranging from formal paid/unpaid work to monetized, informal cashin-hand work and non-monetized labour exchanges, such as in-kind transactions and barter, to fully non-commodified everyday practices of mutual aid and self-provisioning. Alacovska and Bille argue that informal, heterodox relational economic practices are the primary mode of coping with and managing precarious artistic livelihoods.

PUBLIC POLICY FOR ARTISTS The purpose of public policy for artists has mostly been to secure them remuneration for their work or has aimed to give new talented artists a chance to develop their talent independently of the market. Concerning the latter purpose, many countries have public art grants, which are distributed to artists based on peer reviews by members of an arm’s-length body. There is little evidence on the impact of these arts grants. Bille et al. (2017) have produced ad hoc evidence on data from Norwegian artists showing that arts grants have a positive effect on the supply of hours devoted to arts work. This supports arts policy as arts subsidies may increase the motivation of artists to work on their arts. General regulations of labour markets can also be important for artists who often have special working conditions compared with those of normal labour markets. The flexibility of general social security schemes and unemployment benefits can be important for making it possible for artists to spend time on developing their art. Similarly, the general taxation rules, especially for self-employed, are important for artists, as their turnovers are often very low and unevenly distributed over time. General schemes to support entrepreneurship and stimulate self-employment have been growing as a tool in societies in general, and similarly for artists. Many artists seem to be reluctant to see themselves as entrepreneurs, and arts education in many countries has been urged to include courses in cultural entrepreneurship in order to develop entrepreneurial skills among artists. Artists’ property rights and copyright law is important to secure artists’ payment and remuneration for use of their work. However, it is the well-known and best-selling artists who are already successful in the market who will benefit the most from copyright (Towse 1999). Excess Supply of Artists General schemes to raise the average income of artists, such as those in France and the Netherlands, have proved unsuccessful (Benhamou 2003). Gurgand and Menger (2006) emphasize that these schemes lead to oversupply and overuse of the system. Abbing (2002) has argued that the low average income of artists is a stable situation in that it is

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Artists’ labour markets  53 impossible with policy initiatives to raise artists’ average income: if more money (public or private) is available for artists, even more people will be attracted to the profession and the average income will remain low. There are always pools of young and talented artists waiting for their artistic breakthrough, thereby creating an excess supply of artists. While the work preference model by Throsby (1994) is applied at the micro level (the individual artist’s work supply decision), the hypothesis of excess supply is a theory applied at the industry level. As explained by Abbing (2002), artistic work can be so attractive for some people that they might be willing to work in the arts sector even at the price of a lower income (the argument used in the work preference model by Throsby 1994). Therefore, more people are willing to work more hours at low wage rates and produce more art than the market can absorb on the demand side. That is, there is an excess supply of art and artists. Abbing (2002) further tells us that low average income and excess supply of artists are inherent and special characteristics of the labour markets for artists.

CONCLUDING REMARKS Artists’ labour markets have been widely researched and some of the most important themes and contributions have been mentioned in this chapter. However, there are also interesting new venues for future research. Digitization has led to new cultural products, and new ways of producing, distributing and consuming. Huge international platforms such as Google, YouTube, Facebook, Netflix and Spotify are controlling an increasing share of the market. What is the impact of this development on artists’ incomes and careers? How do these new developments change artists’ labour markets? Similarly, the informal labour market practices are a new turn in the literature, which needs more research. These are topics which the study of artists’ labour markets could now explore.

NOTE 1. This article draws on earlier work by the author: Bille and Jensen (2016) and Bille et al. (2017).

SEE ALSO: Chapter 46: Performing arts; Chapter 54: Superstars.

REFERENCES Abbing, H. (2002), Why Are Artists Poor: The Exceptional Economy of the Arts, Amsterdam: Amsterdam University Press. Adler, M. (1985), ‘Stardom and talent’, American Economic Review, 75 (1), 208–12. Alacovska, A. and T. Bille (2019), ‘The formal and informal economies of visual artists’, paper presented at the Ninth Nordic Conference on Cultural Policy Research (nccpr2019), 28–30 August, Bifröst University, Iceland.

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54  Handbook of cultural economics Alper, N. and G.H. Wassall (2006), ‘Artists’ careers and their labor markets’, in V.A. Ginsburgh and D. Throsby (eds.), Handbook of the Economics of the Arts and Culture, Amsterdam: Elsevier Science, North-Holland, pp. 813–64. Baldin, A. and T. Bille (2018), ‘A latent class analyses of visual artists living conditions’, paper presented at the Twentieth International Conference on Cultural Economics, 26–29 June, Melbourne. Becker, H. (1982), Art Worlds, Berkeley and Los Angeles, CA: University of California Press. Benhamou, F. (2000), ‘The opposition of two models of labour market adjustment: the case of the audiovisual and performing arts in France and in the United Kingdom’, Journal of Cultural Economics, 24 (4), 301–19. Bille, T. (2012), ‘Creative labor: who are they? What do they do? Where do they work? A discussion based on a quantitative study from Denmark’, in C.J. Mathieu (ed.), Careers in the Creative Industries, London: Routledge, pp. 36–65. Bille, T. and S. Jensen (2016), ‘Artistic education matters: survival in the arts occupations’, Journal of Cultural Economics, 42 (1), 23–42. Bille, T., K. Løyland and A. Holm (2017) ‘Work for passion? – Labor supply of artists’, KYKLOS, 70 (3), 347–80. Bille, T., B.S. Frey, L. Steiner and C.B. Fjællegaard (2013), ‘Happiness in the arts – international evidence on artists’ job satisfaction’, Economic Letters, 121 (1), 15–18. Bille, T., A. Alacovska, A. Baldin, S.N. Horndrup and R.H. Mikuta (2018), ‘Billedkunstens økonomiske rum – Danske billedkunstneres økonomiske levevilkår’ (‘The economic living conditions for Danish visual artists’), Copenhagen Business School, Copenhagen, accessed 16 December 2019 at https://research.cbs. dk/en/publications/billedkunstens-%C3%B8konomiske-rum-danske-billedkunstneres-%C3%B8konomiske-. Bourdieu, P. (1996), The Rules of Art: Genesis and Structure of the Literary Field, Stanford, CA: Stanford University Press. Casacuberta, C. and N. Gandelman (2012), ‘Multiple job holding: the artist’s labor supply approach’, Applied Economics, 44 (3), 323–37. Caserta, M. and T. Cuccia (2001), ‘The supply of arts labour: towards a dynamic approach’, Journal of Cultural Economics, 25 (3), 185–201. Caves, R. (2000), Creative Industries: Contracts between Arts and Commerce, Cambridge, MA: Harvard University Press. Champarnaud, L. (2014), ‘Prices of superstars can flatten out’, Journal of Cultural Economics, 38 (4), 369–84. Cook, P.J. and R.H. Frank (2010), The Winner-Take-All Society: Why the Few at the Top Get So Much More than the Rest of Us, 2nd edn, New York: Random House. Coulangeon, P., H. Ravet and I. Roharik (2005), ‘Gender differentiated effect of time in performing arts professions: musicians, actors and dancers in contemporary France’, Poetics, 33 (5–6), 369–87. Eikhof, D.R., A. Haunschild and F. Schössler (2012), ‘Behind the scenes of boundarylessness: careers in German theatre’, in C. Mathieu (ed.), Careers in Creative Industries, New York: Routledge, pp. 69–87. Eliassen, K.O., J.F. Hovden and Ø. Prytz (eds.) (2018), Contested Qualities, Oslo: Fagbokforlaget. Felton, M.V. (1980), ‘Policy implications of a composer labor supply function’, in W.S. Henderson, J.L. Shanahan and A.J. MacDonald (eds), Economic Policy of the Arts, Cambridge, MA: ABT Books, pp. 186–98. Filer, R. (1986), ‘The “starving artist” – myth or reality? Earnings of artists in the United States’, Journal of Political Economy, 94 (1), 56–75. Filer, R. (1990), ‘The arts and academe: the effect of education on earning of artists’, Journal of Cultural Economics, 14 (1), 15–38. Forbes (2019), The world’s top-earning musicians of 2019’, Forbes, 6 December, accessed 16 December 2019 at https://www.forbes.com/sites/zackomalleygreenburg/2019/12/06/the-worlds-top-earning-musicians-of-2019​ /#4684d6c2164e/. Frey, B.S. and J. Gallus (2017), Honours Versus Money. The Economics of Awards, Oxford: Oxford University Press. Frey, B.S. and W.W. Pommerehne (1989), Muses & Markets: Explorations in the Economics of the Arts, Oxford: Basil Blackwell. Garrett, T. and R. Sobel (1999), ‘Gamblers favour skewness, not risk: further evidence from United States’ lottery games’, Economic letters, 63 (1), 85–90. Gurgand, M. and P.-M. Menger (1996), ‘Work and compensated unemployment in performing arts. Exogenous and endogenous uncertainty in artistic labour markets’, in V. Ginsburgh and P.-M. Menger (eds), Economics of the Arts, Amsterdam: Elsevier, pp. 347–81. Karttunen, S. (2001), ‘How to make use of census data in status-of-the- artist-studies: advantages and shortcomings of the Finnish register-based census’, Poetics, 28 (4), 273–90. Klamer, A. (2011), ‘Cultural entrepreneurship’, Review of Austrian Economics, 24 (2), 141–56. Marshall, A. (1930), Principles of Economics, London: Macmillan. Mathieu, C. (ed.) (2012) Careers in Creative Industries, New York: Routledge. Menger, P.M. (1999), ‘Artistic labor markets and careers’, Annual Reviews, 25 (August), 541–74.

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Artists’ labour markets  55 Menger, P.M. (2006), ‘Artistic labor markets: contingent work, excess supply and occupational risk ­management’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: Elsevier Science, North-Holland, pp. 765–811. O’Brien, J. and A. Feist (1995), ‘Employment in the arts and cultural industries: an analysis of the 1991 census’, Arts Council of England, London. Robinson, M.D. and S.S. Montgomery (2000), ‘The time allocation and earnings of artists’, Industrial Relations, 39 (3), 525–34. Rosen, S. (1981), ‘The economics of superstars’, American Economic Review, 71 (5), 845–58. Shishko, R. and B. Rostker (1976), ‘The economics of multiple job holding’, American Economic Review, 66 (3), 298–308. Steiner, L. and L. Schneider (2013), ‘The happy artist? An empirical application of the work-preference model’, Journal of Cultural Economics, 37 (2), 225–46. Throsby, D. (1994), ‘A work-preference model of artist behaviour’, in A. Peacock and I. Rizzo (eds), Cultural Economics and Cultural Policies, Dordrecht: Kluwer Academic, pp. 69–80. Throsby, D. (1996), ‘Disaggregated earnings functions for artists’, in V. Ginsburg and P.M. Menger (eds), Economics of the Arts: Selected Essays, Amsterdam: Elsevier, pp. 331–46. Throsby, D. (1997), ‘Artists as worker’, in R. Towse (ed.), Cultural Economics: The Arts, the Heritage and the Media Industries, Cheltenham, UK and Lyme, NH, USA: Edward Elgar, pp. 201–37. Throsby, D. (2001), Economics and Culture, Cambridge: Cambridge University Press. Throsby, D. and K. Petetskaya (2017), Making Art Work: An Economic Study of Professional Artists in Australia, Strawberry Hills, NSW: Australia Council for the Arts. Towse, R. (1993), Singers in the Marketplace: The Economics of the Singing Profession, Oxford: Clarendon Press. Towse, R. (1999), ‘Copyright, incentives and performers’ earnings’, KYKLOS, 52 (3), 369–90. Towse, R. (2006), ‘Human capital and artists’ labour markets’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of the Arts and Culture, Amsterdam: Elsevier Science, North-Holland, pp. 865–94. Tsiang, S.C. (1972), ‘The rationale for mean-standard deviation analysis, skewness preference and the demand for money’, American Economic Review, 62 (3), 354–71. Withers, G. (1985), ‘Artists’ subsidy of the arts’, Australian Economic Papers, 24 (5), 290–95.

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6.  Artists’ resale rights

Victor Ginsburgh and Clare McAndrew

The artist’s resale right (ARR) is the right enjoyed by the creator of an original work of art (and their heirs, as the right runs for 70 years after the artist’s death) to an economic interest in its successive sales. Artists’ resale rights are levied in the European Economic Area (comprising the European Union, Iceland, Liechtenstein and Norway) and in over 70 other countries (Anderson 2019). It also existed in California, though in 2018, the Ninth Circuit of the US Appeals Court struck down the Californian law (Kinsella 2018), and there is no other US state where it is enforced. In this chapter, we discuss its application in the European Union (EU). According to the Directive of the European Parliament,1 the right is supposed to ensure that artists benefit from successive ‘exploitations’2 of their work. The principal objective of the EU Directive was to address a competitive distortion within the internal art market caused by the uneven application of ARR and its non-application in some member states.3 By imposing a uniform system of ARR throughout all EU member states, introducing the right in some countries for the first time, and obliging others to change their existing arrangements in order to conform with the terms of the Directive, it was hoped that the Directive would remove the distortion and EU art markets would compete on equal terms. All EU countries had to comply with the Directive before 1 January 2006, although a derogation was given to those member states which had not recognized the resale right before the Directive was agreed, to allow them to apply the royalty only to living artists and not to their heirs, until January 2012. In principle, the right extends to all resales, with the exception of transactions between persons acting in a private capacity. The royalty is calculated as a percentage of the sale price of a work of art, and not of the increase (or decrease) in its value. Economists (and lawyers) who have analysed the economic consequences of ARR have generally reached the conclusion that it is inefficient. Those who are in favour of its introduction have tended to concentrate on the uneven bargaining position between the artist and the art dealer, and condemn the profits that dealers and auction houses supposedly reap from the artist’s labour. Whether or not these injustices can be corrected by introducing ARR is dealt with from a protectionist perspective and, consequently, the deeper implications of the right are not usually analysed.4 We suggest that ARR can not only worsen the position for the contemporary artist, but it could also have a detrimental effect on international art trade for the states in which it is introduced. We show that it also happens to be severely anti-redistributive.

EFFECT ON PRICES It is at the time when the artist is likely to value the marginal increases of income most highly that he or she is placed in a position of forgoing a percentage of earnings, since 56

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Artists’ resale rights  57 in principle the initial price will adjust to a lower level. The rationale behind this is that rather than the full bundle of property rights passing over to the new owner at the first sale, the artist still retains certain ownership rights, and this is likely to lower the value of the work to the buyer. The decrease will depend on the amount of the resale right, the expectations the artist and buyer have about future resale values, the way they both value risk, and on their time preference discount rate. However, the resulting effect is clear: in competitive markets, the rebate on the price of the new artwork will exactly represent the expected discounted value of the future ARR. Although many artists start out with the hope of becoming famous, those who find their works being sold among the auction houses in centres such as London, New York and Paris are the exception rather than the rule. Singer (1990) suggests that an estimate would put the figure of such a possibility at one in every 3000, or even lower. It is from these few success stories that the image of the exploited artist in their younger days is drawn. For the majority, selling works on the secondary market is unlikely (particularly during their early careers), and any increase in the value of the work will be relatively small and entail little real gain of future royalty income for the artist. The effect of ARR for the exceptional artist is thus to distribute his or her income from a period of greater necessity (the first years as an artist) to a time when money has lower utility. We can wonder how large the decrease on the price of the first sale would be. To give an estimate, let us assume that the ARR is 3 per cent, that the probability that a work gets sold at auction is 5 per cent, that the discount rate is 4 per cent and, finally, that the average period of time after which a painting is sold again is 20 years. Then, the order of the expected discounted value of the future ARR should be equal to (0.03 3 0.05) / (1.04) exp (20) 5 0.0033. This is a very small effect on the first price that would probably be impossible to detect in practice. This is what Banternghansa and Graddy (2011) show in their study on what happened in the UK between July 2006 (ARR was implemented in February 2006, and collected for living artists only) and July 2007. They run a very careful econometric analysis, and find no evidence of a reduction in prices in the UK relative to other countries, and no evidence of paintings being moved from the UK to countries where there is no ARR. On the contrary, they find that over the period 1996 to 2007, the total price growth in the UK market segment subject to ARR increased significantly relative to other countries and relative to the segment of the market that is not subject to ARR. This may, according to the authors, be due to econometric identification problems, in particular that the market for living artists in the UK behaved differently than elsewhere, or that buyers and sellers are happy and treat the payment to living artists as a donation to the arts. They also suggest that their ‘current findings are not necessarily a good indication of the effects on the art market from a further extension of coverage [to dead artists5], and the UK authorities should proceed with caution’ (Banternghansa and Graddy 2011, p. 98). It may be fair to add that the authors themselves are puzzled by their own results. In practice, many auction sales are planned one to two years in advance, and therefore this period may not have been adequate to consider the effects of a regulation only introduced in 2006. Still, it is reasonable to think that a rational, risk-averse artist would choose to take the full and certain price of the work immediately, instead of investing in the hope  that  the work will be resold in the future. It is remarkable that some artists,

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58  Handbook of cultural economics including Appel, Baselitz, Hockney and Polke, who have been opposed to ARR, seeing it as a violation of their human rights, particularly given its inalienability versus other author’s rights.6 The Seller’s Perspective The seller of a work of art is also carrying the risk that the artist may lose favour.7 Yet it has never been suggested that compensation should exist for this, nor for the opportunity cost of their capital used in purchasing and holding the work of art that could have earned a higher rate of return. The introduction of ARR adds to the overall costs of selling a work, particularly as it is levied on the value of the work at the time of the sale, and not on the profit or loss that the seller has made. If the price of a work of art declines between sales, the seller is still forced to pay the artist a royalty on the resale, despite their own financial loss on the transaction. Effect on the Quantity of Art Produced If artists are faced with even a slightly lower present income, this will be the turning-point for a number of them to leave the industry and the deciding factor for others not to enter. Those who remain will face lower earnings, and this will have two consequences. First, through a mechanism that is too long to describe here,8 fewer works may be produced. It is fair to presume that the effect on production will be small, but there is certainly little reason to hope, as was claimed a few years ago by EU Commissioner Mario Monti, that ‘the Directive [on resale rights] will contribute decisively to the development of modern art in the European Union’ (European Commission 1996).

INALIENABILITY AND RETROACTIVITY Under the European Commission’s proposals, the right is inalienable. Those who promote an inalienable right follow the belief that artists are in an inferior bargaining position. What is it that makes a painter’s position so different from that of actors or novelists who are free to waive their rights? Note also that the right cannot be transferred (it is unassignable), an additional restriction. Retroactivity is also an issue, since in many legal systems, including the UK, nonretroactivity of law is the rule. Here, ARR will affect those sellers who bought the work of art while there was no ARR, but therefore at a higher price. They will lose when selling, since the resale price will take into account the newly introduced levy. Tepper (2007) analysed the legal effects of introducing ARR into the US. He concluded that ‘most importantly, the [right] neither promotes the creation of art, nor adds to the public domain, and thus fails to meet the dual purposes prescribed by the Constitution. For these reasons, the US should not implement [the right]’ (Tepper 2007, p. 41). See also the very thorough legal analysis by Stokes (2006).

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Artists’ resale rights  59

TRANSACTION COSTS AND COLLECTING SOCIETIES According to the Directive, member states are responsible for the exercise and the management of the right. Collecting societies are one possibility, but member states should ensure that these operate in a transparent and efficient manner. This has turned out not to be the case currently in practice in Europe. The Danish society which manages ARR charges 40 per cent of the royalty to cover its administrative costs. The Société des Auteurs dans les Arts graphiques et plastiques (ADAGP), the French collecting agency, currently levies 20 per cent, and the Design and Artists Copyright Society (DACS) in the UK charges 15 per cent.9 In some cases, especially in France, very little is left for the artists, and both Belgian and French collecting societies have experienced difficulties with their respective Departments of Justice.

REDISTRIBUTIVE EFFECTS A memo issued by the European Commission on 14 December 1999,10 claimed that ARR would benefit ‘approximately 250 000 artists [and] any suggestion that the resale right would benefit only eight rich families (for example, Picasso heirs) is therefore inaccurate’. They claimed that ARR is redistributive. When they are young, the artist sells at low prices, in the belief that he or she will be compensated when older, as ARR will compensate them for past misfortunes, owing to the high prices obtained on early paintings when resold. This assumption is wrong for two reasons. First, ARR detracts from the price of a work when sold for the first time. Although most artists struggle to make sales in the primary market and never achieve secondary market sales, if an artist ever becomes entitled to ARR and are aligned with a fair collecting society, they will only receive, on average, the benefit forfeited when they were young, minus the levy charged by the collecting society. Second, as can be expected, the proceeds of artists’ resale rights are very unevenly redistributed. In Table 6.1, we analyse what happened in the four most important European art markets (France, Germany, Italy and the UK)11 in 2003 and 15 years later, in 2018.12 Although in 2018 the number of European living artists who collect ARR is much greater than in 2003, as can be seen in the second row for each country, it is still dramatically smaller than the 250 000 figure hazarded by the European Commission. Also in all four countries, the number of artists’ heirs who collect ARR is greater than the number of living artists. How much does ARR represent for living artists and their heirs? We again turn to the results in Table 6.1. This shows that each of the top 50 artists collect at least ten times more than the others, and in the UK, this number is much greater. Once again, this is so for both living artists and the heirs of deceased eligible artists. This, we can claim, concerns auction sales only. However, the situation is similar in the gallery and dealer sector, and these sales are a reasonable proxy for the distribution of sales in the market as a whole, where a very small number of artists generate the majority of sales by value. In Germany, for instance, in 1998, a living artist, whether their work was sold at auction or by a gallery, collected less than €1000, while each heir collected €8500. Out of the 7400 artists represented by collecting agencies, only 480 collected ARR.13

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60  Handbook of cultural economics Table 6.1  Who benefits from resale rights? Works auctioned in France, Germany, Italy and the UK    

2003 Living Top 50  

2018 Heirs

Other

Top 50

Other

7.7 204 38.0 1.1

51.1 45 1136.0 34.1

34.3 996 34.0 1.0

France: Total sales (€ million) No. of artists (units) Sales by artist €1000) ARR by artist (€1000)

3.5 5 700.0 21.0

Germany: Total sales (€ million) No. of artists (units) Sales by artist €1000) ARR by artist (€1000)

1.8 7 257.0 7.7

  2.2 108 20.0 0.6

16.7 43 388.0 11.6

12.3 660 19.0 0.6

Italy: Total sales (€ million) No. of artists (units) Sales by artist €1000) ARR by artist (€1000)

1.7 7 243.0 7.3

  4.1 152 27.0 0.8

24.8 43 577.0 17.3

8.1 413 20.0 0.6

UK: Total sales (€ million) 23.1 No. of artists (units) 9 Sales by artist €1000) 2567.0 ARR by artist (€1000) 77.0

  25.1 299 84.0 2.5

128.7 41 3139.0 94.2

Living Top 50  

28.7 9 3187.5 95.6

Other  

Heirs Top 50

Other

18.1 878 42.7 1.3

129.5 59.9 41 1256 3157.8 75.0 94.7 2.3

  20.2 18 1124.2 33.7

  6.1 440 30.8 0.9

34.2 32 1069.4 32.1

14.2 808 36.9 1.1

  5.1 5 1016.2 30.5

  3.9 178 22.1 0.7

45.5 45 1010.7 30.3

8.9 317 28.1 0.8

    100.1 264.1 70.0 721.1 1385 20 1214 30 72.0 13 207.5 132.6 24 036.3 2.2 396.2 4.0 721.1

148.8 885 223.1 6.7

Notes: ARR = resale rights. Top 50 relates to artists ranked according to the value of their sales across the markets for the work of both living artists and heirs. For Italy and the UK in 2003, the numbers are illustrative, since no ARR was collected in that year. The ARR calculations are based on the observed values of sales by artist. For more consistent comparison across the two years and across countries, sales below €3000 (the maximum minimum price allowed under the directive) are omitted and ARR is applied at an average rate of 3 per cent on sales by artist. In implementing the directive in 2006, member states were allowed to impose different threshold prices once they did not exceed €3000. In 2018, these thresholds were €750 in France, €400 in Germany, €3000 in Italy and €1000 in the UK. In practice, the royalty is also calculated using a sliding scale: 4 per cent for the portion of the price up to €50 000, 3 per cent between €50 001 to €200 000, 1 per cent for the portion between €200 001 and €350 000, 0.5 per cent for the portion between €350 001 and €500 000, and 0.25 per cent for that exceeding €500 000.

This would be fine, though unreasonably small, if artists or their heirs received the full proceeds. However, 10 to 40 per cent goes to collecting societies. In some countries, such as Germany, a share of the ARR is paid to a fund that supports needy or elderly artists. In Finland and Sweden, funds have also been used to support young artists. The levy may be socially desirable and its implementation loaded with good intentions, but it is no longer an intellectual right, which is a poor excuse for social security contributions, or compensations for past immoral acts.14

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Artists’ resale rights  61

EFFECTS ON THE PLACE OF TRANSACTION The Directive’s intention is to smooth out distortions of competition, as well as displacements of sales within the Single Market, but very little is said about displacements to the rest of the world. And this is forgetting what had already been realized in 1958 by Jean Cassou, director of the Musée National d’Art Moderne in Paris, who in a letter addressed to the President of the Comité Professionnel des Galeries d’Art, dated 13 November 1958, writes: ‘I am aware that Paris does no longer host important sales, and I am afraid that ARR will impose a new threat [on the Paris art market]’ (Comité des Galeries d’Art 1997, p. 127). There are many unpublicized examples of displacements. One public example is the case where the £50 million French Gaffé collection was sold in New York in 2001, because UNICEF, the beneficiary of the sale, publicly recognized that they wanted to avoid paying ARR.15 How many paintings would be involved, and how much would this represent for European salerooms? Nobody can provide definitive answers to these questions, but it is possible to examine some data on which answers could be based. Our suggestions are based on Tables 6.2 and 6.3. Table 6.2 provides figures concerning all sales (living artists and their heirs) for a selection of years from 2002 to 2018. Contrary to what the ARR Directive claimed about levelling the playing field in Europe, it has in effect changed nothing, as is obvious from the upper part of the table: the UK still dominates all other markets by a very substantial margin. Harmonization of ARR has not led to a redistribution of the EU’s art market, and the UK has gained global market share over time, while the share of the rest of the EU (Other EU) sharply declined between 2008 and 2018. Table 6.2  Share of sales by value (percentage)

Share of EU sales: Austria Belgium Germany France Italy Netherlands Sweden UK Other EU Total EU Share of global sales: UK Other EU Total EU United States Rest of the World World total

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2002

2008

2010

2018

1.4 0.8 8.0 16.4 1.7 2.7 2.6 63.6 2.9 100.0

1.3 0.4 4.7 10.7 4.8 0.9 1.3 72.2 3.7 100.0

2.2 0.7 5.2 11.5 5.4 1.7 2.5 64.2 6.6 100.0

1.8 0.1 4.6 14.3 3.9 0.8 1.0 71.0 3.9 100.0

35.3 20.2 55.5 41.4 3.0 2.9

46.8 18.0 64.8 32.1 3.0 3.7

37.5 21.0 58.5 37.1 4.4 6.6

38.7 15.8 54.5 43.0 2.5 3.9

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62  Handbook of cultural economics Table 6.3  Sales by region in price brackets, 2002 and 2018 Price brackets

Number of Number of works artists

Value of sales (€ million)

Share of global sales by value (%) UK

Other EU

US

Rest of the World

2002 €3000–€50 000 €50 000–€200 000 €200 000–€2 million Over €2 million Total

17 245 1561 551 69 19 426

4996 644 342 41 6023

190.3 147.4 280.5 310.2 928.4

16.7 17.2 37.1 29.2 100.0

51.9 23.8 20.6 3.6 100.0

8.9 10.8 28.5 51.7 100.0

35.2 22.9 31.2 11.5 100.0

2018 €3000–€50 000 €50 000–€200 000 €200 000–€2 million Over €2 million Total

22 480 2780 1334 219 26 813

4160 640 257 56 5113

273.1 265.8 726.4 1791.3 3056.6

5.4 7.7 27.6 59.3 100.0

32.5 22.8 36.4 8.3 100.0

3.6 4.6 14.5 77.3 100.0

16.8 12.0 50.4 21.5 100.0

Table 6.3 shows that that the UK, the US and the Rest of the World gained market share in the highest price bracket (over €2 million), although the ARR levy has a cap of €12 500 in Europe, meaning it is quite a low percentage of these sale prices (0.25 to 0.50 per cent). But it is also true that Other Europe displaced low-priced works to the Rest of the World, and captured more high-priced works. It is vexing to see that Europe may be encouraging a system that could lead to incentives to export its cultural heritage to countries such as the US.16 This would also increase the risk of the works to remain there, as European collectors may be discouraged from paying customs duties in order to reimport them. Table 6.2 only considers sales of European artists’ works. When considering the wider Post-war and Contemporary art sector (which includes works by artists of all nationalities born after 1910), the EU auction market’s global share by value has fallen from 46 per cent in 2008 to just 24 per cent in 2018, while the share of sales of Modern art (artists born between 1875 and 1910) have fallen from 52 per cent to 24 per cent in the same period. Europe’s share of these markets has declined steadily over time as higher-priced works are siphoned to New York for sale and the Chinese market has gained in value. Without the UK, the EU market’s share in both of these auction sectors (which account for a combined 79 per cent of the global fine-art auction market by value in 2018) was less than 7 per cent in 2018.17

CONCLUSIONS To us, ARR appears to lack any appeal, both in theory and because it solves no practical problem and fails to target the artists that are most in need of financial assistance. The disadvantages weigh heavily, while the positive proposals of the European Commission lack the guidance of long-term efficiency considerations. A world without ARR would

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Artists’ resale rights  63 seem to be the most efficient solution. There is a danger of over-regulation that the European Commission is not willing to recognize. Simple economic analysis shows how even a well-intentioned law could bring about the opposite effect to its intended purpose. Nevertheless, we confess that there is as yet no conclusive empirical proof that the art markets in countries where ARRs were introduced suffered specifically because of the Directive. The economic effects are small and, therefore, difficult to estimate. Moreover, to show that ARR caused a decline in the art market or a price increase in countries where it is levied, is just too much to ask. This, however, is not a sufficient reason to reject the theoretical arguments developed in this chapter, which all plead against ARR. The ARR would appear to be an instrument that illustrates this pitfall and requires urgent reassessment, even if it is not based on empirical work. Since the UK was very negative at the time it was forced to follow EU legislation on ARR, it will be interesting to see what happens if Brexit goes ahead, as this removes the obligation for the UK then to follow the ARR rules that were imposed by the EU Directive. While there are many reasons for the decline in Europe’s share of the global art market, a primary factor is the perception that its regulatory structure makes it a costly and complex place in which to transact sales. Perhaps more worrying with Brexit looming is that the main reason for Europe still retaining a third of the global art market’s value has been that it can still include the UK in its count, without which it drops to some 10 per cent. Art is a mobile, durable and portable asset: Both buyers and vendors can and do use regulatory arbitrage to access the best sales terms, especially as the values of works increase. This is yet another reason why global sales have gravitated towards a few key market hubs such as the US and the UK, both of which have strongly followed the Anglo-Saxon model of low regulation, competition and strong private property rights. Despite many attempts by the EU to level the competitive playing field for art in the Single Market, the UK has consistently retained a dominant position, accounting for over 60 per cent of sales by value over the past decade and being the primary centre of international transactions. This has been a consistent picture since the 1960s, when the market moved from Paris to the US and the UK. This relocation occurred because of the underlying shifts in the established bases of wealth and economic power, but also owing to the introduction of a complicated system of taxes and royalties on art sales that drove buyers and sellers away from France and towards more liberal trading regimes. Wealth and a favourable regulatory environment remain two of the key drivers of where global art sales take place.

NOTES  1. Directive 2001/84/EC of September 2001 on the resale right for the benefit of the author of an original work.  2. This is the word used in the Directive. According to the Oxford Advanced Learner’s Dictionary, ‘to exploit’ means ‘to use or treat sb/sth in an unfair and selfish manner for one’s own advantage or profit’. We found important to quote this word, since it gives an idea of the tone of discussions at the time the decision to implement ARRs was made.  3. When the Directive was introduced in the original EU-15, 11 member states applied this right, although it was effectively enforced in only eight states. The UK, Ireland, the Netherlands and Austria had never applied resale royalties legislation.  4. See, however, Solow (1998) who shows that ARR may have positive welfare effects for artists.

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64  Handbook of cultural economics  5. Recall that at the time, the ARR had not yet been extended to resales that took place up to 70 years after the artist’s death.  6. The Art Newspaper, December 2000, p. 75.  7. The Directive suggests that ‘the person by whom the royalty is payable should, in principle, be the seller’. However, the result holds no matter who pays the ARR. In 2018, Christie’s Paris convinced the French Supreme Court that the ARR should be charged to the buyer, rather than to the seller. See Harris (2018).  8. For details, see Filer (1984).  9. The Art Newspaper, October 2004. See also Hummel et al. (1995). 10. ‘Proposed Directive on artists’ resale right – clarification’, Memo/99/68, accessed 19 December 2019 at https://ec.europa.eu/commission/presscorner/detail/en/MEMO_99_68. 11. The two other very important art markets, the US and China, are not considered here, since they do not collect resale rights. 12. See Kusin and McAndrew (2005) for the year 2003. 13. Declaration of Norbert Lammert member of the German Parliament, and culture and media spokesman of the CDU/CSU parties. 14. Australia proposed to introduce ARR to compensate aboriginal painters who have, in the past, sold at very low prices, while their works command very high prices today. See The Art Newspaper, July–August 2004, p. 27. 15. The Art Newspaper, April 2001, p. 67. 16. Also Switzerland, a market that is often overlooked, since it is dominated by art galleries for which data are difficult access, and not by salerooms. 17. See McAndrew (2019) for a summary of sales in the global art market in 2018.

SEE ALSO: Chapter 7: Artists’ rights; Chapter 12: Copyright; Chapter 34: Intermediaries.

REFERENCES Anderson, M. (2019), ‘Why American artists should benefit from the resale of their works’, The Art Newspaper, 4 January, accessed 11 February 2019 at https://www.theartnewspaper.com/comment/why-american-artistsshould-benefit-from-the-resale​-of-their-works. Banternghansa, C. and K. Graddy (2011), ‘The impact of droit de suite in the UK: an empirical analysis’, Journal of Cultural Economics, 35 (2), 81–100. Comité des Galeries d’Art (1997), Les Galeries d’Art en France Aujourd’hui (Galleries in France Today), Paris: L’Harmattan. European Commission (1996), ‘Intellectual Property: Commission proposes directive on artists’ resale right’, accessed 13 December 2019 at https://ec.europa.eu/commission/presscorner/detail/en/IP_96_219. Filer, R. (1984), ‘A theoretical analysis of the economic impact of artists’ resale royalties legislation’, Journal of Cultural Economics, 8 (1), 1–28, June. Harris, G. (2018), ‘Christie’s France wins the artist resale royalty battle’, The Art Newspaper, 31 December, accessed 11 February 2019 at https://www.theartnewspaper.com/news/christie-s-france-wins-the-artist-resale-royalty-battle. Hummel, M., L. Becker and P. Huber (1995), ‘The droit de suite’, report commissioned by the French authors’ society ADAGP, the German authors’ society BILD-KUNST and the Groupement Européen des Sociétés d’Auteurs et Compositeurs (GESAC), Munich: IFO-Institute. Kinsella, E. (2018), ‘Ending a seven-year dispute, a US court rules that artists aren’t entitled to royalties for artworks resold at auction’, Artnetnews, 9 July 2018, accessed 11 February 2019 at https://news.artnet.com/ art-world/us-appeals-court-strikes-royalties-law-1314857. Kusin, D. and C. McAndrew (2005), The Modern and Contemporary Art Market: A Study of the Global Resale Market, Maastricht: European Fine Art Foundation. McAndrew, C. (2019), The Art Market 2019, Basel: UBS and Art Basel. Singer, L. (1990), ‘The utility of art versus fair bets in the investment market’, Journal of Cultural Economics, 14 (2), 1–13. Solow, J. (1998), ‘An economic analysis of the droit de suite’, Journal of Cultural Economics, 22 (4), 209–26. Stokes, S. (2006), Artist’s Resale Right, Leicester: Institute of Art and Law. Tepper, J. (2007), ‘Le droit de suite: an unartistic approach to American law’, unpublished paper, American

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Artists’ resale rights  65 University Washington College of Law, Washington, DC, accessed 13 December 2019 at https://works.bepress. com/jonathan_tepper/1/.

FURTHER READING In December 2013, the United States Copyright Office published a 124-page report, Resale Royalties: An Updated Analysis, which contains a large amount of information. It is available at https://www.copyright.gov/ docs/resaleroyalty/usco-resaleroyalty.pdf (accessed 11 February 2019).

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7.  Artists’ rights

Michael Rushton

At the foundation of the economic analysis of property and contract is the hypothesis that the common law, and other institutions, evolve to ensure that rights will be exchanged between individuals so that in the end the rights are held by those who value them the most. The Coase (1960) theorem holds that, as long as property rights are clearly defined, and there are no transaction costs associated with their exchange, the resulting allocation of rights will be efficient and will be independent of their initial allocation. It is the existence of transaction costs that makes things interesting. When transaction costs are high, so that rights will be difficult to exchange, efficiency will be obtained only when the law awards rights initially to those who will value them most highly. In this sense the law mimics the market. Therefore, in cultural economics, we look to see whether the various property rights granted to artists represent an efficient allocation. An application of this principle is in the economic analysis of the law of copyright, where efficiency dictates awards of limited rights to creators (the copyright) and users (fair use) so that aggregate wealth is maximized (Landes and Posner 1989). For a more specific case, consider an artist creating a parody of a work. Landes (2002) and Posner (1992) claim that a transaction cost analysis would allow unlicensed use of works for parody if the target of the parody were the original work itself, since a bargain between the two creators is unlikely even though society at large would receive a net benefit from the parody. That is, in these cases it makes sense to grant the right of parody to the parodist rather than to grant the right to prevent parody to the creator of the first work. However, Landes and Posner would not grant fair use when the original work is used by the parodist to attack something else, say the banality of consumer behaviour, since ‘if the defendant uses the parodied work as a weapon to comment on society, he should have little trouble licensing the work’ (Landes 2002, p. 15). However, this is a difficult distinction to make. For example, is a comic book that takes Walt Disney’s Mickey and Minnie Mouse and has them engage in various anti-establishment activities attacking Disney or American Culture? (Walt Disney Prods. v. Air Pirates 581 (F.2d 751 (9th Cir. 1978))). The parody issue highlights an unresolved issue among economists studying copyright: is the purpose of fair use to balance the costs and benefits of increased copyright protection, or is it a means of solving a transaction cost/market failure programme, where the formation and monitoring of contracts between original creators and subsequent users is difficult? Posner’s solution to the parody problem is based on the transaction cost rationale, but his solution is questionable if fair use is not the result of market failure but is instead based on his balancing approach. See Rushton (2002) for further discussion of the copyright–artistic freedom trade-off. The allocation of moral rights to creators within the law of copyright – rights that the creator retains in the integrity, attribution, disclosure and withdrawal of a work even after the physical object and/or its reproduction rights have been transferred – can also be assessed within the efficiency framework (Hansmann and Santilli 1997; Rushton 1998). 66

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Artists’ rights  67 In general, with variations between countries, artists hold the moral rights in their works, and if they so choose can waive those rights in specific instances by using a contract with the owner of the work. A justification can be found in the potential harm that a current owner of a work of art might do to the reputation of the artist and to other owners of the artist’s work. When a creator’s rights in his or her work have been established, the question arises as to the best means of protecting those rights. The canonical essay on the means of enforcing rights is Calabresi and Melamed (1972), who begin by noting that property rules, which stipulate that a right can only be transferred by mutual agreement between buyer and seller, are the best means of protecting rights in a situation of low transaction costs. However, there may be circumstances where the superior way to protect a right is a liability rule, where a potential user of a right owned by somebody else need not obtain the owner’s agreement, but instead may use the good as long as a fee, set by some other agency, is paid to the owner. In the cultural sector compulsory licensing is an example of a right protected by a liability rule. Transaction costs would be prohibitively high in setting the terms for each public broadcast of each song, and so royalty schemes are established. However, Merges (1994) claims that statutory compulsory licensing discourages players in the market from developing technologies that could reduce the costs of a property rights system, and so the industry may be locked into a suboptimal liability rule. The third way ownership rights can be protected is through an inalienability rule. A narrow definition of inalienability is that there are restrictions on whether and how the ownership of a right may be transferred to someone else, although Rose-Akerman (1985) would broaden the definition to include restrictions on who may own the entitlement and whether there are duties or restrictions on the owner in his or her relationships to the property (on this last point, see Sax 1999, who considers cases where there is private ownership of cultural works of great social significance, and where there should be restrictions on those owners). Calabresi and Melamed (1972) suggest that inalienability could be efficient in circumstances of high transaction costs and externalities, that is, where only a restriction of transfer could prevent an externality from occurring, since bargaining between the potentially harmed parties and the buyer and seller contemplating the sale would be prohibitively costly. Laws prohibiting the sale for export of cultural goods of national importance would be an example of an inalienability rule justified (possibly) by efficiency considerations (on this topic, see Kearns 1998). Even though inalienability can, in some circumstances, be justified for efficiency reasons, when artists’ rights are restricted by inalienability it is often on distributional grounds, to protect the naive and possibly starving artist from unscrupulous dealers. A form of inalienability, occurs for example, when contracts that ex post are regrettable from the perspective of the artist (consider for example a songwriter who accepted an upfront payment in exchange for accepting low royalty rates on future earnings, and the work turned out to generate much more in royalties than anyone would have predicted) are invalidated by the courts on the grounds that they are unconscionable. Do these rulings benefit all songwriters? If these judgments became routine, the law would be imposing an inalienability restriction on the human capital of songwriters; the terms under which they could rent their song-writing potential on a long-term basis would be limited, since publishers would not be willing to enter contracts that might be overturned by the courts. The expected outcome is that publishers would be less willing to deal with unknowns,

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68  Handbook of cultural economics and so would offer them less favourable terms. Care must be taken, in restricting artists’ ability to contract and exchange, to ensure efforts to protect the artist are not making him or her worse off. Rushton (2001) discusses inalienability restrictions on artists that are often, and wrongly, justified on distributional grounds. Consider again the example of moral rights. Most countries stipulate that moral rights may be waived only with the written consent of the artist in a particular circumstance; blank waivers are frowned upon. This is a slight restriction on alienability of rights, but some commentators hold that waiver should not be permitted at all, on the grounds that the presumably superior bargaining power of the purchaser of the copyright will force artists to waive their moral rights even when it is against their interest: ‘making moral rights freely assignable and waivable will in practice eliminate them entirely’ (Vaver 1987, p. 774). A second case of inalienability, in some jurisdictions, is droit de suite, an entitlement that artists maintain in works of art after initial sale that provides them with a royalty on subsequent resales (Perloff 1998). While artists are certainly the intended beneficiaries of such an entitlement, if the right is inalienable it has the effect of forcing artists to be investors in their own works, which is inefficient if they are, as is quite likely, inferior owners of risk. However, Solow (1998) notes that investors in art are willing to pay a higher price for works if there is a greater probability that the artist will continue to build his or her reputation through valuable new works. No artist can guarantee to a potential buyer that he or she will in future take steps that lead to appreciation in the value of the works; an inalienable droit de suite could be a useful way to convince buyers that the artist will continue to produce; and the artist now has an inalienable financial stake in his or her own works. Another example of inalienable rights comes from the USA, where constitutional freedoms cannot be forgone in exchange for payments from the government; the doctrine is named unconstitutional conditions (Sullivan 1989). For example, the government cannot ask a social-assistance recipient to refrain from criticism of the government in exchange for continued receipt of assistance to which he or she would normally be entitled. The issue is important in the public funding of art: what conditions may government place on publicly funded arts-granting councils and the content of the art they fund before creating unconstitutional conditions that ask artists to trade their rights to free expression for government funding? Rushton (2000) argues that the rationales traditionally put forward to justify state support of the arts generally allow for some restrictions on what is funded. However, that does not imply that these restrictions are compatible with a nation’s constitutional rights and their inalienability. Again, this is a case of what superficially seems like a protection for artists being a double-edged sword; artists might win the right to remove any restrictions on publicly funded art, only to find that legislators cease to be interested in funding such agencies at all. In the USA, the issue reached the Supreme Court in National Endowment for the Arts v. Karen Finley (118 S.Ct. 2168 (1998)), which revolved around the issue of whether the amendment to the legislation governing the National Endowment for the Arts (NEA) requiring the chair of the NEA to ensure that ‘artistic excellence and artistic merit are the criteria by which [grant] applications are judged, taking into consideration general standards of decency and respect for the diverse beliefs of the American public’ violated the constitutional rights of the artist. The case was discussed intensively in the popular

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Artists’ rights  69 media, and was undoubtedly one of the contributing factors to the ultimate demise of NEA grants to individual visual artists. Without delving into the complex world of US constitutional law, cultural economists will be interested in this important aspect of public funding for the arts. The economic justification for public spending lies, not in the desire to subsidize the expression of selfdeclared artists, but to correct the perceived under-provision of cultural goods that would arise under laissez-faire. The efficient level of cultural production is a function of the technology of production and of consumer preferences. If a significant number of consumers would find certain works of art utility reducing rather than enhancing, should those works of art be awarded public funding? Rushton (2000) argues that restrictions on the content of publicly funded works along the lines of the NEA provisions can be justified, whether the rationale for public funding is based on economic analysis or on other considerations such as liberal theory or communitarian/nation-building reasons. Written guidelines for government grants to artists are not the sole determinant of what gets funding. There are always more proposals from artists than there is funding available, so some individuals must be in the position to choose who is funded and who is not. Is the need for artists to satisfy the government-appointed decision-makers for public funding a restriction on their artistic freedom? Hamilton (1996) argues that it is a restriction that necessarily distorts what artists do, and so we are left with a bureaucratic art whether or not the granting agency stipulates that excellence is the only criterion in its adjudication process. The economic analysis of freedom of expression has primarily developed through the law-and-economics tradition that plays down any consideration of abstract rights and instead looks for legal frameworks that maximize aggregate wealth, broadly defined. Richard Posner (1986) provides a systematic approach to freedom of expression based on a cost–benefit framework first articulated by Judge Learned Hand in United States v. Dennis (183 F.2d 201 (2d Cir. 1950)). By this model restriction of freedom of expression is justified when V 1 E , PL / (1 1 i)n where V is the social loss from suppressing valuable information, E is the legal-error cost of trying to distinguish which expression is valuable and which is not, P is the probability that harm will occur if the expression is allowed, L is the cost if no harm occurs, i is the discount rate, and n is the amount of time between potentially harmful expression and the occurrence of the loss resulting from it. The lefthand side of the inequality is the cost of suppressing expression, and the right-hand side is the probable cost if the expression is allowed. We can observe Posner’s application of the economic approach in his rulings as Judge on the United States Court of appeals for the Seventh Circuit. In Miller v. Civil City of South Bend (904 F.2d 1081 (7th Cir. 1990)), Posner ruled that a municipal ordinance banning nude dancing should not be allowed, on the grounds that the harm of the dancing could not be demonstrated. In Piarowski v. Illinois Community College District 515 (759 F.2d 625 (7th Cir. 1985)), he held that the shutting down by a college administration of an arts exhibition by a faculty artist was justified on the grounds that the exhibition, placed in a prominent location on campus, and containing works with racial and sexual themes that many unwilling viewers found offensive, could easily have been relocated to a place where the only viewers would have been those actually wanting to see the art. In this case the result reminds us of the Coasean solution to externalities where transaction costs are high: assign the rights to the party (here the college community at large) who would face the highest costs in avoiding the externality. Eric Rasmusen (1998) takes the economic

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70  Handbook of cultural economics approach to what is perhaps its limit, arguing that whether an expressive activity ought to be allowed should be determined entirely by comparing the willingness to pay for prohibition by those harmed by the expression with the willingness to pay for the right to expression by the expressor. One complication from cost–benefit analysis is common: willingness to pay depends upon ability to pay, and although many cost–benefit decisions might have negligible distributional consequences, economists will appropriately be wary of making recommendations on artistic freedom where those in favour of censorship are rich and the artist is poor (see Nussbaum 2000, for a critique of applying cost–benefit analysis to the case of freedom of expression). A second complication is whether political expression deserves special protection. If government represents a particularly dangerous place to have a monopoly, it might make sense to give an especially wide allowance for artistic works that contain political criticism, as hard as this might be to define. The question of whether and how to restrict political expression raises an issue relatively unexplored by economists, namely, the reason why in most Western political systems there is constitutional protection of freedom of expression, especially if economists are correct in treating the regulation of expression as simply a cost–benefit matter (see Mackaay 1997; Cooter 2000).

SEE ALSO: Chapter 6: Artists’ resale rights; Chapter 12: Copyright.

REFERENCES Adler, A. (2009), ‘Against moral rights’, California Law Review, 97 (2), 263–300. Boyle, M., S. Nazzaro and D. O’Connor (2010), ‘Moral rights protection for the visual arts’, Journal of Cultural Economics, 34 (1), 27–44. Calabresi, G. and D.A. Melamed (1972), ‘Property rules, liability rules, and inalienability: one view of the cathedral’, Harvard Law Review, 85 (6), 1089–128. Coase, R.H. (1960), ‘The problem of social cost’, Journal of Law and Economics, 3 (1), 1–44. Coase, R.H. (1974), ‘The market for goods and the market for ideas’, American Economic Review Papers and Proceedings, 64 (2), 384–91. Cooter, R.D. (2000), The Strategic Constitution, Princeton, NJ: Princeton University Press. Epstein, R. (1975), ‘Unconscionability: a critical reappraisal’, Journal of Law and Economics, 18 (2), 293–315. Farber, D.A. (1991), ‘Free speech without romance: public choice and the first amendment’, Harvard Law Review, 105 (2), 554–83. Ginsburgh, V. (2005), ‘The economic consequences of droit de suite in the European Union’, Economic Analysis and Policy, 35 (1), 61–71. Graddy, K. and C. Banternghansa (2011), ‘The impact of droit de suite in the UK: an empirical analysis’, Journal of Cultural Economics, 35 (2), 81–100. Hamilton, M. (1996), ‘Art speech’, Vanderbilt Law Review, 49 (1), 73–122. Hammer, P.J. (1988), ‘Free speech and the “acid bath”: an evaluation and critique of Judge Richard Posner’s economic interpretation of the first amendment’, Michigan Law Review, 87 (2), 499–536. Hansmann, H. and M. Santilli (1997), ‘Authors’ and artists’ moral rights: a comparative legal and economic analysis’, Journal of Legal Studies, 26 (1), 95–143. Kammen, M. (2006), Visual Shock: A History of Art Controversies in American Culture, New York: Random House. Kearns, P. (1998), The Legal Concept of Art, Oxford: Hart. Landes, W.M. (2001), ‘What has the visual artists’ rights act of 1990 accomplished?’, Journal of Cultural Economics, 25 (4), 283–306.

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Artists’ rights  71 Landes, W.M. (2002), ‘Copyright, borrowed images and appropriation art: an economic approach’, in R. Towse (ed.), Copyright in the Cultural Industries, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 9–31. Landes, W.M. and R.A. Posner (1989), ‘An economic analysis of copyright law’, Journal of Legal Studies, 18 (2), 325–63. Lewis, A. (2007) Freedom for the Thought We Hate: A Biography of the First Amendment, New York: Basic Books. Mackaay, E. (1997), ‘The emergence of constitutional rights’, Constitutional Political Economy, 8 (1), 15–36. Masiyakurima, P. (2005), ‘The trouble with moral rights’, Modern Law Review, 68 (3), 411–34. Merges, R.P. (1994), ‘Of property rules, Coase, and intellectual property’, Columbia Law Review, 94 (8), 2655–73. Nussbaum, M. (2000), ‘The costs of tragedy: some moral limits on cost-benefit analysis’, Journal of Legal Studies, 29 (2), pt 2, 1005–36. Perloff, J. (1998), ‘Droit de suite’, in P. Newman (ed.), The New Palgrave Dictionary of Economics and the Law, London: Macmillan, pp. 645–8. Posner, R.A. (1986), ‘Free speech in an economic perspective’, Suffolk University Law Review, 20 (1), 1–54. Posner, R.A. (1992), ‘When is parody fair use?’, Journal of Legal Studies, 21 (1), 67–78. Rasmussen, E. (1998), ‘The economics of desecration: flag burning and related activities’, Journal of Legal Studies, 21 (1), 67–78. Rose-Ackerman, S. (1985), ‘Inalienability and the theory of property rights’, Columbia Law Review, 85 (5), 931–69. Rushton, M. (1998), ‘The moral rights of artists: droit moral ou droit pecuniaire?’, Journal of Cultural Economics, 22 (1), 15–32. Rushton, M. (2000), ‘Public funding of controversial art’, Journal of Cultural Economics, 24 (4), 267–82. Rushton, M. (2001), ‘The law and economics of artists’ inalienable rights’, Journal of Cultural Economics, 25 (4), 243–57. Rushton, M. (2002), ‘Copyright and freedom of expression: an economic analysis’, in R. Towse (ed.), Copyright in the Cultural Industries, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 51–62. Sax, J.L. (1999), Playing Darts with a Rembrandt: Public and Private Rights in Cultural Treasures, Ann Arbor, MI: University of Michigan Press. Shipley, D.E. (2017), ‘Droit de suite, copyright’s first sale doctrine and preemption of state law’, Hastings Communication and Entertainment Law Journal, 39 (1), 1–42. Solow, J.L. (1998), ‘An economic analysis of droit de suite’, Journal of Cultural Economics, 22 (4), 209–26. Stokes, S. (2016), ‘Ten years of artist’s resale right in the United Kingdom: success or failure?’, Art Antiquity and Law, 21 (2), 133–43. Strauss, D.A. (2011), ‘The false promise of the First Amendment’, in L. Rothfield (ed.) Unsettling ‘Sensation’, New Brunswick, NJ: Rutgers University Press, pp. 44–51. Sullivan, K.M. (1989), ‘Unconstitutional conditions’, Harvard Law Review, 102 (7), 1413–506. Sullivan, K.M. (1992), ‘Are content restrictions constitutional?’, Journal of Arts Management and Law, 21 (4), 323–7. Sullivan, K.M. (1995), ‘Free speech and unfree markets’, UCLA Law Review, 42 (4), 949–65. Trebilcock, M. (1976), ‘The doctrine of inequality of bargaining power: post Benthamite economics in the House of Lords’, University of Toronto Law Journal, 26 (4), 359–85. Vaver, D. (1987), ‘Authors’ moral rights – reform proposals in Canada: charter or barter of rights for creators?’, Osgoode Hall Law Journal, 25 (4), 749–86.

FURTHER READING For economic analysis of the effects of moral rights legislation on artists, in particular the Visual Artists’ Rights Act of the USA, see Landes (2001) and Boyle et al. (2010). Critiques of the granting of moral rights include Masiyakurima (2005) and Adler (2009). On the economic analysis of ‘unconscionable’ contracts, see Epstein (1975) and Trebilcock (1976). Evidence on the effects of droit de suite is provided by Graddy and Banternghansa (2011), Ginsburgh (2005), Shipley (2017) and Stokes (2016). A concise history of freedom of expression in the USA is Lewis (2007), and Kammen (2006) deals with US controversies over art and censorship. On whether we ought to assess regulation of expression with the same methods we would apply to the regulation of markets for goods and services, see Coase (1974) and Sullivan (1995). A detailed critique of the economic approach to freedom of expression is given by Hammer (1988). For a public choice approach, see Farber (1991). On content restrictions on publicly funded art, also see Sullivan (1992) and Strauss (2001).

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8.  Broadcasting* Glenn Withers

For mass media transmission of information, print media reigned supreme for centuries: books, newspapers and magazines. Postage services long dominated interpersonal communication media. The telegraph and telephone changed the picture in the nineteenth century for interpersonal communication. However, it was cinema and then broadcasting that changed the landscape for mass media in the twentieth century; for broadcasting, radio was first, then black and white and, later, colour television. Now, in the twenty-first century, it is digital media platforms that have changed the communications scene again. This chapter examines the operation of the electronic media services of broadcasting, that is, radio and television services for entertainment, educational and informational purposes, while recognizing that ‘broadcasting . . . [has become) a portmanteau bursting at the seams as more and more activities [are] stuffed into it’ (Inglis 2006, p. 582), as both business models and technology change further. The chapter proceeds by reviewing the traditional broadcasting landscape of the twentieth century, examines the analytic interpretation of this and the associated policy responses, and then it looks at the changes emerging in the late twentieth century and early twenty-first century as the digital revolution proceeds.

TRADITIONAL BROADCASTING From the introduction of radio and television, the dominant technology for such broadcasting programme delivery has been terrestrial transmission via an airwave signal sent from a broadcasting station transmitter to receivers owned by listeners and viewers. The technical quality of the transmission has depended on the frequency spectrum occupied, strength of signal transmitted, and topography and distance to the receiver. A second delivery platform did emerge with the advent of the space age. Satellite technology enabled powerful transmitters (transponders) in geostationary orbit above the earth to distribute signals over a very wide footprint on the earth’s surface. A third delivery platform of increasing use and power, wire and cable networks, used telephone lines or dedicated separate cable systems for transmission (Cave et al. 2005). With wire and cable, geography did not affect signals, multi-channel capacity became immense and two-way transmission was possible. From these technology determinants the dominant models in national broadcasting systems globally became two: commercial and public. The former model is based on commercial or profit-orientated stations deriving revenue from advertiser or private individual payment linked to listener or viewer numbers. The alternative model is based on government funding of state-owned public broadcasting organizations. Individual countries adopted different blends of private and public provision, and the accommodation of new technology proceeded at different rates across countries. 72

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Broadcasting  73 Common to both models, however, is dominance of centralized structures for control of programming decisions, whether through commercial networks or state authorities. This enabled significant economies of scale and scope. An extensive system of regulation has been common to both national structures. In contrast to print media, the requirement for public control of access to the frequency spectrum for most broadcasting gave government a more logical role in this industry than in most. Financing of traditional broadcasting of this kind has, as indicated, come from three main sources: advertiser payment, audience payment and government or community subvention. In the case of advertiser support, programmes typically have been supplied free of direct charge to the audience. The audience in turn is sold wholesale to advertisers who seek, by attaching their messages to the programmes, to inform or persuade consumers about their products and services. The ultimate incidence of payment depends on the extent to which advertising costs can be passed on in product prices to consumers of the advertised goods and services (Roson 2008). It was this distinctive reliance at the time on advertiser funding rather than listener/viewer direct payments that, together with the idiosyncrasies of a limited frequency spectrum for transmission, produced analysis of broadcasting as a distinct field of economics (Cave 2007; Maude 2011). For direct payment by audiences, as this emerged, the analysis then recognized that the incidence would lie with individual viewers or listeners who determine for themselves their willingness to pay for programmes or programme services, including under subscription arrangements. In this instance, broadcasting purchase is closest to purchase arrangements for standard commodities. The growth of pay television with cable indicated a willingness of audiences to pay for an expanded menu of choices as technology increasingly made this option accessible and convenient. Subvention occurs with voluntary donations by community members, as is common in community broadcasting, or subsidy by governments based on their taxation power. Tax payments for broadcasting may be from general taxation, as in countries such as Australia, or from hypothecated taxes or charges enforced by government, such as earmarked state lottery revenues, or broadcasting licence fees as in the UK. In many countries, state broadcasters have been funded through a mix of advertising and public money. In most European countries, public broadcasting has been regarded as a public good with state revenues often extensively supporting public and community broadcasting, though at times also subsidizing commercial activities. Analysts have sometimes looked at the comparative incidence of these finance options, recognizing that tax-based funding under progressive income taxation has differing implications from advertiser funding where incidence may be more regressive, with direct purchase somewhere in between. However, equity concerns in this area have never been a main focus. In the pursuit of government objectives that have been established in broadcasting, a mix of the following specific instruments of public intervention is commonly observed across countries: access controls to existing technology and controls over introduction of new technology for broadcasting; government award or auction of spectrum licences; fiscal subsidy for community and public broadcasting; regulation of ownership (vertical, horizontal and foreign); and regulation of programme content, particularly advertising time, local content, children’s programming and offensive content. The assignment of instruments to particular objectives is not strict. Some may affect multiple objectives. For example, foreign ownership restrictions may affect both anti-monopoly objectives and local content objectives.

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74  Handbook of cultural economics

ECONOMIC ANALYSIS FOUNDATIONS Analysis of this broadcasting intervention can be positive or normative in approach. The former seeks to explain what governments do, and the latter what they should do. Positivist analysis has especially been conducted in political and managerial sciences, and recognizes that there is a significant capacity for media organizations to influence public decision-makers to provide media subvention and/or regulation that may reflect the media’s interests as much as the public interest. It also observes that the scope and scale of government intervention in the broadcasting market is influenced by the political complexion of national governments. For example, a growing deregulatory emphasis of conservative or neoliberal governments in the Anglosphere has eased or abolished a number of regulatory controls, including in relation to media ownership and foreign ownership and control restrictions in national broadcasting legislation. In the European Union, deregulation of cross-border television broadcasting is said to have led to a high level of investment flight and to resistance to further deregulation by governments of many member states. Economic science and law have, by contrast, focused more on the normative approach to regulation, specifying what government should be doing if it is to serve the public interest. For economists, broadcasting policy analysis starts from the presumption that competitive market processes will ensure that individual preferences, as expressed through the market, will be met at the least resource cost to society. However, it is then acknowledged that there are distinctive problems nevertheless with the operation of competition in broadcasting markets. In particular, market failure has been seen as arising from technologically imposed supply limitations and associated funding requirements. In free-to-air broadcasting, this has led to concern not only over any monopoly pricing that occurs, but also to concern over reduced programme diversity which results from a limited number of channels being available in the dominant frequencies (medium wave for sound and very high frequency for television). In this situation, profit maximization is predicted to result in a lowest commondenominator approach in commercial broadcasting, whereby competition for market share favours mainstream generic programmes, currently crime dramas and reality television, rather than audience-targeted and special-interest programmes based on, for example, age, ethnicity or minority tastes, such as arts and culture. Duplication of similar programmes will occur as long as the audience share obtained is greater than that from programme diversity (Steiner 1952). The result is a reinforcement of programme duplication and lowest common-denominator programmes, with advertisers who fund programmes assumed to be motivated by maximization of audience (Motta and Polo 1997; van de Wurff 2005). Beyond competition concerns, a second focus of the economics of broadcasting has been the separate market failure issue of externalities, where externalities refer to nonmarket effects beyond the services contracted for in the supply of broadcasting services. There have been two particular groups of concerns about externalities in broadcasting: the particular issue of congestion or signal interference from competitive access to limited spectrum, and the wider issue of cultural, social and political effects of broadcasting. The former externality problem has been dealt with through government determining spectrum allocation in a form that prevents signal interference. This raises the question,

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Broadcasting  75 what criteria are used for this allocation? This question has been discussed by economists ever since Ronald Coase’s economic analysis of spectrum allocation, which criticized spectrum licensing by government and suggested auctions be used to create property rights as a more efficient method of allocating spectrum to users (Coase 1959). Proponents of competitive auctions say they are generally an efficient tool for assigning exclusive rights, and they eliminate many costs of alternative methods and bring transparency to government awards. What of social, cultural and political externalities? These are potentially important given the extensive penetration of broadcasting in modern society and its influence on social and political behaviour and national culture. Examples include positive effects from quality news and current affairs in improving national political decision-making and from education programming enhancing children’s development, or negative social effects including from programmes containing explicit sex and violence that may debase family relationships and encourage greater crime. A presumed positive role of broadcasting in enhancing national culture through local content is also highlighted. It is hard to quantify or value these effects, given the diversity of probable views about the value of different programmes and their effect on behaviour. By definition, there is no direct measure provided by the market (Snowball 2008). However, use of complementary behaviour to impute value (Gentzkow 2007) and also use of contingent valuation methodology, based upon willingness-to-pay measures (Withers 2019), have shown new ways forward on this. There is also a threshold conceptual issue; how much such notions are truly externalities which do not reflect individual valuations but instead some over-riding social values informing judgements about what should be provided. In broadcasting, the difference would be between wanting to prevent people from watching programmes with explicit violence because it induces actual violence from some viewers (an externality), and wanting to restrict such programmes because they are inherently immoral even if they do not affect behaviour (merit good). The distinction between externality and merit goods can be very fine, and both are hard to measure. What is clear, however, is that if either externalities or merit goods are present, social, cultural or political characteristics will only be taken into account in commercial broadcasting decisions if they are consistent with profit imperatives or are required by regulation. Similarly, for monopolistic broadcasters, exercising public responsibility is less likely and monopoly pricing is arguably more likely in the absence of regulation.

THE DIGITAL REVOLUTION Recent changes in technology have especially been driven by information technology and computer science. In particular, digitization has allowed the infrastructure foundations provided by wireless, cable and satellite transmission systems to be utilized further to permit new digital service providers to flourish. With new associated equipment from hardware and product manufacturers, and operational management through software, online platforms for use of the Internet also for information and entertainment have emerged prominently alongside broadcasting, print and cinema. These platforms embrace

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76  Handbook of cultural economics services for email and messaging, social networking, search engines and maps, e commerce, entertainment platforms and games, and voice-activated assistants. All feature creation and/or use of big data which is managed through using algorithms specifying the decision rules for the complex decision-making software, and these systems can be seen to be linked to processes referred to as machine learning or, more broadly, artificial intelligence, which also have applications well beyond broadcasting activities (Peitz and Waldfogel 2012). The new broadcasting environment that has emerged from the evolution of such delivery platform technology, and its substitute and complementary effects for users, has seen the dramatic increase in each of: user-pay television’s share of the overall television market; Internet downloading of broadcasts and other media, either freely or by subscription; the emergence of a mobile broadcasting sector in many countries using personal computers, cell-phones and wireless headphones; and the growth of new interactive applications and activities ranging from games to social media. Personalization and interaction are major changes in the character of products, including in broadcasting areas ranging from Netflix movie choice to Tinder dating apps. Overall, the speed and array of these digital-era technological changes have had massive implications for the cost, quality and control of transmission, the extent of the market, the degree of direct competition, and the efficiency and public value of the resulting broadcasting. The role of government intervention in these changing markets therefore is also under challenge. Some commentators even see the technology changes as being so great that previous market failure considerations in broadcasting lose their weight and any special status accorded government funding or regulation of broadcasting by administrative fiat (Murdoch 2009) has disappeared. Certainly, the limits on supply coming from a limited frequency spectrum are transcended, and greater direct-user pay delivery of broadcasting services instead of third-party purchase is facilitated – muting two distinctive features of traditional broadcasting that provided the rationale for the past intervention in broadcasting relative to print media. Broadcasting is indeed rendered more like other user-pay, supply-responsive industries. However, it is not clear that, in these circumstances, greater deregulation or liberalization in broadcasting is automatically the appropriate policy response. This is because, just as the Queen’s croquet mallets turned into flamingos in Alice in Wonderland, so new liberations in broadcasting technology also create their own issues. For example, a key feature of the new digital world is the importance of new network economies where the value of the service increases with greater user numbers owing to the improved interpersonal communication possible with more people. It is on the back of these network economies that the situation has evolved of massive concentration of the activity in the digital sector in a few firms. For example, five GATAM firms alone (Google, Apple, Twitter, Amazon and Microsoft) currently dominate their respective service markets and represent hundreds of billions in market value. This is a clear issue of new sources of market monopolization and the implications of that for allocative efficiency (van der Wuff 2005; Department of Communications and the Arts 2018). There is also a more traditional allocative efficiency issue in the emergence of greater userpays pricing in these markets as, in the presence of network economies, pricing may exceed the marginal cost of provision as extra product provision has little extra cost to providers.

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Broadcasting  77 Vehicles around this exist, such as the sale of user data to reduce price. However, the net efficiency outcome even in static efficiency terms is yet to be adumbrated, and is added to the issues of ownership or control of new as well as old common carrier delivery platforms. Also, there is the dynamic efficiency issue. One argument is that these large firms expend substantial sums on research and development and therefore are promoting innovation. A counter-argument is that predatory behaviour of incumbents in acquiring start-ups reduces potential new competition and locks-in dominant product standards, irrespective of improvements or alternatives. Product standard issues are hardly new; consider the roll-out of the National Television Standards Committee (NSTC) colour system in the United States, versus the Phase Alternate Line (PAL) standard from Europe. However, they are accentuated afresh with digital technology. In all of these monopolization arguments, both analysis and policy are bedevilled by the underlying issue of the definition of the markets. Together with more traditional distinctions between electronic media and print media, in what has become known as the mainstream media, the question now asked is, where does broadcasting end and information technology begin? Also, what of national boundaries? Does the existence, say, of alternative high market-share firms such as Baidu, Alibaba and Tencent (BAT) in China constitute sufficient latent competition to constrain the GATAM concentration in Western markets and elsewhere? Beyond the economic arena, the new technologies also have implications for social and political behaviour and institutions as they affect broadcasting. These are the externality and merit-good issues afresh and their implications for policy. Sometimes the new digital technologies have accentuated concerns in these areas, but in other areas they enable new solutions. In the social sphere, concern emanates from the potential for expansion of offensive material in broadcast content. This includes phenomenon such as pornography and social media trolling and harassment. It also relates to problems of maintenance of privacy, given the data compiled about individuals. Key cases make the point, such as the suicide of Dolly Russell, a young victim of trolling reported and discussed prominently. In the political sphere, concern arises over such issues as fake news emerging from the proliferation of news sources and reduced editorial intermediation and validation. Similarly, there is the issue of what quality of broadcasting is viable with fragmented audiences? These concerns have led to what is variously described as a dumbing down of broadcasting or a crisis in journalism. The privacy issue also intrudes for political matters, as the widely reported Cambridge Analytica case made clear, where secret sale of private digital data from social media company Facebook to this consultancy helped Donald Trump to be elected as US President.

CONTEMPORARY POLICY RESPONSES The issue therefore remains as to the need to consider appropriate competition and product law and regulation, with many of the new digital services currently being much less subject to this type of control than the traditional broadcasting sector (Hoynes 2007; Australian Competition and Consumer Commission 2019). Existing law applies to digital providers, just as to traditional broadcasters, but, even there, problems apply because of the nature of the technology. The prominent case of

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78  Handbook of cultural economics Senior Vatican Official, Cardinal George Pell, in 2018 illustrates the problem. Under trial in Australia for offences against children, court suppression orders were put in place restricting reporting of trial proceedings and deliberations. However, these proved substantially unenforceable, given publication through modern media in other jurisdictions and the accessibility of this to users in Australia. The need for new additional sectorfocused policy is therefore the key issue. The principal response in the law and regulation literature has been to emphasize transparency and informed consent by users, plus duty of care and code of conduct operation. There is also an emphasis on looking again to developing single-agency approaches to overcoming the product boundary problem, and to international coordination for the cross-border problem (Harcourt 2007; Puppis 2008). In relation to product boundaries, the need for competitive neutrality has led to widespread discussion of how diverse and overlapping regulation can be rendered more consistent and coherent across the new media and digital landscape. An over-arching single authority or agency is a common refrain in the emerging policy discussion, but with numerous variants. The variants relate to tough issues such as whether it covers funding as well as regulation, is it advisory or executive, how does it relate to regular competition agencies and many more. A 2019 UK House of Lords Select Committee on Communications review is indicative of this approach. For national boundary issues there has been ongoing increased engagement in this area by non-national forms of governance, for example the European Commission. Similarly, while some governments support the further liberalization of audio-visual services under the umbrella of the General Agreement on Trade in Services (GATS) and the World Trade Organization (WTO), other countries see this as undermining national media and broadcasting governance and culture and the United Nations 2001 Declaration on Cultural Diversity. A third and different way of responding to some of the challenges has been to argue for re-invigorated funding for public broadcasting and for other public finance measures. The argument is that public broadcasting still fulfils important functions. It is a light-handed intervention primarily based on transparent public subsidy, rather than upon regulatory mechanisms. It can continue to provide countervailing power in situations of concern over monopolization, concentration and programme quality, and to offer alternative funding arrangements to both advertiser and user-pay methods, each of which has inefficiency properties. It provides an alternative to programming that allows for divergence of social from private costs and benefits, and it can promote recognized merit objectives. Criticism is offered that this type of public broadcasting will be provided inefficiently compared with that from commercial providers; and theoretical property-rights critiques may have merit in many applications. For broadcasting, though, there is strong and long-standing empirical evidence that public broadcasting can and does operate at lower unit costs of production than commercial broadcasting (Withers 1982), partly because it avoids the high transactions costs of private revenue-raising whether through advertising or by subscriptions and user payments. Public broadcasting by being free of a direct response requirement for consumers, itself runs the danger of emergence of its own staff culture or partisan government direction. In many countries, arm’s-length arrangements are devised that seek to limit short-term political interference in editorial functions, while still retaining public accountability for use of taxpayers’ monies. Guaranteeing public broadcasters’ independence, for example by statute, allows content creators a measure of independence from management and

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Broadcasting  79 from government, and arguably more creative risk-taking than is the case in bottom-line, profit-maximization orientated commercial broadcasting. Public broadcasters do ultimately remain vulnerable, though, to government for ongoing subvention, especially in time of straitened government budgets. For this reason, there are proponents of allowing advertising and other commercial revenue-raising by public corporations. However, this implies competitive neutrality issues vis-à-vis private providers and, more importantly, it compromises the core not-for-profit distinction that justifies the very establishment of public broadcasters. Another policy approach is supplementation of public broadcasting by community broadcasting to overcome a number of the deficiencies of sole reliance upon either commercial or public broadcasting. Direct subsidy is feasible for this, as are provisions for tax exemption or concessional status. These alternative funding mechanisms have emerged as especially important in the public-interest journalism sphere where revenue diversion from traditional journalism, including phenomenon such as news aggregators, has seen massive reductions in employment of journalists and the diminution of their news curatorial function. How much public funding is enough? To assist with this, a new notion of public value adopted from Mark Moore’s analysis has been increasingly employed to provide more strategic guidance for government and public broadcasters (Moore 1995). Public value is the equivalent of shareholder value in corporate management but seeks to embrace the full value of public value-based investments, including both the internal value to government operations and the broader political and social returns to the public at large. Creating and demonstrating net economic and broader social value in the social and political arena is, as emphasized, inherently difficult, though it has been embraced with enthusiasm by some broadcasters such as the UK’s BBC and Australia’s ABC. This enthusiasm has helped kindle greater research into measurement of the components of such value via market impact analysis, industry modelling and contingent valuation analysis, and perhaps also greater recognition of the mainly non-economic argument that in culture and the arts there is value ‘beyond price’ (Hutter and Throsby 2008; Withers 2019).

CONCLUSION In summary, there is market failure and there can be collective failure. For these reasons a mixed system of broadcasting allowing for the divergent strengths and weaknesses of each principal approach is a sensible application of the balanced-portfolio principle that has been adopted in many countries. The question is, in a world of contending principles with divergent histories, cultures and stages of development, and ceaselessly changing technology, just what is the right balance? The challenges in answering this question ensure that broadcasting economics has an interesting future.

NOTE * This chapter is a revision by Glenn Withers of Chapter 11 by Glenn Withers and Katrina Alford in the second edition of this Handbook (Withers and Alford 2011).

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80  Handbook of cultural economics

SEE ALSO: Chapter 14: Creative industries; Chapter 37: Media economics and regulation; Chapter 47: Platforms.

REFERENCES Australian Competition and Consumer Commission (2019), Digital Platforms Inquiry – Final Report, Canberra: ACCC,  accessed 12 December 2019 at https://www.accc.gov.au/publications/digital-platforms-inquiry-finalreport. Cave, M. (2007), Essentials of Modern Spectrum Management, Cambridge: Cambridge University Press. Cave, M., S. Majumda and I. Voselgang (2005), Handbook of Telecommunication Economics: Technology Evolution and the Internet, Amsterdam: Elsevier. Coase, R.H. (1959), ‘The Federal Communications Commission’, Journal of Law and Economics, 2 (October), 1–40. Cowen, T. (2000), ‘Why everything has changed: the recent revolution in cultural economics’, Journal of Cultural Economics, 32 (4), 261–73. Department of Communications and the Arts (2018), Inquiry into the Competitive Neutrality of the National Broadcaster – Report by the Expert Panel, Canberra: Australian Government. Finkelstein, R. and M. Ricketson (2012), Report of the Independent Inquiry into the Media and Media Regulation, Canberra: Department of Broadband, Communications and the Digital Economy. Gentzkow, M. (2007), ‘Valuing new goods in a model with complementarity: online newspapers’, American Economic Review, 97 (3), 713–44. Goldfarb, A., S. Greenstein and C. Tucker (2015), Economic Analysis of the Digital Economy, Chicago, IL: University of Chicago Press. Harcourt, A. (2007), ‘Institution-driven competition: the regulation of cross-border broadcasting in the EU’, Journal of Public Policy, 27 (3), 293–317. House of Lords, Select Committee on Communications (2019), ‘Regulating in a digital world’, HL Paper 299, 9 March, House of Lords, London. Hoynes, W. (2007), ‘Public broadcasting for the 21st century: notes on an agenda for reform’, Critical Studies in Media Communication, 24 (4), 370–76. Hutter, M. and D. Throsby (eds) (2008), Beyond Price: Value in Culture, Economics and the Arts, Cambridge: Cambridge University Press. Inglis, K. (2006), Whose ABC? The Australian Broadcasting Corporation 1983–2006, Melbourne: Black Inc. Maude, C. (2011), ‘Television’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton MA, USA: Edward Elgar, pp. 413–19. Moore, M. (1995), Creating Public Value: Strategic Management in Government, Cambridge, MA: Harvard University Press. Motta, M. and M. Polo (1997), ‘Concentration and public policies in the broadcasting industry: the culture of television’, Economic Policy, 12 (25), 295–334. Murdoch, J. (2009), ‘MacTaggart lecture’, at the Edinburgh International Television Festival, 28 August. Noam, E. (ed.) (1985), Video Media Competition: Regulation, Economics and Technology, New York: Columbia University Press. Noll, R.G., M.J. Peck and J.J. McGowan (1973), Economic Aspects of Television Regulation, Washington, DC: Brookings. Picard, R.G. (1989), Media Economics: Concepts and Issues, Newbury Park, CA: Sage. Peitz, M. and J. Waldfogel (2012), The Oxford Handbook of the Digital Economy, Oxford: Oxford University Press. Puppis, M. (2008), ‘National media regulation in the era of free trade: the role of global media governance’, European Journal of Communication, 23 (4), 405–24. Roson, R. (2008), ‘Price discrimination and audience composition in advertising-based broadcasting’, Journal of Media Economics, 21 (4), 234–57. Samuelson, P.A. (1964), ‘Public goods and subscription television’, Journal of Law and Economics, 7 (1), 81–4. Snowball, J.D. (2008), Measuring the Value of Culture: Methodology and Examples in Cultural Economics, Berlin and New York: Springer. Spence, M. and B. Owen (1977), ‘Television programming, monopolistic competition and welfare’, Quarterly Journal of Economics, 91 (1), 103–26.

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Broadcasting  81 Steiner, P.O. (1952), ‘Program patterns and preferences and the workability of competition in radio broadcasting’, Quarterly Journal of Economics, 66 (2), 194–223. Van der Wurff, R. (2005), ‘Competition, concentration and diversification in European television markets’, Journal of Cultural Economics, 29 (4), 249–75. Withers, G. (1982), ‘The Australian Broadcasting Commission: a case study in public enterprise’, in L.R. Webb and R.H. Allan (eds), Industrial Economics: An Australian Study, Sydney: Allen & Unwin. Withers, G. (2019), ‘Community Value Survey: key findings’, Public Interest Journalism Initiative, Melbourne, 20 November, accessed 12 December 2019 at https://piji.com.au/wp-content/uploads/2019/11/191118-communtyvalue-web.pdf. Withers, G. and K. Alford (2011), ‘Broadcasting’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 76–85.

FURTHER READING The foundations of broadcasting economics were laid in seminal contributions by Steiner (1952), Coase (1959), Samuelson (1964) and Spence and Owen (1977). Developments in the literature as analysis and technology evolved is summarized for the 1960s in Noll et al. (1973), for the 1970s in Noam (1985), the 1980s in Picard (1989), the 1990s in Cowen (2000) and in the new century Goldfarb et al. (2015).

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9.  Business models

Pierre-Jean Benghozi

The concept of business model has recently emerged strongly in economics and management. One of the reasons is the expansion of the Internet, which has opened up new opportunities to build innovative offering modalities and to support dematerialized, globalized and extended transactions. The development of information and communication technologies (ICTs) has also changed, through their flexibility and modularity, managerial and competitive strategies, the availability of goods and services and the way they are produced. These movements have stimulated new forms of innovation in all sectors, particularly in the configuration of business models: diversified pricing forms, value-added service bundles and applications grafted onto content (recommendations, social media, and so on), and multi-channel distribution taking advantage of mobile uses and terminal interoperability (De Prato et al. 2014). Currently, more than anywhere else in the cultural sector, the modes of production, distribution and consumption of goods and services are being disrupted by the digitization of all activities. Music, photography, video games, media, audio-visual and the art market have proved it since they have been the first economic sectors to be so deeply overwhelmed by the advent of new digital solutions. New markets and new actors are emerging, many sectors are undergoing rapid change, value chains are restructuring, threatening the position of large traditional players, shifting dominance relations within cultural industries. New business models are being tested, opening up new ways of financing activities (subscription, freemium pay per view, and so on) other than traditional forms of income (ticket purchase, for example). It is these transformations that are addressed in this chapter, by highlighting some of the new strategies that cultural organizations are deploying around business models, and by providing a framework for analysing such models. The chapter is organized in three parts. The first specifies the reasons and factors that give business models a decisive role in the digital age. The second part shows how the creative industries have been emblematic of the important changes brought about by the digital economy and to what extent they have made them a genuine laboratory for the digital transformations at work more broadly in the rest of society. The third part details the dynamics that can be observed in this area and, more precisely, the different components through which we can apprehend and understand the structuring of economic models. Finally, the conclusion raises the issues that are open in this context to cultural industries concerning the types of strategies they can develop.

THE TOPICALITY OF BUSINESS MODELS The vigorous evolution driven by digital technology is the result of several structural changes, with profound consequences. The very rapid growth of the digitization of society 82

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Business models  83 and the economy is now affecting the internal life of organizations, market relationships and individual practices as much as the way of creating art works and cultural content. Most obviously, the technological acceleration driven by equipment, networks and applications is accompanied by a constant flow of innovations. Its features make ICTs a useful tool that opens up wide promises for appropriation by the most diverse sectors – from agriculture to health and to culture – allowing them to be used by the most diverse users – artists, managers or simple workers – by promoting increased globalization and greater local control capacity. In doing so, digital technology completely redefines the key strategic resources and bottlenecks on which cultural firms relied, that is, talent, artistic projects, technology control, information control, availability and articulation between the virtual and the physical, appropriation and control of uses. Business Models in the Digital Age These features of the models of the new digital economy have given rise to several hypotheses (Benghozi and Paris 2007). In the cultural economy, some authors (Moreau 2013) have discussed to what extent digitization corresponds to a real disruption in the cultural economy or whether the Internet is perceived in cultural sectors as a potential threat (Blanc and Huault 2014) and therefore should be used to develop the existing business model instead of radically change it. More generally, it has also been suggested that the Internet would lead to the end of intermediaries, in favour of short distribution channels: creators or producers can distribute their content without the need for broadcasters (Brousseau 2002). The convergence of economic models and prices then appeared inevitable owing to the permanent possibility of comparison between competitors and the particularity of fixed cost and investment structures, reducing industrial effects of size and scope (Brynjolfsson and Brian 2000; Caves 2002). The decisive economic advantage available to new entrants in a context of rapid technological change has been highlighted, creating a ‘First-mover advantage’ (Varadarajan et al. 2008). The decoupling between capitalization dynamics based on a financial valuation of the audience of sites and sustainable industrial performance was highlighted. Finally, economists noted the importance of the networks externalities and the dynamics of ‘Winner-take-all’ favouring concentration and monopoly movements in particular (Frank and Cook 1996). These developments have stimulated the development of a literature on business models that has quickly become substantial (Chesbrough 2010; Demil and Lecocq 2010). Yet, as noted in Baden-Fuller and Haefliger (2013), the role of business models (and, by extension, ecosystems) in enabling a new technology to create a competitive advantage has often been underplayed in the literature. In most of the analysis of the digital economy and the Internet, and particularly in culture, however, this digital dimension is, paradoxically, most often treated in a global and very abstract way. Consequently, there is a great risk that the central importance of technology in ongoing changes will be underestimated, or even completely eliminated, in favour of a single vision of service and distribution innovations. The too-high degree of generality of the statements therefore hinders thinking about the specific features of ICTs in cultural and creative industries, by hiding behind the references to Netflix, Amazon, Apple or Google, which have very different ways of appropriating and mobilizing these technologies.

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84  Handbook of cultural economics In addition to its digital dimension, another major feature of what can no longer be called the new economy is the opportunities opened up by ICTs for remote communication and cooperation, and for inclusion in interconnected infrastructure and networks. From the outset, they have given the digital economy an international, or global, dimension. In a global and international market, the issue of protection of cultural diversity, support for creativity and independent works is at the core of all cultural policies. In the cultural sector, confronted for a long time with internationalization, the protection of diversity is at the heart of trade policies. Their backgrounds and objectives are, however, questioned by digitization. As a result of new technologies, the production, distribution and internationalization processes of cultural industries have expanded, blurring national as well as sectoral borders. The question of the relationship between the digital global economy and local economies is central to culture, but the national challenges of this globalized economy remain poorly understood. A double movement overwhelmingly alters the bond between the virtual and the physical world. The complete dematerialization of certain services and content opens the way to ubiquitous forms of consumption that favour the globalization of markets, business models and the field of action of economic actors, and especially for music or audio visual. Audio-visual markets are, for example, highly fragmented from a linguistic and cultural perspective. There is, consequently, a clear cleavage of preferences for local or national products, on the one hand, and international, on the other. However, the necessary physical presence or materiality of the culture items (that is, printed books, newspapers, live shows or art objects) has also stimulated the emergence of new forms of remote distribution achieving the dematerialization of information and transactions as part of an optimized distribution, giving space to material availability and the localization of consumption. The Multiplication of Business Models The combination of these characteristics defines new economic dynamics in culture that reflect the completely new place in the digital economy of business models and associated financing methods. They mark the shift from an economy historically anchored in the exploitation of scarcity (talents, exclusive contents and unique heritage or piece of art) to development structures that are based on economies of abundance. The traditional foundations of the economy, particularly in the cultural sector, have always been based on the principle of uniqueness and scarcity of resources,1 and therefore on the search for the best conditions for their use and allocation. Strategic control of key resources, logistical organization and catalogue management, physical limitation of space and sales forces, targeting of market segments, and so on, are therefore all aspects of cultural companies’ actions deeply marked by the limited resources available. Alternatively, the widespread connectivity opened up by digital technologies reflects a radical shift towards an economy of abundance that profoundly changes the economic dynamics at work in culture. Several illustrations can be given. A first factor of abundance is the emergence of a world of hyperoffering2 and –­ ­analogously, for consumers – by situations of hyperchoice. A major structuring feature of the digital cultural economy is the almost unlimited possibilities it offers to connect, store and offer dematerialized information and content. The multiplication of exchanges, the

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Business models  85 contribution of a prodigious multitude of contributors, the cumulative enrichment, over time, of existing portfolios of works and the multiplicity of forms of valorization create a complete change of scale in the proliferation and availability of content and services. For example, in Europe alone there are several hundred online music platforms, and these are only those identified as legal. Consequently, in music, as in other cultural fields, the unlimited accumulation of existing works and the multiplicity of content offered by Internet users make it difficult for consumers to make their usual choice, based on cognitive control of the structure of the offering and their own criteria of selection. This control is no longer possible because the possibility of choosing from a plethora of offers presupposes the use of automatic selection and recommendation tools (assistance in the choice and personalization of recommendations, and statistical proposal on the basis of similar clients). Such a plethora prevents consumers from finding their way around on their own and, in return, gives platforms and prescribers a leading role (Gawer and Cusumano 2008). The possibilities of constantly multiplying and reconfiguring the forms of offers, services and monetization generate a multiplication of business models that can be observed in the same field. Historically, industry and management have been built around the idea that there is a one best way to organize and produce goods. Among phonographic publishers, there are certainly differences between Universal, Sony and Warner, but the means by which artists are produced and recorded remains roughly similar from one label to another. This is not the case in the digital world. On the contrary, the flexibility of technologies and the way they are combined open up the possibility of designing the provision of the same goods and services in very different ways, by coalescing very closely uses, technology, service production, consumer relations and income models. The choice of a music streaming platform – Spotify, Apple or Amazon, for example – is less about the specificity of a particular music than about the business model and the overall size of the available catalogue. A first explanation for this proliferation of business models results from companies’ exploration strategies to find the ‘right’ online model. This is what we see in the press today, for example. The multiplication in this hypothesis is due to the addition of trial and error mechanisms, where every cultural company tests options before converging on the right solution. In this case, we would be in a temporary phase that should stabilize in the near future. However, there is also a second, more disturbing explanation, which sees business models as the very basis for innovation. Thanks to ICT, companies are now innovating less on the intrinsic nature of the offer than on, for example, transaction methods, traceability, users’ data, and the possibility of using usage information to create new activities or new services.

CULTURAL INDUSTRIES: A LABORATORY OF INNOVATION From this perspective, it is important to study the cultural industries sector. It appears to be a very important precursor to the dynamics driven by the Internet and makes it possible to understand the central role of business models in the digital economy. Several factors explain this situation: the weight of new entrants in pre-existing sectors (for example, Amazon in publishing, iTunes in music and Netflix in video), the radical

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86  Handbook of cultural economics nature of alternative forms of valuation (user-generated content and free sharing sites such as YouTube), the predominant role of community portals and content aggregation platforms (such as photography or audio-visual sites such as Flickr or Instagram), the emphasis on a prescription economy that challenges the economics of traditional content distribution systems (in the case of Google News in the press) and the variety of parallel open marketing methods (for example, multiplayer video games). The importance of the technical dimension combined with the high instability of business models and forms of competition leads to a rethinking of traditional forms of financing, investment and remuneration (Benghozi and Salvador 2016). Digital technology combines two very different economies which find their full manifestation in culture: that of cultural projects and infrastructure, and that of data and services. The former are in fixed-cost industries with low marginal cost of distribution, where externalities and network effects are significant. Conversely, the service economy is more changeable and can be thought of as a low-investment structure when works and networks already exist and are available. The consequences are multiple. A particularly important consequence in culture concerns the way in which the value created on services is shared between the different actors in the value chain. More precisely, this is the extent to which this value is captured by downstream actors (retailers, distributors and online platforms) or contributes to the financing of content (producers and publishers) (Benghozi et al. 2017). Several major innovations in business models have thus emerged in the culture. Usergenerated content sites, such as YouTube or Dailymotion, fed by Internet users’ productions, are representative of new relationships built with customers who are both consumers and producers (Noam and Pupillo 2008). Kickstarter in the USA or KissKissBankBank in France are just as emblematic of the radical innovation that participatory financing models represented. In addition to these new schemes, cultural sites also offer new ways of thinking about the hybridization between traditional marketing methods and online distribution. In the audio-visual sector, for example, Netflix has ensured the transition from the distribution and rental of video cassettes to a platform for the aggregation of professional audio-visual content offering, in original and disruptive forms, cinema films, catch-up television and video on-demand (VOD). There are several reasons why the cultural industries constitute such an experimental laboratory. These are related both to the specific characteristics of these industries and to their place in the economy. First, the whole economy has become aware of the central role of creativity and design in economic growth and value creation. Forms of management in cultural industries are increasingly used as a reference for other companies, whether it is to organize production, manage talent or stimulate the creation of goods or services (Hadida and Paris 2014). However, if the cultural industries appear so creative in their business models, it is also owing to their structural characteristics: the immaterial dimension of their contents, the specific articulation they operate between symbolic value and use value, and the permanent renewal of forms and stylistic content. These characteristics are expressed in the particular modalities of business models: variety of pricing forms (payment of unit support in the book, by subscription in the press, or flat-rate single payment in the performing arts) or the central role of free services that have long existed in the media and are now being renewed in a unique way.

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Business models  87 Finally, another distinctive feature is the particular articulations and tensions that are created in the supply chains between the phases (design/creation) of value creation on the one hand, and those (distribution and relationship to the consumer) of value appropriation, on the other. They give rise to alternative forms of organization where professional productions and editorial choices of traditional models are replaced by self-produced content selected from automatic recommendation systems. More broadly, technological developments are thus contributing to the multiplication of the modalities of availability: on the one hand, the same online content is found on several types of terminals and access; on the other hand, the offers do not only come from the usual publishers or producers of culture but also from new actors – often powerful and with considerable resources – taking root in culture from original positions and new competitive resources, for example, Google, Apple, Amazon or Altice.

THE BASICS OF BUSINESS MODELS The new economy of culture that is being set up on the Internet is shaped by strategic and management dynamics that respond to original forms of trade organization, the emergence of new entrants and new market mechanisms. The notion of business models makes it possible to understand how the strategy, the firm’s organization, the structuring of its offer, its customer management and its revenue structure, and the ability to think dynamically and coherently about their articulations and architecture are designed together. From this view point, the definition we gave at the time of the first Internet bubble remains valid (Benghozi and Kervern 2000). We then qualify a business model as ‘the economic configurations (investment structure, prices and pricing methods, organization of production and distribution, partnership and competitive positioning) that characterize the forms of production and marketing of a good ensuring, for a given economic actor, the sustainability and profitability of its activity’ (Benghozi and Kervern 2000, p. 19). The same bases are found in the often cited definitions of Osterwalder and Pigneur (2010) or Johnson et al. (2008). They can be operationalized from a strategic perspective, distinguishing in particular four main dimensions (Figure 9.1): 1.  What is the supply of cultural products and services offered and provided to consumers? 2.  How are these products and services produced and made available in practice through a technical production infrastructure? 3.  By whom and by what means are relationships built and structured, on this occasion, with users? 4.  How much income and how is it generated, and what are the economic provisos of financing? The Supply Structure: What? The first layer of business models therefore lies in the configuration of the offering structure. What is the spectrum of products and services offered? What value do they have

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88  Handbook of cultural economics WHO?

How to manage relationships with customers, satisfy them and generate revenues to be on the winning side?

HOW? Customer relationship

Infrastructure logistics

Product innovation

WHAT?

What is the scope of products and services, its value (its benefits) for the customer, the capabilities to deliver them in an innovating way?

How to organize the infrastructure, its resources, the knowledge and the structure of resulting costs, manage the value chain and processes, build alliances to achieve performance?

Financial aspects

HOW MUCH?

What is the revenue model? The profit model? Designed to last?

Figure 9.1  The four components of business models for the customer? To what extent does the firm have the capacity to provide them in an innovative way? While expressing themselves in a specific way according to the context, these questions raise new ways of approaching the production and creation of content in culture. The composition of cultural supply, for example, directly questions the ways in which content is highlighted. This function of publishers, producers or artistic directors, consisting of selecting and promoting artists and works, is traditionally at the heart of the cultural industries. However, in the digital age, it finds specific expressions with the shift produced by dematerialization and an economy that favours functionality and service (distracting yourself for two hours, watching a video programme or listening to music) instead of bringing the content itself (such a film or CD). Increasingly, more sites are thus building their value in effect around prescription or what is now known as curating. This consists, on a thematic basis, in researching, sorting, formatting and disseminating. These approaches are integrated into existing content aggregation sites but also give rise to specific sites (Scoop.it, for example). Editorial capacity is also affected by the unlimited accumulation of existing cultural works and the multiplicity of productions spontaneously proposed by Internet user – professional or not. This abundance of content is the result of the new and almost limitless capacity for storing and making content available. It is then due to the multiplication of cultural works that are no longer produced and proposed only by professionals, but also by amateurs or actors at the margins of the profession. This oversupply and ­hyperoffering alters the exercise of the detection and choice function. These are no longer the sole responsibility of a publisher but are carried out by mobilizing communities of users and by using automatic selection and ­recommendation tools (‘those who have loved . . . also loved . . .’): they are therefore

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Business models  89 carried out a posteriori on existing content rather than a priori on projects and artists in the making. These dynamics therefore make it particularly critical for cultural companies to develop their distinctive position based on the stability of tastes and the quality of editorial choices, by taking specific risks on the coupling, in the sales structure, between ­bestsellers and niche products. However, in hyperchoice contexts,3 the focus of consumers on particular goods is uncertain with regard to particular content. Companies therefore seek to avoid the random nature of Internet users’ attention by directing success through recommendation mechanisms and information tools (Bain & Company 2013). The Organization Infrastructure: How? The second necessary component of any business model is the technical and logistical infrastructure that the company puts in place to support its production and distribution. How to organize the processes of resource provisioning, manufacturing and content provision? What constraints do they pose and what prospects do they open up in relation to innovation, the enrichment of services or the production of works? How does this infrastructure influence the value chain and the development of partnerships? Beyond the possibilities offered to redesign the offer and services provided to ­customers (for example, significant reduction in cataloguing and order processing costs), ICTs create opportunities to optimize processes and improve the efficiency of companies. As the success of the App Store demonstrates, the modular nature of these technologies also makes it possible to design infrastructures as technical platforms, capable of constantly evolving as the types of applications and content offered are renewed, by updating the platform’s interfaces and functionalities, by the appearance of new terminals or access channels, and by the evolution of performance allowed by the evolution of throughput or network infrastructures (Gawer et al. 2008). It is therefore possible to think and organize the organization, autonomy and articulation of the different circuits mobilized in sales and transaction administration very differently: logistics, financing, marketing, payment, information, and so on. These transformations take place under the effect of internal dynamics within the firm and through new entrants bringing management innovation. Thanks to the flexibility of information technologies, intermediaries can be grafted at different levels of the value chain, in transactions between artists and producers, in relationships between artists and potential consumers and in relationships between producers and consumers. We often talk of these types of development as disintermediation/­ re-intermediation movements because the old forms of intermediation (think booksellers or record shops) are disappearing in the wake of the new ones (online aggregation platforms, App Store or specialized engines, for example). This calls for a profound redefinition of the creative company’s core competencies: in the perception of its business as well as in the ways in which its resources are valued, in its innovation and development capacities, in its diversification strategies and in its position in the value chain. Online transactions are changing the nature of relationships with content providers within traditional cultural channels. They stimulate intermediation configurations covering contractual relationships, the products themselves, information and customer marketing. Information no longer contributes only to the evolution of the value chain, but to the creation of value itself. These new value-creation mechanisms cannot be reduced just to

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90  Handbook of cultural economics big data, to which the entire knowledge-based economy is, unfortunately, too frequently reduced. The importance of the changes at work lies, in particular, in the very diverse nature of the information that can be used to create value. First, processing of upstream information, which concerns production management, makes it possible to deeply rethink the sources of performance. However, there is also information downstream, which concerns the characteristics of the market and the traces of use. Users are no longer just consumers. By using cookies as well as the notifications they post or the transactions they perform, including in case of live show platforms such as TicketMasters, they create value for cultural stakeholders. They produce data continuously, dynamically, by opening up new ways of valuing and exploiting the data: selling user profiles, selling visibility in the form of advertising promotion, enhancing the predictability of behaviour, aggregation and data processing. The Revenue Model: How Much? Business models are most often reduced to the financing and monetization dimension. By focusing mainly – if not exclusively – on their effectiveness and sustainability, they are often confused with simple transaction models (for example, how to invoice the consumer, by unit or by subscription, in free or paid form). However, several questions arise for companies from a financial point of view. What is the profitability to be expected from online activities? What is the performance of the different forms of transaction that can be considered? What (new) measurement and evaluation tools should be used to monitor these activities? The effect of monetization forms is important and goes well beyond that of remuneration. It modifies the cost structures of these productions and the very nature of the works and creation. In the field of culture, the debates on income have focused mainly on free access. The Internet has opened up the possibility of shaping new price structures and profitability models around unique market architecture. In addition, ‘prescription’ (Benghozi and Paris 2007) or ‘two-sided’ (Rochet and Tirole 2003) markets make it possible to compensate between free-of-charge mechanisms and complementary revenue structures, as was historically used in media such as newspapers, radio or television channels. This has led to a redefinition of traditional financial flows between customers, distributors and producers, opening up new income structures and new forms of distribution of added value within the production/distribution/marketing channels of works. This possibility of designing alternative valuation models has directly changed the distribution of investments and income between partners. This is the main focus of the debates that have emerged in recent years, under the name of net neutrality, around the economic interdependence of the technical layers that form content publishers, infrastructure access providers and, finally, equipment and terminal manufacturers. Dominant players (platforms such as Google or YouTube) can now benefit from a position where they can take advantage of new distribution channels without having to invest directly in networks or content. These issues are all the more important as online advertising becomes more widespread as a potential source of revenue. Any site can now very easily deploy an advertising offer, regardless of its level of traffic. Internet advertising therefore opens an important space for thinking about the concrete methods of remuneration or formatting of the advertisements received, by developing inventiveness in the design of promotional materials

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Business models  91 articulated with the content, to better understand and think about the practices and uses of visitors. However, the new framework opened up by the Internet for advertising revenue only appears truly significant for a limited number of sites and can become the sole source of funding only for those who succeed in building an exceptional popularity of several hundred thousand or million page views. The result is consistent with the whole Internet economy, which remains dominated by strong network effects, favouring the creation of dominant sites, or even quasi-monopolies (YouTube in video, Facebook in social media and Netflix in video), thanks to the concentration of traffic in favour of the most attractive sites and content, in what could be called a podium or star system logic, well known to the cultural industries. The Relationship with Customers: Whom? The final important dimension of business models concerns the configuration of customer relations. This component is all the more decisive as the dematerialization of content and the shift towards a service economy have a profound impact on consumer use: multiple media and terminals used, mobile access, high consumption practices and the development of self-production. The issue for cultural industries is therefore, how, in such a context, to manage customer relations, satisfy them and generate revenue. Cultural practices are changing and the logic of demand–pull production is taking place, which substitutes the historical model of production (aesthetic project-push) of works of art and cultural contents. We are also witnessing a consumerization of content production and distribution, introducing new ways of interacting between creators and customers (Simon 2016). Users thus generate more content and occupy a more important place through self-publishing or self-production (book, video, photograph or music), the animation of exchange communities and their possible involvement in the form of participatory financing. The value chain (production/distribution/consumption) has opened up. Structuring customer relations requires knowing how to build a relationship of attachment and community belonging through the network: this implies knowing how to promote the matching between the tastes and contents offered and to ensure a permanence of the relationship with consumers – over time and beyond a specific form of content or support. This ultimately helps to reduce editorial risk through more effective forms of adjustment. However, firms in the cultural sector are largely dependent on the offering placed on the market by equipment manufacturers (readers, tablets and smartphones) or on the forms of marketing devised by network operators or main Internet players (multiple play offers, unlimited subscriptions, and so on). Controlling consumer relations therefore presupposes that these firms take charge of, control and value the information associated with their uses, even though they are not used to having it. This is the information necessary for companies (data on customers, markets and competition, and so on) as well as that made available to customers (for example, data on products, qualities, prices and availability).

CONCLUSION Information and communication technologies and the Internet offer a special opportunity to improve all dimensions of business models. They make it possible to improve

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92  Handbook of cultural economics t­ransaction tracking, to provide new loyalty tools and to customize the offer and recommendations. These developments require that sites can constantly evolve their existing economic design by giving themselves the means to adapt the goods they supply, to produce them, to vary the forms of transactions and revenues, but also to build new relationships with their users. Online activities can particularly help to give more substance to consumer relations by fully exploiting the notions of community and interactivity, which is true for all cultural industries and not only for sites that have built their model on social networks. The existing players and brands established in the cultural sector have considerable assets. The symbolic dimension of culture and the emotional attachment it generates encourage consumers to collaborate with cultural sites by spontaneously providing information on their uses (personal data, preferences and consumption history), which they do not necessarily do for other more anonymous or for-profit sites. New entrants or service providers, unknown to the public, must therefore invest heavily to build a brand and build Internet users’ trust, unless they are condemned to extremely specialized and restricted niches. It is therefore not surprising that some historical cultural media offer a unique capacity for their audience and good resistance to new entrants. However, the rapid renewal of the technical and economic context is putting significant pressure on culture companies to succeed in building stability in a changing environment where alternative business models are multiplying. The speed of technological and economic change requires cultural industries to be highly adaptable in order to be able to make adjustments but also, sometimes, to profoundly reconsider their positioning, their model and some of their strategic choices. In particular, they must take into account the evolution of Internet users’ practices, which are leading them towards ever greater mobility and an ever-decreasing dependence on the traditional media and historical methods of viewing, reading, listening or watching cultural goods. All sites are now faced with the need to increase the availability and continuity of their service by offering it on fixed Internet, smartphones, tablets and roaming. They must be able to extend the accessibility of content and existing service offerings to take into account the demand for service continuity in multi-channel distribution. Faced with this situation, economic actors have two options. The first is the ability to constantly adapt and innovate in response to observed changes, which is the current choice of the press. A second possibility is to design content platforms from the outset that can integrate the variety of possible business models or implement them without having to fundamentally question the infrastructure; in cultural sectors, this is what only new entrants such as Google or Apple have been able to do thus far. The digital revolution is prima facie a revolution in technological intermediation, driven by new players who bring new solutions allowing the aggregation and distribution of content, and who introduce their own technical devices around which they organize their offer; for example, iPhone/iPod, Kindle for Amazon and books, Fire for the same company and videos, Netflix. This leads to strong pressure to eliminate traditional intermediaries (distributors, booksellers and record stores) through a disintermediation/ re-intermediation process that significantly reshapes the market structure and changes existing value chains and business models (Simon et al. 2015). The emergence of platforms, the structuring of two-sided markets and the development of a prescription economy are the most striking phenomena. By stimulating innovative

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Business models  93 and entrepreneurial strategies around them, platforms promote the development of industrial and cultural ecosystems, and transform all associated cultural sectors, such as the emergence of new offers, the creation of new business models and the emergence of new players. Through the network externalities from which they benefit, these platforms create new forms of domination, including the aggregation of supply and demand on an unprecedented scale, vertical integration, the ability to ensure transactions, attention and prescription control, and the mastery of proprietary standards. Consequently, new forms of competition are currently being played out, even within value chains. Until now, we have seen traditional horizontal competition between similar actors producing similar goods: music record labels, publishers, newspaper, television producers, art galleries, art auction houses, and so on. Now, new forms of vertical competition are emerging between a large range of different actors; for example, artists and producers, suppliers of goods and services, information intermediaries, terminal providers and access providers. Everyone is fighting to be as close as possible to the consumer in order to constitute, thanks to the strength of its name or its brand, the preferred entry point for goods that are now aggregated. Since the trigger for a transaction can be the search for a particular content but also the opportunity given by an Internet service provider’s plan, the choice of terminal and operating system, the application providing the content or service, or even the search engine that led to the application. The digital economy of culture thus becomes, in many ways, a branding economy.

NOTES 1. Moreover, we often speak of cultural industries as prototype industries to illustrate that each production is based on a unique project and specific resources. 2. The neologism of hyperoffering aims precisely to capture the particular character of the mass of content available online (that is, books, video, music, and so on), reflecting a radical change of scale in relation to the ranges of products and services available in the traditional distribution channels of the cultural industries. 3. The existence of a hyperoffering, on the supply side, is reflected, on the consumer demand side, in a situation of hyperchoice where each individual is faced with a mass of content for which his cognitive abilities are insufficient.

SEE ALSO: Chapter 26: Digitization in the cultural industries; Chapter 36: Marketing the arts; Chapter 47: Platforms; Chapter 49: Pricing the arts.

REFERENCES Baden-Fuller, C. and S. Haefliger (2013), ‘Business models and technological innovation’, Long Range Planning, 46 (6), 419–26. Bain & Company (2013), ‘The age of curation: from abundance to discovery’, accessed 8 December 2019 at www.forum-avignon.org/sites/default/files/editeur/2013ForumAvignon_EN_BD-23-10-2013OneonOne.pdf. Benghozi, P.-J. and G.Y. Kervern (2000), ‘L’économie du multimédia sur Internet: de nouveaux modèles pour des principes immuables’ (The economics of multimedia on the Internet: new models for unchanging foundations), La Jaune et La Rouge, 551 (January), 18–22.

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94  Handbook of cultural economics Benghozi, P.-J. and T. Paris (2007), ‘The economics and business models of prescription in the Internet’, in E. Brousseau E. and N. Curien (eds), Internet and Digital Economics – Principles, Methods and Applications, Cambridge, MA: Cambridge University Press, pp. 291–310. Benghozi, P.-J. and E. Salvador (2016), ‘Investment strategies in the value chain of the book publishing sector: how and where the R&D someway matter in creative industries?’, Technology Analysis & Strategic Management, 28 (5), 568–82. Benghozi, P.-J., E. Salvador and J.-P. Simon (2017), ‘The race for innovation in the media and content industries: legacy players and newcomers. Lessons from the video game and cinema industries’, Journal of Arts Management, Law and Society: Digital Cultural Policies in Comparison, 47 (5), special issue, 346–60. Blanc, A. and I. Huault (2014), ‘Against the digital revolution? Institutional maintenance and artefacts within the French recorded music industry’, Technological Forecasting & Social Change, 83 (C), 10–23. Brousseau, E. (2002), ‘The governance of transaction by commercial intermediaries: an analysis of the reengineering of intermediation by electronic commerce’, International Journal of the Economics of Business, 8 (3), 353–74. Brynjolfsson, E. and K. Brian (2000), Understanding the Digital Economy, Boston, MA: MIT Press. Caves, R.E. (2002), Creative Industries: Contracts Between Arts and Commerce, Cambridge, MA: Harvard University Press. Chesbrough, H.W. (2010), ‘Business model innovation: opportunities and barriers’, Long Range Planning, 43 (2–3), 354–63. De Prato, G., E. Sanz and J.P. Simon (eds) (2014), Digital Media Worlds: The New Economy of Media, Oxford: Palgrave. Demil, B. and X. Lecocq (2010), ‘Business model evolution: in search of dynamic consistency’, Long Range Planning, 43 (2–3), 227–46. Frank, R.H. and P.J. Cook (1996), The Winner-Take-All Society: Why the Few at the Top Get so Much More than the Rest of Us, New York: Penguin Books. Gawer, A. and M. Cusumano (2008), ‘How firms become platform leaders’, MIT Sloan Management Review, 49 (2), 28–35. Hadida, A.L. and T. Paris (2014), ‘Managerial cognition and the value chain in the digital music industry’, Technological Forecasting & Social Change, 83 (March), 84–97. Johnson, M.W., C.M. Christensen and H. Kagermann, (2008), ‘Reinventing your business model’, Harvard Business Review, 86 (12), 50–59. Moreau, F. (2013), ‘The disruptive nature of digitization: the case of the recorded music industry’, International Journal of Arts Management, 15 (2), 18–31. Noam, E. and L.M. Pupillo (2008), Peer to Peer Video: The Economics, Policy, and Culture of Today’s New Mass Medium, New York: Springer. Osterwalder, A. and Y. Pigneur (2010), Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, New York: John Wiley & Sons. Rochet, J.C. and J. Tirole (2003), ‘Platform competition in two-sided markets’, Journal of European Economic Association, 1 (4), 990–1029. Simon, J.P., (2016), ‘User generated content. Users, community of users and firms: toward new sources of co-innovation?’, Info, 18 (4), 4–25. Simon, J.-P., P.-J. Benghozi and E. Salvador (2015), ‘The new middlemen of the digital age: the case of cinema’, Info, 17 (6), 97–115. Varadarajan, R., M.S. Yadav and V. Shankar (2008), ‘First-mover advantage in an Internet-enabled market environment: conceptual framework and propositions’, Journal of the Academy of Marketing Science, 36 (3), 293–308.

FURTHER READING Benghozi et al. (2017) and, on the disruptive nature of digitization, Moreau (2013).

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10.  Contingent valuation Tiziana Cuccia

Contingent valuation (CV) is a method of estimating in monetary terms the economic value of non-market goods (for example, public goods) or of some public-good attributes of market goods. Contingent valuation can be used when the price-clearing mechanism does not work (for example, in case of externalities) or it is not able to reveal the economic value of an attribute of a good (for example, in the case of demand functions à la Lancaster 1966). The literature distinguishes two main classes of economic valuation methods: revealed preference methods, which infer the economic value of non-market goods and/or services from consumers’ behaviour, and stated preference methods that infer the economic value of non-market goods and/or services from consumers’ statements reported in surveys. Contingent valuation is a stated preference (SP) method; it consists in the design of a questionnaire to submit to a representative sample of the population directly, in survey or experimental settings, to estimate the willingness to pay (WTP) for qualitative and quantitative increments in non-market goods or services, or the willingness to accept (WTA) or tolerate qualitative and quantitative decrements of the non-market goods or services. Both WTP and WTA can be used as measures of the individual’s demand of non-market goods or services.1 The individual evaluations depend on the scenarios described in the questionnaire; thus, it is contingent to the proposed scenarios, and a hypothetical market is mimicked. The CV estimates aim to support policy initiatives devoted to increasing social welfare through a more efficient allocation of public and/or private funds. Contingent valuation studies started in the 1960s and were mainly applied to environmental goods that typically present the characteristics of public goods: non-rivalry and non-excludability in consumption. The seminal book by Mitchell and Carson (1989) contributed to speed up the dissemination of this method and to start a debate on its pros and cons. Beyond environmental economics, CV has been applied mainly in transportation and health economics (Carson 2011).2 Contingent valuation was applied for the first time to cultural economics in the 1980s: Throsby and Withers (1983) conducted a CV study to compare public transfers for arts with consumers’ WTP in Australia. Since then, CV studies have been applied in eliciting the individual preferences for a wide range of cultural goods. Heritage, historical and archaeological sites are typical examples of public goods that are considered by CV studies (Navrud and Ready 2002). However, CV has been also applied to the evaluation of the social benefits of other cultural institutions (theatres, museums, libraries and public broadcasting) that can be considered mixed goods (chargeable goods or common goods). More recently, different projects of renovation of urban centres and marketing strategies of cultural institutions have been considered in CV and other SP method studies.3 Compared with other methods of eliciting individual preferences, CV is extremely flexible: it can easily be adapted to different objects of analysis, and it is capable of estimating all the different components of the total economic value (TEV) of goods: use values and, 95

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96  Handbook of cultural economics above all, non-use values or passive use values (Arrow et al. 1993). These characteristics also justify the increasing interest on the part of international organisations, such as the World Bank, in CV for the evaluation of development plans, and of private and public institutions, such as insurance companies and courts, respectively, for the evaluation of damages in environmental litigation. Adopting CV studies to estimate the citizens’ WTP for different public project appraisals that directly or indirectly affect cultural goods, and considering this monetary value in the benefit–cost analysis of public investment projects, represent a big step ahead from a political perspective. It means avoiding a paternalistic approach. In this chapter, we describe this method in more detail and why it is preferable to other methods in the valuation of cultural assets. We resume the main issues of the theoretical debate on the pros and cons of CV, and we discuss the cultural policy implications of recurring to CV and other SP models. Finally, we trace out the future of the research on CV from the theoretical and applied viewpoints.

THE STRUCTURE OF A CV STUDY Contingent valuation can be considered a particular case of SP discrete choice experiment (CE) in which the same proposal, alternative to the status quo, is submitted to a sample of population at different prices that randomly vary (Willis 2014, p. 150). The price is the only attribute that changes; this is the main difference from the other SP choice experiments, where alternative combinations of the different attributes of cultural goods and services, including price, are combined, and the WTP for each attribute can be inferred only indirectly. Therefore, the characteristic of CV rests on respondents directly stating their preferences for a non-market good or service filling in a structured questionnaire which is specifically prepared by the analyst to reproduce a hypothetical market situation where the good or the service can be exchanged. The main steps of CV analysis are the sample selection, the description of the contingent market and the choice of technique for eliciting the WTP. However, under this apparently simple structure, many problems concerning economics, psychology and political theory must be solved to obtain reliable information on individual WTP and/or WTA. Many of these problems have been discussed by the National Oceanic and Atmospheric Administration (NOOA) panel4 who suggested that a large number of stringent requirements must be satisfied in order to obtain reliable WTP estimates in CV studies. The first problem concerns what has to be measured. The choice between WTA and WTP could be relevant in the case of cultural assets for two main reasons: first, because they have no substitutes; and, secondly, owing to the loss aversion (or endowment effect) of the respondents.5 However, the NOAA guidelines suggest that WTP estimates are preferable. The second critical point of a CV study concerns the stratification of the sample. In the case of cultural assets with international historical and artistic recognition, the size and the stratification of the sample should be very large and should include people from everywhere. The cost of the study increases with the sample size. Cost considerations can also influence the choice of how to submit the questionnaire (face-to-face, telephone or mail interviews). This choice may have an effect on the response rates (usually lower in

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Contingent valuation  97 mail surveys). Currently, Internet surveys seem to be a valid alternative to face-to-face interviews (Lindhjem and Navrud 2011). The third key point of the CV method is the questionnaire design. The increasing use of CV studies in policy decision-making and litigations (Natural Resource Damage Assessment) makes the definition of a common design inevitable. The main sections of the questionnaire include (Kerry Smith 2006; Whitehead 2006): 1.  An introductory section that includes attitudinal questions to discover what is the respondents’ opinion and behaviour about cultural goods or services in general. 2.  A valuation section with the key questions on the WTP for the specific cultural good or service under scrutiny. It should include: a plausible description of the hypothetical scenario to be valued, supported, if possible, by visual aids; the payment vehicle, to make respondents aware of budget constraints, and the question on the WTP for the scenario described. Some follow-up questions on the WTP questions should be also included to validate the estimates. 3.  A final section with questions on the socio-demographic characteristics of the respondents (age, income, profession, education, and so on). This allows researchers to analyse the possible determinants of the price and income elasticity of the demand. The choice of the questioning format for eliciting WTP in the valuation section is the most important aspect of the questionnaire design. Different biases would be present depending on the WTP elicitation question adopted. The two main formats are: the open-ended and the close-ended or dichotomous-choice format. The open-ended format consists in the simple question ‘What is the most you would pay . . .?’. This could be a difficult question when applied to cultural goods or services. Respondents have no reference amount and may prefer not to answer the question or to give values with very high dispersion (Carson et al. 2001; Vossler and Holladay 2018). The dichotomous choice, suggested by NOOA guidelines, seems to overcome the weakness of the open-ended elicitation format. The dichotomous-choice format requires only a yes or no answer from the respondents on a stated amount for the item. This format reproduces the situation individuals face in the market or in a referendum setting, and it has been shown to be incentive-compatible, and it helps limiting free-rider behaviours. However, this elicitation format, based on a stated initial bid, can be statistically biased and inefficient, owing to starting-point bias, anchoring and yea-saying. The choice of the bids is very important as the estimates of WTP depend on the first bid of the iterative process (the anchoring bias). A key point is how to define the bid vector from which to choose at random the bid to insert in the questionnaire. An open-ended or a payment-card CV survey submitted to a focus group of experts is usually used as a pre-test to determine the possible distribution of WTP. The presence of a bid favours more answering than does an open-ended format (yea-saying). The double-bounded format (Hanemann et al. 1991) helps to improve the statistical efficiency of the dichotomous-choice format, and it makes it possible to overcome the starting-point bias and the anchoring effect, as the second bid can be very different. A well-designed questionnaire enables the researcher to minimise the bias and zero WTP values, and increase the validity and reliability of the estimates. The validity of

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98  Handbook of cultural economics the CV estimates can be evaluated by resorting to estimates produced by other, indirect, revealed valuation methods, such as hedonic pricing, travel-cost studies6 and referenda (convergent validity).7 Reliability would require the possibility of replicating the study either in a different context, or at a different time (temporal reliability). The validity and reliability of this method are still controversial, and the debate concerns both technical and theoretical aspects.

PROS AND CONS OF CV Two main positive aspects of the CV method can be underlined: (1) the great opportunity to recover all the components of TEV, that is, use and non-use values of a good or service,8 and (2) its flexibility which enables analysis of new policy options for cases in which data are not available (Hanemann 1994). The negative aspects concern the validity and reliability of the CV estimates (Diamond and Hausman 1994). Theoretical criticisms are related to: (1) hypothetical markets and free-rider behaviour – asking respondents for a hypothetical payment is different from asking for a real payment, and they can act strategically; and (2) the embedding effect and insensitivity to scope. In this case the usual assumption that more will always be better is not applicable.9 Respondents’ WTP may not increase with the size and/or the quality of the goods under evaluation as respondents can be more interested in the general content of the project (that is, the preservation of cultural heritage, and so on) than in the specific cultural site preservation project under evaluation. The WTP value for some specific goods could be found to be similar or even larger compared with the WTP value for more inclusive goods; for example, the WTP to restore a single monument could be found to be equal to the WTP for restoring two or more monuments, that is, the scope of the project does not influence WTP. Moreover, in a hypothetical framework, respondents could be induced to overestimate their WTP to show positive attitude and moral satisfaction (impure altruism or ‘warm glow’; Bishop 2018). Welldesigned surveys and scope tests are suggested to overcome the risk of inadequate response to scope.10 Further criticisms based on technical aspects concerning the questionnaire design are: 1.  Information bias. Information on the vehicle of payments (tax, entry fee, voluntary contributions, and so on), on the payment schedules (one-time, periodic or annual payment),11 on the current tax burden,12 and on other categories of goods, that can be in trade-off with cultural goods (for example, health care and education), influence the WTP responses. Providing the right level of unbiased information and avoiding the cognitive overload of the respondents are important to the correct design of the questionnaire. 2.  Positive valuation bias. The common assumption of CV studies is that the cultural goods or projects always have a positive value, and the WTP should be increasing along some quantity dimension. We do not usually consider the possible negative externalities of the goods or projects considered, owing to the trade-off that public budget constraints can impose (Epstein 2003; Heberlein et al. 2005).

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Contingent valuation  99 Even the most optimistic experts on CV studies advocate caution in the adoption of the outcomes obtained in CV studies and suggest that checking the quality (peer review) of the specific CV study is appropriate.

WHY IS CV USEFUL FOR CULTURAL ECONOMICS? The characteristics of CV make it particularly suited to estimate cultural goods (CGs). Cultural goods are typically non-market goods and present one or both the characteristics of public goods. Aesthetic, identity and authenticity values are non-use value components. The indirect use value, strictly connected to the exploitation of CGs as tourism attractors, has to be considered also, but must not be overestimated, to avoid two potential negative effects: namely, over-exploitation caused by tourism congestion phenomena (superstar destinations), and the irreversible depletion of CGs. On the basis of the welfare economics principles, the quantification in monetary terms of all the TEV components of CGs allows public intervention for their preservation. However, public budget constraints impose a ranking among the typical public intervention sectors (for example, health, education and culture) and, within each sector, among specific actions (for example, preservation of monuments versus promotion of contemporary arts). Usually, experts (that is, arts historians and architects) support policy-makers in the ranking of the public projects on CGs, evaluating their aesthetic and authenticity value. Contingent valuation studies can contribute to combine the opinion of experts with the preferences for the non-use values expressed by the respondents in the survey that can be based on other components of the non-use value, such as identity and symbolic value. Even if it is controversial whether the non-use or existence value has to be considered in public project appraisal, a large body of literature shows that the non-use values of cultural assets have to be estimated. The values obtained are usually significant and sometimes exceed use values by a considerable margin (Mourato and Pearce 1999). Therefore, CV surveys have the great advantage of allowing every individual – expert and non-expert – to express their different motivations for WTP using the same measure, that is, monetary terms. Moreover, scarcity of public resources for the preservation and valorisation of CGs can induce policy-makers to adopt different instruments to raise funds. For excludable CGs, a pricing mechanism can be introduced to obtain access. Free-entrance policies are based on general taxation that collects funds from everyone but gives benefits to only a very limited segment of the population that probably can afford to pay for cultural goods and services. Introducing a pricing mechanism, where it is technically possible, can be a more efficient and equitable funding scheme. If price discrimination is possible, public cultural goods suppliers can capture a larger part of consumers’ surplus and they can provide the incentive for cultural consumption to some low-income segments of the population (the young, senior citizens, students, teachers, and so on). Contingent valuation is a useful tool for policy-makers for assessing the likelihood of success of a pricing policy to manage cultural assets, to design the appropriate structure of private funds’ collection and to compute the total revenue potential.

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100  Handbook of cultural economics

THE APPLICATION OF CV IN CULTURAL ECONOMICS Admittedly, CV studies on CGs are still more academic exercises than instruments for supporting decision-making in the real world.13 Policy-makers are not used to resorting to individual preference evaluation methods in public project appraisals, and cultural experts probably think that their professional opinion does not need any other validation. Currently, CV studies concern a large variety of CGs and situations which make them difficult to classify and compare. We can distinguish CV studies by the type of CG observed and the type of the benefit estimated.14 In CV surveys on cultural heritage (CH), which represent the main object of CV studies on CG, the respondents’ WTP concerns different types of benefits: protection from air pollution, protection from abandonment/neglect, protection from urban development/ infrastructure, gaining access, maintaining present level, and so on. The objects of CV studies on CH are single items (for example, a cathedral) or multiple goods and services (such as a group of monuments or buildings, or different heritage sites to compare). Studies of multiple CGs should minimise the embedding effect; studies that compare more famous and less famous historic sites show that the WTP exists for both historic sites (Kuhfuss et al. 2016). Despite this classification, it is difficult to compare the findings obtained by different CV studies as rarely do they follow all the NOAA guidelines and they can differ in many aspects that influence the WTP estimation, for example, the different format of the elicitation question, the instrument of payment and the survey mode. Nevertheless, some interesting observations emerge from the meta-analysis by Noonan (2003) aimed at verifying the consistency of the findings with expectations, and trying to extrapolate the estimate values to other cultural resources (benefit transfers). This study, based on the data from 65 studies on more than 100 citations reviewed, provides the regression of average WTP values on survey characteristics and on the features of goods. It finds that door-to-door surveys, small sample size, surveys of archaeological sites and aggregated goods, together with the observance of NOOA guidelines, lead to higher WTP. Larger sample size and cost information are associated with lower WTP. A time trend is evident: WTP estimates appear to fall over time. Surprisingly, the payment vehicle does not seem to influence WTP estimates.15 A common characteristic of CV studies (on CG or not) is the large proportion of nonresponses and zero WTP bids.16 This can be partially interpreted as a form of protest or a lack of information among respondents in the survey. Some of the respondents, however, could be expressing their real preferences, and a crucial problem is whether or not to take them into account in the data processing. Another common aspect concerns the different WTP expressed by user and non-user respondents: the WTP expressed by users is typically higher. Therefore, the recreational and educational aspects of CG seem to be more appreciated than the non-use benefits. If policy-makers are evaluating whether or not to introduce entrance fees to cultural sites, they have to be aware that the average WTP could not correspond with the optimal price, and some form of price discrimination could be appropriate. Alternatively, voluntary contribution schemes can play a significant role in financing cultural initiatives, as the pioneering CV study on Durham Cathedral by Willis and Garrod (1998) and the CV survey on Napoli Musei Aperti by Santagata and Signorello (2000) demonstrate.

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Contingent valuation  101

BEYOND CV IN CULTURAL ECONOMICS The debate on the improvements of CV results’ validity and reliability has been focused on the design of CV study and on the choice of the econometric estimator. Significant advances have been made in the econometric analysis and in the analysis of the different SP methods applied to the valuation of CG.17 As far as the design of the CV studies is concerned, attention has been paid to survey development and implementation, value elicitation, data analysis, validity assessment and study reporting.18 A great deal of work has been done, borrowing from other social sciences, such as marketing research, behavioural economics and neuroscience. Currently, using pre-tests, focus groups or other forms of interview (the Delphi technique), which mainly involve experts with different backgrounds in defining the range of values to submit to the full sample, is routine practice. The increasing adoption of the NOAA procedure in CV studies on CGs should help to get results which could be also generalised and transferred to other similar CGs for which little or no data exist. As to the choice of the most appropriate SP method, choice experiments (CE) could be preferred to CV if in the survey it is assumed that both the price and the bundle of the attributes of the CG vary. One weakness of a CV survey is the radical choice it imposes (all or nothing); CE models (for example, conjoint analysis and contingent ranking), simulate the real process of formation of individual preferences, which usually compare different attributes of goods and levels of consumption, and give information about the value of each attribute. This is particularly relevant in CV studies which aim to investigate the WTP for different combinations of price and outcomes (for instance, more or less congested museums) or attributes of a cultural tourism destination (such as, accommodation facilities and local attractions; see Cuccia and Cellini 2007; Cuccia 2009). As the number of comparable CV studies on CG increases, other meta-analyses should be carried out that overcome the present limitations in data availability and provide reliable estimates for benefit transfers. Research is also devoted to improve the reliability of data, and the stability and reproducibility of results, with repeated surveys and tests over different periods of time.

CONTINGENT VALUATION SURVEYS AND CULTURAL POLICIES The results of SP and CV surveys can give useful insights to policy-makers concerning strategies of cultural policy. These results can have both a positive and a normative relevance. From the positive point of view, the CV method of estimating demand for public and partially public CGs can be a useful instrument to assess the TEV of CGs (use and non-use). Some aspects of the non-use values of CGs can easily be reduced to psychological foundations (the sense of identity and cultural memories) that have economic relevance. Contingent valuation surveys can also help to explain the motivations on which social preferences are based. Self-interested behaviour may not be the only determinant of individual preferences for the provision of public goods (Throsby and Withers 1986). Rational free-rider behaviour is frequently contradicted by empirical research. The role of social preferences and altruistic behaviours can be tested in CV studies on CGs. Once we

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102  Handbook of cultural economics know that CGs have an economic value for experts and non-experts, cultural policy must be planned to manage and preserve CGs. From the normative point of view, the empirical aspects and positive findings mentioned in this chapter may provide policy-makers with useful indications. On the basis of welfare economics, policy-makers should choose the economic allocation of public funds that maximises social welfare, resulting from the aggregation of individual preferences. Cultural policies are justified only if social welfare increases. In a context of increasingly scarce public economic resources, decision-makers may adopt a cost–benefit analysis (CBA) approach to assess the net social effect of alternative projects. Including the benefit that individuals attribute to CGs in the CBA strengthens actions concerning CGs when compared with other public policies. However, methodological advances have to be pursued for an efficient application of CV and SP studies in cultural policy programmes. Indeed, if an inadequate response to the problem of scope persists, smaller projects for preservation and valorisation of CGs could be preferred to larger projects as both have about the same benefit but very different costs (MacFadden and Train 2017). Moreover, if the CG under consideration is a global public good, the opinion of experts involved in different rounds of a Delphi CV survey could be an efficient solution (Carson et al. 2013). However, a distance still persists between methodological researches and their policy applications, as well as between researchers and policy-makers. Contingent valuation results are rarely used in public project appraisals and in the resolution of litigation. Two examples can be mentioned: the estimation of damages caused by oil spills, and the estimation of benefits coming from the renovation project of Fez-Medina in Morocco. The support that CV can provide in decision-making has not been sufficiently exploited yet. Probably, SP methods could be more requested by public and private managers for the design of tourism valorisation projects of CGs. Stated preference methods can also provide useful advice in the public management of CGs. Cultural policies are usually based on general taxation and have inequitable distribution effects: they benefit a very limited niche of consumers who, in most of the surveys conducted, show a WTP or willingness to donate higher than the access price or tax they pay. Therefore, where it is technically possible, pricing schemes should be designed to obtain the funds from the people who really benefit from the CG, and complementary services for a better fruition of CGs should be supplied to increase the revenues from CG valorisation policies. In this way, the regressive effect of cultural policies based on general taxation could be overcome. In spite of all the weaknesses of CV, this evaluation method and all SP methods represent the only instruments that allow policy-makers to abandon a paternalistic approach to cultural policies. If cultural policies are based on individual preferences, the final scope of policy-makers will be giving individuals the opportunities to gain adequate cultural knowledge and to express their own preferences for CGs.

NOTES  1. The demand is the Hicksian (or compensated) demand which depends on prices and utility; so, what is evaluated is the minimum expenditure that individuals are available to pay (WTP) or to accept (WTA) for a good or a loss, respectively, in front of constant utility.

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Contingent valuation  103  2. A search on Google Scholar (accessed 10 February 2019) for the exact phrase ‘contingent valuation’ in the title yielded about 4880 entries for the period 1990–2018, corresponding to about 168 entries per year on average.  3. For recent reviews of CV and stated preference methods studies to value cultural heritage, see Noonan (2003), Snowball (2008) and Willis (2014).  4. The special panel of economists appointed by the US National Oceanic and Atmospheric Administration in 1993 following the Exxon Valdez oil spill in Alaska in 1989 (Arrow et al. 1993).  5. The endowment effect is one of the milestones of the prospect theory developed and tested by Kahneman et al. (1990).  6. Hedonic pricing and travel cost method (TC) are revealed preference methods that enable us to infer indirectly the WTP for cultural goods from consumers’ behaviour in related markets; respectively, the housing market in the hedonic pricing method and the demand for outdoor recreational goods in the TC method. For a comparison of the CV and TC estimates in the valuation of cultural experience see Armbrecht (2014).  7. A referendum is a direct revealed preference method that has been proposed as a good alternative to CV (Frey 1997). The two instruments have different aims, however. Referenda enable the obstacles inside the economic policy process to be overcome. Contingent valuation studies can be used in different cases: litigation, introduction of new cultural services, and planning a more efficient cultural policy design based on information about the consumer’ surplus of different classes of respondents.  8. For instance, the TEV for cultural heritage includes the actual use, the vicarious use (through pictures and/ or films) and the indirect benefits deriving from the use revealed or not revealed by the market mechanism (for example, higher hotel and restaurant fares in the area around the cultural asset). Connected to the use value, there is the option value, which is the value that individuals attribute to the possibility of using the cultural asset in the future for their own utility and/or the utility of future generations. The non-use or existence value has many components (aesthetic, historical and symbolic) that are linked by the fact they do not concern the use of the cultural asset at all.  9. This criticism has been underlined by Kahneman and Knetsch (1992) and by Hausmann (1993). 10. The NOAA guidelines (Arrow et al. 1993) suggested that CV studies should pass scope tests. Whitehead (2016) reopened a still-alive debate on the scope effect and the scope tests in CV studies. 11. Myers et al. (2017) show that the present value of the WTP in CV studies is larger if the payment schedule consists in an annual payment instead of in a one-time payment. 12. Information about current tax burdens can bias respondents’ answers toward that amount (Throsby and Withers 1986). 13. The Journal of Cultural Heritage and the Journal of Cultural Economics published many CV studies on CH. See, for example, Baez and Herrero (2012) and Bedate et al. (2009). See also the 2003 monographic issue of the Journal of Cultural Economics (vol. 27, issue 3–4). 14. For a more detailed classification of CV studies on CG see Noonan (2003) and Snowball (2008). 15. Noonan (2003) himself invites us to consider the results of his analysis with caution, taking into account the sign and the significance of coefficients instead of their quantitative dimension. 16. For further details see Snowball (2008, pp. 155–7). 17. See Willis (2014) for a methodological review of the stated preference methods to value CH. 18. These are the five categories of recommendations reported in the new NOAA guidelines (Johnston et al. 2017).

SEE ALSO: Chapter 23: Cultural value; Chapter 27: Economic impact of the arts; Chapter 31: Heritage; Chapter 50: Public support; Chapter 58: Welfare economics.

REFERENCES Armbrecht, J. (2014), ‘Use value of cultural experience: a comparison of contingent valuation and travel cost’, Tourism Management, 42 (C), 141–8. Arrow, K., R. Solow, P.R. Portney, E.E. Leamer, R. Radner and H. Schuman (1993), ‘Report of the NOAA Panel on Contingent Valuation’, National Oceanic and Atmospheric Administration, US Department of Commerce, Washington, DC.

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104  Handbook of cultural economics Baez, A. and L.C. Herrero (2012), ‘Using contingent valuation and cost-benefit analysis to design a policy for restoring cultural heritage’, Journal of Cultural Heritage, 13 (3), 235–45. Bedate, A., L. Herrero and J. Sanz (2009), ‘Economic valuation of a contemporary art museum: correction of hypothetical bias using a certainty question’, Journal of Cultural Economics, 33 (3), 185–99. Bishop, R.C. (2018), ‘Warm glow, good feelings, and contingent valuation’, Journal of Agricultural and Resource Economics, 43 (3), 307–20. Carson, R. (2011), Contingent Valuation: A Comprehensive Bibliography and History, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Carson, R., M. Conaway and S. Navrud (2013), ‘Preliminary valuation of a cultural heritage site of global significance: a Delphi contingent valuation study’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 586–611. Carson, R., N. Flores and N. Meade (2001), ‘Contingent valuation: controversies and evidence’, Environmental and Resource Economics, 19 (2), 173–210. Cuccia, T. (2009), ‘A contingent ranking study on the preferences of tourists across seasons’, Estudios de Economia Aplicada, 27 (1), 161–76. Cuccia, T. and R. Cellini (2007), ‘Is cultural heritage really important for tourists? A contingent rating study’, Applied Economics, 39 (2), 261–71. Diamond, P.A. and J.A. Hausman (1994), ‘Contingent valuation: is some number better than no number?’, Journal of Economic Perspectives, 8 (4), 45–64. Epstein, R.A. (2003), ‘The regrettable necessity of contingent valuation’, Journal of Cultural Economics, 27 (3–4), 259–74. Frey, B.S. (1997), ‘Evaluating cultural property: the economic approach’, International Journal of Cultural Property, 6 (2), 231–46. Hanemann, M.W. (1994), ‘Valuing the environment through contingent valuation’, Journal of Economic Perspectives, 8 (1), 19–43. Hanemann, M.W., J. Loomis and B. Kanninen (1991), ‘Statistical efficiency of double-bounded dichotomous choice contingent valuation’, American Journal of Agricultural Economics, 73 (4), 1255–63. Hausmann, J.A. (1993), Contingent Valuation: A Critical Appraisal, Amsterdam: North-Holland. Heberlein, T., M. Wilson, R. Bishop and N. Schaeffer (2005), ‘Rethinking the scope test as a criterion for validity in contingent valuation’, Journal of Environmental Economics and Management, 50 (1), 1–22. Johnston, R.J., K.J. Boyle, W. Adamowicz, J. Bennett, R. Brouwer, T.A. Cameron, et al. (2017), ‘Contemporary guidance for stated preference studies’, Journal of the Association of Environmental and Resource Economics, 4 (2), 319–405. Kahnemann, D. and J. Knetsch (1992), ‘Valuing public goods: purchase of moral satisfaction’, Journal of Environmental Economics and Management, 22 (1), 57–70. Kahnemann, D., J. Knetsch and R. Thaler (1990), ‘Experimental tests of the endowment effect and the Coase theorem’, Journal of Political Economy, 98 (6), 1325–48. Kerry Smith, V. (2006), ‘Fifty years of contingent valuation’, in A. Alberini and J.R. Kahn (eds), Handbook on Contingent Valuation, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 7–65. Kuhfuss, L., N. Hanley and R. White (2016), ‘Should historic sites protection be targeted at the most famous? Evidence from a contingent valuation in Scotland’, Journal of Cultural Heritage, 20 (July–August), 682–5. Lancaster, K. (1966), ‘A new approach to consumer theory’, Journal of Political Economy, 74 (2), 132–57. Lindhjem, H. and S. Navrud (2011), ‘Are Internet surveys an alternative to face-to-face interviews in contingent valuation?’, Ecological Economics, 70 (9), 1628–37. MacFadden, D. and K. Train (2017), Contingent Valuation of Environmental Goods: A Comprehensive Critique, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Mitchell, R.C. and R.T. Carson (1989), Using Surveys to Value Public Goods: The Contingent Valuation Method, Washington, DC and Baltimore MD: Johns Hopkins University Press for Resources for the Future. Mourato, S. and D. Pearce (1999), Dealing with Low Willingness to Pay for Cultural Heritage: Statistical and Policy Implications, London: CSERGE. Myers, K., G. Parsons and K. Train (2017), ‘Inadequate response to frequency of payments in contingent valuation of environmental goods’, in D. MacFadden and K. Train (eds), Contingent Valuation of Environmental Goods: A Comprehensive Critique, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 43–57. Navrud, S. and R.C. Ready (eds) (2002) Valuing Cultural Heritage: Applying Environmental Valuation Techniques to Historic Buildings, Monuments and Artefacts, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Noonan, D.S. (2003), ‘Contingent valuation and cultural resources: a meta-analytic review of the literature’, Journal of Cultural Economics, 27 (3–4), 159–76. Rizzo, I. and A. Mignosa (2013), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar.

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Contingent valuation  105 Santagata, W. and G. Signorello (2000), ‘Contingent valuation and cultural policy: the case of “Napoli Musei Aperti”’, Journal of Cultural Economics, 24 (3), 181–204. Snowball, J.D. (2008), Measuring the Value of Culture, Berlin Heidelberg: Springer-Verlag. Throsby, D. (2001), Economics and Culture, Cambridge: Cambridge University Press. Throsby, D. and G. Withers (1983), ‘Measuring the demand for the arts as a public good: theory and empirical results’, in W.S. Hendon and J.L. Shanahan (eds), Economics of Cultural Decision, Cambridge, MA: Abt Books, pp. 177–91. Throsby, D. and G. Withers (1986), ‘Strategic bias and demand for public goods: theory and application to the arts’, Journal of Public Economics, 31 (3), 307–27. Vossler, C.A. and J.S. Holladay (2018), ‘Alternative value elicitation formats in contingent valuation: mechanism design and convergent validity’, Journal of Public Economics, 165 (C), 133–45. Whitehead, J.C. (2006), ‘A practitioner’s primer on the contingent valuation method’, in A. Alberini and J.R. Kahn (eds), Handbook on Contingent Valuation, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 66–91. Whitehead, J.C. (2016), ‘Plausible responsiveness to scope in contingent valuation’, Ecological Economics, 128 (C), 17–22. Willis, K.G. (2014), ‘The use of stated preference methods to value cultural heritage’, in V.A. Ginsburgh and D.  Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsterdam: North-Holland, pp. 145–81. Willis, K.G. and G.D. Garrod (1998), ‘Estimating the demand for cultural heritage: artefacts of historical and architectural interest’, in K.G. Willis (ed.), Heritage, the Arts and the Environment: Pricing the Priceless (Hume Papers on Public Policy), Edinburgh: David Hume Institute and Edinburgh University Press, pp. 1–16.

FURTHER READING To deepen the study on the economic value of culture see Throsby (2001), Snowball (2008) and Rizzo and Mignosa (2013). For a review of CV studies on cultural heritage see Navrud and Ready (2002). A methodological review of the different techniques used in CV and in the stated preference methods applied to value cultural heritage is provided by Willis (2014). A more general analysis on the history and the state of the art in CV is provided by Carson (2011) and a symposium on CV has been published in 2012 in the Journal of Economic Perspectives (vol. 26 no.4, pp. 3–56).

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11.  Contract theory and information goods Richard Watt

The creative sector of an economy encompasses those economic activities for whom their principal business is found somewhere along the value chain of generation and exploitation of creative goods. By creative goods, we generally understand any consumable item that is based upon knowledge or information (art, music, stories, software, new designs for consumer goods, ideas that solve pressing industrial problems, and so on). It will be useful for all that follows if, instead of the term ‘creative goods’, we refer to the outputs of creative processes as ‘information goods’. Many of these goods comprise a large part of an economy’s cultural sector. Information goods are typically characterised by large initial costs of creation, and low (perhaps close to zero) costs of reproduction. For example, we can think of the massive costs of producing an initial recording of a new musical work (effort and time costs of the authors in writing the music and the lyrics, effort and time costs of the musicians in learning and performing the work for the recording, and the studio costs of making the recording and fixing it to an MP3 file) compared with the costs of reproducing exact copies of the resulting MP3 (a few seconds of computer time). In this example, the information is the musical work itself, and the information good is the MP3 file. What is of value in an information good is the information that it contains, and information is inherently intangible. The information good itself is merely a tangible means of storing the information – a book that contains a novel, an MP3 file that contains a musical work.

CREATIVE ACTIVITIES AND INFORMATION GOODS By definition, the creative industries rely upon two fundamental aspects, namely (1) creative individuals spending their time in creating valuable information goods, and (2) a mechanism under which the information goods thus produced can be transferred to those who most value them. Assuming that aspect (1) will occur as long as the activity of creating information goods carries with it sufficient promise of eventual financial recompense (a stream of financial payments that provides a level of personal utility that is greater than what can be found in the next-best alternative option, where both the benefits and the costs of each activity are taken into account), then it is useful to look at the whole system through the lens of backward induction – we should first find a mechanism that can support a market that provides sufficient expected return to creators. Then we can be assured that aspect (1) will be fulfilled. That is where contracts come into the picture.

MARKETS AND CONTRACTS As long as we can ensure sufficient expected financial recompense to creative individuals, we should expect that they will be willing to spend their time in creative activities, and 106

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Contract theory and information goods  107 this will lead to the existence of a supply of valuable information goods.1 The problem, then, is to consider exactly how sufficient financial recompense can be guaranteed, and how it should be structured over time. The answer that modern economies have come up with is a two-pronged system; on the one hand, intellectual property protection for the information contained in information goods and, on the other, contracts. We look at both of these in turn.

INTELLECTUAL PROPERTY PROTECTION Intellectual property (IP) refers to a set of laws that determine who holds the economic rights in given information goods. The laws set out which acts can be freely carried out by any user of an information good, and which other acts can only be carried out with the permission of the rights holder. The two principal IP regimes are patent (which protects valuable ideas) and copyright (which protects valuable expressions), although many other regimes also exist (covering, for example, trade secrecy and plant variety protection). As far as the cultural sector is concerned, copyright is more relevant than is patent, simply because most cultural goods are expressions of authorship (art, designs, writings, music, film, and so on) rather than ideas that solve industrial problems. Given that, in this chapter we restrict our attention and discussion to copyright protection of information goods. It is pertinent to ask, why should the law provide copyright protection at all? All too often it is argued that the reason is that copyright provides the incentive for creative authorship to take place. That is not strictly correct. The copyright system does not provide incentives, at least not directly. The copyright system provides ownership, or more precisely, it clarifies the definition of the information good in question, and it clarifies the individual who can legally charge a payment from users of that information good. However, once ownership is clear, then contracts can be written, and it is the contracts that provide the incentives for creative authorship activities, because it is the contracts that allow for payments to flow from users to creators. Therefore, copyright is required only in as far as it allows contracts to exist. Imagine, for instance, what the market for information goods would look like in absence of copyright. As Kenneth Arrow (1962) noted, information goods suffer from what has become known as the disclosure paradox. We can illustrate this by thinking about the very first attempt at a transaction in the value chain of an information good, when the author attempts to secure payment from the first user in a hypothetical world without copyright. In order to command an acceptable price, the user (potential purchaser) needs to know exactly the value of the information that is being offered to him or her. Therefore, the author needs to divulge the information to the potential user so that it can be examined and its true value ascertained. However, once the information is thereby disclosed, all that is of value has immediately been gained by the user, and so the incentive to pay is greatly reduced. Once it is disclosed, the information good can be appropriated without payment. In Arrow’s own words ‘there is a fundamental paradox in the determination of demand for information; its value for the purchaser is not known until he knows the information, but then he has in effect acquired it without cost’ (Arrow 1962, p. 615). The disclosure paradox is a simplification. Say the information is a musical work, and say the way the author discloses the work to a potential publisher (perhaps a record label)

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108  Handbook of cultural economics is to offer a one-off live performance. Unless the publisher somehow records the work as it is performed, it would be difficult for the entire work to be instantly memorised so that it can be appropriated without payment (although, apparently Mozart was able to do this, see https://www.classicfm.com/composers/mozart/guides/mozart-allegri-miserere/, accessed 14 December 2019). However, in practice, new works are not performed live to potential publishers; instead the publishers insist that they receive a recording (for example, an MP3 file, or perhaps a YouTube clip), which the publisher could clearly appropriate. The disclosure paradox is a severe form of the information asymmetry that is known as adverse selection, or the ‘lemons’ principle (for the seminal paper, see Ackerlof 1970). The seller of the information good knows its true value, but the potential user (the buyer) does not. The only way that the seller can convince the user of the true value of the information is to disclose it to the user, but then, with the demonstration, the user in effect receives the information, and would no longer be willing to pay for it. Knowing that by showing the good to the user the seller will lose any potential financial recompense, he or she would logically decide not to show the information good, and the user, afraid of being cheated into overpaying for information of low value, will only be willing to pay a minimal price. Under those conditions, many useful information goods cannot be traded, and this will imply that they would not be created in the first place. There are two ways around this adverse selection problem: joint venture contracts and copyright protection. The first option is only available if the user of the information good is not the final consumer, but is an intermediary in the value chain. The user and the seller can enter into a joint enterprise in which the seller provides the information good as an input into the business, and they then sign a contract to share in the proceeds of the business together. Appropriation (which would be the intermediary withholding the agreed share of profits from the author of the work) would then involve a breach of contract, and the author of the work would presumably have access to whatever remedies are stipulated in the contract. However, there are several problems with this solution to the disclosure paradox. First, as there would be a contract only between the two parties (the author and the user), it is difficult for the author to restrict the user from entering into other contracts with third parties for exploitation of the same information good; these contracts are likely to reduce the value of the original joint venture contract, and at the same time they limit the ability of the original author to exploit the work with other users. Second, joint venture contracts would rapidly become an untenable system if the information good only provides a small part of the user’s proposed business. For example, if the information good is a single song, and the user is a radio station which requires access to many songs to be profitable, then this model would require many individual contracts. The transaction costs of such a system would be particularly unwieldy.2 Alternatively, if the user is a final consumer (for example, an individual buying a book in a bookshop, or an MP3 file from the iTunes store), then there is no further payment stream beyond the initial payment to gain access to the work (assuming that the consumer does not go ahead and use the work as the basis for income, as might be the case of uploading an MP3 file to an Internet streaming service such as YouTube, in which case the consumer is not really the final consumer but an intermediary user), and so there is no joint enterprise that the seller can enter into with the user. The transaction between the two generates utility for the user, not a stream of financial profits. In those cases, the option of jointly sharing profits is not available.

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Contract theory and information goods  109 A more efficient way around the adverse selection problem is to put in place a legal barrier to use of the information good without the seller’s expressed consent; and that is what copyright is in place to do. When both the full description of the information good, and the identity of the seller, are perfectly defined, then we have properly defined ownership, and thus we can restrict use in the same way that owners of tangible goods such as cars and houses can restrict access to those assets by unconsented users. Copyright then is an artificial means under which an intangible information good becomes tangible, and therefore able to be the subject matter of a contract between the seller (the owner) and the user. That is, a legal concept of ownership is a necessary ingredient for meaningful contracts to exist. It is important to notice that, although copyright may go a long way towards eliminating unconsented use, it is not a mechanism that is primarily designed to have negative effects on usage. Quite the opposite; copyright exists so that the underlying information good can be easily accessed by others, not so that all access is denied. The idea is that copyright denies unconsented access, but promotes consensual access. All of that, of course, does rely on the ownership, as defined by the copyright in question, being adequately protected by law. Also, assuming that enforcement is in place, if a potential user appropriates the good, then the copyright holder has recourse to the legal system for a remedy from the infringing user. The threat of that happening may be sufficient for appropriation not to occur. Therefore, an appropriately enforced copyright regime is what market contracts for cultural works of authorship rest upon. Copyright allows contracts to exist, and the contracts provide the incentives for the original creative effort to occur.

CONTRACTS FOR COPYRIGHT PROTECTED INFORMATION GOODS Any transaction involving an information good can be thought of as the realisation of a contract. In the simplest case, it is a payment in cash in exchange for access to the good (perhaps for outright ownership of the information good itself, that is, the identity of the copyright holder can change). However, there are many more complex arrangements, involving contingent payments, time-dependent clauses and any number of other features. That is, the contracts involved can be rather complex. Mostly, the complexities involved are efficient responses to the types of difficulties that may arise when a copyright holder and a user get together to work out how access to the work can best be organised. This is how parties to the contracts provide the incentives to each other so that they can all rest assured that the outcome is the best possible for all concerned.

PARTICULAR FEATURES OF CONTRACTS FOR INFORMATION GOODS When it comes to contracts for information goods, there are certain similarities with any other contract, but also some features that are unique to these types of goods. Here we only discuss these features in a general manner, and the interested reader is directed to Caves (2000) for details regarding contracts for copyright protected goods.

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ACCESS RATHER THAN PURCHASE The first aspect that distinguishes information goods from most others relates to the public-good nature of information. A single item of information can be consumed by many people simultaneously, such that the consumption by any one person does not diminish the consumption by another. Information goods can be used without ever being used up. This feature implies that normally users are not interested in owning the information good itself (that is, in becoming the new copyright holder), but only require the ability to access the information. Radio stations, for example, do not own the copyright to the songs they play, they only need permission to broadcast them. Similarly, publishers of books do not require ownership of the copyright in a novel, only the permission to reproduce copies of the book for sale. For that reason, contracts for access to copyrightprotected information goods are normally structured as licensing contracts that grant a user permission to a given set of modes of access for a given duration of time, instead of outright sale of the copyright itself. The modes of access will normally stipulate what can and cannot be done with the information good in question; for example, a licensing contract for a musical work might allow it to be publicly broadcast, or copied to physical supports for sale, or performed live at a concert, but might not allow the licensee to alter the work in some way, or to contract with third parties to access it in any way.

TIME AND RISK Contracts for the exploitation of copyright protected information goods do share a feature of many other contracts; there is often a time dimension involved between when the contract is entered into and when payments are made, and that directly implies that there is almost surely an element of risk involved. Economists have a long history of analysing how contracts not only provide remuneration, but also share risk, and licensing contracts for information goods are no exception. To understand this issue, think about how a typical licensing contract between a copyright holder in an information good and a user of that information might look. The copyright holder makes the information good available for the user to access in carefully outlined ways, and for a specific duration of time. At the time the contract is signed, the user only gets access, and it will typically take some time before actual exploitation happens, and revenue is earned – that is, we can think of the information good being an input into the user’s business. Also, since the revenue from the user’s business is almost surely uncertain, or risky, at the moment of signing of the licensing contract, the parties need to contemplate both the remuneration of the copyright holder and the way in which the risk is shared between them. For example, if the contract stipulates a single up-front payment from the user to the copyright holder at the moment of signing, then that amount of money is a risk-free compensation to the copyright holder. In this scenario, the user suffers all of the eventual risk, and the copyright holder does not suffer any risk at all. We would say that the user has fully insured the copyright holder. An example of this type of contract is when an author sells copies of the information good he or she has created directly to consumers, at a set per-unit price, under the stated condition that the consumer may not reproduce the good in any way for the benefit of others. This type

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Contract theory and information goods  111 of full-insurance situation is also prevalent for paying backing musicians in a recording, who normally work for buy-out payments and so they have no further claim on any future revenue. Another way in which the user can fully insure the copyright holder is by a licensing contract that stipulates a given absolute payment from the user to the copyright holder at specific dates during which the contract is in force. As long as the payments are unconditional (that is, the amount of each payment does not depend on anything that might or might not happen), then again the copyright holder holds no risk. The only difference is that the copyright holder in this case needs to work out the present value of the payments that the contract guarantees will happen, in order to know what the contract is actually worth, that is, to know the compensation that the contract offers. In any other scenario, the payments made from the user to the copyright holder are conditional upon outcomes that occur within the duration of the contract – most relevantly, perhaps, the levels of sales of the product that the user sells to consumers. This might apply, for example, to the royalty payments that a book publisher passes on to the author of the work contained in the book. When there is a risk in the income stream that the copyright holder realises from the licensing contract, then the concepts of remuneration and risk-sharing become blurred. The best measure of compensation is the mathematical expectation of the present value of the payments under the contract. At each payment moment, we would calculate the sum of the each feasible amount of payment multiplied by the probabilities of each payment to get the expected payment at that period of time. Then we would still have to multiply each of these expected payments by the discount factor for that period of time (with a smaller discount factor the further into the future is the expected payment) to arrive at the present value of the expected payments. Notice that when there is no risk (that is, each contracted payment is a guaranteed amount), then at each payment period there is only one feasible payment amount, and so the probability of that payment amount is equal to 1. Statistically, the expected payment is the first moment of the payment distribution, or the mean payment. Just as the compensation that the contract offers the copyright holder can be measured by the expected value of the payments, risk can be measured by the variance (or the standard deviation) of the contracted payment stream (that is, the second statistical moment of the payment distribution, or dispersion around the mean). When there is risk, and assuming that the copyright holder is risk averse, then he or she would be willing to reduce the expected compensation in exchange for a more favourable income stream from the perspective of the risk that it entails; that is, a risk-averse copyright holder is willing to pay for insurance with a lower expected compensation. So, there is now a trade-off possible; expected value can be sacrificed for less risk, and the contract is the mechanism under which the two parties (the copyright holder and the user) can work out how to efficiently share the expected profits of the business and the risks involved. When considering whether a risky payment stream is worthwhile or not, the copyright holder should evaluate the expected present value of the utility that the contracted payments provides, and that would be compared to the expected present value of the utility of the next best option. When risk is unavoidably present, and both of the participants in the contract are risk averse, an efficient contract will share the risk between the parties. Each will participate in some way in the risk; that is, neither of the two will fully insure the other. We should only

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112  Handbook of cultural economics see riskless payments when either there is no risk in the contract, or when one of the two parties is risk averse and the other is risk neutral, neither of which are particularly relevant assumptions for real-world contracts. The way a licensing contract achieves risk-sharing is by using a royalty element, under which the payments to the copyright holder are made conditional upon the outcome of the risky variable involved. The licensing payments in the contract become contingent payments, that is, payments whose value is determined by the outcome of a random variable at a given moment of time. Thus, contracts in a risky environment have a double purpose – they provide recompense for actions carried out and they provide insurance against risk – and both purposes affect the utilities of the two parties involved. Perhaps a concrete example of how this works is of use. Consider a recording artist and a recording label who are negotiating the possibility of fixing a musical work, written and performed by the artist, onto a tangible support (a CD Rom, or perhaps an MP3 file) that the label can then sell to music consumers (perhaps via another intermediary, such as a radio station or an Internet streaming service). The revenue that the business will end up providing to the label is risky at the moment at which the licensing contract needs to be signed, and assuming that both the artist and the label are risk averse, the risk will require that the contract contains royalty payments that are conditional upon the outcome of the eventual sales of the work. If we further assume that the label is less risk averse than the artist, then we might expect that under an efficient contract the label should provide partial (but not full) insurance to the artist. This is often done by the label paying an up-front advance on royalties to the artist at the moment of signing of the contract. Under this sort of deal, the artist’s total income cannot fall below the amount of the up-front advance no matter how poorly the work ends up performing in the market, which is a situation that exactly mimics the well-known deductible format of insurance contracts. It is equally well-known that for a risk-averse individual, the optimal insurance mechanism is full coverage above a deductible (for the seminal work on this result, see Arrow 1963, 1971, 1974), so the up-front royalty advance provides the artist with a theoretically optimal risk profile. Another way in which we see contracts for copyright-protected information goods providing risk-sharing benefits is when many individual copyright holders join together to offer an entire repertoire of their works as a single object. This is the case, for example, of copyright collectives, such as the American Society of Composers, Authors, and Publishers (ASCAP) in the USA, which offer repertoires of a huge number of individual songs to users such as radio stations. The general theory of collective administration of copyrights is historically based on the transaction cost savings that this provides (see, for example, Hollander 1984; Handke 2014), but there is also a clear element of risk management in collective administration, owing to the aggregation of risky prospects (see Watt 2015).

ASYMMETRIC INFORMATION: MORAL HAZARD We have looked at how copyright royalty contracts exist as an efficient response to risk in the contracting environment. In many cases we will have risk and an element of asymmetric information at the same time, and in particular the information asymmetry can be

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Contract theory and information goods  113 closely related to the risk. This is so when there is a problem of moral hazard, which is a situation in which one of the parties to the contract can take actions that are unobserved by the other party, but that affect the value of the contract to both. The existence of moral hazard will again tend to lead to a contract with contingent royalty payments of some sort, but where now the royalty payments are calculated more with incentives, rather than strict risk-sharing, in mind. The incentives are for a party able to carry out beneficial actions to actually carry them out, or incentives for a party able to carry out actions with a negative effect not to carry them out. As an example of this, consider again a label and an artist who enter into a contract to record a song so that the label may market the song to the consuming public. Both the artist and the label can carry out actions after the contract is signed that might affect the level of sales. They can spend their time (and money) promoting the recording, for example, in concerts and album signing sessions (the artist) or by offering record stores an attractive price to stock the album (the label). The label might also work closely with other media, such as MTV or Rolling Stone magazine, to promote the new group’s music. Exactly how each of the two parties to the contract go about these types of activities is hard for the other to monitor, and therefore a situation of moral hazard arises. A very good outline of the types of contractual responses to moral hazard can be found in Macho Stadler and Perez Castrillo (2014) but, in general, moral hazard activities will affect the probabilities of the different risky outcomes, and so the payments under the contract should be weighted so that a party with the opportunity to improve the stochastic profile of the payments should receive an increased payoff when good outcomes eventuate. This is to provide the correct incentive to undertake the beneficial action, rather than a response to efficient risk-sharing.

CONCLUSIONS Copyright is the legal mechanism that determines ownership of certain information goods, and ownership is a necessary ingredient for meaningful transactions related to the information good to occur. Only when the parties to a contract for the exploitation of an information good are confident about what the good is and who owns it, can they write a contract that will provide benefits to both. That is, copyright establishes property rights, and contracts stipulate how the property rights are used. The benefits that the contract gives to the original creator, or author, of the work in question is the source of the incentives for that author to create the work in the first place. Without copyright, Arrow’s disclosure paradox implies that far fewer (perhaps no) information goods will be produced, since without copyright it is difficult to see how any contracts for exploitation of information goods could be written. A distinguishing feature of contracts in the space of information goods is that they are almost always characterised by some form of restricted access rather than full unconditional exchange, owing to the public-good aspect of information. We have also seen in this chapter that contracts for copyright-protected information goods have many of the same features as contracts for any other good or service. When there is risk present (perhaps owing to the time dimension of the contract), the contracted payments share the risk between the parties. For copyright-protected goods, that feature can readily be found

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114  Handbook of cultural economics in the royalty payments of a licensing agreement. Royalty payments that are conditional upon the outcomes of certain stochastic variables can also be seen to be incentive mechanisms that are in place to deal with the problem of moral hazard.

NOTES 1. It is a much more difficult problem to guarantee that the mechanism of compensation is that which would guarantee that it is the most appropriate creative individuals who end up choosing to produce information goods, in that the final economic value of the set of information goods that ends up existing is the greatest possible for the users of these goods. We do not attempt to address this higher-order problem here. 2. This example leads directly to a system of joint exploitation of many complementary information goods – collective administration. We say more about this later in the chapter, but for now it is sufficient to notice that even under collective administration of a large set of individual works, when there is no copyright there are many contracts required – one between the collective and the user, but many between the collective members themselves.

SEE ALSO: Chapter 12: Copyright; Chapter 32: Information goods; Chapter 41: Music publishing; Chapter 47: Platforms.

REFERENCES Ackerlof, G. (1970), ‘The market for “lemons”: quality uncertainty and the market mechanism’, Quarterly Journal of Economics, 84 (3), 488–500. Arrow, K. (1962), ‘Economic welfare and the allocation of resources for invention’, in R.R. Nelson (ed.), The Rate and Direction of Inventive Activity, Washington, DC: National Bureau of Economic Research, pp. 609–25. Arrow, K. (1963), ‘Uncertainty and the welfare of medical care’, American Economic Review, 53 (5), 941–73. Arrow, K. (1971), Essays in the Theory of Risk Bearing, Chicago, IL: Markham. Arrow, K. (1974), ‘Optimal insurance and generalized deductibles’, Scandinavian Actuarial Journal, (1), 1–42. Caves, R. (2000), Creative Industries: Contracts Between Art and Commerce, Cambridge, MA: Harvard University Press. Easterbrook, F.H. (2005), ‘Contract and copyright’, Houston Law Review, 42, 953–73. Handke, C. (2014), ‘Collective administration’, in R. Watt (ed.), Handbook on the Economics of Copyright: A Guide for Students and Teachers, Cheltenham, UK and Northampton, MA USA: Edward Elgar, pp. 179–204. Hollander, A. (1984), ‘Market structure and performance in intellectual property: the case of copyright collectives’, International Journal of Industrial Organization, 2, 199–216. Kretschmer, M. (2010), ‘Regulating creator contracts: the state of the art and a research agenda’, Journal of Intellectual Property Law, 18 (1), 141–72. Lindsay, D. (2002), The Law and Economics of Copyright, Contract and Mass Market Licences, Strawberry Hills, NSW: Centre for Copyright Studies, accessed at https://static-copyright-com-au.s3.amazonaws.com/ uploads/2015/08/CentreCopyrightStudies_AllenGroup-TheLawandEconomicsofCopyright.pdf. Macho Stadler, I. and D. Perez Castrillo (2014), ‘Copyright licensing under asymmetric information’, Review of Economic Research on Copyright Issues, 11 (2), 1–26. Nimmer, R. (1998), ‘Breaking barriers: the relation between contract and intellectual property law’, Berkeley Technology Law Journal, 13 (3), 827–89. Rub, G. (2017), ‘Copyright survives: rethinking the copyright-contract conflict’, Virginia Law Review, 103 (6), 1141–245. Watt, R. (2010), ‘Copyright and contract law: economic theory of copyright contracts’, Journal of Intellectual Property Law, 18 (1), 173–206. Watt, R. (2015), ‘The efficiencies of aggregation: an economic theory perspective on collective management of copyright’, Review of Economic Research on Copyright Issues, 12 (1–2), 26–45.

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Contract theory and information goods  115

FURTHER READING The legal literature has a history of studying the relationship between copyright and contracts, but with an emphasis on the idea of whether or not parties should be allowed to contract around the limitations that copyright law imposes upon freedom of contract (see, for example, Nimmer 1998; Easterbrook 2005; Rub 2017). On the same general topic, chapter 6 in Lindsay (2002) provides a great general outline of this topic from a more economics oriented perspective. In 2006, volume 3 issue 1 of the Review of Economic Research on Copyright Issues (RERCI) published a symposium of papers by economists on a variety of topics at the intersection of copyright and contracts. Mostly, economists have studied contracts related to copyright protected goods under the general subject of copyright licensing, and the mentioned issue of RERCI captures much of the state of the art on that topic. Finally, in 2010 the Journal of Intellectual Property Law published a small symposium on copyright and contracts (see Kretschmer 2010; Watt 2010), which highlights many of the issues that are relevant.

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12.  Copyright

William M. Landes

This chapter sets out the economic rationale for copyright protection and describes the basic structure of copyright law.1 It shows that copyright law has an implicit economic logic. Its doctrines can be best explained as efforts to create rights in intangible property in order to promote economic efficiency.

THE BENEFITS OF COPYRIGHT PROTECTION Copyright protects original works of authorship that are fixed in a tangible form. A copyright covers not just unauthorized copying but also rights over the distribution of copies, derivative works and public performances and displays. However, property rights in copyrightable goods are subject to significant limitations. Original does not mean novel or creative, but simply that the work originates with the author; that is, the author did not copy it from another person. Originality is a threshold question. Its purpose is to save administrative and enforcement costs by screening out low-value works that probably would be created even without copyright protection. Fixation also saves enforcement costs because it would be more burdensome for a court to decide, for example, if an alleged infringer had copied the plaintiff’s live jazz performance than if it had been taped or recorded (and, therefore, fixed) (see Lichtman 2001). Original works include, among others, books, photographs, paintings, sculpture, musical compositions, technical drawings, computer software, situation comedies, movies, maps and business directories. These works all have in common what economists term a public goods aspect to them. Creating these works involves a good deal of money, time and effort (sometimes known as the cost of expression). Once created, however, the cost of reproducing the work is so low that additional users can be added at a negligible or even zero cost. To illustrate, suppose the marginal cost of manufacturing and distributing a copy of a novel is $1, there are no fixed production costs (for example, typesetting and editing costs are nil) and the author incurs a $1000 cost (mainly, his or her time) in writing the book. Once the $1000 cost of expression has been incurred, it can be incorporated into additional copies of the book at zero cost. That is, once expression is created it is not diminished by one or 1 million uses. In the absence of copyright protection, competition among publishers would drive down the price of a book to $1. Publishers would just cover their full costs, with nothing left over to compensate the author for his or her efforts. As a result, the incentive for authors to write books will diminish, as will the supply of new books. Copyright protection enables the publisher to charge a price above $1 without worrying about competition from unauthorized copies. A price of, say, $2 would more than cover the costs of publishing and provide compensation to the author, encouraging him or her to write new books.2 116

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Copyright  117 Some original works will still be created even in the absence of copyright protection. There may be substantial benefits from being recognized as the creator or from being first in the market, or the copies may be of inferior quality. Creators may also use contract law or other private enforcement means to discourage unauthorized copying. For example, a software manufacturer could license the software subject to a contract term that prohibits the licensee from making unauthorized copies or derivative works. However, a contract, unlike a copyright, would be difficult to enforce against third parties or subsequent purchasers of the original work. There is also the possibility that the creator will be able to capture some of the value of copies made by others by charging a higher price for the copies he or she makes. For example, the publisher of an academic journal may be able to charge a higher price to libraries to capture some of the value that individuals receive from copying articles in the journal. In summary, given the speed and low cost of copying as well as the difficulty of employing private measures to prevent copying, we would expect a decrease in the number of new works created in the absence of copyright protection. This leaves open the question of how extensive copyright protection should be. The answer depends on the costs as well as the benefits of protection.

THE COSTS OF COPYRIGHT PROTECTION Unlike most ordinary goods, copyright protection generates access costs related to the public goods aspect of copyrighted works. Access costs fall on both consumers and creators of subsequent works who substitute other inputs that cost society more to produce or are of lower quality, assuming (realistically) that copyright holders cannot perfectly price discriminate. In the previous numerical example, consumers who value the work by more than the $1 cost of making additional copies, but less than the $2 price being charged, will be deterred from using the work. This generates a social loss. Similarly, some creators will be deterred from building upon prior works because they are unwilling to pay the price the copyright holder demands. In this case, copyright protection raises society’s cost of creating some new works. Paradoxically, too much copyright protection can reduce the number of new works created. The copyright owner has an incentive to lower prices to potential customers initially denied access, but information costs and arbitrage may make price discrimination infeasible. In contrast, access costs are not a significant problem for most tangible goods. In a competitive industry, the price of a tangible good equals its marginal cost. Only individuals who value the good at less than its price (equal to marginal cost) are denied access. The second major cost of a copyright system is administrative and enforcement costs. These include the costs of setting up boundaries or erecting imaginary fences that separate protected and unprotected elements of a work. They also include the costs of excluding trespassers, proving infringement and sanctioning copyright violators. Moreover, the public goods character of copyrightable works also raises enforcement costs because it makes detecting theft a greater problem. We may be able to copy a copyrighted work without the author knowing it. We cannot steal a car or house without the owner discovering it. Overall, the administrative and enforcement costs tend to be greater for intangible than for tangible property.

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SEPARATION OF OWNERSHIP A fundamental feature of copyright law separates ownership of the copyright from the good it embodies. From an economic standpoint, this separation might appear puzzling since, normally, concentrating in a single owner all rights to a good will minimize transactions cost and promote economic efficiency. For a copyrighted work, however, the opposite is often the case. First, consider a work that has many copies. Imagine that each purchaser of a copy of a Batman comic book also acquired the copyright as well. Then someone wanting to make a movie, television series or clothing collection based on the comic book might have to obtain permission from millions of individual copyright holders in order to avoid infringement. This would create potential hold-out problems and add to transaction costs, compared to the alternative of separating ownership of the copyright from the physical good. Then a potential licensee need only negotiate a single transaction with the sole copyright owner. A related reason for separation is that it enables the original creator to earn a return to cover the cost of creating the work. Although each owner of a copy of the comic book might be willing to pay a little more if he or she also owned the copyright, this amount is likely to be trivial because the high transaction costs of dealing with millions of copyright holders will make it uneconomical for a potential user to license the copyright in the first place. Alternatively, if each owner of a copy had the right to license the copyright, transaction costs would fall but the price of the comic book would not reflect any premium for the copyright. Competition among holders of copies would drive the licensing fee to zero and, thereby, reduce the incentive to create the original work. The efficiency explanation for separating ownership of the good from the copyright is less clear for a unique work such as a painting or sculpture where copying is likely to be very limited or not to occur at all.3 To illustrate, suppose A sells a unique work to B but retains the copyright. If C wants to reproduce A’s work, he or she must obtain access from B and a license to copy from A. Typically, this will involve greater transaction costs than if B owned both the copyright and the work. However, even here there are offsetting benefits from divided ownership. In the painting example, it will be more difficult for the artist to return to earlier themes because he or she risks infringing the copyright on his or her earlier work. Similarly, the author of a detective novel might be barred from writing sequels by the copyright owner. These problems will tend to multiply if the artist or author builds upon several of his earlier works in which he or she no longer holds copyrights. Alternatively, take the case of letters in which the copyright is held by the letter writer while the recipient owns the letter. The circumstances in which anyone desires to publish a single letter will be rare. Typically, the letter writer (say, a famous author) will have corresponded with many individuals. If a publisher desires to publish the collected letters, transaction costs will be lower if the author holds the copyrights (and retains copies of the letters) rather than numerous recipients who may be scattered throughout the world. A related problem concerns joint authorship, such as a composer and lyricist who create a copyrighted song. Transaction costs are minimized because either the composer or lyricist without the other’s consent can license the song provided he or she shares equally the licensing revenues with the other party.

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Copyright  119

DOCTRINES THAT LIMIT COPYRIGHT PROTECTION Since copyright tends to be a costly system of property, economics predicts that property rights in copyrighted works will be more limited than for tangible or physical property. Positive economic analysis of copyright law aims to show that various copyright doctrines that limit protection can best be explained as rough efforts to achieve the optimal balance between incentive benefits, and access and other costs in order to promote economic efficiency. Consider the following important copyright doctrines. Protection of Expression Copyright protects expression but not ideas, concepts, principles, techniques or processes (hereafter, ideas). Protecting original ideas would involve substantial administrative and enforcement costs. From an evidentiary standpoint, it is far simpler to determine if B has copied A’s original expression instead of A’s original idea. In addition, most original ideas in copyrighted works are trivial and involve small expenditures of time and effort relative to the cost of expressing them. Hence the added incentive benefits from protecting ideas would probably be swamped by the resulting access and administrative costs. Closely related to the idea–expression dichotomy is the merger doctrine. If we suppose there are only a few ways of expressing an idea, protecting expression will, as a practical matter, protect the idea. Here copyright protection will be denied. Merger might occur, for example, in the case of instructions explaining a paint-by-numbers game. The game itself is an unprotected idea and the instructions are the expression. Since there are only a handful of ways of writing the instructions and the costs involved are probably small, the absence of copyright will reduce administrative, enforcement and access costs without having a significant effect on the incentive of firms to produce these games. A related explanation is that, since competitors are bound to produce substantially similar instructions whether or not they copied, it would not be worth the evidentiary costs to figure out whether copying took place (see Lichtman 2001). Protection against Copying Copyright protects against copying but not independent duplication.4 Here ‘free-riding’ is missing, so independent duplication will not significantly undermine the incentives to create new works. Two other points reinforce this result. First, independent duplication should be rare for most works. Second, if independent duplication were actionable, authors would spend less time creating new works and more time checking earlier works to avoid copyright liability. This would lead society to expend greater resource on administering the copyright system in order to facilitate searching old records.5 In summary, since independent duplication is probably rare, it is unlikely that the added incentive benefits from making independent duplication actionable would be worth the extra costs it would entail. Right of Adaptation Copyright gives the creator adaptation rights on his or her work. This right, named the derivative works right, is broader than the right to prevent unauthorized copying, for it

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120  Handbook of cultural economics covers ‘any other form in which a work may be recast, transformed or adapted’.6 Examples of derivative works include the musical My Fair Lady, based on George Bernard Shaw’s play Pygmalion, mechanical dolls based on the Walt Disney characters, the movie Clueless based on Jane Austen’s Emma, or a dance performance based on a Jackson Pollock painting. If the underlying work is not in the public domain, the party creating the derivative work must get the copyright owner’s permission. The economic rationale for giving the original copyright holder rights over derivative works depends both on the added incentives to create original works and on the savings in transaction and enforcement costs that result from concentrating property rights in a single party. Consider first the incentive argument. We might reason that the added incentive benefits will be negligible if only a few copyrighted works will generate income from derivative works. Moreover, there is likely to be a substantial time lag between the date of the original work and the later derivative works. This, however, confuses ex ante and ex post returns. Even if the number of copyright holders who receive substantial income from adaptations is small, the ex ante return, which depends on both the small probability and the potentially large income, could be relatively large. Turning to transaction and enforcement costs, consider derivative works based on a Walt Disney character. Many ancillary products, ranging from umbrellas to lunch boxes, incorporate Disney images. By concentrating the copyrights in Disney rather than having each creator of a derivative work hold a separate copyright, the court avoids potentially burdensome lawsuits involving multiple plaintiffs. For example, how would a court decide, among many similar and widely accessible works, which work the defendant copied from? Licensing costs would also rise because a potential licensee would be advised to seek licenses from many parties to avoid the risk of being sued by one of them. Finally, the copyright on the original Disney character will be sufficient to prevent unauthorized copying of the various derivative works since a party copying from a derivative work will still infringe the copyright on the original work. Fair Use Fair use limits the rights of the copyright holder by allowing unauthorized copying in circumstances that are roughly consistent with promoting economic efficiency. One of these instances involves high transaction costs. For example, copying a few pages from a book probably does not harm the copyright holder because the copier would not have bought the book. Here A might be willing to pay B, the copyright holder, a sum that B would be happy to accept for the use of the work, but the cost of locating and negotiating with B may be prohibitive if all A wants to do is quote brief passages from B’s work. A fair use privilege creates a clear benefit to A but does no harm to B, whereas, if copying were prohibited, transactions costs would prevent an otherwise beneficial exchange from taking place. Here fair use creates a net social gain. The copier benefits, and the copyright holder is not harmed.7 Another circumstance that justifies fair use may be termed implied consent. Take a book review that quotes brief passages from the book. A book is an experience good so that accurate pre-use information about its quality is probably, on average, to enlarge the demand for it and benefit authors. A critical review may destroy the market for a particular work but, on balance, reviews will provide information to

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Copyright  121 potential ­customers and thereby benefit authors. Moreover, if the law required the reviewer to obtain the author’s consent to reproduce these passages, readers would have less confidence in the objectivity of the review, fearing that consent might well be conditional on the reviewer deleting critical parts of the review. Also, the more valuable the information, the greater, on average, should be the demand for the underlying works. In these circumstances, fair use can produce beneficial incentive effects and reduce access cost as well. The final category of fair use involves some harm to the copyright holder that is more than offset by lower access costs and possible benefits to third parties. Here the courts are more likely to find fair use for a productive than for a reproductive use of a borrowed work. The former transforms the original work into a new work and reduces the cost of creating the transformative work since transaction and licensing costs are avoided. Still, deeming a productive use a fair use may result in lost licensing revenues to the author of the copied work. This loss, however, would have little effect on the incentive to create the copied work since the prospect of these revenues was largely unanticipated at the time the work was created. A reproductive use, however, is more likely to substitute for the original work and, therefore, have significant negative effects on the incentives to create that work in the first place. The well-known veil-of-ignorance concept provides a helpful way to explain why the law treats productive uses more leniently than reproductive uses. Behind a veil of ignorance, authors would be more likely to favor a rule allowing productive fair use, since it would enable an author to borrow some expression from others and lower his or her costs, while his or her expected revenues would not change much when others borrowed from him or her. In contrast, a reproductive use risks substantially reducing the profits of the original author and hence his or her incentives to create the work in the first place. Parody is often protected as a fair use. Parody can involve high transaction costs because of the difficulty of negotiating with someone you want to poke fun at. It provides information or critical comment, similar to a review. Finally, it is a transformative use of the original work. Nonetheless, calling something a parody is not a blanket license to copy the parodied work. Parody is limited in two ways. One is that the parody can only take what is necessary to conjure up the original work. It cannot take so much of the original work that it effectively substitutes for that work. The other is that the parody must be aimed at the work it parodies (see Posner 1992). Here the economic rationale is that a voluntary transaction is less likely when the parody attacks a particular work than when it uses the work to comment on or criticize society at large.

OTHER COPYRIGHT ISSUES Infringement Evidence that the defendant copied from the plaintiff is usually circumstantial because the public-goods aspect on intellectual property makes it rare to catch a copier in the act.8 The two key evidentiary factors that support an inference of copying are a reasonable probability of access to the plaintiff’s work (for you cannot copy without access) and

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122  Handbook of cultural economics s­ ubstantial similarity between the works. In some cases, striking similarity alone may support an inference of access. If the plaintiff’s work is so unique and complex and ­nothing similar exists in the public domain, its appearance in the defendant’s work is strong evidence of access, eliminating the possibility of independent creation. Once the plaintiff shows access and substantial similarity, the burden then shifts to the defendant to rebut the evidence. From an economic standpoint, this tends to minimize dispute resolution costs because the defendant possesses the information on how he or she created the work and, therefore, has the lowest cost of proving independent creation. Finally, even if the defendant copied, his or her copying may not be illicit. The plaintiff must show that the substantial similarities between the two works go to what the law protects: expression not ideas, the non-utilitarian parts of useful works, what was original in the plaintiff’s work, and that the copied material was not a fair use. Authorship and Work-for-Hire Authorship conveys a bundle of rights because copyright vests initially in the author of the work but, since most works are the product of numerous parties, how does the law decide the question of authorship? One possibility is that the author is the person who physically executes the work. However, that might mean that the Copyright Act would deem a typist or research assistant the author or joint author. From an economic standpoint this would be inefficient for it would lead to added contracting and transaction costs as the party responsible for creating the work would require that his or her assistants assign the copyright to him or her. Consistent with efficiency considerations, the copyright statute provides that the author may be someone other than the person who actually fixes the work in a tangible form, though it leaves undefined the term author. A more modern view of authorship is that it lies with the person who conceives of the work and arranges for its execution. Thus the market regards a conceptual artist as the author even though he or she hires other individuals to execute the work. Coase’s theorem is helpful in both deciding which party or parties should be deemed the author and the futility of legal rules that are inconsistent with promoting efficiency. Recall that the Coase theorem states that, in the absence of transaction costs, the initial assignment of property rights will not affect the efficient allocation of resources. Suppose A and B are involved in creating a copyrighted work, A values the copyright more than B does, and the law regards B as the author because B has fixed the work. Then the initial contract between A and B will include a term that transfers the copyright to A or, if the contract is silent on this point, A will buy the copyright from B in a subsequent transaction. If the law had deemed A the author at the outset, contracting or transaction costs would be saved. This suggests that the law would promote efficiency if it assigned authorship and hence the copyright to the party who values it more; that is, the party who would wind up with the copyright if transaction costs were negligible. There is another conception of authorship that is worth mentioning. Here, the author is the party who finances the work and bears the financial risks although he or she may delegate the creative decisions to the party who actually executes the work. The work-forhire doctrine is based on this conception. A work created pursuant to an employment relationship (such as when Disney hires an animation artist who is paid a regular wage,

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Copyright  123 receives fringe benefits and can be assigned to work on different projects) is unambiguously a work-for-hire. However, a commissioned work executed by an independent artist may also be a work-for-hire if the commissioning party pays a monthly stipend, health and other fringe benefits during the time the artist works on the project, covers the cost of materials and exercises overall, but not day-to-day, supervision. Consistent with the Coase theorem, the work-for-hire doctrine lowers transaction and contracting costs by assigning the copyright to the party in the best position to exploit it. In the Disney example, transaction costs would be very high if each artist employed by Disney owned the copyright to his or her work. Then, each artist/employee would be in a position to hold up and delay projects (for example, publication of a comic book) that require Disney to coordinate the efforts of many employees. Knowing this in advance, Disney would acquire the separate copyrights before embarking on a project. By assigning the copyrights to Disney at the outset, the work-for-hire doctrine saves contracting and potential hold-up costs. Copyright Duration Let me conclude by mentioning a major economic puzzle about copyright – its long duration. Currently, a copyright lasts for the life of the author plus 70 years. In the case of a work-for-hire, the term is 95 years. However, from an incentive standpoint, the present value of $1000 in say 80 or 90 years is trivial given any reasonable discount rate. Alternatively, life plus 70 years can create substantial access costs (including the cost of tracking down the copyright owner and licensing the work) since a smaller amount of public domain material will be available at any point in time.9 Thus a shorter copyright term would reduce access costs without significantly reducing the incentives to create new works. There are several possible explanations for a long copyright term. These include the possibility that the returns from copyrighted works occur mainly in the last few years, that the value of an author’s earlier works will be enhanced by his or her later efforts and that a near perpetual term avoids the tragedy of the commons. The first argument appears factually wrong, based on an analysis of US data showing that copyrights were rarely renewed (for an additional 28, and later 47, years of protection at the end of the initial 28-year term) for works created before the 1978 Copyright Act (see Landes and Posner 2003). The second argument might account for a copyright term that extends 20 or so years after the author’s death, but not 70 years. The third argument appears to overlook the widespread belief that copyrighted expression is not exhaustible, so the tragedy of the commons does not apply. We called this the public-good aspect of copyright works. Unlike natural resources that can be used up by overexploitation, previous editions of Shakespeare’s works do not preclude publishers from bringing out new editions. This objection to a lengthy copyright term, however, is overstated. It overlooks the possibility that unlimited use of a still valuable copyright that was dumped into the public domain (even many years after the work was created) could create negative externalities that might reduce the overall value of the work compared with extending the copyright term. A related economic argument against limiting the duration of copyright is that it reduces the incentive to invest resources in developing markets for works that have fallen into the public domain.10

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INDIRECT LIABILITY An important question in copyright today is under what circumstances can C be held liable for B’s infringement of A’s copyright? Since B is the infringer, C’s liability would be indirect. There are two longstanding common law doctrines of indirect liability: contributory infringement and vicarious liability.11 Contributory Infringement Contributory infringement applies when C induces, causes or otherwise materially contributes to the infringing conduct of B. Consider the following example: suppose C manufactures a decoder box that enables any purchaser B to unscramble premium and pay-per-view cable programs without paying for them. A is the injured copyright holder who owns those programs and B is the direct infringer. Should the equipment maker C be held liable for B’s infringement of A’s copyright? Two considerations are worth noting. First, there are probably substantial enforcement and administrative savings if A is allowed to sue C instead of pursuing each B individually. The costs of tracking down many Bs, gathering evidence as to the specific activities of each, and then litigating many separate lawsuits involving small damages would probably make it uneconomical for A to enforce its copyright. Since B knows this in advance, B has little incentive to comply with the law. By contrast, if the law holds C liable for the total damages caused by the many Bs, the savings in enforcement costs are likely to be sufficiently large for A to enforce its copyright. In turn, the prospect of liability will most likely put C out of business and lead some or most Bs to pay for cable rather than infringe A’s copyright. Second, if there are lawful uses of C’s product, the case for liability is weakened. The lawful-use question does not arise in the decoder example since the decoder’s only use involves violating the law. However, consider a firm that makes photocopiers or personal computers. The firm knows that some of its customers will infringe copyright, but the firm does not have specific knowledge about any particular customer. Thus, even though substantial savings in enforcement costs might still arise in these cases were courts to impose liability, it is unlikely that any court would be willing to do so. The benefits in terms of increased copyright enforcement come at too high a cost in terms of possible interference with the sale of a legitimate product. In some cases it may be possible for the equipment maker C to redesign its product in a way that would eliminate or greatly reduce the level of infringement without significantly cutting down on the quantity and quality of lawful uses. In cases such as this, liability is again attractive. Often, however, these types of solutions are out of reach. For instance, it is hard to imagine a redesigned photocopier that would make infringement less attractive without substantially interfering with lawful duplication. As a result, holding the equipment manufacturer liable would be equivalent to imposing a tax on the offending product. The ‘tax’ would reduce overall purchases of photocopiers and it would redistribute income to copyright holders, but it would not in any way encourage users to substitute non-infringing for infringing uses. The examples of the decoder box and the photocopier mark two extremes and serve to delineate the key issues. Holding all else equal, contributory liability is more

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Copyright  125 ­ ttractive: (1) the greater the harm from direct copyright infringement; (2) the less the a benefit from lawful use of the indirect infringer’s product; (3) the lower the costs of modifying the product in ways that cut down infringing activities without substantially interfering with legal ones; and (4) the greater the extent to which indirect liability reduces the costs of copyright enforcement as compared with a system that allows only direct liability. Vicarious Liability Vicarious liability applies in situations where one party, often an employer, has control over another and also enjoys a direct financial benefit from that other’s infringing activities. A typical case arises where an employer hires an employee for a lawful purpose, but the employee’s actions on behalf of the employer lead to copyright infringement. One rationale for imposing liability is to encourage the employer to exercise care in hiring, supervising, controlling and monitoring its employees to make copyright infringement less likely. Another is the cost savings from suing an employer instead of multiple infringing employees. A final rationale is that liability helps to minimize the implications of an infringing employee who lacks financial resources to pay damages, by putting the employer’s resources on the line.12 Consider the example of a dance-hall operator who hires bands and other performers who sometimes violate copyright law by performing copyrighted work without permission. It is probably less expensive for a copyright holder to sue the dance-hall operator than it is for him or her to sue each performer individually, both because there are many performers and because the dance-hall operator is probably easier to identify and to serve with legal process. Putting litigation costs to one side, it is also the case that dance-hall operators are typically in a position to monitor the behavior of direct infringers at a relatively low cost. Finally, since performers are more likely than dance-hall owners to lack the resources to pay copyright damages, vicarious liability prevents the externalization of copyright harm. It is worth noting that the threat of vicarious liability has encouraged dance halls, concert halls, stadiums, radio stations, television stations and other similar entities to look for an inexpensive way to acquire performance rights. For the most part, they do this by purchasing blanket licenses from performing rights societies, the two largest of which are Broadcast Music International (BMI) and the American Society of Composers, Authors, and Publishers (ASCAP). The blanket license gives licensees the right to perform publicly all the songs in the performing rights society’s repertoire for as many times as the licensee likes during the term of the license. The blanket license saves enormous transaction costs by eliminating the need for thousands of licenses with individual copyright holders and by eliminating the need for performers to notify copyright holders in advance with respect to music they intend to perform. In addition, the blanket license solves the marginal-use problem because each licensee will act as if the cost of an additional performance is zero – which is the social cost for music already created. Current Controversies Probably, the most significant legal decision in recent years was the 1984 Supreme Court decision in Sony v. Universal City Studios.13 The plaintiffs were firms that produced

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126  Handbook of cultural economics programs for television; the defendants manufactured an early version of the videocassette recorder (VCR). The plaintiffs’ legal claim was that VCRs enable viewers to make unauthorized copies of copyrighted television programs. This allowed viewers more easily to skip commercials, which diminishes the value of the associated copyrighted programming. Suing viewers directly would have been both infeasible and unpopular, so the program suppliers sued the VCR manufacturers on theories of both contributory infringement and vicarious liability. The Supreme Court rejected vicarious liability because it did not believe that VCR manufacturers had sufficient control over their infringing customers. The only contact between VCR manufacturers and their customers occurred at the moment of sale, a time far too removed from any infringement for the manufacturers to be rightly compared to controlling employers.14 The Supreme Court rejected contributory infringement because the VCR is capable of substantial non-infringing uses – legitimate uses that in the court’s view left manufacturers powerless to distinguish lawful from unlawful behavior. Importantly, the main concern in Sony v. Universal City Studios was a fear that indirect liability would have given copyright holders control over what was then a new and still developing technology. The analogous modern situation would be a lawsuit attempting to hold Internet service providers liable for online copyright infringement. It is easy to see why courts would be reluctant to enforce such liability. Copyright law is important, but at some point copyright incentives must take a backseat to other societal interests, including an interest in promoting the development of new technologies and an interest in experimenting with new business opportunities and market structures. Congress became involved with indirect liability again in 1998 when it passed the Digital Millennium Copyright Act.15 One provision immunizes from indirect liability a broad class of Internet access providers, telecommunications companies and Internet search engines, as long as these entities satisfy certain specific requirements designed to safeguard copyright holders’ interests. The Digital Millennium Copyright Act established a safe harbor: if these Internet entities follow the requirements laid out by the statute – which typically require the entity to act when a specific instance of infringement is either readily apparent or called to the entity’s attention by a copyright owner – they are immune from charges of vicarious liability and contributory infringement. Probably the most talked about litigation on indirect copyright liability is the music industry’s successful lawsuits against Internet startups Napster and Grokster.16 Napster provided software that allowed a user to identify any song he or she was willing to share with others, and it provided a website where that information was made public so that an individual looking for a particular song would be able to find a willing donor. Napster had the ability to limit copyright infringement in ways that VCR manufacturers do not. Napster knew that specific infringing material was available using its system, and it could have used that knowledge to identify and block at least some of the infringing material. As regards vicarious liability, Napster could have refused service to users who were violating copyright law. Grokster provided software for peer-to-peer sharing but did not index the songs that users were willing to share nor did it monitor what songs were being downloaded. Still, the Supreme Court held Grokster liable because (unlike Sony v. Universal City Studios) its product was mainly used to enable consumers to infringe copyrights in music.

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Copyright  127

NOTES  1. Although I focus on copyright law in the United States, the principal copyright doctrines are similar throughout most of the world. For a more complete analysis, see Landes and Posner (1989).  2. In the case of unique works, such as a painting, the case for copyright protection is weaker because the main source of income typically comes from the sale of the work itself, not from copies. Still, unauthorized copying or free-riding on unique art works will reduce the income an artist receives from posters, note cards, puzzles, coffee mugs, mouse pads, T-shirts and other derivative works that incorporate images from the original work.  3. A may explicitly transfer ownership of the copyright to B or anyone else. Our illustrations concern default rules in which there is no explicit contract governing ownership of the copyright.  4. In Sheldon v. Metro-Goldwyn Pictures, 81 F.2d 49, 54 (2d Cir. 1936), Judge Learned Hand stated that: if by some magic a man who had never known it were to compose anew Keats’s Ode on a Grecian Urn, he would be an ‘author’ and, if he copyrighted it, others might not copy that poem, though they might of course copy Keats’s. But though a copyright is, for this reason, less vulnerable than a patent, the owner’s protection is more limited, for just as he is no less an ‘author’ because others have preceded him, so another who follows him, is not a tort-feasor unless he pirates his work.  5. It is worth noting that the copyright registration system involves minimal cost. Registration creates a public record of the basic facts of the copyright. An applicant seeking to register his work submits a $30 filing fee and fills out a short form listing the work’s title, author, year of creation, and date and place of publication (if published). The applicant must also deposit a copy of the work (or, in cases where this is not feasible, a photograph of the work). Registration is optional and is not a condition for copyright protection, though it is a prerequisite to an infringement action in the United States (but not in most countries outside the United States). The Copyright Office makes no effort to search prior copyrighted works for similarities with the applicant’s work before registering the copyright. Registration information and forms are available online from the US Copyright Office website (http://www.loc.gov/copyright).  6. See 17 U.S.C.A. § 106(2) (2000) and the definition of a derivative work in 17 U.S.C.A. § 101 (2000).  7. The high transaction cost rationale should be narrowly construed. Otherwise, it would reduce the incentive to develop innovative market mechanisms that reduce transaction costs. These include performing rights societies such as American Society of Composers, Authors, and Publishers (ASCAP) and Broadcast Music International (BMI), the Copyright Clearance Center for journals, and two arts organizations (Visual Artists’ and Galleries Association and The Artists’ Rights Society) that license reproduction rights to the works of many artists.  8. In the case of maps, directories, software and information-type works, the copyright holder often deliberately includes a few errors. If the errors show up in the alleged copier’s work, this is pretty good evidence that he has copied from the original copyright holder. This is known as the common error doctrine. It is useful in discovering unauthorized copying because of a special feature of the copyright as distinct from the patent system. Under the patent system, the patentee must point out and distinctly claim what he or she regards as his or her invention. In copyright, you do not have to identify beforehand the elements for which you claim protection. Thus, if you publish a book based on public domain material plus your own material, you do not have to point out which is which.  9. I add, however, that, just as potential future revenues from a longer copyright term must be discounted, so must future access or deadweight losses. 10. Both the negative externality and investment arguments in favor of an unlimited copyright term (more correctly, permitting copyrights to be renewed if they are sufficiently valuable to cover the costs of renewal) are developed in Landes and Posner (2003). 11. This section is based on Landes and Lichtman (2003). 12. Note that employers are only held responsible for infringements that occur within the scope of employment. Infringement committed by an employee on his or her own time and for personal reasons would not trigger vicarious liability. See Sykes (1998). 13. Sony Corporation of America v. Universal City Studios, Inc., 464 U.S. 417 (1984). 14. The Supreme Court took a restrictive view of what it means for a manufacturer to control its purchasers. For example, it did not consider whether a relatively simple technology solution – say, making the fastforward button imprecise and thus diminishing the ease with which purchasers can skip commercials – might have gone a long way toward protecting copyright holders without interfering unduly with legitimate uses. 15. Pub. L. No. 105-304, 112 Stat. 2860 (1998) (codified in scattered sections of 17 U.S.C.). 16. See A&M Records, Inc. v. Napster, Inc., 239 F.3d 1004 (9th Cir. 2001) and MGM Studios, Inc. v. Grokster, Ltd. 545 U.S. 913 (2005).

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SEE ALSO: Chapter 6: Artists’ resale rights; Chapter 7: Artists’ rights; Chapter 11: Contract theory and information goods; Chapter 14: Creative industries; Chapter 25: Digital piracy.

REFERENCES Landes, W. and D. Lichtman (2003), ‘Indirect liability for copyright infringement: Napster and beyond’, Journal of Economic Perspectives, 17 (2), 113–24. Landes, W.M. and R.A. Posner (1989), ‘An economic analysis of copyright law’, Journal of Legal Studies, 18 (2), 325–66. Landes, W.M. and R.A. Posner (2003), ‘Indefinitely renewable copyright’, University of Chicago Law Review, 70 (2), 471–518. Lichtman, D. (2001) ‘Copyright as a rule of evidence’, Working Paper in Law and Economics No. 151, University of Chicago Law School. Posner, R.A. (1992) ‘When is parody fair use?’, Journal of Legal Studies, 21 (2), 67–78. Sykes, A.O. (1998) ‘Vicarious liability’, in P. Newman (ed.), The New Palgrave Dictionary of Economics and the Law, vol. 3, Basingstoke: Palgrave Macmillan, p. 673. Towse, R., C. Handke and P. Stepan (2008) ‘The economics of copyright law: a stocktake of the literature’, Review of Economic Research in Copyright Issues, 5 (1), 1–22.

FURTHER READING Suggested further reading: Towse et al. (2008) is an accessible survey of the literature. Landes and Posner (1989) is the seminal article on the law and economics of copyright.

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13.  Cost of production*

Víctor Fernández-Blanco and Juan Prieto-Rodríguez

In this chapter, we focus on the cost structure of cultural industries, that is, the segment of the cultural sector in which digitization has become most prominent. Digitization is not exclusive to them, but it has completely changed the way films, videogames, broadcasting, publishing and music industries are currently organized. We are aware that this choice omits from our analysis the most traditional part of the cultural sector, such as the performing arts, the traditional visual arts (painting or sculpture), museums and cultural heritage. Although digitization is also impacting production costs of theatres, orchestras or museums as they engage new ways to reach consumers and reduce costs, this impact can be considered just partial as the core of their activity is not fully affected. To represent La Traviata you need, among other things, an orchestra, the cast and a stage. These three elements cannot usually be digitized for live performances. Another question that may arise is how digitization can help electronic broadcasting of live content reach new audiences, as the Metropolitan Opera House in New York is doing with great success. High fixed costs, in both the specialization of human capital and technical equipment, is a common characteristic associated with the production of any cultural good. However, there is a big difference regarding variable and marginal costs when we distinguish between traditional and digital cultural goods. Traditional cultural goods and services, or cultural goods produced using traditional methods, also have very high variable costs that tend to remain high as salaries rise but productivity remains stable, as described by Baumol’s cost disease (Baumol and Bowen 1966). However, variable and marginal costs of producing digital goods differ completely. As stated by Throsby (2006, p. 12) ‘the media, the movies, popular music, and book publishing. All four industries are characterized by the fact that they produce under high fixed costs but negligible marginal costs, and under conditions of considerable uncertainty’. Instead of being an incontestable advantage, this generates an important pricing problem for cultural industries in the new economy. Since price must be equal to the marginal cost to achieve an efficient equilibrium, optimal prices could be so low that, given the high fixed costs, producers will suffer losses under perfect competition. This situation could be worse if there were no direct contact between producers and consumers and trade is controlled by an intermediate, that is, a two-sided market (Rochet and Tirole 2006). However, this is the case since most of the large companies that currently dominate the exchange of digital creative contents (for example, Amazon, iTunes, Netflix) are multi-sided platforms that intermediate in two-sided markets. Although consumers and record companies may consider this situation ideal since, in a simple way, just by visiting a single web page, the former can access products from many record companies and the latter can access thousands of consumers, the existence of very large network economies has the impact of transforming these multilateral platforms into almost natural monopolies. Moreover, sometimes, as with YouTube, free universal access is granted to the consumers and revenues come from advertising. However, this could be a problem 129

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130  Handbook of cultural economics because it dissociates price formation from the logic of costs and supply, and may lead to two extreme outcomes: almost zero access price for consumers with low remuneration per unit for the creators, or no quality creation at all if the prices are too low. In the next section, we examine the cost structure of cultural industries, putting the emphasis on those characteristics that may have a larger impact on concentration, market power and prices.

THE COST STRUCTURE OF CULTURAL CONTENTS IN THE DIGITAL ECONOMY The cost structure of a company, and by extension the economic sector where it operates, is a reflection of the technology available to undertake its productive tasks and, consequently, a key element in understanding the basic decisions of output and pricing. A large part of the culture and arts sector, and particularly cultural industries, is characterized, on the one hand, by relatively low variable costs, those depending on the level of production and, on the other, by very high fixed costs, that is, those that will be incurred regardless of the level of production undertaken. Moreover, many of the fixed costs associated with cultural industries are impossible to recover; therefore, they are sunk costs. The process of obtaining an audio-visual product can illustrate all this. Before any audio-visual product can be sold, it will have been necessary to cover a number of stages that include the design of a financing plan, the development and creation of the first copy or master and other preproduction arrangements, the production itself and the postproduction, including distribution, promotion and advertising. By definition, all the costs incurred before moving on to the production phase are fixed costs since they do not depend on the number of units produced. As soon as that first copy is available, whether in a physical or electronic format, obtaining new units involves incurring new costs that depend on the number of units that you want to produce. These are the variable costs. However, most costs associated with the distribution and the making of the product available to the public, such as promotion and advertising, are not variable but fixed costs. As cultural industries have moved from an industrial to a digital model of production, some costs have fallen, such as production and transport costs associated with distribution, but this decrease has affected more intensively the variable and marginal costs rather than fixed costs. ‘[O]nce information is transformed into digital form, it can be copied and distributed at near-zero marginal costs’ (Waldfogel 2017, p. 195). Therefore, the relative importance of fixed costs has increased in recent years. From a cost structure such as this, there are three characteristics that will have a great impact on the market: the importance of sunk costs, decreasing average total costs and marginal costs of almost zero. The Role of Sunk Costs As pointed out by Baumol (2006), the need of creating new content means that investment is required each time an output emerges. Since this investment is not recoverable, it is a sunk cost incurred each time a new album, film, book or song is launched. Standard wisdom in economics, as indicated by Baumol and Willig (1981), is that sunk costs may act as an entry barrier because new potential firms will face larger losses if, once in the

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Cost of production  131 market, they decide to leave. This idea was refined by Sutton (1991) using the concept of endogenous sunk costs. These are costs, such as advertising, that are determined by the firm, are not linked to the number of units produced and are not recoverable. Alternatively, exogenous sunk costs are costs not recoverable, not linked to the number of units produced and determined exogenously, such as a single fee issued to allow a firm to broadcast or perform a copyrighted work for a defined period. In the model proposed by Sutton (1991, 1996, 1998), quality can be determined by firms but at an increasing research and development (R&D) cost. If these costs are determined by the firm and are product specific, they will be endogenous sunk costs. Advertising would also be an endogenous sunk cost that would be characterized by the firm’s attempt to generate greater product appeal. For the cultural industries,1 investment in quality and advertisement would lead to a greater ex ante appraisal of quality by consumers and, thus, a better marketability of the new book, film, song, and so on. This, in turn, would imply a higher willingness to pay and a larger revenue for any level of production. Hence, firms always have a short-run incentive to raise quality (or its ex ante appraisal) up to the point where the (marginal) return of the investment in quality is equal to its cost. However, these costs linked to quality can be viewed as entry barriers by potential competitors. Therefore, the considerable importance of these endogenous sunk costs has long-run implications for the cultural industries since, as occurred in the past, they lead to a competitive escalation of production expenditures, increasing industrial concentration (Bakker 2015). Decreasing Average Total Costs Average total costs are defined as the sum of average fixed and variable costs, and we can assume that they are decreasing for digital cultural goods. First, we can assume that, for digital goods, the average variable cost is constant and practically nil; while average fixed costs are always decreasing, since as output rises the same fixed cost will be allocated among an increasing number of product units. Under these assumptions, the average total cost will be decreasing. When average total cost decreases as the volume of production increases, the company operates under economies of scale. In this situation, it is profitable to increase the size of the company, and the volume of production, because it results in a lower cost per unit. This is the standard definition of a natural monopoly that, in the presence of sunk costs, will also generate incentives to increase firm concentration in the cultural industries. Therefore, cultural industries are a fertile ground for the presence and dominance of large companies that can take advantage of these economies of scale. Their position will be strengthened if, as in the cultural sectors, the fixed costs are high and a large part of them are associated with sunk costs, which protects established companies from the possible entry of new competitors. That is, digitization has favoured the process of concentration that has given rise to large conglomerates and, in turn, demands new answers from regulators (see, for instance, Doyle 2014). As an example, in the field of the music industry and using data offered by Billboard, in 2015 three large companies (Universal Music Group, Sony Music Entertainment and Warner Music Group) accounted for approximately 86 per cent of the market2 including physical albums, digital sales and streaming consumption.3

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132  Handbook of cultural economics The situation is very similar for the distribution of digital cultural content. Distribution through digital companies and networks also requires significant high fixed costs of establishment, but the average variable cost and the marginal cost of serving a new customer are constant and approximately zero. The result leads to a few large companies to control the sector. For example, Amazon has further increased its market share in the US e-book market from 74 per cent in October 2015 to 83.3 per cent in February 2017. In summary, on the production side, there are mainly two factors explaining the concentration of the industry: the existence of sunk costs and economies of scales.4 The Marginal Cost Almost Zero If the average variable cost is constant, the marginal cost will also be constant and equal to the average variable cost. Digitization of cultural goods does not alter the form of the cost functions but accentuates some of their features. In particular, average variable costs and marginal costs are now practically negligible. How much does an additional copy of an e-book or an additional stream of a movie cost? It is also very important to bear in mind that this property is not limited to the production segment, but extends to the distribution, storage and placing of the product available to consumers. This cost structure also has its effects on the setting of prices and the remuneration of creators (Baumol 2006). The efficient and socially optimal solution involves charging for each unit exactly the marginal cost. Under close to zero marginal costs, this price rule does not enable recovery of the fixed cost that includes the remuneration received by the creators. Therefore, under perfect competition, incentives for creation diminish, if not disappear, and will be reduced in number, quantity and variety. That is, current technology under competitive markets does not provide attractive remuneration to the creators of digital content and leaves them, once again, vulnerable and waiting for public action, either through regulation, which may include changes in copyright legislation, or alternative mechanisms that facilitate the provision of cultural goods. Alternatively, for those services that are distributed through new digital channels, it may be convenient to consider a scheme of fixed payments that are not proportional to consumption (Holmstrom and Milgrom 1994). Although perfect competition may have some undesirable results for creativity, it is not the expected market structure in the creative industries, as high sunk costs, economies of scale and network externalities will lead to the existence of fewer companies that will use their market power to set prices above marginal cost.

CONCLUSION Throughout this chapter, we have seen that new technologies have brought about a radical change in the cost structure of the creative economy, leading to a very low marginal cost, many times almost nil, for the production, distribution and reproduction of digital products.5 However, the cost structure characterized by high fixed and sunk costs, low constant marginal costs and decreasing average total costs favour concentration for both production and distribution of digital cultural goods. The combination of repeated and endogenous sunk costs that can act as entry barriers, plus the presence of economies of

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Cost of production  133 scale associated with decreasing average total costs, have led to a high concentration and a reduction in the number of companies in the culture sector, whose latest example has been the acquisition of Fox by Disney in the spring of 2019. High sunk costs lead to non-contestable markets, rising market shares of some companies in their own subsectors (for instance, Disney in the film industry, Amazon in music distribution or Amazon in the e-book market). The implicit market power has helped them to raise prices above marginal costs moving the equilibrium away from the social optimum.6 For instance, it does not seem that the digitization of the cinematographic exhibition and, consequently, of film distribution has impacted cinema ticket prices taking them down to the new marginal costs of distribution: the annual average US ticket price was $5.39 in 2000 and $9.11 in 2018, implying a skyrocketed rise of 60 per cent in nominal terms but, also, 15 per cent in real terms.7 Moreover, large companies in the cultural industries have another feature that reinforces their position in the market. Currently they comprise large conglomerates, born through vertical and horizontal integration processes, providing large firms a privileged presence in all stages of the value chain of cultural products. Sony is a good example; its interests range from consumer electronics to the production, distribution and sale of audio-visual, musical or hardware and software content for interactive games. Also, Apple is a similar case, combining the design, production and supply of electronic products and online services, including the largest digital music shop. The fall of marginal costs in the digital world has meant that technology has introduced an additional threat to authors. Once created and digitized, a work has a great capacity to acquire the features of a public good. On the one hand, its consumption is not a rival, that is, the download or access by an individual to a certain digital content does not diminish the amount that remains available others to access. On the other hand, technology has opened multiple ways to obtain these contents almost freely, although in some cases illegally. The marginal cost of an additional download will be zero, or close to zero, unless we provide it with an attribute that introduces scarcity, such as copyright. Consequently, it could be difficult, at least in theory, to apply the principle of exclusion to these digital goods if the price is set close to the marginal cost. If price limits have to be established through regulation, networks become especially relevant. New technologies have made network economies much easier. The importance of these network economies has led to the growth of two-sided and multi-sided markets in many sectors of the digital economy. If the regulatory authorities demand that the price be raised to better reflect the cost of providing the service (and transfer part of what was collected to, for example, the creators) this can generate the ‘waterbed’ effect, that is, unexpected and unwanted effects owing to the reducing network economies (see Schiff 2008). If consumers of digital content have a very elastic demand, that is, they will reduce their demand significantly in the face of a small rise in prices, this regulatory change tending to favour content owners and creators could generate a new balance in which social welfare would be drastically reduced and demand would be much lower. Therefore, the effects of digital technologies and network economies on the distribution of income of creators cannot be easily corrected. There are two distributive effects. First, new technologies and network economies encourage the polarization of consumption and induce the creation and maintenance of superstars. Secondly, they facilitate higher market concentration as new technologies lead to decreasing average costs. These two realities

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134  Handbook of cultural economics lead to increased inequality in the income of artists and creators as superstars emerge and the reward of the middle and lower parts of this distribution decline. In summary, new cost structure associated with technological change and the digitization process offers ambivalent results for the evolution of cultural industries. On the one hand, they have stimulated demand and made things easier for consumers, thanks, among other things, to the reduction in access costs and the increase in variety (Potts 2014). However, on the other, they have introduced new difficulties: the remuneration of creators, with a copyright system that must necessarily be adapted (Waldfogel 2014), and the consolidation and strengthening of the oligopolistic structures on the production side.

NOTES *

1. 2. 3.

4. 5.

6. 7.

This study received funding from the Government of Spain (ECO2016-76506-C4-1-R and ECO2017-86402C2-1-R) and the Regional Government of Asturias (FC-15-GRUPIN14-064). We are especially grateful to Fundación Alternativas which generously funded a previous Spanish version of this chapter. The usual disclaimer applies. Since Sutton’s model was based on quality, its translation to the creative industries was straightforward. Motta and Polo (1997) applied this model to the television sector, Bakker (2005) to the film industry and to the creative industries (Bakker 2015). Their corresponding market shares were 39.2 per cent for Universal, 27.3 per cent for Sony and 19.4 per cent for Warner (Christman 2015). Since December 2014, in order to assess the consumption of digital products, Billboard has incorporated a new algorithm, along with physical sales, that considers digital and consumer sales data via streaming from the largest subscription audio on demand providers, including Spotify, BeastMusic, Google Play and Xbox Music. According to this new methodology, the sale of an album is equivalent to the sale of ten tracks or the hearing of 1500 songs via streaming (Billboard 2014). Network economies, on the distribution side, also tend to favour concentration. However, their analysis is outside the scope of this chapter. Digital media are spectacularly powerful channels when it comes to extending the ways in which we access cultural content. It can be argued that this diversification, at very low cost, has created ways for the exposure of all kinds of artists and creators. The ‘long tail’ economy (Anderson 2006) assumes that even modest artists may have access to markets through the Internet and, with it, to a potentially global market. However, this extreme abundance has raised the costs of searching and handling information for consumers. This has increased the importance of gatekeepers. Aggregators, search engines and dissemination platforms occupy a privileged position in this new world, allowing them to exploit new rents. By channelling preferences towards certain artistic options, they could polarize consumption, allowing the creation of superstars (see Salganik et al. 2006). Amazon’s large profits in the first quarter of 2019 can be a signal of this market power. Also, Apple reported record revenues associated with i-Tunes in 2018. Own calculation using average ticket price from the National Association of Theatre Owners at www. natoonline.org/data/ticket-price (accessed 10 December 2019).

SEE ALSO: Chapter 26: Digitization in the cultural industries; Chapter 45: Performance indicators; Chapter 47: Platforms.

REFERENCES Aguiar, L. and J. Waldfogel (2018), ‘Netflix: global hegemon or facilitator of frictionless digital trade?’, Journal of Cultural Economics, 42 (3), 419–45.

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Cost of production  135 Ambrus, A., E. Calvano and M. Reisinger (2016), ‘Either or both competition: a “two-sided” theory of advertising with overlapping viewerships’, American Economic Journal: Microeconomics, 8 (3), 189–222. Anderson, C. (2006), The Long Tail: Why the Future of Business is Selling Less of More, New York: Hyperion Books. Anderson, S.P. and J.J. Gabszewicz (2006), ‘The media and advertising: a tale of two-sided markets’, in V.  Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 567–614. Bakker, G. (2005), ‘The decline and fall of the European film industry: sunk costs, market size, and market structure, 1890–1927’, Economic History Review, 58 (2), 310–51. Bakker, G. (2015), ‘Sunk costs and the dynamics of creative industries’, in C. Jones, M. Lorenzen and J. Sapsed (eds), The Oxford Handbook of the Creative and Cultural Industries, Oxford: Oxford University Press, pp. 351–86. Baumol, W. (2006), ‘The arts and the “new economy”’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 339–58. Baumol, W.J. and W.G. Bowen (1966), Performing Arts, The Economic Dilemma: A Study of Problems Common to Theater, Opera, Music, and Dance, New York: Twentieth Century Fund. Baumol, W.J. and R.D. Willig (1981), ‘Fixed costs, sunk costs, entry barriers, and sustainability of monopoly, Quarterly Journal of Economics, 96 (3), 405–31. Billboard (2014), ‘Billboard 200 makeover: album chart to incorporate streams & track sales’, Billboard, accessed 11 December 2019 at http://www.billboard.com/articles/columns/chart-beat/6320099/billboard-200-makeoverstreams​-digital-tracks. Castiglione, C., D. Infante and M. Zieba (2018), ‘Technical efficiency in the Italian performing arts companies’, Small Business Economics, 51 (3), 609–38. Christman, E. (2015), ‘Q3 SoundScan report: Taylor Swift and Bruno Mars dominate, streaming surges’, Billboard, accessed 10 December 2019 at www.billboard.com/articles/business/6722597/q3-soundscan-2015-taylor-swiftbruno-mars-streaming​-surge. Del Barrio-Tellado, M.J. and L.C. Herrero-Prieto (2019), ‘Modelling museum efficiency in producing interreliant outputs’, Journal of Cultural Economics, 43 (3), 485–512. Doyle, G. (2014), ‘Media ownership: diversity versus efficiency in a changing technological environment’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsterdam: North-Holland, pp. 215–97. Fernández-Blanco, V., A. Rodríguez-Álvarez and A. Wiśniewska (2019), ‘Measuring technical efficiency and marginal costs in the performing arts: the case of the municipal theatres of Warsaw’, Journal of Cultural Economics, 43 (1), 97–119. Gil, R. and R. Lampe (2014), ‘The adoption of new technologies: understanding Hollywood’s (slow and uneven) conversion to color’, Journal of Economic History, 74 (4), 987–1014. Holmstrom, B. and P. Milgrom (1994), ‘The firm as an incentive system’, American Economic Review, 84 (4), 972–91. Motta, M. and M. Polo (1997), ‘Concentration and public policies in the broadcasting industry: the future of television’, Economic Policy, 12 (25), 295–334. Peukert, C. (2018), ‘The next wave of digital technological change and the cultural industries’, Journal of Cultural Economics, 43 (2), 189–210. Potts, J. (2014), ‘New technologies and cultural consumption’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsterdam: North-Holland, pp. 215–31. Rochet, J. and J. Tirole (2006), ‘Two-sided markets: a progress report’, RAND Journal of Economics, 37 (3), 645–67. Salganik, M.J., P.S. Dodds and D.J. Watts (2006), ‘Experimental study of inequality and unpredictability in an artificial cultural market’, Science, 311 (5762), 854–6. Schiff, A. (2008), ‘The “waterbed” effect and price regulation’, Review of Network Economics, 7 (3), 393–414. Sutton, J. (1991), Sunk Costs and Market Structure: Price Competition, Advertising, and the Evolution of Concentration, Cambridge, MA: MIT Press. Sutton, J. (1996), ‘Technology and market structure’, European Economic Review, 40 (3), 511–30. Sutton, J. (1998), Technology and Market Structure, Cambridge, MA: MIT Press. Throsby, D. (2006), ‘Introduction and overview’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 3–22. Towse, R. (2010), A Textbook of Cultural Economics, Cambridge: Cambridge University Press. Towse, R. (2014), Advanced Introduction to Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Waldfogel, J. (2014), ‘Digitization, copyright and the flow of new music products’, in V. Ginsburgh and D.  Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsterdam: North-Holland, pp. 277–98.

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136  Handbook of cultural economics Waldfogel, J. (2017), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214.

FURTHER READING A general introduction to the theory of the costs of production is to be found in Towse (2010 and 2014). For a more specialized treatment of two-sided markets in the media market see Anderson and Gabszewicz (2006) and Ambrus et al. (2016). Production and cost functions for different cultural sectors are estimated in FernandezBlanco et al. (2019), Castiglione et al. (2018) and del Barrio et al. (2019). The impact of new technologies, including digitalization, on creative industries is analysed by Gil and Lampe (2014), Aguiar and Waldfogel (2018), Peukert (2018) and Waldfogel (2017).

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14.  Creative industries Ruth Towse

By the end of the twentieth century, the term creative industries had been adopted in the UK, whose 1998 Creative Industries Mapping Document (DCMS 1998) triggered a wider interest in the topic, while Richard Caves’ influential book, Creative Industries (Caves 2000), brought mainstream economics into the analysis of these industries. A decade later ‘creative industries’ had become an established concept in cultural economics, although ‘cultural and creative industries’ (CCI) is also widely used. ‘Creative industries’ seems to chime with the creative economy paradigm1 that has been adopted by many national governments and by international organizations, notably in the Creative Economy Report 2008, produced annually by a consortium of United Nations agencies (UNCTAD 2008, 2018). The list of creative industries which variously includes advertising, architecture, the art and antiques market, crafts, design, fashion, film, games, heritage services/­museums and libraries, Internet, publishing, software, television and radio, and video is not standardized, making it necessary to check the list for the purposes of the measurement of growth rates, international comparisons and so on. Another type of classification involves ordering the industries or part of their activities as core and peripheral, or based on the degree of creativity entailed in their output, or on the engagement with copyright. Whichever definition is adopted, the crucial point for economists is that there is no double-counting if data are to be used to indicate the relative size of the sector in national income. It matters not whether the industries are called cultural or creative (or both) as long as the industry classification of the activity is properly defined. A possibly more pressing problem is dealing with the increasing overlap in the production and consumption of digital goods and services, often confusing amateur and professional output, which is coordinated by multi-product and social media platforms, and other similar entities. The creative industries may be defined as consisting of firms that mass-produce or distribute goods and services with sufficient artistic content to be considered creative and culturally significant. The essential features are the combination of industrial-scale production with creative content. The creative content mostly results from work by trained artists, or ‘creators’ as they are now often known – creative artists, performers, craftspeople and designers – who may be self-employed freelancers or employees of firms in the creative industries. That is the first stage in the production of goods and services that are supplied to the market by both for-profit commercial enterprises and non-profit organizations. Mass production, however, is not routinely a feature of live performing arts or visual arts, and so the overlap between the creative industries and the cultural industries is not complete. Although digitization has had a huge impact on the mass distribution of creative goods, it will probably not erode the artisanal qualities of the creation of the basic content for some time to come, though there are signs of the use of artificial intelligence (AI) in their production. 137

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138  Handbook of cultural economics

COMMERCIALIZATION Commercial mass production was enabled by the development of technologies – printing, sound recording, photography, film, video, Internet and digitization – and the growth of the creative industries gathered force during the twentieth century. Reproduction techniques, such as printing and lithography, had existed for several centuries previously, but did not permit output on a mass international scale, as occurs today. The term cultural industry (in the singular) was first introduced by Adorno and Horkheimer (2002) to disparage low culture, which they believed necessarily resulted from repeated output, distinguishing it from high culture produced by true artists whom they believed would not repeat a work of art and who would have no truck with commercialization. The theme of the commercialization of art and culture dominated the literature on cultural industries that was written almost entirely by sociologists or political economists until the 1990s. By contrast, the contemporary notion of creative industries clearly includes both high and low culture, and makes no distinction between them on artistic grounds, which is in keeping with a world in which there is a great deal of cross-over activity on the part of both producers and consumers of cultural goods and services. Over the past 20 or so years, there has been a burst of interest by cultural economists in the creative industries, especially in television, film, books and music, in addition to a long-term interest in the economics of the arts and heritage; economists are also active in media economics and in the economics of copyright in these industries (Towse 2008). The shift in policy circles, though, is probably responsible for the now dominant view that the future generation of wealth and economic growth rely on creativity and the creative industries in the world of the creative economy. Instead of the view that it is wealth that drives creativity (held among others by John Maynard Keynes), that position is reversed and creativity is viewed as the engine of wealth creation. There is also concern in policy circles, though, that commercialization of culture via international trade in creative goods and services has led to globalization and homogeneity. For some, free trade needs to be curbed by interventionist policies to protect national cultures, while others welcome the effect of unregulated market forces on creativity and diversity. Cultural economics has accordingly been involved with the question of cultural diversity; Acheson and Maule (2006) review these arguments. Since then, the expansion of the digital creative economy has greatly extended the global reach of producers and access by many consumers, creating huge worldwide markets. The ‘long tail’ discussion about its facilitation of diversity remains unresolved, some arguing that there is greater concentration on superstars and fewer top products and others that the Internet has enabled niche products and less well-known artists to gain a viable share of the market. Without appearing to sit on the fence, it is possible to accept both scenarios: oligopolies have long tolerated the presence of smaller-scale outfits that do not threaten their market shares. Work by cultural economists on the creative industries can be classified as, on the one hand, the macroeconomic measurement of the economic contribution of the creative industries to national income of gross domestic product (GDP) and, on the other, as the application of microeconomic theory of production and supply to analyse their economic organization, in which concepts drawn from neoclassical theory of the firm, contract theory, transaction cost economics and, latterly, platform economics with its emphasis on multi-sided markets and network effects, are variously adopted.

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Creative industries  139

MEASURING THE CREATIVE INDUSTRIES Measurement requires clear, standardized itemization of products and industries. In the 1980s, when systematic collection of data on the arts began, the question arose which industries merited inclusion: should the low-culture commercial cultural industries in be distinguished from high-culture produced by non-profit organizations? The presence or absence of a state subsidy seemed a likely criterion. International comparisons, however, revealed that for-profit firms were in receipt of a subsidy for some purposes (for example, publishing contemporary music or poetry) and industries that were subsidized in one country were successful profit-making enterprises in another (for example, the press). Moreover, even if the cultural industries in a country do not receive a subsidy, they are often regulated either by copyright law or by specific cultural policy measures, such as those in the audio-visual sector. These arguments have been superseded by events with the development of the digital creative economy. More recently, standard international classification for measurement purposes has been developed, notably by the United Nations Educational, Scientific and Cultural Organization (UNESCO). This is not the place for a detailed discussion of the topic, for which see Goodridge (2013). There have been persistent problems with figures that have been produced for the size and growth of the creative industries. Early data in developed countries were gathered from a multitude of sources and measured in different ways (value-added, market size and turnover); in some cases, data were used from industry lead bodies or organizations with a grievance. These problems have not always been resolved in developing countries, in which some cultural activity may not be commercialized. Furthermore, the long-standing problem of distinguishing amateur and professional creators’ and performers’ content creation is exacerbated by the ease of disseminating work via the Internet. Data therefore may not be internally compatible or comparable across countries. In most developed countries in which the size of the creative industries sector has been measured, its contribution to GDP exceeds that of manufacturing (which is a declining sector), individual industries may also be higher than average exporters (film in the USA, music in the UK and publishing in the Netherlands), imports are rarely mentioned in either the academic or government literature and few apart from the USA are net exporters. In those countries where measurements have been taken over several years, the growth rate is higher than that of the whole economy. It is also believed that the creative industries offer good employment prospects, but the measurement of cultural employment and earnings in this sector is fraught with difficulties and these claims are hard to verify. It is worth stressing, however, that what is of more interest to cultural economists than size (and so-named economic importance is not an economic concept) is the organization and other economic features of the cultural industries.

ECONOMIC CHARACTERISTICS ‘Are the cultural industries different?’ is a question that has been very important in cultural economics. After all, if cultural industries or organizations are no different from those in the rest of the economy, why do we need a special field to study them? The same question

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140  Handbook of cultural economics applies to artists’ labour markets. A quick answer is that it is the economic characteristics of cultural content production that makes them different. This theme is developed in this section. The creative industries share features of other knowledge or information goods producers. The fixed cost of producing the original is high, whereas the marginal cost of making a copy is very low, even approaching zero – the classic characteristics of a natural monopoly – which justifies either subsidy or price regulation by the state. This feature has become even more marked with digitization, though governments have been loath to intervene in the digital market economy. Moreover, private enterprises (Google, Amazon, TenCent, and so on) have been extremely successful in these circumstances. In addition, it is generally held by cultural economists that the novel products of the creative industries are subject to radically uncertain reception by consumers, resulting in a high failure rate (ratio of financial successes to failures): the success of individual titles in the creative industries cannot be predicted from any specific characteristic, such as star participation or the amount of financial outlay. That adds to firms’ fixed or sunk costs and exacerbates barriers to entry owing to high initial capital requirements for production and global marketing. Barriers to entry also exist because products are protected by intellectual property law (patents, copyright, trademarks and design rights). Indeed, it seems likely that copyright encourages a tendency towards mergers in the creative industries (Bettig 1996 – a study that could well be updated).2 These characteristics offer at least a partial explanation for the observed concentration of ownership and control, which has greatly increased over the past few decades. Despite this, there is no shortage of new entrants to the creative industries or of novel creative output (Waldfogel 2018). In addition to economies of scale and scope, network effects are a central feature of the digital economy, enabling a few large corporations to dominate the production and/ or distribution to international markets of all types of cultural goods. Network effects are demand-side externalities associated especially with online consumption, whose benefits, unlike those associated with the arts that give rise to the case for public subsidy, can be captured commercially via online markets. The more people who buy the good or use the network, the greater the value to others using it, and the greater the value they derive from it and the higher their willingness to pay. Network effects operate both directly and indirectly – online gamers benefit from the participation of other gamers (a direct effect) as well as benefiting game developers (an indirect effect).

INDUSTRIAL ORGANIZATION Industrial organization is the field of economics that analyses the structure of firms, industries and markets, dealing with questions such as competition and price-setting. Caves (2000) applies this analysis to the creative industries, taking the stance that they differ from other industries in significant ways. It is useful to think of cultural production as consisting of two distinct aspects, content creation and its delivery; the former is the province of the artist and the latter of the businessman. Caves names this second element of the combination of art and commerce humdrum inputs – a memorable tag. Humdrum inputs constitute a substantial portion of the outlay of firms in the creative industries – think of the promotion costs of a film

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Creative industries  141 or bestseller book. These products have particular characteristics that lead Caves to an overarching analysis: they require sequential (often large) outlays of sunk capital on the humdrum side and considerable coordination of creative workers with different skills for content creation. At every stage in this entrepreneurial activity, contracts need to be made to enable delivery of the final output at a specific date (the opening). Owing to uncertainty (nobody knows) about the quality and novelty of creative input, however, contracts cannot stipulate fully all details or envisage all contingencies and therefore cannot provide optimal incentives to input suppliers. Contracts are therefore incomplete. Caves’ analysis of the creative industries has at its core organizational structures that overcome, or minimize, the potential losses of capital outlay to entrepreneurs in the whole production process, from content creation to delivery in the marketplace, in conditions of radical uncertainty. That is what determines the economic organization of markets in the creative industries. Moreover, the individual artist or creator of the creative content also faces uncertainty and is typically in a weak a bargaining position in contracting with the commercial entrepreneur over payments and the transfer of rights. According to Caves’ analysis, the simple handshake contract between a visual artist and his or her dealer is subject to the same economic problems as a lengthy written contract between all the different participants in a sound recording or movie production, the only difference being the complexity of the creation and delivery process and the sheer number of people and amount of money involved. The movie industry offers a particularly interesting case study because its structure was changed dramatically by the coincidence of a single institutional change, the anti-trust ruling of the United States v. Paramount Pictures, Inc. (334 U.S. 131 (1948)) case. The Paramount case destroyed the control movie producers had had over cinema. The Hollywood-studio system, in which artists were hired on a salary, with exclusive long-term contracts, broke down and was replaced by flexible specialization, the precursor to the current gig economy, in which content creators freelance on short-term contracts, thereby sharing risk with the creative industry entrepreneurs, who no longer have the incentive to invest in their training and development.

THE GATEKEEPER ROLE Caves (2000) also notes the important intermediary or market-making function of gate-keeping, a concept adopted from sociology. Gate-keeping is an interim process that takes place within the chain of production and, in effect, determines the nature of cultural supply. Firms in the creative industries perform the task of selecting which items to produce and market from an abundant supply of creative content and they therefore decide what cultural goods and services are offered to consumers; that is, which music or books are on offer or whether poetry is available at all. The desire to maximize profits and/or to ensure the long-run growth of the firm does not, however, have a neutral effect upon cultural production and that, in turn, affects cultural development. Thus, if record companies believe hip-hop or heavy-metal music will be commercially successful, they can influence youth culture. Alternatively, if publishers think their women readers only want to read love stories with happy endings, they commission works from authors producing those stories and do not publish others of greater literary merit or social significance,

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142  Handbook of cultural economics thereby perpetuating a particular female stereotype. Firms in the creative industries, whether for profit or non-profit organizations, act as filters or mediate between artists and the consuming public, a role that has implications for cultural policy. The gatekeeper role has also become an aspect of Internet social media postings, ratings and so on, which influence people’s choices by providing professional and layperson information and opinion which may not be in harmony with the choices made by the creative industries. Indeed, gate-keeping may be considered an industry in its own right.

COPYRIGHT AND CREATIVE INDUSTRIES A principle that has been adopted for unifying the creative industries is their relationship with copyright law to protect the creative or cultural content, that is, the underlying intellectual property. Thus, industries protected by copyright have become virtually synonymous with the creative industries, and they have been measured in those terms for their contribution to GDP in a number of countries by the World Intellectual Property Organization’s Guide on Surveying the Economic Contribution of the Copyright-Based Industries (WIPO 2003, 2015) which classifies activities and ranks them based on their dependence on copyright. The production of cultural content is the core copyright activity and the classification fans out to those activities concerned with its distribution as being more or less dependent upon copyright. The WIPO is not the only United Nations agency that brackets together copyright and creative industries, though (UNCTAD 2008, 2018); many national policy documents and those of the European Union do the same – some going further with the claim that copyright is essential for creativity itself. It is easy therefore to believe that there is a causal relation between the two, and that copyright is the driver of the creative industries and therefore of the creative economy. There is no economic evidence to date, however, of the responsiveness of cultural production to changes in copyright, for instance, that strengthening copyright increases creative output, a claim that is frequently made by creative industry lobbyists. Even the economic effects of unauthorized copying (piracy) on production have proved difficult to evaluate (Waldfogel 2018). The economic case for copyright is that without statutory property rights for authors and publishers, the production and dissemination of new works would be less than the socially desirable level. It evokes the public-goods characteristics of information and knowledge that imply under-investment in them for the reason that, without the ability to control their use, sufficient revenues from their sale cannot be appropriated to make it worthwhile to produce them. So, copyright is an institutional solution to the financing of cultural production via market forces: by being able to control the rights to a work in copyright, the rights holder can set a price for a copy that is above the marginal cost of producing it and that provides extra revenue that can be used to finance the initial outlay on the creation of the work – the economic incentive that copyright law offers. Copyright has costs and benefits, however, and overly strong copyright protection of one generation of authors and publishers imposes higher costs on the next generation owing to search costs of obtaining permissions and the charges that copyright owners may impose for subsequent use (such as a translation or musical arrangement). The economics of copyright tells us that costs and benefits must be balanced in order to find the optimal strength of

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Creative industries  143 copyright, meaning its term, scope and degree of enforcement, but that is very difficult to calculate, especially as technological development is altering them all the time. The law always lags behind technical change, and change risks being out of date or irrelevant; new rights have had to be introduced to deal with digital material and satellite distribution, for instance. Markets can adapt more quickly, and policy-makers often take the view that the law should be technologically neutral in order not to impede technological progress. Digitization has presented interesting questions for the economics of copyright. Some economists have seen it as just another technological change that can be accommodated by copyright law, as happened with photocopying, sound recording and radio, which in turn fundamentally affected the production and consumption of cultural goods and services. Different entrepreneurs benefit and those well established in a business are often slow to adapt and lose out, but that is the price of innovation – the Schumpeterian concept of creative destruction. Adapting is not just a matter of producing goods in a different way, but of adopting new business models. Advertiser-based free distribution is a viable way of financing the delivery of creative goods and services, but has caused problems for contracting with and paying the creators who have individual rights. Some economists have argued that business models alone can provide sufficient incentive to the creation of new works and the production of cultural products, and that copyright is not necessary; some legal scholars seek to change the whole tenor of individual copyright for the digital economy. Meanwhile, copyright law continues to be strengthened and adapted to new developments.

CONCLUSION The creative industries paradigm has been a very successful rhetorical device for the promotion of this sector, though it has had a mixed reception: cultural analysts have objected to the economic slant on cultural production, while economists ask themselves what difference it makes to measurement in national income accounts and the industrial organization. Caves’ analysis demonstrated that the term has meaning in respect of the economic structure of the producers in these industries (although his institutional material risks being outdated by the onset of digitization and Internet delivery, and he had little to say about the role of copyright). Technological change is ongoing and this chapter is likely to be out of date fairly soon after it was written; for instance, the prospect of AI is already on the horizon, with profound changes to the concept of authorship and to authors’ rights and copyright.

NOTES 1. In this context ‘paradigm’ means the notion of a shift in the way of thinking about the arts and cultural production. An example from the institutional viewpoint is the development in the UK of the the Creative Industries Council (CIC) (www.gov.uk/government/groups/creative-industries-council). However, I would also argue there has been a paradigm shift in economics with the development of platform economics. 2. Related to this is the much larger topic of the measurement of copyright and other intellectual property as intangible assets. The digital economy has given rise to the question of how appropriate national income accounting is given the obvious long-term value of intangibles (see Goodridge 2013).

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SEE ALSO: Chapter 4: Artificial intelligence; Chapter 9: Business models; Chapter 12: Copyright; Chapter 15: Creativity; Chapter 21: Cultural entrepreneurship; Chapter 26: Digitization in the cultural industries; Chapter 28: Event cinema; Chapter 57: Video game industry.

REFERENCES Acheson, K. and Maule, C. (2006), ‘Culture in international trade’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1141–82. Adorno, T. and M. Horkheimer (2002), Dialectic of Enlightenment, Stanford, CA: Stanford University Press. Bettig, R. (1996), Copyrighting Culture: The Political Economy of Intellectual Property, Boulder, CO: Westview Press. Caves, R. (2000), Economics of the Creative Industries, Cambridge, MA: Harvard University Press. Department of Culture, Media and Sport (DCMS) (1998), Creative Industries Mapping Document, London: DCMS, accessed 14 November 2019 at www.gov.uk/government/publications/creative-industries-mappingdocuments​-1998. Goodridge, P. (2013), ‘Measuring the creative economy’, in R. Towse and C. Handke (eds), Handbook on the Digital Creative Economy, Cheltenham, UK and Northampton, MA, USA, Edward Elgar, pp. 162–77. Towse, R. (2008), ‘Why has cultural economics ignored copyright?’, Journal of Cultural Economics, 32 (4), 243–59. Towse, R. (2019), A Textbook of Cultural Economics, 2nd edn, Cambridge: Cambridge University Press. United Nations Conference on Trade and Development (UNCTAD) (2008), Creative Economy Report 2008, Geneva: UNCTAD. United Nations Conference on Trade and Development (UNCTAD) (2018), Creative Economy Outlook, Geneva: UNCTAD, accessed 14 November 2019 at https://unctad.org/en/PublicationsLibrary/ditcted2018d3_en.pdf. Waldfogel, J. (2018), Digital Renaissance, Princeton, NJ and Oxford: Princeton University Press. World Intellectual Property Organization (WIPO) (2003), Guide on Surveying the Economic Contribution of the Copyright-Based Industries, Geneva: WIPO. World Intellectual Property Organization (WIPO) (2015), Guide on Surveying the Economic Contribution of the Copyright-Based Industries, Geneva: WIPO, accessed 14 November 2019 at www.wipo.int/edocs/pubdocs/en/ copyright/893/wipo_pub_893.pdf.

FURTHER READING Caves’ book should be required reading for anyone interested in the economics of creative industries. I recommend the UNCTAD (2008) Creative Economy Report as a non-specialist summary of the subject; the 2018 version provides a great deal of country by country data on creative industries and international trade. Acheson and Maule (2006) deal particularly well with international trade and its wider implications for cultural development. Waldfogel (2018) is an accessible book on what ‘data and economics tell us about the future of popular culture’ to quote the sub-title. Towse (2019) is a textbook treatment of most of these issues, while many chapters in this Handbook of Cultural Economics offer more expert detail and analysis than is to be found there.

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15.  Creativity

Karol Jan Borowiecki

Creativity is of fundamental value to common thinking about the arts and culture. The concept of creativity seems to be at the very least a hallmark or a characteristic feature of art generally, if not a necessary condition of artistic practice. Nowadays routinely invoked as having not only cultural, but also economic value, creativity is greatly desired in the context of the creative industries. It is also, however, an elusive concept for economists, as measurement of creativity is extremely difficult, while outstanding creativity is often recognized years or even decades after the creation of an artwork. Therefore, the attempts thus far to develop an economic analysis of creativity are limited, and their number does not reflect the importance of creativity in cultural economics per se. More generally, the interest in creativity – and the value assigned to it – is a recent phenomenon. Creativity was not priced highly on labour markets throughout most of history. In the past, employers have valued disciplined, diligent and hard-working, as opposed to creative, workers. However, this has vastly changed in recent years, with a surge of interest in creativity: firms want creative workers, policy-makers hope for creative societies, people wish for creative cities, and perhaps even journal editors expect creative research. Creativity has been traditionally a domain of interdisciplinary scholarship and has received a particular focus in psychology, but also in education, philosophy, sociology, business studies, art history, musicology, and so on. In a summary of these interdisciplinary studies into creativity, Mumford (2003, p. 110) suggests a definition of creativity as the ‘production of novel, useful products’. Creativity may be thus seen as a phenomenon whereby something new and in some way valuable is formulated, which makes it applic­ able to the context of the arts and culture. It is, however, beyond the scope of this chapter to pay more attention to the important work done in the many interdisciplinary domains. Instead, the chapter considers primarily creativity scholarship conducted within economics with the aim of providing an introduction to the subfield, including suggestions for future reading for those interested in pursuing cultural economics of creativity. This chapter is divided into two sections. The first focuses on the individual artist and presents attempts to disclose the motivation for individual creativity and, especially, whether it is amenable to economic incentives. Related to this is the literature on artists’ labour markets, which has thrown light on artists’ supply decisions as regards their time allocation to creative and other income-earning work. The second section presents a range of studies dealing with permutations of the following important question: is it possible to understand what enhances creative output and how to encourage it? Much of this work aims to illuminate how creativity develops. In particular, the most recent contributions have looked at how creativity can be induced by an increased demand for innovation, whether the institutions of copyrights and property rights can foster creativity, and how specific extraordinary individuals make their discoveries and produce creative output owing to peer effects or emotional factors. 145

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THE ARTIST Artist’s Motivation Creativity involves a dive into the unknown. It is therefore interesting to think about what motivates people to undertake creative ventures. In his book Not Just for the Money, Frey (1997) makes the distinction between intrinsic motivation, whereby a person does something from inner conviction, such as artistic drive or social conscience, and extrinsic motivation when people respond to outside stimuli; he also makes the distinction between intrinsic reward, such as recognition or satisfaction, and extrinsic reward, for example, payment or promotion. Frey’s contribution is his crowding theory (Frey 1997). Crowding-out takes place when intrinsically motivated people are given extrinsic rewards, such as monetary payment. This has the unintended consequence whereby that which is supposed to act as an incentive acts instead as a disincentive or could even elicit the opposite response. Expressed as a moral hazard problem, the classic example of an unwanted response is that paying blood donors encourages people such as drug addicts to sell blood while crowding out the gift of it that would be made by intrinsically motivated and healthier people. Frey (2000) applies crowding-out to personal creativity, suggesting that extrinsic motivation leads to an increase in quantity of lower-quality works of art. He also discusses the opposite possibility, crowding-in, whereby intrinsic motivation can be fostered by extrinsic reward if this is presented in a way that is acceptable to artists. One way is to give unconditional grants; another is to let expert panels consisting of peers decide how to distribute the money. The main point Frey makes is that institutional arrangements matter in offering a stimulus to creativity. A different approach is undertaken by Prendergast (2018), who explores creativity through the lens of dynamic agency theory. The quality of the creative output depends on the interaction between the creator’s effort and her creative ambition. On the one hand, more creative projects have higher returns and, so, naturally induce more effort. On the other, there is an offsetting incentive in that, if success is not achieved, it becomes more difficult to evaluate the cost of the efforts provided. This adversely influences the incentive to provide effort and the circumstances under which the observed trade-off arises is described by the model. Prendergast’s setting also enables further insights; for example, the dynamics of creative discovery where major breakthroughs are shown to be followed by periods of less-important innovations, and this cycle continues steadily over time. Creativity and Artists’ Labour Market Behaviour The other area of research in cultural economics that throws light on creativity by individual creators is that on artists’ labour markets. The results of this research can be related to intrinsic motivation as they show that maximising pecuniary reward is by far not what is sought by creators and performers. Literature going back to the 1980s recognises the non-pecuniary psychic reward of artists, and even measures the value of the opportunity cost of working as an artist by comparing artists’ alternative earnings with those of other workers with equivalent education and years of experience. In Economics and Culture, Throsby devotes a chapter to the economics of creativity, for the most part considering whether the creative process is capable of being interpreted

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Creativity  147 in rational decision-making (Throsby 2001). He has tested models of artists’ economic decisions about their allocation of labour time to working in the arts, where the decision is cast in terms of how much time to allocate between arts and non-arts work, using data from his surveys of artists’ labour markets in Australia. Allocating time to working in their chosen artistic occupation is subject to the constraints of the need to earn sufficient income for the household, not as the loss of leisure time as it is perceived in ordinary labour economics – hence Throsby’s term, ‘work preference’ model. He finds that when rates of pay rise, creators spend more time on their preferred creative work. This and other work on artists’ labour markets is reviewed in Alper and Wassall (2006). In later work, Throsby (2006) models the artist’s decision to devote effort to commercial rather than creative work, viewing creative art work as intrinsically satisfying and commercial work as extrinsically rewarding using a production function instead of a work preference model. Bryant and Throsby (2006) extend the production function by introducing an index of creativity or talent to explain artists’ decisions to supply commercial rather than creative work. That trade-off is also to be found in Cowen and Tabarrok (2000), who consider the artist’s decision from among pursuing aesthetic satisfaction, the desire for fame and the need for income from market sales. Cellini and Cuccia (2003) approach the question as a repeated game between a private for-profit financier and an artist choosing between experimental and conservative work, in which the artist learns to adapt the extent of his or her creativity to the expectation of obtaining finance. An inescapable and universal conclusion of studies of artists’ labour markets is that there is excess supply of artistic labour even at low rates of pay. This ties in with Frey’s analysis of artistic motivation – art for art’s sake is unconcerned with financial gain – and it has been associated with a very high elasticity of supply as regards subsidised training of artists, and even with grants and other financial support for artists – unintended consequences of policies designed to support artists.1 This uncomfortable reality underlies many of the problems that artists and other primary creators experience in bargaining for rates of payment, particularly as individuals but in collectively bargained situations as well. Another uncomfortable reality is that studies of artists’ earnings repeatedly show that the length of training and experience have no influence on earnings from creative work (though they do for non-arts work). It has to be concluded, therefore, that individual creativity cannot be increased by investment in training, despite the frequent but unsubstantiated claims made for it (Towse 2006b). This sub-section has summarised the work that has been undertaken specifically on the economic aspects of the motivation of individuals to create and it shows that economic factors play a role in influencing the creator’s decision about how creative they choose to be. The underlying model is that of utility maximisation of inner satisfaction with a budget constraint that consists of extrinsic reward and crowded-in financial payments. This is in contrast to the motivation of firms in the creative industries: assumed to be profit maximisation in for-profit enterprises and a mixture of motives (revenue maximisation, reaching new audiences, and so on) for non-profit organisations. Furthermore, research on artists’ labour markets models the use of time whose value is measured in earnings, while the measure for firms is the value and quantity of output. Finally, research has concentrated on earnings from sales of work, fees and wages but, recently, there has been additional interest in earnings from copyright royalties and other remuneration from the use of copyright works. As might be expected from other research on artists’ earnings,

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148  Handbook of cultural economics the distribution of income from royalties is greatly skewed – those of the superstars are high and the majority’s royalties are trivial.2

ENHANCING CREATIVITY Demand for Innovation Following standard economic theory, many scholars use prices to approximate the value of goods and services, and this includes artistic output. Within visual arts, this can be achieved with past results from art auctions and under the assumption that market prices reflect the true creative value of a painting. In a landmark article (Galenson and Weinberg 2001) and then in the book, Old Masters and Young Geniuses (Galenson 2007), auction prices are used as a proxy for the quality of an artwork. Focusing on nineteenth-century French artists, Galenson and Weinberg (2001) suggest a significant shift in demand for innovation in art. The authors explore how an artist’s quality of artworks changed over her lifetime and show that the peak age occurred much earlier for later cohorts, who were exposed to increased demand for innovation. These demand changes have radically influenced the careers of successful practitioners and stimulated the emergence of outstanding artworks. It was therefore not by chance that Paul Cezanne and Pablo Picasso, although born more than 40 years apart, created their most significant works within a period of less than one year. Apart from market conditions in a given time and place, other political and policy factors can have an important effect on artistic creativity. Vaubel (2005) approaches the hypothesis that competition among neighbouring states, who demand musical composition and performance, may favour cultural innovation. This hypothesis is then backed up with the empirical observations that European instrumental music had its breakthrough during the Baroque era and that the most famous composers came from the two countries characterized by the highest degree of political fragmentation: Italy and Germany. Vaubel suggests then to measure the average duration of employment as a proxy for competition on the demand side and shows that famous Italian and German composers of the Baroque period changed their employers significantly more often than their French and British counterparts did. These insights suggest not only that political fragmentation and the corresponding higher demand has promoted musical composition and encouraged quality, but also that they have stimulated mobility of composers. Creativity and Copyright Creativity is frequently evoked in the debates about copyright that have taken place over the past century; claims that strengthening copyright increases creativity are frequently made nowadays by lobby groups and also by policy-makers. Copyright law, however, makes no mention of creativity nor is really concerned with it. In economic terms, copyright is supposed to finance creativity by providing an incentive to the creation and dissemination of literary and artistic works. By granting statutory property rights to creators that make it illegal to copy someone’s copyright works without their permission, authors are able to control and charge for the use of their work. Without these rights,

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Creativity  149 creative works that are non-rival and non-exclusive (which is the case with all digital works and many others) would become public goods. Copyright finances the creation of works of art by charging users for the use they make of those works; the more popular the work, and the higher the price, the greater the income it generates for the copyright holders. Thus the economic rationale for copyright is that it provides an incentive for the creation of works of art, literature, music, drama and so on, financed via the market. Copyright, or authors’ rights as they are in many countries, applies only to authors of original works. Therefore, performers do not have copyright proper but rights related to copyright or neighbouring rights which allow them, for example, to control recording of live performances, and they have rights to remuneration for the use of their work, which are typically administered by copyright collecting societies or rights management organisations.3 Where a copyrightable work is created in the course of employment, the employer, and not the employee, is considered the creator and therefore the copyright attaches to the employer rather than to the person(s) who took part in creating it. This is known as a work made for hire in US copyright law. The incentive to the creator or the performer is, however, mediated through two channels: first, the creative content is typically combined with a medium of delivery and with the creative work of others to form a good or service as a product for the market; and secondly, this process is undertaken by an enterprise that requires the transfer of rights conferred by copyright in exchange for a contract for royalties. Since copyright is an individual right and individual creators generally have low bargaining power with firms in the creative industries, as Caves (2000) amply demonstrates, it is not hard to conclude that copyright in practice has a limited impact on creativity by individual creators and is more valuable to creative industries. Many scholars have examined how copyright protection over time and across countries and regions has created different creative environments. Ruth Towse has contributed widely to this research strand and has improved our understanding of the effects of copyright protection on a variety of creative industries (Towse 2001) and conflicts between artists and intermediaries over ownership of intellectual property. Towse’s work deals primarily with contemporary policy and economic conditions. More historical in her focus, Petra Moser has researched about the effects of copyright and patent protection across a variety of industries, geographies and eras (for example, Moser 2011, 2013). Recently, she has worked with artistic data, specifically about book publishing in the UK in the nineteenth century (Li et al. 2018) and the effect of Napoleonic rule on Italian operas (Giorcelli and Moser 2016), to examine the effects of copyright on innovation. Giorcelli and Moser exploit variation in the adoption of copyrights, owing to the timing of Napoleon’s military victories in Italy. The authors are therefore able to estimate the causal effects of copyrights on creativity, and find that basic levels of copyright protection increased not only the quantity of the creative output, but also its quality. Peer Effects and Geographic Clustering Turning next to geographic factors, Hellmanzik (2010) has observed that famous visual artists have been shown to exhibit remarkable clustering patterns. This observation motivated her study on the existence of location premiums by exploiting a sample of prominent modern artists born between 1850 and 1945. She combines auction data with

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150  Handbook of cultural economics records on whether the artist has worked in Paris or New York, that is, in one of the two main cluster locations of that period. The findings suggest that paintings created in Paris or New York have been valued higher by 11 per cent or 43 per cent, respectively. Furthermore, the artists working in one of these two cluster locations are shown to reach a peak in the age–price profile of their work significantly earlier than artists working elsewhere. Comparable findings are disclosed by Mitchell (2016) for literary artists. Mitchell shows that an author becomes more creative and produces around 11 per cent more significant works each year when residing in London. When exploring the causal effects of clustering, it must be asked whether geographic clusters attract the most creative artists or whether artists who cluster are more productive because of positive externalities associated with cluster locations. That is, is self-selection determining the empirical evidence on superior performance in geographic clusters, or does a clustering benefit exist? This question – and escaping the endogeneity problems faced in answering it – is of considerable policy importance not only for the arts, but also for other sectors (see Rosenthal and Strange 2004). Attempts at answering this question have been made by Borowiecki (2013), who uses data for a global sample of 116 prominent music composers born between 1750 and 1899. The historical approach enables him to exploit the variation in the geographic distance between a composer’s birthplace and a geographic cluster as an exogenous source of clustering, and thus to assert that the association between clustering and productivity is a causal relationship instead of simply a correlation. Borowiecki’s results suggest that geographic clustering raises creativity: composers were creating around one additional influential work every three years they spent in a cluster. Exploring in more depth the dynamics of important artistic clusters provides some indication as to how clusters may stimulate higher-quality artistic produce. Borowiecki (2015a) proposes a simple theoretical framework explaining the trade-off between agglomeration economies (peer effects) and diseconomies (peer crowding), which implies that the productivity gain associated with the presence of peers is characterized by an inverted U-shaped relationship and eventually decreases if the peer-group size becomes very large. These theoretical predictions are supported by data for music composers. Borowiecki discloses that there exists a sizable and causal impact of peer-group size on the number of important compositions written in a given year: a composer was about 10 per cent more productive when an additional prominent composer was located in the same city. However, the effect is non-linear and may begin to decrease for very large numbers of peers. Economists and economic historians have increasingly established that some historical events may continue to play a role in contemporaneous settings. In an attempt specific to artistic creativity, Borowiecki (2015b) sets out to understand the persistence of support for the arts and demand for cultural and creative goods in some cities in Italy. He finds that cities and provinces that had high levels of cultural activity in the past – measured by the number of active composers in the area during past eras – continue currently to have more concerts and operas performed, and residents spend relatively more money on high-culture activities than on other entertainment, such as sporting events. Demand for and support of the arts, once established in a given city, appears to persist even over centuries, and may raise the question of how effectively in these settings is contemporary policy stimulating creativity.

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Creativity  151 Emotional Factors Beyond market forces, and political or geographic considerations, there is an emerging interdisciplinary literature that explores how biological factors drive artistic creativity. Scholars since Aristotle have hypothesised that creativity and emotional state are connected. Other disciplines – notably psychology literature – has probed this link, together with the apparent correlation between famous creative people and psychiatric disorders such as depression and bipolar disorder.4 Cultural economists have recently engaged with this literature by looking at the letters of famous artists and seeing how their stated emotional state correlates with their creative output. Borowiecki (2018), for example, uses textual analysis to measure the extent of positive and negative emotions expressed in a large number of letters written by Wolfgang Amadeus Mozart, Ludwig van Beethoven and Franz Liszt. This allows him to construct well-being indices denoting emotional states throughout each composer’s lifetime. Borowiecki then shows that negative emotions have a causal impact that leads to increased creativity, as measured by the number of highquality compositions written.

CONCLUSION This chapter has briefly reviewed the literature in cultural economics that show how economists have approached the question of creativity. They deal in different ways with incentives to creators to create works of art of all types and suggest, in the language of Frey, that the institutional arrangements by which intrinsic and extrinsic rewards reach creators are central to creativity. The emphasis that is placed on stimulating creativity for reasons of economic growth in the context of the creative industries, creative clusters and so on needs therefore to consider how much can be achieved by market forces or economic policies, including copyright law, and how much is predetermined by geographic and historic factors. There is also an open question as to whether it is quantity or quality of creative output that is the objective. What is clear is that there is a great deal of work to be done on this topic which is fundamental to many aspects of cultural economics.

NOTES 1. 2. 3. 4.

See Abbing (2002) and Towse (2001). See the Chapter 54, ‘Superstars’, in this volume. See Towse (2006a) for more details. See review of this literature in Simonton (2014).

SEE ALSO: Chapter 5: Artists’ labour markets; Chapter 12: Copyright; Chapter 19: Cultural districts.

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REFERENCES Abbing, H. (2002), Why are Artists Poor? The Exceptional Economy of the Arts, Amsterdam: Amsterdam University Press. Alper, N. and G. Wassall (2006), ‘Artists’ careers and their labour markets’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 815–64. Borowiecki, K.J. (2013), ‘Geographic clustering and productivity: an instrumental variable approach for classical composers’, Journal of Urban Economics, 73 (1), 94–110. Borowiecki, K.J. (2015a), ‘Agglomeration economies in classical music’, Papers in Regional Science, 94 (3), 443–68. Borowiecki, K.J. (2015b), ‘Historical origins of cultural supply in Italy’, Oxford Economic Papers, 67 (3), 781–805. Borowiecki, K.J. (2018), ‘How are you, my dearest Mozart? Well-being and creativity of three famous composers based on their letters’, Review of Economics and Statistics, 99 (4), 591–605. Borowiecki, K.J. and D. Greenwald (2019), ‘Arts and culture’, in C. Diebolt and M. Haupert (eds), Handbook of Cliometrics, Heidelberg: Springer. Bryant, W. and D. Throsby (2006), ‘Creativity and the behaviour of artists’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 507–28. Caves, Richard (2000), Creative Industries. Contracts Between Art and Commerce. Cambridge, MA: Harvard University Press. Cellini, R. and T. Cuccia (2003), ‘Incomplete information and experimentation in the arts: a game theory approach’, Economia Politica, 20 (January), 21–34. Cowen, T. and A. Tabarrok (2000), ‘An economic theory of avant-garde and popular art, or high and low culture’, Southern Economic Journal, 67 (2), 232–53. Frey, B.S. (1997), Not Just for the Money, Cheltenham, UK and Lyme, NH, USA: Edward Elgar. Frey, B.S. (2000), Arts and Economics, Heidelberg: Springer. Galenson, D.W. (2007), Old Masters and Young Geniuses: The Two Life Cycles of Artistic Creativity, Princeton, NJ: Princeton University Press. Galenson, D.W. and B.A. Weinberg (2001), ‘Creating modern art: the changing careers of painters in France from Impressionism to Cubism’, American Economic Review, 91 (4), 1063–71. Giorcelli, M. and P. Moser (2016), ‘Copyright and creativity: evidence from Italian operas’, SSRN working paper, Social Science Research Network, accessed 5 December 2019 at https://papers.ssrn.com/sol3/papers. cfm?abstract_id=2505776. Hellmanzik, C. (2010), ‘Location matters: estimating cluster premiums for prominent modern artists’, European Economic Review, 54 (2), 99–218. Li, X., M. MacGarvie and P. Moser (2018), ‘Dead poets’ property – how does copyright influence price?’, RAND Journal of Economics, 49 (1), 181–205, doi:10.1111/1756-2171.12223. Mitchell, S. (2016), ‘Essays on synergies from the geographic clustering of literary artists’, PhD thesis, Trinity College Dublin. Moser, P. (2011), ‘Do patents weaken the localization of innovations? Evidence from world’s fairs’, Journal of Economic History, 71 (2), 363–82. Moser, P. (2013), ‘Patents and innovation: evidence from economic history’, Journal of Economic Perspectives, 27 (1), 23–44. Mumford, M.D. (2003), ‘Where have we been, where are we going? Taking stock in creativity research’, Creativity Research Journal, 15 (2–3), 107–20, doi:10.1080/10400419.2003.9651403. Prendergast, C.J. (2018), ‘Creative professions’, working paper, University of Chicago Booth School of Business, 16 April. Rosenthal, S.S., and W.C. Strange (2004), ‘Evidence on the nature and sources of agglomeration economies’, in J.V. Henderson and J.-F. Thisse (eds), Handbook of Regional and Urban Economics, vol. 4, Amsterdam: Elsevier, pp. 2119–71. Simonton, D.K. (2014), ‘The mad-genius paradox: can creative people be more mentally healthy but highly creative people more mentally ill?’, Perspectives on Psychological Science, 9 (5), 470–80. Throsby, D. (2001), Economics and Culture, Cambridge: Cambridge University Press. Throsby, D. (2006), ‘An artistic production function: theory and an application to Australian visual artists’, Journal of Cultural Economics, 30 (1), 1–14. Towse, R. (2001), Creativity, Incentive and Reward, Cheltenham UK and Northampton, MA, USA: Edward Elgar. Towse, R. (2006a), ‘Copyright and artists: a view from cultural economics’, Journal of Economic Surveys, 20 (4), 567–85.

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Creativity  153 Towse, R. (2006b), ‘Human capital and artists’ labour markets’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 867–94. Vaubel, R. (2005), ‘The role of competition in the rise of Baroque and Renaissance music’, Journal of Cultural Economics, 29 (4), 277–97.

FURTHER READING Chapter 8 in Bruno Frey’s collection Arts and Economics (2000) is a good introduction to his crowding theory applied to the motivation of creativity. Chapter 6 in David Throsby’s (2001) Economics and Culture clearly lays out his viewpoint on creativity in the context of artists’ labour markets and my survey (Towse 2006b) covers the economic literature on copyright and artists. Much of the analysis of artists’ supply behaviour is based on the human capital paradigm in labour economics that is relevant to the question whether creativity can be invested in through arts training courses; this is surveyed in Towse (2006b). The economic history of the arts and artistic creativity is overviewed in more depth in the chapter ‘Arts and culture’ by Karol Jan Borowiecki and Diana Greenwald (2019) in the Handbook of Cliometrics (Claude Diebolt and Michael Haupert, eds).

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16.  Criticism

Samuel Cameron

The production and consumption of criticism is an enduring feature of culture. This does not necessarily mean that it is economically important. As is hinted at in the title of Dhar and Chang (2009), it may simply be a form of cheap talk. Many current studies of its impact are motivated by the disruptive force of digital technologies. Again, this does not prove criticism is actually important, as it may still just be changing the landscape of a trivial phenomenon. Criticism might be culturally important in and of itself. For example, some people may have enjoyed noted film critics such as Paulie Kael or Siskel and Ebert more than the majority of films they have watched. Its more direct economic importance may be demonstrated in impact which is usually on demand volume rather than pricing, although there have been attempts in the art field to use critical views as an index of value via hedonic regression equations (Olckers et al. 2015). The direct effect on demand may have an indirect avenue of operation through consumer access – for example, in the case of films they may stay on screens longer if well received (Souza et al. 2019) and books may be more readily available for purchase in the same circumstance. As regards welfare economics, criticism may be important for its capacity to increase social welfare. However, this aspect of the problem is largely neglected in most work as it tends to be empirical. Many studies have examined the impact of criticism on traditional cultural matters such as ticket sales for live performances, for movie exhibitions, and so on. Currently, there is an explosion in this general area in the number of studies and breadth of study area owing to the disruptive digital innovations. These studies tend to explore the obvious hypothesis that good results from criticism lead to increased sales using publicly available data often from Internet sources (for example, Clement et al. 2007; Gemser et al. 2007; Hennig-Thurau et al. 2012; Wallentin 2016; Souza et al. 2019). Generally across music, video games, movies, books and so on it is found that favourable information drives sales, although there will always be exceptions to this, as in popular music, where artists such as the Go-Betweens had a relentless flow of praise in mainstream information sources but still no meaningful economic success. This anecdotal case refers to the impact of influence by individual critics in leading outlets for the dissemination of criticism. A great deal of recent research concerns the impact of aggregated critical information, often from non-specialist or citizen critics. It is worth noting that the IMDb database distinguishes between professional and user reviews. One of the key problems with aggregated non-expert information is its possible high noise content (information that does not add value). We could resort to selective aggregation to overcome this, as Internet sources do. Historically, prizes and awards emerged to serve this function. Hence the many studies of the impact of Oscars on film success may be deemed to demonstrate the influence of critics and, for live-events studies such as Boyle and Chiou (2009), show that the Tony Awards (formed from the opinions of 700 critics) have a statistically significant positive impact on New York’s Broadway theatre. 154

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Criticism  155 So far we have assumed that it is obvious what criticism is. We need to clarify the definition of criticism. In economic terms, it involves provision of information for complex goods which involve risk for the consumer. Therefore it may be welfare-enhancing by reducing risk, especially via any public good properties. The criticism may be consumed prior to the consumer choosing in order to help him or her make that choice, but it may also be consumed afterwards for several reasons. It may also influence decisions to repeat consumption, such as go to the same live event more than once. The simplest theoretical approach is to assume that all people have identical tastes but knowledge of products is limited and costly to acquire especially in the culture sector owing to the uniqueness of many products. The principal–agent model is the relevant tool for this topic. Specialized critics1 are agents who consume plays, soap operas, music, films and books on behalf of the principals in order to try them out. Specialization might bring benefits from scale economies in studying the genre of work, although it could be argued that producer cum critics are superior as they bring more understanding of the creative process to bear. Nevertheless, if markets were efficient, consumers would be able to identify critics whose tastes were similar to their own or different, in a stable way, in a manner which could be reliably mapped to their own preferences. The critic may also operate as the voice of the consumer, which can be welfare-enhancing as many consumers are locked in by loyalty. If the creator changed their style, it might still lead to purchases by loyal consumers, hence there would be no indication of exit until disappointment began to affect future products. There have been some ad hoc empirical studies of the principal–agent nexus, such as the paper by Wallentin (2016) which uses Swedish data to look at differences between cinema audiences and cinema critics. Historically, in the pre-digital era, criticism has been jointly supplied with other items in a newspaper or magazine, that is, it is supplied at zero marginal production cost to the consumer. The full-time critic or professional thus seems to operate in a type of labour market. We note here a distinct difference between cultural economics and sports economics. In the latter, critics (known as pundits) are generally retired practitioners, given that retirement is forced by physical decline, who can acquire very significant fame and income relative to even the best-known cultural critics. Full-time cultural critics tend not to be retired practitioners. It may seem that digital disruption has severely undermined the traditional status and function of newspaper and magazine print journalism (which was carried over into television criticism and reviewing). However, traditional print journalism outlets have managed to develop a business model for online dissemination which still allows a substantial role for critics. In addition, digital platforms have seen the rise of significant non-print magazine coverage of culture on websites such as The Quietus, despite the existing volume of blog and free-for-all review site material. This signifies the need to overcome the noise problem in the signal from the free-for-all sources. The attempted solution is to embed reputation capital in the information signal from the critical content.

BIAS AND QUALITY The noise problem becomes greater with complexity of products, which for cultural goods raises the problematic notion of quality. The history of criticism is connected with notions

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156  Handbook of cultural economics of quality, which are in danger of subjectivism, therefore we may get a noise-induced market failure where bias can lead to provision of too high or too low quality. Given the traditional bourgeois tone of cultural economics, the focus has typically been on the latter problem, as in Frank (2008). These problems occur even when tastes are regarded as static and fixed. Critics have a potentially important role in taste formation in a dynamic context. We might argue that critics have been the guardians of values: in 1777, a writer believed to be Nicolas Etienne Framery wrote: Music, painting, all the arts which depend on taste are everywhere subject to the errors of ignorance, to the blind whims of the masses, and, what is worse, to the false judgments of those would-be amateurs, who, without truly liking the arts or ever having cultivated them, join a party, pass judgment without knowledge, speak without understanding, applaud with a yawn, and thrive on destroying performer’s reputations. (Framery 1777 [1995], pp. 43–4)

This has become prominent in television talent shows where people are entertained by the extreme abusive opinions of ‘Mr Nasty’ figures who may be more significant than the performers. This leads to the market failure problem dissected by Frank (2008) who sees the television talent show of the Idol franchise type (such as the UK’s Pop Idol and the USA’s American Idol) of presentation as competition which lowers quality rather than increasing it. Here we have a problem of joint production where the primary output, say, of singing, is revered and it is seen as requiring the veneration and maintenance of quality. However, the need to attract the attention of gimmicky self-seeking judges may lead to more success for those who trade off quality in singing against a more spectacular facet of performance.

CONCLUSION Study of the general field of criticism is currently a vibrant research area in cultural economics, with many ongoing empirical projects across a range of cultural fields. However, there are two areas for concern here. The first is that it might be questioned how much more can be usefully learned from econometric studies using an Internet critic composite index. However, at the time of writing we learn that more control is being exercised over what gets into the content of the Rotten Tomatoes website. This may facilitate scope for some innovative research. The second issue is that there tends to be a shortage of theoretical papers on the role of critics in cultural economics. While there have been works such as Frank (2008), there is possibly a problem that cultural criticism is generally not paid for and does not have any direct impact on price, therefore the adaptation of models from housing and medical markets is not straightforward and may be ill-advised.

NOTE 1. In the early nineteenth century a flourishing market in literary magazines allowed the criticism of writers such as de Quincey, Hazlitt and Lamb to function in this way.

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Criticism  157

SEE ALSO: Chapter 30: Google Trends data; Chapter 52: Ratings, reviews and recommendations; Chapter 54: Superstars.

REFERENCES Boyle, M. and L. Chiou (2009), ‘Broadway productions and the value of a Tony Award’, Journal of Cultural Economics, 33 (1), 49–68. Clement, M., D. Proppe and A. Rott (2007), ‘Do critics make bestsellers? Opinion leaders and the success of books’, Journal of Media Economics, 20 (2), 77–105. Dhar, V. and E.A. Chang (2009), ‘Does chatter matter? The impact of user-generated content on music sales’, Journal of Interactive Marketing, 23 (4), 300–307. Framery, N.F. (attributed) (1777), ‘On the best means for naturalizing a taste for good music in France’, Journal de Musique, no. 5, repr. 1995 in H. Haskell (ed.), The Attentive Listener: Three Centuries of Music Criticism, London and Boston, MA: Faber and Faber, pp. 43–5. Frank, J. (2008), ‘Perverse outcomes of intense competition in the popular arts and its implications for product quality’, Journal of Cultural Economics, 32 (3), 215–24. Gemser, G., M. Van Oostrum and M.A. Leenders (2007) ‘The impact of film reviews on the box office performance of art house versus mainstream motion pictures’, Journal of Cultural Economics, 31 (1), 43–63. Hennig-Thurau, T., A. Marchand and B. Hiller (2012) ‘The relationship between reviewer judgments and motion picture success: re-analysis and extension’, Journal of Cultural Economics, 36 (3), 249–83. Olckers, M., C. Kannemeyery and M. Stevenson (2015), ‘Art critic index: a proxy for cultural value in the context of South African art market’, ESRA Working Paper No. 500, Economic Research Southern Africa, February. Souza, T.L., M. Nishijima and A.C. Fava (2019), ‘Do consumer and expert reviews affect the length of time a film is kept on screens in the USA?’, Journal of Cultural Economics, 43 (1), 145–71. Wallentin, E. (2016), ‘Demand for cinema and diverging tastes of critics and audiences’, Journal of Retailing and Consumer Services, 33 (1), 72–81.

FURTHER READING Two articles in the Journal of Cultural Economics, Gemser et al. (2007) and Hennig-Thurau et al. (2012), illustrate the effect of critics on film consumption.

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17.  Crowdfunding

Carolina Dalla Chiesa and Christian Handke

A universal problem in cultural industries is that creators incur substantial up-front costs of creation, whereas any rewards are uncertain and transpire over time. Crowdfunding is a novel method, facilitated by digital information and communication technology (ICT), to mitigate that problem. Crowdfunding initiatives involve open calls for the provision of resources to support specific purposes (Belleflamme et al. 2014). By 2015, online crowdfunding calls featuring on around 1250 websites had raised an estimated $25 billion worldwide (Massolution 2015).1 The first online crowdfunding platform, ArtistShare, launched in 2000, specialized in the cultural sector (Cambridge Center for Alternative Finances 2017). While crowdfunding is now used for many types of projects, cultural and creative industries continue to be one of the most important areas for applications of crowdfunding (Boeuf et al. 2014; Mollick 2014; Mendes-da-Silva et al. 2016). Crowdfunding is an example of where the cultural sector has spawned an innovative business idea with much wider applications. This makes crowdfunding an important topic for cultural economics. Also, general themes in cultural economics – such as intrinsic motivation to participate in creative activities, the economic consequences of public good, and experience-good attributes as well as social interdependence in demand formation – may help explain the crowdfunding phenomenon. However, for all its growth over recent years, the application of crowdfunding is still modest in the bigger scheme of the cultural sector, and its future relevance is hard to predict.

CROWDFUNDING PLATFORMS ONLINE This chapter focuses on crowdfunding via online platforms. Collective patronage has a long history offline. The financing of the pedestal of the Statue of Liberty, by a call for donations in newspapers, is an example of crowdfunding before the emergence of online platforms (Gras et al. 2017). The contemporary term crowdfunding is predominantly associated with the Internet and online platforms, however. Figure 17.1 depicts the main, typical elements and the process of crowdfunding via an online platform. A founder comes up with a project and feeds the information on the crowdfunding call for this project into a template provided by the platform. Issues covered in the call are a description of the project and its founder(s) in text, images or video, any funding goal required to commence with the project, the time period in which the call will be open and any rewards for backers. The platform files the call into its database and includes it in its recommendation system that determines in what sequence calls appear for visitors to the website. The platform also provides standardized contractual terms, possibly with some pre-set options for the founder to choose, which should reduce bargaining costs and the potential for mistrust and conflict between founders and backers. 158

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Crowdfunding  159 Founders

Developing and suggesting projects

Crowdfunding platform

Backers

Templates for project information, filing and recommendation systems

Info

Standardized contractual terms between founders and backers $

Vehicle for monetary transaction

Selecting and supporting projects

Info

$

Other communication channels

Figure 17.1  The process of crowdfunding via a platform Backers can access information on many projects on the site and get to choose to which projects they would like to pledge any funding. The crowdfunding platform receives the money and forwards the total amount pledged by all backers to the founder, or reimburses the backers in case the call does not reach its funding target. Successful projects then go ahead. Backers often use other communication channels to inform themselves about founders and their activities or to interact with them, for instance, via social media. Founders with broader online outreach have greater chances of success (Mollick 2014). Some crowdfunding raises donations only and the founder does not provide any quid pro quo to backers. For reward-based crowdfunding, the backers receive some non-monetary good or service, for instance, attribution, some involvement in the project, or preferential access to events or works produced. In equity-based crowdfunding, the founder pays backers subject to the terms of the investment, which usually depends on success metrics, so that some of the entrepreneurial risk is taken on by the backers. Crowdfunding makes it easier to fund projects for which it is hard to raise professional finance (say small projects, projects that are hard to communicate to commercial investors or projects with strong non-commercial benefits), and where willingness to invest in or pay for a specific project is widely dispersed and low. Such conditions are common for cultural projects. Crowdfunding makes investments more divisible but it requires many, and relatively complex, transactions. Online, transaction costs – the costs of exchanging all types of information required to establish an exchange – are relatively low. Online crowdfunding platforms are a particularly effective means to reduce transaction costs (Belleflamme et al. 2014): they establish standards in presenting information and in the terms and process of exchanges; they can also execute some control over the conduct of the transaction partners, facilitating trust. To finance themselves, crowdfunding platforms usually keep a share of the total amount of funds pledged by backers to a project, usually between 5 and 15 percent.2 As is typical for online platforms in two- or multi-sided markets (Armstrong 2006;

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160  Handbook of cultural economics Rysman 2009), current crowdfunding platforms do not charge substantial initial fees for participants, nor do they invest in projects themselves.3 This helps them expand the number of participating founders and potential backers. They can thus exploit economies of scale by spreading fixed costs over a larger range of activities. They can also exploit network effects, and thus the appeal of their platform for backers and founders, and their competitiveness (Belleflamme et al. 2018). Crowdfunding does not by definition require an online platform. For instance, individual artists have used their own websites to invite financial support for projects. However, crowdfunding largely occurs via online platforms.

A SHORT HISTORY OF CROWDFUNDING PLATFORMS AND MODELS Important platforms are listed in Table 17.1 in chronological order of their foundation. ArtistShare, an early online crowdfunding platform created for cultural projects, was innovative in providing an opportunity to mix various rewards (such as tickets, free copies of works produced and meetings with the artist). This is now the norm among many popular crowdfunding platforms. In 2006, Sellaband was launched to help, for instance, musicians without a record deal to finance albums. It used royalty crowdfunding, where backers/investors participate in profits from creative projects (Agrawal et al. 2015). Kickstarter launched in 2009 with a novel mode of financing itself, by keeping a share of the revenues generated by successful projects. In this instance, the interests of founders and the platform are aligned and the risk of founders is reduced. During the same year, Indiegogo started offering the keep-it-all model, in which a founder receives pledged funds even if the goal set by the project is not reached. Indiegogo and Kickstarter were initially focused on cultural projects, hosting many calls on the fine arts, comics, dance, design, fashion, film and video, music, photography, creative writing and theater. They allowed many newcomers and niche artists to finance projects. The capacity of crowdfunding to mitigate superstar effects in cultural industries should not be exaggerated, however. Well-established creators enjoy massive advantages in crowdfunding too (Doshi 2015). Later, Indiegogo expanded its scope and now hosts special categories for projects with, for example, social causes, technology gadgets and health. Since 2009, many new platforms with varying models have been launched (Cambridge Center for Alternative Finances 2017). Symbid in the Netherlands, for instance, specializes in equity-based crowdfunding. Kiva is an example of a peer-to-peer (P2P) lending platform, where founders commit to paying back regardless of the pecuniary success of the project, similar to a conventional loan. Nevertheless, Allison et al. (2013) show that on this site, backers/lenders accept terms that are not competitive with other types of financial investments, and thus seem motivated by charity, at least in part. Since 2013, Patreon popularized another crowdfunding version; it helps establish a longer-term association between founders and backers, beyond the scope of a single project. Backers (or patrons in this case) commit to fund a founder/creator more continuously, in what is called subscription-based crowdfunding.4

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Crowdfunding  161 Table 17.1  Features of popular crowdfunding platforms Platform

Founded in

Territories served

Main industries served

Main reward scheme for backers

Preconditions for transactions

Platform fee

Artist Share

2001

USA

Music

Nonpecuniary rewards

Sellaband (bankrupt in 2015)

2006

European Union and USA

Music

Royalty sharing and/ or equity

Deliver the product or reimburse backers Reach goal or reimburse backers

Indiegogo

2008

Global

Nonpecuniary rewards

Reach goal or reimburse backers, or none

Kickstarter

2009

Global

Creative industries; also others such as health, technology, social causes Creative industries

5% of funds raised by succeeding calls 33% of earnings from album sales, for instance 5% of funds raised by calls

Nonpecuniary rewards

Reach goal or reimburse backers

Symbid

2011

Global

Any

Equity

Reach goal or reimburse backers

Patreon

2013

Global

Creative industries

Nonpecuniary rewards

Non-project based (subscription)

5% of funds raised by succeeding calls 1% of funds raised by succeeding calls 5% to 9% of funds raised

Source:  All data was retrieved from the respective crowdfunding websites in April 2019, using the Waybackmachine archive for the defunct Sellaband.

EMPIRICAL RESEARCH Two rich and recent sources of data on crowdfunding are reports by the European Commission (2017) and the Cambridge Center for Alternative Finance (2018). Table 17.2 gives an overview of four crowdfunding models according to the type of rewards for backers (if any). The reward-based model is relatively popular for cultural projects. Nonpecuniary rewards to backers vary widely. They can be a type of pre-selling, where backers receive final goods without further payment. Backers’ rewards can also be intangible or tangible perks that are not marketed otherwise; see Belleflamme et al. (2014), Frydrych et al. (2014) or Cecere et al (2017). A main theme in the empirical-economic literature on crowdfunding is the factors determining the success of calls, usually measured either by the amount pledged or

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162  Handbook of cultural economics Table 17.2  An overview of main crowdfunding models in Europe Donation

Reward-based

Equity

P2P lending

Description

Funds provided without specification of any rewards to backers

Backers of successful calls receive a non-pecuniary reward

Backers receive profit or revenue shares

Borrowing from a number of lenders and paying back with or without interest

Growth 2015–16

49%

37%

37%

90%

Amount raised in 2016

€32.4 million

€190.7 million

€218.6 million €696.8 million

Charity Social enterprises Arts, music and design

Filmmaking Arts, music and design Technology

Technology Real estate and housing E-commerce

Most important areas  of application (ranked)   1st   2nd   3rd

Not available

Source:  Adapted from the Cambridge Center for Alternative Finances (2018).

by whether funding goals were reached. Several studies address factors such as gender and other personal characteristics of entrepreneurs, and how they are associated with funding success, compared with other methods of raising finance from banks or venture capital (Barasinska and Schäfer 2014; Greenberg and Mollick 2017; Younkin and Kuppuswammy 2017; Gafni et al. 2019). Crowdfunding seems to have relative advantages for females (Greenberg and Mollick 2017). Mollick (2014) also shows that the size of the network of founders, in particular on social media, is positively associated with the success of crowdfunding calls. In their study of P2P-lending, Allison et al. (2015) show that verbal references to intrinsic motivation in the call increases the chances of investments. The linguistic style seems to matter more for social projects than for solely commercial projects (Parhankangas and Renko 2017). Other studies cover the use of various credibility signals (Kim et al. 2016), as well as the effect of geographical proximity of founders and backers (Agrawal et al. 2015; Mendes-Da-Silva et al. 2016) and how they affect crowdfunding success. As regards the motivation of backers, Ryu and Kim (2016) propose a typology with the categories interest, playfulness, philanthropy, reward, relationship and recognition (cf. Lin et al. 2014). Backers are often personal acquaintances of founders (Gerber and Hui 2016). Kuppuswammy and Bayus (2017) observe that backers are less willing to pledge further funding, once a call’s crowdfunding goal is reached. Given the variety of backers’ motivations, it would be interesting to study the appropriate combinations of rewards to backers in greater detail (cf. Shi 2018).5 A great deal of work remains. In particular, there are few studies on explaining the differences in crowdfunding between various economic sectors or industries, and how these correspond to different economic characteristics. Kickstarter (2019) often publishes

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Crowdfunding  163 data on success rates of calls from various industries. On this platform, calls regarding cultural projects tend to attract more backers and higher total amounts pledged, and have a higher probability of achieving their funding goals, than projects in other industries. Approximate success rates for projects in dance (61 percent), theater (59 percent) and comics (57 percent) and music (50 percent) are much higher than in technology (20 percent), journalism (22 percent) and crafts (24 percent).

CROWDFUNDING IN THE PERSPECTIVE OF CULTURAL ECONOMICS Theoretical frameworks used to structure discussions of crowdfunding include signaling theory (Short et al. 2017) and herding behavior. The theory of two- or multi-sided markets has been influential on crowdfunding websites (Belleflamme et al. 2015). This section analyzes crowdfunding for cultural projects based on typical themes in cultural economics, beyond the basic insights in the crowdfunding literature, regarding the spreading of entrepreneurial risks for innovative projects, and the reduction of transaction costs. Incomplete Information on the Supplier Side Similar to any supplier of a novel or innovative product, suppliers of new cultural products suffer from uncertainty about the quality of their own products and prospective demand. Crowdfunding not only allows creators to outsource potential risk to backers, but the success of a crowdfunding campaign also provides them with valuable information on the interest in their project – a means to test the market before incurring much of the costs of production. This information can be valuable in its own right, even when a call is not funded. Creators can use it to make revisions or develop new projects (Viotto da Cruz 2018). Experience-Good Attributes and Incomplete Information on the User Side Crowdfunding mostly attracts funding from private individuals, not from professional investors, and purchasing of final goods is a more common mode for private individuals to participate in markets. Since crowdfunding backers cannot inspect a final good when deciding to spend their money, problems owing to asymmetric information are expected to be rife (Vismara 2018). This is often mitigated by signals of quality6 and by reimbursement arrangements, whereby backers are refunded if a project is not completed according to the specifics of the call. Nevertheless, as with any investor, backers run some risk that their expectations are not met and are without any recourse. Backers can still face delays or even fraud. However, according to Mollick (2014), fraud has been rare in reward-based crowdfunding, and delays are most common for extremely successful projects. Also, a cornerstone of cultural economics is the notion that cultural products have experiencegood attributes; thus, users, buyers or investors always take decisions under incomplete information. Then the discrepancy in information for crowdfunding backers and buyers of final cultural goods may not be as pronounced as it would be in the case of search goods or goods that are sold with a money-back guarantee, for instance (see Kretschmer et al. 1999).

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164  Handbook of cultural economics Socially Interdependent Demand Formation In response to the experience-good attributes and quality uncertainty in markets for cultural products, potential buyers often seek signals of quality from others – purchases and reports of fellow users, prizes and awards, critics, and so on. A crowdfunding call not only informs potential backers that the founder has made the effort to develop and propose a project; once the call receives some attention or pledged funding, it also makes appreciation by other parties visible, which could become self-perpetuating. Also, a successful crowdfunding call may help a project or creator attract more conventional commercial or public funding. Public-Good Attributes Crowdfunding can also mitigate problems owing to the public-good attributes of cultural products. On the one hand, a call may appeal to potential backers who appreciate the effects that a product may have for others, without expecting to use or buy it themselves. On the other, a reasonably successful call signals to any potential backer that some others are not free-riding, either. Finally, a potential backer may even be incentivized by curiosity about what a project would yield, where he or she would have preferred to access a finished good without paying. Varian (2005, p. 136) is more explicit, referring to appeals for pre-financing of creative projects from end-users as ransoms – pay us now, or you will never get to find out how great this movie would have been. With some optimism, we could even hope that crowdfunding would mitigate the need for other remedies of market failure owing to the public-good attributes of cultural products, such as the perpetually contentious issue of copyright enforcement. Intrinsic Motivation It is well documented that participation in cultural and creative activities entails non-pecuniary rewards (Towse 2001); it may be intrinsically motivated as an end in itself or it may be a means to foster positive interactions with others. How intense and creative participation has to be for non-pecuniary rewards to transpire is less clear. Some crowdfunding calls do offer attribution or participation in the creative process. Even without that, some potential backers may appreciate the feeling of influencing what is produced and being part of the process early on. The crowdfunding literature has begun to harness the theory of intrinsic motivation. Hui et al. (2014) and Gerber and Hui (2016) use it to explain incentives of backers and the terms of crowdfunding calls. Lin et al. (2014) incorporate various degrees of extrinsic and intrinsic motivation in their typology of pledges and backers.

OUTLOOK This chapter introduced some potential benefits of crowdfunding, based on main themes in cultural economics. Assuming that crowdfunding is here to stay, there is considerable scope for future research. First, crowdfunding has many variations. Which variation is most suited for specific cultural industries or creative projects of different types – say from

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Crowdfunding  165 established stars or newcomers – is not yet well documented. Second, crowdfunding may lower barriers to entry in the cultural sector, as it offers promising creators an additional source of funding. However, it is far from clear to what extent crowdfunding is effective for newcomers, whether it can overcome superstar effects and help bring about a more equitable or efficient allocation of resources. Third, crowdfunding platforms probably operate in a similar way to other online platforms in two- or multi-sided markets. Owing to direct and indirect network effects, there may be a tendency for monopolization and centralized control in this online service too. Nevertheless, there are many crowdfunding platforms and there seem to be low barriers to entry so far. This may change as the market for crowdfunding platforms and relevant technologies mature, or due to regulation of this novel type of finance. That relates to a fourth area of further research on crowdfunding: the appropriate type of statutory regulation. As crowdfunding has grown and expanded beyond, in general, charitable giving into commercial investments in technology and real estate, more extensive regulation similar to that for conventional finance is probable in the near future. However, in the cultural sector, donation and reward-based crowdfunding remains pre-eminent. This is consistent with the notion that cultural products are mostly appreciated for their consumption value and their non-use value owing to positive externalities that they entail, instead of for their value as a financial investment. The need for regulation may thus be very different than for profit-orientated investments. As with most novel technologies, it is difficult to predict the potential of crowdfunding at a relatively early stage, and we are not trying to make that call here. Cultural economics provides a useful structure for explaining much of the crowdfunding phenomenon. Crowdfunding also generates abundant data and changes restrictions for participants in the cultural sector, which entails opportunities to develop new empirical insights on cultural industries, over and beyond crowdfunding itself. Last but not least, crowdfunding is fascinating for cultural economists because it constitutes an innovation from the cultural sector that has already had broad applications in many other aspects of the economy.

NOTES 1. More recent market volume figures are not yet available (Cumming and Hornuf 2018). 2. Exceptions are common in donation-based crowdfunding and platforms, which often waive the platform fee for specific calls to stimulate donations. 3. Typically, large platforms such as Kickstarter do not curate calls or impose other restrictions either, except for cases of law infringements. 4. A typical constellation for projects on Patreon is that backers make a series of payments at regular intervals to support a creator, who periodically releases exclusive creative content if sufficient total funds are raised. 5. Relating to schemes to reward crowdfunding, Belleflamme et al. (2014) separately analyze profit-sharing (pecuniary) and pre-ordering (non-pecuniary) options. 6. A crowdfunding calls’ narrative, the reputation of the founder, the goal set and the rewards specified, as well as the social network outreach of the founder, can all signal quality (cf. Mollick 2014).

SEE ALSO: Chapter 14: Creative industries; Chapter 47: Platforms; Chapter 52: Ratings, reviews and recommendations; Chapter 55: Tax concessions.

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166  Handbook of cultural economics

REFERENCES Agrawal, A.K., C. Catalini and A. Goldfarb (2015), ‘Crowdfunding: geography, social networks, and the timing of investment decisions’, Journal of Economics & Management Strategy, 24 (2), 253–74. Allison, T.H., A.F. McKenny and J.C. Short (2013), ‘The effect of entrepreneurial rhetoric on microlending investment: an examination of the warm-glow effect’, Journal of Business Venturing, 28 (6), 690–707. Allison, T.H., B.C. Davis, J.C. Short and J.W. Webb (2015), ‘Crowdfunding in a prosocial microlending environment: examining the role of intrinsic versus extrinsic cues’, Entrepreneurship Theory and Practice, 39 (1), 53–73. Armstrong, M. (2006), ‘Competition in two-sided markets’, RAND Journal of Economics, 37, (3), 668–91. Barasinska, N. and D. Schäfer (2014), ‘Is crowdfunding different? Evidence on the relation between gender and funding success from a German peer-to-peer lending platform’, German Economic Review, 15 (4), 436–52. Belleflamme, P., T. Lambert and A. Schwienbacher (2014), ‘Crowdfunding: tapping the right crowd’, Journal of Business Venturing, 29 (5), 585–609. Belleflamme, P., T. Lambert and A. Schwienbacher (2018), ‘Network effects in crowdfunding’, Social Sciences Research Network, October, accessed 2 April 2019 at ssrn.com/abstract=3259191. Belleflamme, P., N. Omrani and M. Peitz (2015), ‘The economics of crowdfunding platforms’, Information Economics and Policy, 33 (C), 11–28. Boeuf, B., J. Darveau and R. Legoux (2014), ‘Financing creativity: crowdfunding as a new approach for theatre projects’, International Journal of Journal Management, 16 (3), 33–48. Cambridge Center for Alternative Finance (2017), ‘Crowdfunding in East Africa: regulation and policy for market development’, accessed 3 May 2019 at www.jbs.cam.ac.uk/fileadmin/user_upload/research/centres/ alternative-finance/downloads/2017-05-eastafrica-crowdfunding-report.pdf. Cambridge Center for Alternative Finance (2018), ‘Expanding horizons: the 3rd European alternative finance industry report’, accessed 3 May 2019 at www.jbs.cam.ac.uk/fileadmin/user_upload/research/centres/ alternative-finance/downloads/2018-ccaf-exp-horizons.pdf. Cecere, G., F. Le Guel and F. Rochelandet (2017) Crowdfunding and social influence: an empirical investigation, Applied Economics, 49 (57), 5802–13. Cumming, D. and L. Hornuf (eds) (2018), The Economics of Crowdfunding, London: Palgrave Macmillan. Doshi, A.R. (2015), ‘The impact of high-performance outliers on two-sided platforms: evidence from crowdfunding’, Social Sciences Research Network, July, accessed 15 April 2019 at https://ssrn.com/abstract=2422111. European Commission (2017), ‘Crowdfunding: reshaping the crowd’s engagement in culture’, accessed 10 January 2018 at europa.eu/capacity4dev/crowdfunding/documents/new-report-crowdfunding-reshaping-crowds-engag​ ement​-culture. Frydrych, D., A.J. Bock, T. Kinder and B. Koeck (2014) Exploring entrepreneurial legitimacy in reward-based crowdfunding, Venture Capital, 16 (3), 247–69. Gafni, H., D. Marom, A. Robb and O. Sade (2019), ‘Gender dynamics in crowdfunding (Kickstarter): evidence on entrepreneurs, investors, deals and taste-based discrimination. Investors, deals and taste-based discrimination’, Social Sciences Research Network, May, accessed 12 December 2019 at https://papers.ssrn. com/2442954. Gerber, E.M. and J. Hui (2016), ‘Crowdfunding: how and why people participate’, in J. Méric, I. Maque and J. Brabet (eds), International Perspectives on Crowdfunding: Positive, Normative and Critical Theory, Bingley: Emerald Insight, pp. 37–64. Gras, D., R.S. Nason, M. Lerman and M. Stellini (2017), ‘Going offline: broadening crowdfunding research beyond the online context’, Venture Capital, 19 (3), 217–37. Greenberg, J. and E. Mollick (2017), ‘Activist choice homophily and the crowdfunding of female founders’, Administrative Science Quarterly, 62 (2), 341–74. Hui, J., M.D. Greenberg and E.M. Gerber (2014), ‘Understanding the role of community in crowdfunding work’, in Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW’14), New York: ACM, pp. 62–74. Kickstarter (2019), ‘Stats’, accessed at https://www.kickstarter.com/help/stats?ref=hello. Kim, P.H., M. Buffart and G. Croidieu (2016), ‘TMI: signaling credible claims in crowdfunding campaign narratives’, Group & Organization Management, 41 (6), 717–50. Kretschmer, M., G.M. Klimis and C.J. Choi (1999), ‘Increasing returns and social contagion in cultural industries’, British Journal of Management, 10 (S1), 61–72. Kuppuswamy, V. and B.L. Bayus (2017), ‘Does my contribution to your crowdfunding project matter?’, Journal of Business Venturing, 32 (1), 72–89. Lin, Y., W.F. Boh and K.H. Goh (2014), ‘How different are crowdfunders? Examining archetypes of crowdfunders and their choice of projects’, Academy of Management Proceedings, (1), accessed 12 December 2019 at https://journals.aom.org/doi/10.5465/ambpp.2014.209.

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Crowdfunding  167 Massolution (2015), ‘Crowdfunding industry report’, Crowdsourcing LLC, New York. Mendes-Da-Silva, W., L. Rossoni, B.S. Conte, C.C. Gattaz and E.R. Francisco (2016), ‘The impacts of fundraising periods and geographic distance on financing music production via crowdfunding in Brazil’, Journal of Cultural Economics, 40 (1), 75–99. Mollick, E. (2014), ‘The dynamics of crowdfunding: determinants of success and failure’, Journal of Business Venturing, 29 (1), 1–16. Parhankangas, A. and M. Renko (2017), ‘Linguistic style and crowdfunding success among social and commercial entrepreneurs’, Journal of Business Venturing, 32 (2), 215–36. Rysman, M. (2009), ‘The economics of two-sided markets’, Journal of Economic Perspectives, 23 (3), 125–43. Ryu, S. and Y.G. Kim (2016), ‘A typology of crowdfunding sponsors: birds of a feather flock together?’, Electronic Commerce Research and Applications, 16 (March–April), 43–54. Shi, S.W. (2018), ‘Crowdfunding: designing an effective reward structure’, International Journal of Market Research, 60 (3), 288–303. Short, J.C., D.J. Ketchen, A.F. McKenny, T.H. Allison and R.D. Ireland (2017), ‘Research on crowdfunding: reviewing the (very recent) past and celebrating the present’, Entrepreneurship Theory and Practice, 41 (2), 149–60. Towse, R. (2001), ‘Partly for the money: rewards and incentives to artists’, Kyklos, 54 (2–3), 473–90. Varian, Hal. R. (2005), ‘Copying and copyright’, Journal of Economic Perspectives, 19 (2), 121–38. Viotto da Cruz, J. (2018), ‘Beyond financing: crowdfunding as an informational mechanism’, Journal of Business Venturing, 33 (3), 371–93. Vismara, S. (2018), ‘Signalling to overcome inefficiencies in crowdfunding markets’, in D. Cumming and L. Hornuf (eds), The Economics of Crowdfunding, London: Palgrave Macmillan, pp. 29–56. Younkin, P., and V. Kuppuswamy (2017), ‘The colorblind crowd? Founder race and performance in crowdfunding’, Management Science, 64 (7), 2973‒3468.

FURTHER READING Rich sources of data on crowdfunding are reports by the European Commission (2017), and the Cambridge Center for Alternative Finance (2018). For seminal empirical work, see Mollick (2014). Belleflamme et al. (2015, 2018) contains sophisticated economic analyses of crowdfunding.

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18.  Cultural capital David Throsby

The concept of capital has been fundamental to the interpretation of production processes in economics for more than 200 years. Capital can be defined as durable goods that give rise to a flow of services over time which may be combined with other inputs, such as labour, to produce further goods and services. The original and longest-serving interpretation of capital arising from this definition has been physical or manufactured capital, meaning plant and equipment, machines, buildings, and so on. In the second half of the twentieth century a further form of capital was identified, namely, human capital, being the inherent characteristics of people which make them productive. Subsequently, the idea of natural capital was developed, allowing the designation of renewable and non-renewable resources as capital assets. More recently still, the concept of capital in economics has been extended into the field of art and culture in an effort to recognise the distinctive features of artworks and other cultural goods as capital assets, and to capture the ways in which these assets contribute, in combination with other inputs, to the production of further cultural goods and services. Thus the economic concept of cultural capital has taken shape. It should be noted that use of the term cultural capital in economics differs from its sociological interpretation following Pierre Bourdieu. What is it that is distinctive about cultural capital, allowing it to be set apart from the other forms of economic capital described above? Two possibilities have been suggested. First, it could be proposed that items of cultural capital are simply cultural goods which happen to be capital goods (as defined in the previous paragraph) rather than consumption goods. Such a definition presupposes a definition of a cultural good. Although there has been some debate among economists as to whether cultural goods and services can be differentiated from ordinary economic goods and services, and if so, how, it is now generally understood that a cultural good can be defined as a good that exhibits three characteristics: it has involved human creativity in its making; it conveys symbolic meaning (or multiple meanings); and it is identifiable, at least in principle, as embodying some form of intellectual property. Accepting these characteristics of a cultural good allows us to substantiate the aforementioned definition of cultural capital. Second, an alternative approach to defining cultural capital can be couched in terms of the types of value to which cultural assets give rise. Consider a historic church building. It may have a potential sale price as real estate, and a non-market value measured, for example, by the willingness of people to pay to see it preserved. However, these measures of its economic value may be incapable of representing the full range and complexity of the cultural worth of the building; it may have religious significance unable to be expressed in monetary terms, it may have had an influence over time on architectural styles, it may act as a symbol of identity or place, and so on. All these and many more are elements of what might be termed the building’s cultural value, a multi-dimensional representation of the building’s cultural worth assessed in quantitative and/or qualitative terms and for which money is not an appropriate or relevant metric. Following this route, we can 168

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Cultural capital  169 define cultural capital as an asset which embodies, stores or gives rise to cultural value independently of whatever economic value it may possess. Whichever of these two definitions is accepted, we can proceed to consider the characteristics of cultural capital in comparison with the other types of capital we have mentioned. Cultural capital may exist in two forms, tangible and intangible. Tangible cultural capital occurs in the form of artworks and artefacts such as paintings and sculptures, and heritage buildings, locations and sites. Intangible cultural capital comprises artworks which exist in their pure form as public goods, such as music and literature, and the stock of inherited traditions, values, beliefs, and so on which constitute the culture of a group, whether the group is defined in national, regional, religious, political, ethnic or other terms. Furthermore, intangible cultural capital also exists in the cultural networks and relationships that support human activity, and in the variety of cultural manifestations within communities – that is, in cultural ecosystems and cultural diversity. Both tangible and intangible forms of cultural capital exist as a capital stock held by an individual economic agent, a city, a region, a country or, indeed, by all humankind. This capital stock could be assigned an asset value in both economic and cultural terms at a given point in time. The net effect of additions to and subtractions from the capital stock within a given time period indicates the net investment/disinvestment in cultural capital during the period, measurable in both economic and cultural terms, and determines the opening value of the stock at the beginning of the next period. Any holding of cultural capital stock gives rise to a flow of capital services over time, which may enter final consumption directly, or which may be combined with other inputs to produce further cultural goods and services. So, for example, the services of artworks held as capital items by an art museum may be combined with materials, labour and other inputs to yield consumption experiences for visitors to the museum; in addition, the artworks may stimulate the production of further works through their influence on creative artists who view them, thus leading to further capital formation. As with any other type of asset, cultural capital may deteriorate over time, necessitating investment in its maintenance or refurbishment. Economic evaluation of such expenditure can call upon standard investment appraisal techniques used in economics, such as cost–benefit analysis or cost-effectiveness analysis. For a heritage restoration project, for example, the discounted net present value of the time stream of benefits yielded by the project could be calculated using these techniques and set against the project’s capital cost; the internal rate of return on this project could then be compared with the returns on alternative investment opportunities. Ideally the financial calculations should include an estimate of consumers’ surplus, if relevant, and some account for any non-market effects of the project, measurable as willingness to pay or willingness to accept compensation for loss. It is possible to imagine in principle that, in addition to this type of financial assessment, an appraisal could also be carried out in terms of the expected flow of cultural value to be derived from the project.

CULTURAL VALUE We noted previously that the value assigned to cultural goods in general, and to cultural capital in particular, can be interpreted as comprising economic value, represented as

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170  Handbook of cultural economics both market and non-market components and measurable in monetary terms, and cultural value, which has multiple dimensions and no single unit of account. Given these characteristics, an appropriate way to proceed in analysing the cultural value of an item of cultural capital or of the services it provides is to identify the specific nature of these dimensions so that a more precise account of its various elements can be put together. Although there may be many ways to deconstruct the concept of cultural value into its constituent parts, a standard set of values might include elements such as aesthetic value, symbolic value, social value, historical value and educational value. For particular applications, other values might be referred to, such as the architectural value of a heritage building or the spiritual value of religious art. This approach to identifying cultural value as a multi-dimensional concept is similar to Lancastrian demand theory in which goods and services are defined as a set of characteristics that may be differently weighted in the preference functions of different consumers. The various elements of cultural value as defined above could be similarly weighted in an empirical application so that an estimate of the aggregated cultural value of an item of cultural capital could be derived. However, applying these procedures requires that individual or collective judgements of value can be quantified, bearing in mind that such judgements are subjective and likely to differ between individuals. This requirement presents a methodological challenge. Nevertheless, progress can be made in systematising these sorts of judgements by interpreting them against a set of qualitative criteria (high/ medium/low and so on) and then transforming them into quantitative terms by reference to a numerical scale. For example, an accepted way of applying this type of rating or ranking procedures is to use a Likert scale which calibrates the strength of a respondent’s agreement or disagreement with a series of statements about the characteristics of the item under consideration. For cultural value estimation, the statements can be constructed to reflect each of the specific dimensions of cultural value that are assumed to apply. When a set of scores for the various items has been obtained for each respondent, they can be aggregated across individuals and/or condensed into a consolidated score using weights, as described above. The introduction into economic analysis of a form of value for cultural phenomena that cannot ultimately be rendered into monetary terms is a process that stands outside the narrow confines of neoclassical economics. Even so, traditional economists might be willing to accept that such non-financial values are admissible if it can be shown that they affect the decision-making of economic agents in systematic ways. Ultimately, if a full picture of the value of an item of cultural capital is to be obtained, all dimensions of both economic and cultural value must be taken into account.

PARALLELS BETWEEN CULTURAL AND NATURAL CAPITAL There are close parallels, both theoretical and applied, between the concepts of cultural and natural capital: both have been inherited from the past, both yield use and non-use benefits and both impose a duty of care. One outcome of this similarity is that methods for assessment of the value of environmental amenities have been able to be applied in the cultural arena, especially in the valuation of heritage assets such as historic buildings, or groups of buildings, and archaeological sites. These applications include the measurement

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Cultural capital  171 of non-use values by means of methods such as contingent valuation, discrete choice modelling and hedonic analysis, all of which have been brought across and adapted from environmental economics. Two aspects of the congruence between cultural and natural capital are particularly significant, namely, diversity and sustainability. As regards the former, a similarity can be observed between biodiversity as an element of natural capital, and cultural diversity as a key component of cultural capital. The sources of value that have been articulated in explaining why biodiversity is important have their counterparts in the valuation of cultural diversity, as follows: ●

Both biodiversity and cultural diversity generate existence value for individuals, deriving from the knowledge that the richness of the natural world and the variety of cultures and cultural expressions simply exist. ●● Both natural and cultural ecosystems are necessary to support economic activity; the invisible networks and relationships that hold cultures together and give meaning to people’s lives are as essential in underpinning the functioning of the economy as are the ecosystems of air, land and water that make up the natural environment. ● Biodiversity is valued because some species may have economic value as yet unrecognised; similarly, certain cultural manifestations may have economic and cultural value not yet evident, and their loss could incur economic costs or forgone opportunities in the future. Cultural diversity has emerged from the shadows in recent years to become an important focus for international cultural policy-making, exemplified in the Convention on the Protection and Promotion of the Diversity of Cultural Expressions, an international treaty which was adopted by the United Nations Educational, Scientific and Cultural Organization (UNESCO) member states in 2005 and which entered into force in 2007. A significant motivation for the establishment of this standard-setting instrument was the hope in a number of countries that it would provide protection for local cultural expressions such as film and television productions, whose existence was threatened by imported cultural product. The impetus to safeguard the cultural diversity component of cultural capital springs from the same motives as those that underlie the acceptance by the international community of the need to protect the world’s biodiversity. The second aspect of the parallel between natural and cultural capital lies in that both have long-lasting properties requiring management over time. An appropriate framework within which to consider these long-term aspects is that of sustainability, a concept most often encountered in the phrase sustainable development. This proposition, first enunciated by the World Commission on Environment and Development (the Brundtland Commission) in the 1980s, refers to development that meets the needs of the current generation without compromising the capacity of future generations to meet their own needs. This requirement reflects the principle of inter-generational equity, or inter-temporal distributive justice, that is, fairness in the distribution of welfare, utility or resources between generations. When applied to cultural capital, this principle refers to the need for the present generation to care for cultural assets in a way that allows them to be passed on to future generations in a condition appropriate to their needs.

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172  Handbook of cultural economics The parallel with natural capital goes further; the precepts of environmentally or ecologically sustainable development (ESD), which enunciate guidelines for the sustainable management of natural resources, can be translated into a corresponding set of principles for culturally sustainable development, a paradigm for interpreting sustainability in the management of cultural capital assets. Both inter- and intra-generational equity are invoked in this paradigm, as is the precautionary principle relating to risk aversion in the face of possibly irreversible change. In addition, an overarching principle of sustainability is the proposition that no part of any system exists independently of other parts. In this regard it can be suggested that cultural capital makes a contribution to long-term sustainability which again is similar to that of natural capital; neglect of cultural capital by allowing cultural capital to deteriorate, by failing to sustain the cultural values that provide people with a sense of identity, and by not undertaking the investment needed to maintain the stock of tangible and intangible cultural assets or to increase it (for example, by the production of new artworks) will similarly place cultural systems in jeopardy and may cause them to break down, with consequent loss of welfare and economic output. The final principle enunciated above draws together the entire concept of sustainability when applied to culture. Taken together, the principles that define the concept of culturally sustainable development have the same significance for cultural capital theory as do the criteria for ecologically sustainable development for the theory of natural capital.

CONCLUSION The economic theory of cultural capital is now established, at least in conceptual terms, but empirically the picture is less clear. The financial valuation of individual items of cultural capital stock is reasonably straightforward, and measurement of the economic value of the flow of services that a given item of capital stock produces is also well advanced in both use and non-use components. However, rigorous means for measuring the cultural value of an item of cultural capital in either stock or flow terms remain to be further developed; as indicated in this chapter, the most promising prospects appearing to lie in assessment according to multiple criteria with some weighted aggregation as the end result.

SEE ALSO: Chapter 5: Artists’ labour markets; Chapter 23: Cultural value; Chapter 31: Heritage; Chapter 33: Intangible cultural heritage.

REFERENCES Angelini, F. and M. Castellani (2018), ‘Cultural and economic value: a critical review’, Journal of Cultural Economics, 43 (2), 173–88, accessed 6 May 2019 at https://doi.org/10.1007/s10824-018-9334-4. Bellandi, M., D. Campus, A. Carraro and E. Santini (2019), ‘Accumulation of cultural capital at the intersection of socio-demographic features and productive specializations’, Journal of Cultural Economics, 5 April, accessed 6 May 2019 at https://doi.org/10.1007/s10824-019-09348-1.

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Cultural capital  173 Bucci, A., P.L. Sacco and G. Segre (2014), ‘Smart endogenous growth: cultural capital and the creative use of skills’, International Journal of Manpower, 35 (1–2), 33–55. Cheng, S.-W. (2006), ‘Cultural goods creation, cultural capital formation, provision of cultural services and cultural atmosphere accumulation’, Journal of Cultural Economics, 30 (4), 263–86. Dalziel, P. and C. Saunders (2009), Sustainable Development and Cultural Capital, Wellington: Stats NZ. Rizzo, I. and D. Throsby (2006), ‘Cultural heritage: economic analysis and public policy’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: Elsevier/North-Holland, pp. 983–1016. Shockley, G.E. (2004), ‘Government investment in cultural capital: a methodology for comparing direct government support for the arts in the US and the UK’, Public Finance and Management, 4 (1), 75–102. Throsby, D. (1999), ‘Cultural capital’, Journal of Cultural Economics, 23 (1–2), 3–12. Throsby, D. (2017), ‘Culturally sustainable development: theoretical concept or practical policy instrument?’, International Journal of Cultural Policy, 23 (2), 133–47. Ulibarri, C.A. (2000), ‘Rational philanthropy and cultural capital’, Journal of Cultural Economics, 24 (2), 135–46. Wang, X. (2007), ‘An analysis of optimal allocation and accumulation of cultural capital’, Doshisha University Policy and Management, 9, 197–213.

FURTHER READING The original article defining cultural capital in economic terms is Throsby (1999). Developments of the theory of cultural capital in cultural economics and some applications are contained in Ulibarri (2000), Shockley (2004), Cheng (2006), Wang (2007), Dalziel at al. (2009), Bucci et al. (2014) and Bellandi et al. (2019). A thorough review of the concept of cultural value is in Angelini and Castellani (2018). A fuller account of cultural capital and sustainability is contained in Rizzo and Throsby (2006) and Throsby (2017).

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19.  Cultural districts

Mariangela Lavanga

The development of cultural districts has become a standard practice in policy-making worldwide at different scales – local, regional and national (Braun and Lavanga 2007). Government bodies have used cultural district policies to regenerate and rebrand urban areas, sometimes focusing on increasing cultural consumption, as in the case of museum districts, other times fostering innovation and entrepreneurship, as in the case of cultural production districts. In parallel with the development of cultural districts, academic literature on this topic has skyrocketed. In an article by Lazzeretti et al. (2013), the authors review over 1586 academic articles on cluster or industrial districts published in the period between 1989 and 2010. The number of articles published per year has grown from just a few to over 200. Similarly, the number of journals publishing cluster-related articles has also increased exponentially. The authors discovered a long-tail distribution, with a few journals dominating the debate, mostly in economic geography, and a long list of journals representing a variety of disciplines. The analysis identifies three main features behind the power and rise of cluster research: multidisciplinary, cross-disciplinary and global dimension. Among the top-cited scholars, two in particular have dedicated their analysis to deepening our understanding of cultural districts and clusters: Ann Markusen, professor emerita of urban and regional planning and public policy at the University of Minnesota, and Allen J. Scott, professor emeritus of economic geography at the University of California Los Angeles (UCLA). Markusen engaged with the role of proximity for artists’ communities and arts institutions, and the role of public policy, while Scott focused on the emergence and development of cultural-production districts, such as the movie industry in Los Angeles. Both have been fervent critics and opponents of Richard Florida’s creative-class theory which has preached a single locational behaviour for a very large group of occupations, a formula for successful creative cities (for example, investment in talent, technology and tolerance) and thus a copy-and-paste recipe for cities worldwide (Florida 2002). In the ground-breaking Cities in Civilization, Peter Hall discusses the role of cultural and artistic creativity in the development of cities such as ancient Athens, Renaissance Florence or Paris between 1870 and 1910 (Hall 1998). Certain features seem repeating themselves: (1) rapid economic and social transformation, that is, they were trading places and the global cities of their time, (2) wealth, that is, financial centres, (3) high culture, which meant presence of elite, and (4) in-migration, increasing intercultural urban population. They were cities in transition, troubled cities, uncomfortable and unstable. However, Hall concludes that ‘time and chance happens to cities too’ (Hall 2000, p. 648) and that there is no formula for success. In the past few decades, testing district and cluster theories in the cultural and creative industries has offered, and still is offering, a challenging and fertile ground to advance theories on urban development, to unravel the causes of urban growth, and to understand the spatial patterns and mobility of firms, institutions and individuals in contemporary society. 174

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Cultural districts  175 This chapter first provides a definition of cultural districts and its roots in the Marshallian industrial district; secondly, it looks at the agglomeration economies that firms, organisations and individuals enjoy because they are not only co-located in the same area, but also highly interconnected among each other. The argument put forward in this chapter is the importance of intense face-to-face interaction and spatial proximity in the production, distribution and consumption of cultural goods and services.

FROM INDUSTRIAL DISTRICT TO CULTURAL DISTRICT The concept of industrial districts is not new. In Principles of Economics (1890), Alfred Marshall described the industrial district as a geographic area where an agglomeration of specialised firms, especially small ones, has settled down. When discussing the origin of the concept of industrial district, Belussi and Caldari (2008) stress how Marshall believed in industrial districts to rescue the British economy. Marshall was interested in understanding to what extent the industrial organisation of small and medium-sized British firms (for example, the Lancashire textile district) could compete with large vertically integrated American companies. Through the years, the industrial district would acquire a special atmosphere, ‘something in the air’, which would provide benefits to colocated firms, increase their productivity and efficiency and strengthen their competitive advantage. Among the benefits, Marshall mentioned circulation of information, transfer of know-how and skills, a reduction of input costs, transportation and transaction costs, a local specialised labour pool with clear reduction of search costs, a set of shared rules and practices which would increase trust among firms, and spread and adoption of new ideas. The close connections and interactions among firms would further contribute to their division of labour and specialisation. Belussi and Caldari (2008, p. 338) describe Marshallian industrial districts as: characterised by a peculiar combination of competition and cooperation. In districts, firms specialise in particular phases of the productive process: each phase is not isolated from, but, rather, is functional to, the others. The district comes to be not only competitive owing to the presence of many firms but also, and moreover, cooperative where parts interact in an exchange process.

Porter’s (1998) definition of cluster is very similar to Marshall’s conceptualisation of industrial districts: a geographical agglomeration of horizontally and vertically interconnected companies and associated institutions in a specific field, which compete but also cooperate. According to Porter (1998), geographical proximity improves not only communication, but also reputation and trust among the participants; these elements are fundamental to understanding the dynamics of cooperation and competition. While Porter’s definition of clusters became the one most used in both academia and policy-making circles, it was thanks to the Italian economist Becattini that the Marshallian concept of districts was revitalised in the 1960s and 1970s. Becattini (1962) used the concept of Marshallian industrial district to study the agglomeration of many interconnected small firms, mostly family run, and locally embedded in socio-cultural networks. Through empirical research and theoretical development, he delved into the economic development of Tuscany, in particular the industrial organisation of the textile industry in Prato and, later, the Italian centres of industrial specialisation, especially in

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176  Handbook of cultural economics the Third Italy area (North-East and Central Italy). For the sake of our discussion on cultural districts, it is worth mentioning that Becattini’s studies found applications in many of the crafts-based industries that Third Italy gathered together. It is in the concept of the industrial district that we can find the foundations of cultural districts. In their detailed analysis of the most cited publications on cultural and creative clusters, Chapain and Sagot-Duvauroux (2018, p. 21) argue that ‘authors have . . . used this concept to label what was either understood as a quarter or as a district previously in the literature without necessarily adding more to either of these original concepts’. The idea behind cultural districts is that cultural industries rely on local production networks and have strong place-bound characteristics. Santagata (2011, p. 147) defines cultural district as ‘a social and economic experience at the confluence of two phenomena: that of localization, as first identified by Alfred Marshall (Marshall 1890), and that of the idiosyncratic (peculiar, unique) nature of culture and cultural goods’. First, the majority of companies and organisations in the cultural industries are small in size, labourintensive with project-based work and a pool of specialised workers (Hesmondhalgh and Baker 2013; Leadbeater and Oakley 1999). Second, cultural products are idiosyncratic which means they are time- and place-specific (Santagata 2011). They have strong connections with the place where they are produced, its community and history (Rozentale and Lavanga 2014). Furthermore, cultural goods are highly specialised, differentiated and singular (Karpik 2010), where the infinite variety characteristics highlighted by Caves (2000) dominates. The concept of industrial districts is thus useful to understand why cultural firms colocate and the benefits they derive from geographical proximity. Similarly to industrial districts, cultural districts can be defined as geographical agglomeration of cultural firms that enjoy positive externalities by being located in the same place. The creation, circulation and transfer of knowledge are essential. Firms and organisations in the cultural districts are exposed to noise (Grabher 2002), ‘buzz’ (Bathelt et al. 2004; Storper and Venables 2004) or the Marshallian industrial atmosphere. According to Bathelt et al. (2004, p. 38): buzz refers to the information and communication ecology created by face-to-face contacts, copresence, and co-location of people and firms within the same industry and place or region. This buzz consists of specific information and continuous updates of this information, intended and unanticipated learning processes in organized and accidental meetings . . . Actors continuously contribut[e] to and [benefit] from the diffusion of information, gossip and news by just ‘being there’.

Through planned and unplanned interactions, innovation, knowledge creation and learning are enhanced. All the benefits firms enjoy derive from repeated and direct interactions and faceto-face contacts. Face-to-face interaction (verbal, physical, contextual, intentional and non-intentional) becomes the most effective way to communicate and exchange a form of knowledge which is complex, uncodifiable and sticky to a place. Cultural industries, which produce idiosyncratic and singular cultural goods, rely enormously on this type of knowledge. As Santagata (2011, p. 148) explained, ‘cultural commodities are idiosyncratic not only because tacit knowledge is needed to create and produce them but also because this knowledge is based on people’s prior idiosyncratic experience: personal and collective

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Cultural districts  177 history count’. Transfer of the tacit knowledge (Polanyi 1953) and savoir-faire is facilitated by geographical proximity, the shared norms and practices and trust firms enjoy in the cultural district. Tacit knowledge can be described as an information system with the characteristic of a local public good, or even a commons. Information and knowledge circulate without restrictions and are transmitted via tacit systems of communication (Santagata 2011). A particular aspect that may differentiate cultural districts from industrial districts in other sectors is linked to demand uncertainty, or to nobody-knows characteristics (Caves 2000). A cultural district may help reducing asymmetric information, for example, by coordination devices (Karpik 2010) such as place of origin or ‘made in’ labels which would ensure, protect and signal a certain standard of quality. Santagata (2006) uses the concept of institutional cultural districts, where formal institutions allocate community or collective property rights and trademarks to a restricted area of production. These rights legally protect the cultural capital of a community in a given area. Even in the absence of property rights and trademarks, reference to a place or to a certain area or building has proved to give an aura to the cultural products and firms located there, with clear benefits for the long-lasting reputation of the actors involved (Molotch 2002). Some types of cultural district are more production orientated, and correspond to industrial districts where many small and medium-size firms produce cultural goods or services, such as textile or movies districts (for instance, Hollywood), while in others the emphasis is more on consumption, such as the museum districts (for example, the Museum Quarter in Vienna). A third category is a mix of production and consumption orientations. Cultural districts become cultural quarters or creative buildings where cultural firms are mixed with shops, cafés and art galleries (for example, the Temple Bar in Dublin, the Westergasfabriek in Amsterdam, the Northern Quarter in Manchester, Arabianranta in Helsinki and the Finlayson/Tampella area in Tampere) (Lavanga 2004, 2013; Mommaas 2004; Montgomery 1995, 2003, 2004; Wynne 1992). The variety of cultural districts is reflected in the wide taxonomy of the use of the concepts of districts, clusters or quarters in academia too. Chapain and Sagot-Duvauroux (2018, p. 7) have recently illustrated how some of these concepts seem to be geographically linked: ‘For example, “cultural district” is much more associated with publications from Italy and North America, “cultural cluster” with publications from Australia, “cultural quarter” with UK and Ireland’.

EVOLUTION AND DEVELOPMENT OF A CULTURAL DISTRICT Cultural districts belong to the category of endogenous growth models. How districts come into being and how we can explain their development require us looking at the dynamics of the agglomeration economies. When discussing why cultural industries cluster and the benefits cultural firms enjoy by being located close to each other, Lorenzen and Frederiksen (2007) discuss two main agglomeration economies or positive externalities: localisation and urbanisation economies. Localisation economies are agglomeration economies that, in principle, pertain to a particular set of economic activities co-located in a particular place. Urbanisation economies are agglomeration economies that, in

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178  Handbook of cultural economics principle, have an impact on all economic activities located in a particular place. In the former, benefits come from increased specialisation; in the latter they come from increased diversity. Lorenzen and Frederiksen (2007) argue that non-urban regions often host one district alone, thus co-located firms in that particular district mainly enjoy localisation economies. To the contrary, larger urban areas may host several districts of a diverse range of industries, where firms benefit from both localisation and urbanisation economies. The differences lie in the types of product innovation that are triggered: variety, novelty and radical innovation. Lorenzen and Frederiksen (2007) argue that cultural industries, which fluctuate among those types of innovation and which are mostly concentrated in urban areas, depend on localisation economies together with urbanisation economies. In both, the type of externalities come from industry, labour market, institutions and infrastructure. In the first group of benefits (externalities of industry), localisation economies comes into play when firms in a specific district are able to coordinate their related knowledge bases; for example, being part of the same supply chain or via temporary project work so common in cultural industries. This coordination becomes responsible for increased product flexibility and variety, while technology and information spillovers across firms may support incremental innovation. Only when other districts are present, mainly in larger urban areas, do firms enjoy urbanisation economies which create the pre-conditions for coordination and spillovers between unrelated knowledge bases that lead to new products and radical innovation. A further category of localisation economies pertains to the increase in efficiency following competition among firms, while positive benefits of the diversity of industry are venture capital investments that may lead to start-ups and increased entrepreneurship in larger urban areas. The second group of externalities is related to the labour market. While co-location of firms in the same set of economic activities may provide benefits such as an abundant pool of specialised labour, the diversity of skills and overlapping labour markets when different districts coexist in the same place may be responsible for the spread of ideas and radical innovation. The third group of externalities relates to institutions and infrastructures. In non-urban areas, specialised institutions emerge and accompany the development of the district (that is, technical education and industry associations, but also norms and conventions). They are responsible for the deepening of knowledge and skills, lowering of transaction costs and for efficient communication. In larger urban areas, there exists a diversity of institutions and infrastructures. Higher education institutions and research not only deepen but also broaden the knowledge and skills. Furthermore, pipelines such as airports and fast train connections allow access to global knowledge and ideas, or global buzz. Cultural provision and diverse housing may further contribute to the attraction of global talent. In connection with this, Markusen (2006) found that the locational choices of artists are mostly shaped by investment decisions that cities and regions make in artistic space and organisations, as opposed to an array of amenities as Florida (2002) would argue. When discussing the rise of Hollywood as centre of the US movie industry, Scott (2005, p. 15) suggests that the question to ask is ‘not so much on how the seed of an agglomeration is planted’, but ‘how . . . the emerging local economic system is subject to a structured and self-reinforcing process of growth and development’. The process is dynamic, with circular and cumulative causation: (1) specialised and complementary producers, (2) local labour

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Cultural districts  179 markets, and (3) institutional environment – the externalities of industry, labour market and institutions that we have discussed previously. In the early 1900s New York was the centre of the US film industry. However, many companies would shoot in California probably owing to the better weather all year around and the diversity of landscapes. From one studio in 1909, Hollywood went on to host 17 production companies in 1912. According to Scott (2005) it is not so important to understand why Hollywood. Most of the time districts emerged randomly ‘but then steadily lock into systematically structured, path-dependent outcomes’ (Scott 2005, p. 15). Between 1912 and 1915, Hollywood would take the characteristics of a prototypical industrial district. Additional firms then join (that is, Famous Players-Lasky Corporation, Universal Pictures, the Fox Film Corporation) and move in, and ‘one by one, but if agglomeration economies are at work, their choice of location will become progressively less random’ (Scott 2005, p. 16). Scott (2005, p. 15) recommends looking at ‘when and how a simple agglomeration of firms begins to manifest signs of endogenous development dynamics; and how this place then pulls ahead of actual and latent competitors, and how it subsequently acquires a dominant position in extended markets, sometimes over a long periods of time’ (Scott 2005, p. 15). Companies in Hollywood would focus mostly on film content innovation, while developing a star system to increase their market reach. A process of advanced division of labour would increase the industrialisation of the entire movie sector and bring innovation in the process and management of movie production (for example, continuity script and flashback techniques). By the 1920s, Hollywood surpassed New York for number of companies, workers and number of movies produced and exported. After the Second World War, Hollywood gradually reorganised itself from vertically integrated majors into a disintegrated network of firms, following the anti-trust Paramount Decree and the development of television. Specialised services (for example, script writing and film editing) and institutions emerged (such as the Motion Picture Producers and Distributors of America, and the Academy of Motion Pictures Arts and Science), firms would work with many subcontractor and freelancers, and benefit from a growing and multiple local labour market. During the 1980s–2000s, a new geography of Hollywood would emerge with few majors, independents and specialised services, a large local labour market, and institutions to support firms and workers. Scott (2005) stresses the importance of place-based resources, from cinematic traditions to icons, symbols, landscapes and the potential of synergies with other cultural industries. In conclusion, this organised production system emerged gradually. Paying attention to the evolution of time and space is key. With time, a loose and chaotic collection of activities can develop into a dense interlocking system of firms. Agglomeration economies and localised increasing returns to scale allowed Hollywood to become one of the most important cultural districts in the world. In similar vein, Santagata (2011, p. 148) underlined basic components that contribute to the making of a cultural district: a) a local community, which is cohesive in its cultural traditions and in the accumulation of technical knowledge and social capital (trust and cooperation); b) a significant development of increasing returns to scale and increasing returns to scope; c) accumulation of savings; strongly entrepreneurial cooperative local banking; d) a bent towards open international markets; e) public financial support along the entire chain of the creation of value; f) a high rate of birth of new firms, often of household size, as a result of social capability and interactive learning; the ability to be district minded, to become a system, and to produce positive externalities.

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180  Handbook of cultural economics It is worth noting that point (d) is linked to the opening of the district to global pipelines which would reduce locked-in processes owing to overspecialization; for example, the development of a mono industry unable to adapt to exogenous changes as it is often the case in textile, ceramics, jewellery and other crafts-related districts, such as the Birmingham jewellery quarter discussed by De Propris and Lazzeretti (2009) and the decline of the districts. In this, firms are increasingly benefiting from temporary cluster or temporary organised spatial proximity; it can provide firms with access to knowledge and opportunities for interaction similar to those offered by permanent geographical proximity, albeit in a short-lived and intensified form (Maskell et al. 2006). The study of art fairs, design weeks, fashion trade shows and film festivals offers interesting opportunity to analyse the interplay between local and distant knowledge bases, tacit and codified knowledge, and local and global buzz (Brydges and Hracs 2019; Brydges et al. 2018; Lavanga 2018; Power and Jansson 2008; Rinallo and Golfetto 2011; Skov 2006). Despite digitisation, cultural firms increasingly use temporary clusters to strengthen relational trust, and to reduce asymmetric information and uncertainty in the market for cultural goods and services.

CONCLUSIONS The chapter discussed the roots and concept of cultural districts; it further delved into the agglomeration economies, that is, the benefits that arise for cultural firms, not just from proximity, but from intense interactions and exchange of knowledge, especially tacit knowledge embedded in the skilled labour force, and supporting institutions. Policymakers around the world have tried copy-and-paste strategies to create cultural districts from the top down. In reality, most of the districts develop slowly. Cultural districts develop in an organic and spontaneous way (almost as a creative commons). Random events may plant the seeds of an agglomeration, but it is the dynamics of agglomeration economies of industry, labour market and institutions that trigger endogenous growth development. However, many attempts fail – in the spirit of trial and error. Feasibility studies that are able to estimate risks and costs, and more importantly, evaluate the impacts in relation to the original objectives, are fundamentally necessary (Markusen and Gadwa 2010). Finally, cultural districts are an interesting case of cross fertilisation between theory and practice, and they offer a vantage point to understand the dynamic relations between culture, economy and place. A future question to ask is the extent to which new technological innovations, such as artificial intelligence, may render cultural districts obsolete or, to the contrary, amplify the positive externalities firms enjoy in the district. Thus far, spatial organised proximity, in its permanent or temporary forms, seems the most effective way to exchange tacit knowledge, build relational trust and reduce uncertainty in the production, distribution and consumption of cultural products and services.

SEE ALSO: Chapter 14: Creative industries; Chapter 15: Creativity; Chapter 29: Festivals.

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REFERENCES Bathelt, H., A. Malmberg and P. Maskell (2004), ‘Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation’, Progress in Human Geography, 28 (1), 31–56. Becattini, G. (1962), Il Concetto di Industria e la Teoria del Valore (The Concept of Industry and the Theory of Value), Turin: Boringhieri. Belussi, F. and K. Caldari (2008), ‘At the origin of the industrial district: Alfred Marshall and the Cambridge school’, Cambridge Journal of Economics, 33 (2), 335–55. Braun, E. and M. Lavanga (2007), An International Comparative Quickscan into National Policies for Creative Industries, Rotterdam: Euricur for the Ministry of Education, Culture and Science of the Netherlands. Brydges, T. and B.J. Hracs (2019), ‘The locational choices and interregional mobilities of creative entrepreneurs within Canada’s fashion system’, Regional Studies, 53 (4), 517–27. Brydges, T., B.J. Hracs and M. Lavanga (2018), ‘Evolution versus entrenchment: debating the impact of digitization, democratization and diffusion in the global fashion industry’, International Journal of Fashion Studies, 5 (2), 365–72. Caves, R.E. (2000), Creative Industries: Contracts between Art and Commerce, Cambridge, MA: Harvard University Press. Chapain, C. and D. Sagot-Duvauroux (2018), ‘Cultural and creative clusters – a systematic literature review and a renewed research agenda’, Urban Research & Practice, 1–30, online 19 November, doi:10.1080/17535 069.2018.1545141. De Propris, L. and L. Lazzeretti (2009), ‘Measuring the decline of a Marshallian industrial district: the Birmingham jewellery quarter’, Regional Studies, 43 (9), 1135–54. Florida, R. (2002), The Rise of the Creative Class: And How It’s Transforming Work, Leisure, Community and Everyday Life, New York: Basic Books. Grabher, G. (2002), ‘Cool projects, boring institutions: temporary collaboration in social context’, Regional Studies, 36 (3), 205–14. Hall, P. (1998), Cities in Civilization: Culture, Technology and Urban Order, London: Weidenfeld and Nicolson. Hall, P. (2000), ‘Creative cities and economic development’, Urban Studies, 37 (4), 639–49. Hesmondhalgh, D. and S. Baker (2013), Creative Labour: Media Work in Three Cultural Industries, London: Routledge. Karpik, L. (2010), Valuing the Unique: Economics of Singularities, Princeton, NJ: Princeton University Press. Lavanga, M. (2004), ‘Creative industries, cultural quarters and urban development: the case studies of Rotterdam and Milan’, in G. Mingardo and M. van Hoek (eds), Urban Management in Europe Vol. II: Towards a Sustainable Development, Rotterdam: Erasmus University Rotterdam, pp. 121–57. Lavanga, M. (2013), ‘Artists in urban regeneration processes: use and abuse? Territoire en Mouvement, 17–18 (1), 6–19. Lavanga, M. (2018), ‘The role of Pitti Uomo trade fair in the menswear fashion industry’, in R. Blaszczyk and B.  Wubs (eds), The Fashion Forecasters: A Hidden History of Color and Trend Prediction, London: Bloomsbury Academic, pp. 191–209. Lazzeretti, L., S.R. Sedita and A. Caloffi (2013), ‘Founders and disseminators of cluster research’, Journal of Economic Geography, 14 (1), 21–43. Leadbeater, C. and K. Oakley (1999), The Independents: Britain’s New Cultural Entrepreneurs, London: Demos. Lorenzen, M. and L. Frederiksen (2008), ‘Why do cultural industries cluster ? Localization, urbanizatio, products and projects’, in P. Cooke and L. Lazzeretti (eds), Creative Cities, Cultural Clusters, and Local Economic Development, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 155–79. Markusen, A. (2006), ‘Urban development and the politics of a creative class: evidence from a study of artists’, Environment and planning A, 38 (10), 1921–40. Markusen, A. and A. Gadwa (2010), ‘Arts and culture in urban or regional planning: a review and research agenda’, Journal of Planning Education and Research, 29 (3), 379–91. Marshall, A. (1890), Principles of Economics, London and New York: Macmillan & Co. Maskell, P., H. Bathelt and A. Malmberg (2006), ‘Building global knowledge pipelines: the role of temporary clusters’, European Planning Studies, 14 (8), 997−1013. Molotch, H. (2002), ‘Place in product’, International Journal of Urban and Regional Research, 26 (4), 665–88. Mommaas, H.J.T. (2004), ‘Cultural clusters and the post-industrial city: towards a remapping of urban cultural governance’, Urban Studies, 41 (3), 507–32. Montgomery, J. (1995), ‘The story of Temple Bar: creating Dublin’s Cultural Quarter’, Planning Practice & Research, 10 (2), 135–72. Montgomery, J. (2003) ‘Cultural quarters as mechanisms for urban regeneration. Part 1: conceptualising cultural quarters’, Planning Practice & Research, 18 (4), 293–306.

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182  Handbook of cultural economics Montgomery, J. (2004), ‘Cultural quarters as mechanisms for urban regeneration. Part 2: A review of four cultural quarters in the UK, Ireland and Australia’, Planning Practice & Research, 19 (1), 3–31. Polanyi, M. (1953), Personal Knowledge, Chicago, IL: University of Chicago Press. Porter, M. (1998), ‘Clusters and the new economics of competition’, Harvard Business Review, 11 (November– December), 77–90. Power, D. and J. Jansson (2008), ‘Cyclical clusters in global circuits: overlapping spaces in furniture trade fairs’, Economic Geography, 84 (4), 423−48. Rinallo, D. and F. Golfetto (2011), ‘Exploring the knowledge strategies of temporary cluster organizers: a longitudinal study of the EU Fabric Industry Trade Shows (1986–2006)’, Economic Geography, 87 (4), 453−76. Rozentale, I. and M. Lavanga (2014), ‘The “universal” characteristics of creative industries revisited: the case of Riga’, City, Culture and Society, 5 (2), 55–64. Santagata, W. (2006), ‘Cultural districts and their role in economic development’, in V. Ginsburgh and D. Throsby (eds), Handbook on the Economics of Art and Culture, Amsterdam: Elsevier Science, pp. 1100–119. Santagata, W. (2011), ‘Cultural districts’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 147–52. Scott, A.J. (2005), Hollywood: The Place, the Industry, Princeton, NJ: Princeton University Press. Skov, L. (2006), ‘The role of trade fairs in the global fashion business’, Current Sociology, 54 (5), 764–83. Storper, M. and A.J. Venables (2004), ‘Buzz: face-to-face contact and the urban economy’, Journal of Economic Geography, 4 (4), 351–70. Wynne, D. (1992), The Culture Industry: The Arts in Urban Regeneration, Aldershot: Avebury.

FURTHER READING The dynamics between place, economy and culture are the subject of the book on Hollywood by Scott (2005). A very recent systematic literature review and a renewed research agenda on cultural districts, cultural and creative clusters, and cultural quarters can be found in Chapain and Sagot-Duvauroux (2018). A more general review and research agenda on the intersections between culture and urban planning is offered by Markusen and Gadwa (2010).

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20.  Cultural diversity*

Heritiana Ranaivoson

A broad consensus surrounds the notion of cultural diversity. It has become an unavoidable concept in international negotiations related to the cultural field (Stenou 2004) and has been described as a common heritage of humanity (UNESCO 2005). The sheer existence of cultural diversity enriches the whole of humanity. Having diversity in cultural goods and services offered to citizens, so that they have access to a broad range of available views and ideas, is perceived as a desirable objective for policies addressing the cultural sectors. Another premise is that consumers value diversity because they have different tastes or because every consumer has a taste for diversity (Ranaivoson 2012). Both conditions (diversity of supply and overall taste for diversity) should lead to the ultimate objective that citizens take advantage of the diversity of available content, by having a diverse consumption (Napoli 1999). This chapter provides a brief overview of how cultural diversity has been addressed by cultural economists, in particular in relation to the cultural sector. It first provides a definition of cultural diversity and, secondly, explains how the diversity of cultural identities contributes to team efficiency. The chapter then focuses on the diversity of cultural expressions, considering the ambiguous impact of market concentration, of online platforms and of recommendation systems.

HOW TO DEFINE AND ASSESS CULTURAL DIVERSITY? THE STIRLING MODEL All academic papers on cultural diversity work with a definition of cultural diversity – albeit sometimes an implicit definition. Cultural economists (and scholars in various fields) have been increasingly using the Stirling model, which has the merit of proposing a general way of defining, and furthermore of assessing, diversity (Stirling 2007). It contributes to unifying the approaches towards cultural diversity, thus enabling international and cross-sector comparisons. More importantly, the Stirling model answers criticisms of the concept of cultural diversity being blurry (Bonet and Négrier 2011). The Stirling model defines diversity as a mix of variety, balance and disparity (Moreau and Peltier 2004; Ranaivoson 2007; Stirling 2007). Its main characteristic is to rely on a definition of diversity that goes beyond the sheer number (for example, of films, of titles, and so on) to integrate how, for instance, each genre or origin is represented compared with the others, and how genres or artists that are very different from the others are present or not. More precisely, the diversity of a system can only be assessed when its elements have been grouped into categories. When this categorization has been achieved, variety corresponds to the number of categories, balance is the way the elements are spread among categories (for example, market shares) and disparity corresponds to the level of difference between 183

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184  Handbook of cultural economics the categories (for example, between every pair of categories or between the two most distinct categories; Farchy and Ranaivoson 2011). Every component of diversity appears to evolve independently from the other components. However, this is only true to a certain extent. They are inextricably linked through the notion of diversity, with variations in any component having an impact on the other components (Ranaivoson 2007). To make this definition clear, let us consider the evolution of music diversity on a French radio station (Ranaivoson 2007). This station initially broadcasts around 100 different French pop songs. Five of these songs are played every hour while the others are broadcast far less frequently. To increase variety, one can, for example, increase the number of different songs broadcast, from 100 to 150. To increase balance, one can reduce the number of broadcasts of the most broadcast songs and increase the broadcasts of the others. To increase disparity, one can choose to replace some of the French pop songs by songs of other styles, which were previously not broadcast, for example Brazilian Bossa Nova or Pakistani Qawwali songs. Other, more specific dimensions can be added to the Stirling model, for example, the distinction between source, content and exposure diversities (Napoli 1999), or that between supplied and consumed diversities (Eaton and Lipsey 1989; Van Cuilenburg and Van der Wurff 2001). Also, the Stirling model needs to be applied to specific categories or typologies, themselves based on the issues addressed and, more pragmatically, on the available data. In every case, it is important to define the diversity of what is at stake. There are here two main instances for cultural diversity: the diversity of cultural identities and the diversity of cultural expressions. The diversity of cultural identities can be linked to Hofstede’s definition of cultures as ‘a collective programming of the mind which distinguishes the members of one group of category of people from another’ (Hofstede 1991, p. 6). This definition implies that culture has to be analysed as a collective phenomenon, since it is shaped by the individuals’ social environment with the importance of commonly shared sets of value. Alternatively, the diversity of cultural expressions corresponds to the diversity within, or produced by, cultural sectors. Such an approach is more output orientated.

THE POSITIVE IMPACT OF THE DIVERSITY OF CULTURAL IDENTITIES ON TEAM EFFICIENCY The diversity of cultural identities is often tackled from a management position with the view of how to ensure that organizations best adapt to, or take advantage of, their inner diversity. Reviewing the links between the diversity of cultural identities and entrepreneurship, Vecco and Ranaivoson (2017) show that there is a general consensus on the positive impact of cultural diversity within the entrepreneurial field. The diversity of cultural identities has a positive impact on team performance. Jackson et al. (1995) show that diversity is positively related to the creativity and the decision-­making effectiveness of teams. Cultural diversity can also favour innovation. Cross-cultural teams (that is, those whose members are of diverse cultural backgrounds) tend to be more open to various ideas from their members. The level of acceptance of ideas is supposed to be higher. Different knowledge and thinking processes may facilitate problem-solving, the generation of ideas and their implementation (Nathan and Lee 2013). The interchange of

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Cultural diversity  185 ideas may lead to more innovations and a higher rate of entrepreneurial initiatives (Sobel et al. 2010). All this can support team effectiveness. Teams benefit not only from the diversity of their members but also from these members’ access to more and diversified information and resources thanks to their own networks (Vecco and Ranaivoson 2017). Moreover, owing to these diversified networks, organizations can access international markets better (Nathan and Lee 2013). Finally, diversity (such as of knowledge, skills and approaches) within business networks is a key factor in innovation potential, as it allows the discovery of new opportunities (Ehrenmann and Warschat 2013). There is a well-established literature demonstrating the positive role of these business networks in cultural sectors (de-Miguel-Molina et al. 2012). All this mirrors the United Nations Educational, Scientific and Cultural Organization’s (UNESCO 2001) statement that cultural diversity is a capacity for expression, creation and innovation. However, a diversity of cultural identities can imply some drawbacks that can affect negatively teams’ performance. Different cultures mean different values and, sometimes, different languages. This can lead to communication difficulties and higher levels of conflict (Ehrenmann and Warschat 2013) since rules and codes may not be shared or respected. Thus, organizations or individuals with similar status, for instance (Ebbers 2009), or the same ethnic background (Koopmans and Schaeffer 2015) are more likely to collaborate. This may lead to create cluster sub-groups that can limit the overall team performance.

THE MARKET STRUCTURE’S AMBIGUOUS IMPACT ON THE DIVERSITY OF CULTURAL EXPRESSIONS A large body of research has analysed how market structure, and in particular market concentration, impacts the diversity of cultural expressions, with premises in microeconomics and industrial economics, and ambiguous results (Van Cuilenburg and Van der Wurff 2001). There is a conflict between economies of scale and diversity (Dixit and Stiglitz 1977; Lancaster 1979). Economies of scale exist when fixed costs are large relative to variable costs as is the case for many creative products. For example, this phenomenon leads video-game publishers to focus their development and marketing efforts on a few games since an increase in their consumption will decrease their average production costs (by unit sold). The opposition between diversity and cost reduction is a standard result in the literature on monopolistic competition, starting with Chamberlin (1933). Findings of this strand of research suggest that, in order to reduce production cost, producers tend to provide fewer diverse products than consumers want. In addition, economic models such as Hotelling’s spatial model show a tendency for competing producers to end up offering standardized products (Hotelling 1929), thus reducing products disparity. Producers want to obtain the greatest market share and, to do so, aim to produce the product that best fits the tastes of the average consumer. However, they fail to cater for consumers with more marginal tastes. Although there may seem to be an increasing variety of cultural goods and services, even more of them target the average consumer and are therefore even more alike. Thus, Assogba (2015) argues that having several media companies does not necessarily lead to diversity of news, notably because each then lacks sufficient means to produce quality content.

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186  Handbook of cultural economics Alternatively, economies of scope can also motivate producers and distributors to offer a more diverse range of products as they get bigger. Economies of scope can be realized in those sectors where product diversification can be based on the common and recurrent use of an infrastructure with high fixed costs (for example, a warehouse). In addition, a diversified catalogue has several assets. It first allows companies to limit portfolio risks, akin to the management of financial assets (Markowitz 1952). It is also a way to reduce competition: saturation of the market enables the erection of barriers to entry (Curien and Moreau 2005; Lancaster 1979). For instance, museums diversify their activities to face budgetary restrictions; art galleries and art dealers diversify their portfolio in order to reduce risks.

ONLINE PLATFORMS’ IMPACT ON THE DIVERSITY OF CULTURAL EXPRESSIONS Digitization and the development of the Internet have led to a reformulation of traditional questions on the impact of market structure. Cultural sectors are increasingly becoming organized as two-sided markets (Rochet and Tirole 2002), in which new online companies play the role of platforms mediating between different categories of users. They behave in a different way from traditional cultural industries since they have to take into account the interactions between their various categories of users – consumers, advertisers, application developers, and so on. Online platforms are motivated to provide a huge diversity of products as it gives them a competitive advantage over their competitors (Brynjolfsson et al. 2010). Anderson coined the long tail to predict that digital technology will allow consumption to become a great deal more diverse (Anderson 2006), which consists in two trends: (1) the decreasing importance of the head (blockbusters, best-sellers, and so on) in relative or even absolute terms; and (2) the increase of the tail, that is, the increase of niche products. The latter idea was already put forward by Brynjolfsson et al. (2003) when they discussed the importance of obscure works in online sales. For the moment, online platforms have an interest in remaining open and fostering internal competition (Ranaivoson 2016): openness in ensuring that platforms welcome third party’s content or application, in order to attract users; and competition between their providers, in order to propose as broad a range of catalogues or offers as possible. Online platforms typically offer a large selection of niche products and provide the relevant filters to discover niche products (Brynjolfsson et al. 2010). There is a much greater amount of content available to citizens owing to the democratization of content production, the reduction of distribution to an audience that is potentially global, and the constant emergence of new services relying on innovative business models (Masnick and Ho 2014). These services or new activities are at all steps in the value chain from creation to distribution. A consequence would be greater diversity also at user level (Cowen 2002). However, digital technologies are likely to threaten traditional stakeholders in the cultural sectors (creators and intermediaries) to the benefit of these online platforms. While platforms may provide a huge diversity of cultural content, they tend to become more than actors in value chains, with an impact on consumption choices that is difficult to assess (Kulesz 2015). Goel et al. (2010) believe that there is a risk that the online platforms’

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Cultural diversity  187 increasing control over access to cultural works may threaten the visibility and promotion of marginal cultural works even compared to the current situation. Online platforms’ commercial strategies and business models are likely to lead to more homogeneity in content supply and consumption (Guèvremont et al. 2013). More fundamentally, arguments developed by superstar theory can explain possible evolution towards less diversity. The theory (Adler 1985; Rosen 1981) aims at explaining why consumption is focused on a restricted number of products or creators, the superstars. Rosen’s (1981) most interesting argument is the role played by technology, namely, distribution and consumption technologies’ low marginal costs, which allow better products or more talented creators to benefit from economies of scale when reaching wider markets, and thus become superstars. With digitization, marginal costs for distribution and consumption are decreasing even more. Adler (1985) assumes that consumers get increasingly satisfied the more they know about what they are consuming, and that consumers mainly know via discussion with others. Therefore, information is at the core of his theory. Since consumers try to know as much as possible about what they consume, the most famous creators or products – those that most people are talking about – are advantaged, and this is a self-reinforcing feature (Adler 1985). Information about superstars becomes even more ubiquitous owing to the Internet.

THE DIVERSITY OF RECOMMENDED CULTURAL EXPRESSIONS: A NEW FRONTIER FOR CULTURAL ECONOMICS The diversity of cultural expressions has been primarily analysed from the point of view of production and distribution, and their impact on consumption. With digitization, it is important to consider – beyond what is available – what gets recommended to users. Recommendation systems have been studied since at least the mid-1990s (Adomavicius and Tuzhilin 2005). They are useful to help filter out large amounts of information. An increase in the diversity of available options makes it harder to cope with the related increase in the load of information, as research in psychology shows (for an overview, see Ranaivoson 2012). With digitization, some physical limitations have disappeared, notably space (for storing) and time (for scheduling). Others remain: not only attention but also what can be displayed to users – for example, what the Netflix user will see when connecting to the platform. Thus, Mulligan (2014) argues that the size of the online music services’ catalogue is an inconvenience for their users. This is, he argues, mainly owing to the small amounts of visual display space digital services have compared with bricks and mortar stores’ footage of window space and of front-of-store display space. For these reasons, the selection process of an item can become cumbersome and complicated (Kunaver and Požrl 2017). A strategy for users can therefore be to limit the riskiness of their choice and opt for what they already know (Ranaivoson 2016). Conversely, relevant filters that help consumers find what is likely to please them, in spite of the abundant supply, were already identified in the long tail theory as necessary for the advent of the long tail (Anderson 2006). With, on one side, users with their different tastes and profiles and, on the other, available items, recommendation systems aim at displaying for each user the set of items

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188  Handbook of cultural economics that is the most likely to maximize the user’s utility (Adomavicius and Tuzhilin 2005). Most recommendation systems follow the same steps (Kunaver and Požrl 2017): first they analyse the available information about the user; second, they create a user model which stores the information required by the recommendation process in order to select the most appropriate item(s) for the user; third, they present items to the user; fourth a feedback mechanism enables the recommendation system to track the user’s satisfaction with the presented recommendations and adjust the user model accordingly. This feedback can be implicit (based on the observed behaviour, for example, whether the content was watched until the end), or explicit (based on rating). Recommendation systems are usually classified into three categories, based on how recommendations are made (Adomavicius and Tuzhilin 2005): content-based recommendations (the user will be recommended items similar to those the user preferred in the past), collaborative recommendations (the user will be recommended items that people with similar tastes and preferences liked in the past) and, hybrid approaches, which combine the first two. By definition, recommendation systems reduce the number of items displayed to consumers. This does not necessarily mean that users would have a more diverse consumption in the absence of such recommendation systems. The introduction of diversification into the recommendation process receives growing attention by scholars and practitioners (Kunaver and Požrl 2017). This could be seen as a form of diversity by design (Helberger 2011), where diversity is an objective already at the level of the conception and implementation of the algorithm. However, recommendation systems’ biases can, on the contrary, in some cases lead to a reduction in diversity (Ranaivoson 2019), in particular selection bias and the filter bubble. Selection bias occurs when not all items in the target population are equally likely to be displayed (Groeling 2013), for example, items that do not belong to the catalogue, but also items that do not have sufficient historical data. Tan et al. (2015) explain that recommendation systems can reduce sales diversity because these systems tend to recommend only products with sufficient historical data, and obscure works do not have enough historical data. The filter bubble relies on three specific dynamics (Pariser 2011): a person is alone in his or her filter bubble; the filter bubble is invisible; and, the person does not choose to enter the bubble. Pariser sees the filter bubble as a drawback of personalization, often overlooked by users: ‘in a personalized world, important but complex or unpleasant issues . . . are less likely to come to our attention at all’ (Pariser 2011, p. 18). The direct consequence of the filter bubble is that every user has access to less diverse content – viewpoints, ideas, stories, and so on – than what is available, or than what they think they have access to (Hendrickx 2018). Empirical research proving the existence of a filter bubble remains scarce (Hendrickx 2018). Thus, Zuiderveen Borgesius et al. (2016) conclude that, in spite of the serious concerns voiced, there is no empirical evidence that warrants any strong worries about filter bubbles, but the debate about them is nonetheless important. In a similar vein, Haim et al. (2017) note that empirical evidence on the existence of the filter bubble and its effects, especially in the context of news, is limited. To our knowledge, none of the existing handful of studies has been able to prove genuine negative effects of filter bubbles.

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Cultural diversity  189

CONCLUSION This chapter has provided a brief overview of how cultural economics has tackled cultural diversity in the cultural sector. After explaining how the Stirling model can provide a basis to define it, it has identified four main lines of research: the impact of the diversity of cultural identities on a team efficiency; the impact of market structure on the diversity of cultural expressions; how the question is renewed with the advent of online platforms; and the diversity of recommended cultural expressions. I formulate two conclusions from the overview. A first important aspect is that any research on cultural diversity requires a proper definition of the concept, how it is addressed by the research and, eventually, how it is assessed; otherwise, the concept gets too broad and blurry, leading to contradictory conclusions. It does not mean that I believe there is one definition of cultural diversity and one proper way to analyse it. Instead, each researcher providing their own definition should make it clearer for the reader what are the underlying assumptions. This is more of an attempt to make assumptions as explicit as possible. Finally, as digitization constantly brings innovations, the analysis of its adoption and its impact will lead to very interesting research. In particular, algorithms, how they are integrated in online platforms’ strategies and their role in how citizens are exposed to diversity, remain under-researched in social sciences.

NOTE *

The writing of this paper was made possible through a research grant from the Research Foundation – Flanders (FWO) for the project Diversity and Information Media: New Tools for a Multifaceted Public Debate (DIAMOND), contract S008817N.

SEE ALSO: Chapter 18: Cultural capital; Chapter 33: Intangible cultural heritage; Chapter 54: Superstars.

REFERENCES Adler, M. (1985), ‘Stardom and talent’, American Economic Review, 75 (1), 208–12. Adomavicius, G. and A. Tuzhilin (2005), ‘Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions’, IEEE Transactions on Knowledge and Data Engineering, 17 (6), 734–49. Anderson, C. (2006), The Long Tail: How Endless Choice Is Creating Unlimited Demand, London: Random House Business Books. Assogba, H. (2015), ‘News pluralism threatened in Benin by “contracts”’, in E. George (ed.), Concentration des médias, changements technologiques et pluralisme de l’information, Laval: Presses de l’Université Laval, pp. 197–213. Bonet, L. and E. Négrier (2011), ‘The end(s) of national cultures? Cultural policy in the face of diversity’, International Journal of Cultural Policy, 17 (5), 574–89. Brynjolfsson, E., Y. Hu and M.D. Smith (2003), ‘Consumer surplus in the digital economy: estimating the value of increased product variety at online booksellers’, Management Science, 49 (11), 1580–96.

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190  Handbook of cultural economics Brynjolfsson, E., Y. Hu and M.D. Smith (2010), ‘Research Commentary – long tails vs. superstars: the effect of information technology on product variety and sales concentration patterns’, Information Systems Research, 21 (4), 736–47. Chamberlin, E.H. (1933), The Theory of Monopolistic Competition, Cambridge, MA: Harvard University Press. Cowen, T. (2002), Creative Destruction: How Globalization is Changing the World’s Cultures, Princeton, NJ and Oxford: Princeton University Press. Curien, N. and F. Moreau (2005), ‘Investir les marchés induits de la musique : une voie de sortie de crise pour les majors du disque face au piratage?’ (‘To invest in music-induced markets: a way out of crisis for the major music labels facing piracy’), Revue Télécom, 136 (Winter), 1–5. Dixit, A.K. and J.E. Stiglitz (1977), ‘Monopolistic competition and optimum product diversity’, American Economic Review, 67 (3), 297–308. Eaton, B.C. and R.G. Lipsey (1989), ‘Product differentiation’, in R. Schmalensee and R.D. Willig (eds), Handbook of Industrial Organization, Amsterdam: Elsevier Science, pp. 952–1009. Ebbers, J.J. (2009), ‘Organizational dynamics in social networks: contracts and reputations in the film industry’, PhD thesis, University of Amsterdam. Ehrenmann, S. and J. Warschat (2013) ‘Diversity in the early phases of product development’, International Journal of Industrial Engineering and Management, 4 (1), 19–26. Farchy, J. and H. Ranaivoson (2011), ‘An international comparison of the ability of television channels to provide diverse programme: testing the Stirling model in France, Turkey and the United Kingdom’, UIS Technical Paper, No. 6, UNESCO Institute for Statistics, pp. 77–138. Goel, S., A. Broder, E. Gabrilovich and B. Pang (2010), ‘Anatomy of the long tail: ordinary people with extraordinary tastes’, in Proceedings of the Third ACM International Conference on Web Search and Data Mining, New York: ACM, pp. 201–10, accessed 22 January 2016 at http://dl.acm.org/citation.cfm?id=1718513. Groeling, T. (2013), ‘Media bias by the numbers: challenges and opportunities in the empirical study of partisan news’, Annual Review of Political Science, 16 (1), 129–51. Guèvremont, V., I. Bernier, M. Burri, M. Cornu, L. Richieri Hanania and H. Ruiz Fabri (2013), Implementation of the Convention on the Protection and Promotion of the Diversity of Cultural Expression in the Digital Age: Challenges, Priority Actions, and Recommendations, report presented to the Intergovernmental Committee of the Convention on the Protection and Promotion of the Diversity of Cultural Expressions Seventh Ordinary Session, Paris, 10–13 December. Haim, M., F. Arendt and S. Scherr (2017), ‘Abyss or shelter? On the relevance of web search engines’ search results when people Google for suicide’, Health Communication, 32 (2), 253–8. Helberger, N. (2011), ‘Diversity by design’, Journal of Information Policy, 1, 441–69. Hendrickx, J. (2018), ‘Is the filter bubble #fakenews?’, Diamond, accessed 6 July 2018 at https://soc.kuleuven. be/fsw/diamond/Jonathan%20Hendrickx%20V3.pdf. Hofstede, G. (1991), Organizations and Cultures: Software of the Mind, New York: McGraw Hill. Hotelling, H. (1929), ‘Stability in competition’, Economic Journal, 39 (153), 41–57. Jackson, S.E, K.E. May and K. Whitney (1995), ‘Understanding the dynamics of diversity in decision-making teams’, in R.A. Guzzo and E. Salas (eds), Team Effectiveness and Decision Making in Organizations, San Francisco, CA: Jossey-Bass, pp. 204–61. Koopmans, R. and M. Schaeffer (2015), ‘Relational diversity and neighbourhood cohesion. unpacking variety, balance and in-group size’, Social Science Research, 53 (September), 162–76. Kulesz, O. (2015), ‘UNESCO Convention on the Protection and Promotion of the Diversity of Cultural Expressions: transversal analysis of parties’ periodic reports on digital issues and trends’, accessed 22 January 2016 at http://es.unesco.org/creativity/sites/creativity/files/5CP_INF9_Digital_EN.pdf. Kunaver, M. and T. Požrl (2017), ‘Diversity in recommender systems – a survey’, Knowledge-Based Systems, 123 (May), 154–62. Lancaster, K. (1979), Variety, Equity and Efficiency: Product Variety in an Industrial Society, New York: Columbia University Press. Markowitz, H.M. (1952), ‘Portfolio selection’, Journal of Finance, 7 (1), 77–91. Masnick, M. and M. Ho (2014), The Sky Is Rising, Redwood City, CA: Floor64. De-Miguel-Molina, B., J.-L. Hervas-Oliver, R. Boix and M. De-Miguel-Molina (2012), ‘The importance of creative industry agglomerations in explaining the wealth of European regions’, European Planning Studies, 20 (8), 1263–80. Moreau, F. and S. Peltier (2004), ‘Cultural diversity in the movie industry: a cross-national study’, Journal of Media Economics, 17 (2), 123–43. Mulligan, M. (2014), The Death of the Long Tail: The Superstar Music Economy, London: MIDiA Consulting. Napoli, P.M. (1999), ‘Deconstructing the diversity principle’, Journal of Communication, 49 (4), 7–34. Nathan, M. and N. Lee (2013), ‘Cultural Diversity, innovation, and entrepreneurship: firm-level evidence from London’, Economic Geography, 89 (4), 367–94. Pariser, E. (2011), The Filter Bubble: What the Internet Is Hiding from You, New York: Penguin Press.

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Cultural diversity  191 Ranaivoson, H. (2007), Measuring Cultural Diversity: A Review of Existing Definitions, Paris: UNESCO. Ranaivoson, H. (2012), ‘Does the consumer value diversity? How the economists’ standard hypothesis is being challenged’, in M. Vecco (ed.), The Consumption of Culture, the Culture of Consumption. A Collection of Contributions on Cultural Consumption and Cultural Markets, Sarrebruck: Lambert Academic, pp. 70–95. Ranaivoson, H. (2016), ‘The Internet platforms’ impact on the diversity of cultural expressions: to the long tail, and beyond!’, in L.R. Hanania and Norodom and A.-T. Norodom (eds), Diversity of Cultural Expressions in the Digital Era, Buenos Aires: Teseo. Ranaivoson, H. (2019), ‘Online platforms and cultural diversity in the audiovisual sectors: a combined look at concentration and algorithms’, in L.A. Albornoz and T. García Leiva (eds), Audio-Visual Industries and Diversity Economics and Policies in the Digital Era, Abingdon: Routledge, pp. 100–118. Rochet, J.-C. and J. Tirole (2002), ‘Cooperation among competitors: some economics of payment card associations’, RAND Journal of Economics, 33 (4), 549–70. Rosen, S. (1981), ‘The economics of superstars’, American Economic Review, 71 (5), 845–58. Sobel, R.S, N. Dutta and S. Roy (2010), ‘Does cultural diversity increase the rate of entrepreneurship?’, Review of Austrian Economics, 23 (3), 269–86. Stenou, K. (2004), UNESCO and the issue of cultural diversity. Review and Strategy, 1946-2004. A study Based on Official Documents, Paris: United Nations Educational, Scientific and Cultural Organization. Stirling, A. (2007), ‘A general framework for analysing diversity in science, technology and society’, Journal of the Royal Society Interface, 4 (15), 707–19. Tan, T., S. Netessine and L.M. Hitt (2015), ‘Plenty is no plague, or is it? An empirical study of the impact of product variety on demand concentration’, working paper, accessed 22 January 2016 at http://papers.ssrn. com/sol3/Papers.cfm?abstract_id=2188354. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2001), Universal Declaration on Cultural Diversity, Paris: UNESCO. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2005), The Convention on the Protection and Promotion of the Diversity of Cultural Expressions, Paris: UNESCO. Van Cuilenburg, J. and R. Van der Wurff (2001), ‘Impact of moderate and ruinous competition on diversity: the Dutch television market’, Journal of Media Economics, 14 (4), 213–29. Vecco, M. and H. Ranaivoson (2017), ‘To what extent does cultural diversity support (cultural) entrepreneurship?’, unpublished manuscript. Zuiderveen Borgesius, F.J., D. Trilling, J. Möller, B. Bodó, C.H. de Vreese and N. Helberger, (2016), ‘Should we worry about filter bubbles?’, Internet Policy Review, 5 (1), 1–16.

FURTHER READING Ranaivoson (2007) provides an overview of the economic literature on the diversity of cultural expressions. In Stirling (2007), we can find a thorough definition of the Stirling model, and indexes that can be used to assess diversity. Van Cuilenburg and Van der Wurff (2001) provide a good overview of the impact of competition on diversity. For the impact of digitization on the diversity of cultural expressions, see Brynjolfsson et al. (2010) and Anderson (2006). The former is more rigorous from a scientific viewpoint; the latter is more accessible.

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21.  Cultural entrepreneurship Mark Blaug and Ruth Towse

Entrepreneurship is one of the most elusive and misunderstood concepts in modern economics; ironically, it has been largely ignored by many business economists, while the word is bandied about, often mistakenly, by others. Before discussing cultural entrepreneurship, therefore, it is worth considering the meaning and role of entrepreneurship as understood by economists.

A BRIEF HISTORY Richard Cantillon, an enigmatic Irishman with a Spanish name who spent much of his life in France, was the first to use the term in the modern sense in his Essai Sur la Nature du Commerce en Général, written around 1730 (Cantillon 1755 [2010]). Writing in French (hence the term entrepreneur), he held entrepreneurs to be responsible for bringing about competition in markets through risk-taking – they buy at a certain price and sell at an uncertain one. His contribution was to make it clear that the functions of the entrepreneur and the capitalist are distinct. The capitalist is the owner of capital and employs labour with the intention of obtaining a return on capital; the entrepreneur can ply his or her trade without either. In this perception, Cantillon was far in advance of Adam Smith. Smith did not make that distinction and he used the English terms ‘projector’ and ‘undertaker’ for the business proprietor, who combined the role of capitalist and manager. John Stuart Mill (1848) popularised the term entrepreneur in his Principles of Economics but retained the Smithian concept of his role. That view prevailed until the early twentieth century and the writing of Schumpeter. The Schumpeterian View Joseph Schumpeter was concerned with the ability of the capitalist system to develop through innovation, and he identified the innovator as the entrepreneur in his book The Theory of Economic Development (Schumpeter 1934). ‘Innovations’ in Schumpeter, as distinct from ‘inventions’, were the discovery of new technical methods, new products, new sources of raw materials and new forms of industrial organisation. He perceived innovation to be an inevitable force for the ‘creative destruction’ of the status quo that enabled economic development to take place. Entrepreneurship was therefore the source of dynamic change and growth, and its reward was profit. The entrepreneur might also be a capitalist or a corporate manager, obtaining reward for those activities too; indeed, Schumpeter realised that once a new undertaking was established, the business might settle down and lose its entrepreneurial thrust with the entrepreneur transformed into a mere capitalist or manager. The business would in the first place have a monopoly due to the entrepreneurial factor, and it would take further entrepreneurial effort to defend that monopoly. 192

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Cultural entrepreneurship  193 Modern Developments It took some time before the Schumpeterian view was adopted in modern economics. The neoclassical theory of the firm left no place for either the entrepreneur or the manager, and so it was left to those who did not subscribe to that theory to develop the notion of entrepreneurship. The neo-Austrians debated the nature of entrepreneurial profit, whether it was an income waiting to be serendipitously discovered through alertness to opportunities for Schumpeterian innovation, or whether it was the reward of positive action to create new sources of profit opportunities. Some economists questioned whether entrepreneurship is always beneficial to innovation and whether at times it is not just rent-seeking in the form of activities, such as company takeovers, tax-evasion efforts, patent litigation, and so on. Baumol (1990) distinguishes between productive and unproductive entrepreneurial activity, the latter being capable of reducing rather than increasing the social product, and argues that it is the overall rules of the game of a capitalist society that determine the precise nature of entrepreneurial behaviour. Nor is entrepreneurship confined to economic activity. In principle, it is performed in all societies by individuals whose judgement differs from the norm, and the political and military arena may provide as much scope for entrepreneurship as the economy.

CULTURAL ENTREPRENEURSHIP With these issues in mind, it is interesting to consider cultural entrepreneurship. Skimming through literature on creative industries that refers to cultural entrepreneurship (and there is a considerable volume of it) shows that many authors and organisations simply see it as part of management. The Global Center for Cultural Entrepreneurship, an international network of cultural entrepreneurs, has a view that is close to the economists’ concept. According to its website: ‘Cultural Enterprise Entrepreneurs are cultural change agents and resourceful visionaries who generate revenue from a cultural activity. Their innovative solutions result in economically sustainable cultural enterprises that enhance livelihoods and create cultural value for both creative producers and consumers of cultural services and products’ (Global Center for Cultural Entrepreneurship 2010). Cultural enterprises large and small include for-profit or non-profit enterprises that adopt a business approach and operate in the arts, heritage and cultural industries. Cultural entrepreneurs have specific attributes: passion, vision, leadership, resourcefulness and ‘market savvy’ (Global Center for Cultural Entrepreneurship 2010). Motivation for Cultural Entrepreneurship Although many entrepreneurs, including cultural entrepreneurs, have become wealthy, profit is not the motivation that drives them. Swedberg (2006) notes that according to Schumpeter, the entrepreneur is driven primarily by non-monetary motivation, such as building an empire, and struggles with outside and inner resistance to seize on novelty and carry projects through to their completion. In the spirit of Schumpeter, Swedberg (2006, p. 260) sees cultural entrepreneurship as the creation of something new and appreciated in the cultural sphere; inner, intrinsic motivation is the driving

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194  Handbook of cultural economics force. However, is that sufficient to explain the application of the term to every cultural enterprise? For-Profit and Non-Profit Enterprises Many of the creative industries, such as advertising, design, fashion, film, sound recording, broadcasting and publishing, consist of for-profit enterprises, often large international corporations, for which the measure of their success is profitability. Even small for-profit firms need to pursue sufficient revenues to cover their costs, though they may not be under the same pressure to maximise profits. Individual artists, who are highly innovative and entrepreneurial in their art, may not be seeking profit but may become wealthy. For non-profit enterprises, there is considerable variation in the adoption of businesslike behaviour. In the USA and the UK, non-profit cultural enterprises, such as museums and performing arts organisations, are generally reliant on their ability to appeal to consumers; with their mixed-economy model of private non-profit organisations, being entrepreneurial means a combination of artistic innovation and other strategies to attract more paying audiences, private donors and sponsors. In many countries in Europe, though, such organisations are state owned and managed bureaucracies, and cultural economists have frequently inveighed against their lack of response to consumers let alone to their tendency to create new ways of doing things. There is a big difference between exhorting cultural organisations to be less dependent upon state finance and to be entrepreneurial. As Minister of State for Culture in the Netherlands, the economist Rick van der Ploeg urged cultural entrepreneurship on the state-run cultural organisations, which at the time received 85 per cent of their revenues from subsidies (van der Ploeg 2006); Baumol’s rentseeking would seem more appropriate here, however. Acheson et al. (1996) claim that the non-profit status is no barrier to being entrepreneurial, even where subsidy is involved. Role of the Individual Schumpeter clearly identified the entrepreneur as an individual, a person of action, and the characteristics of cultural entrepreneurs – problem-solving leaders with passion and vision, alertness and energy, imagination and commitment – seem to stress the importance of individuality. Case studies of cultural entrepreneurs suggest that they were founders of cultural enterprises – builders of their own empires, with a strong personal and individual imprint.

CASE STUDIES OF CULTURAL ENTREPRENEURS Any list of famous cultural entrepreneurs should include, for theatre: William Shakespeare, one of the group of Elizabethan playwrights and actors who owned, built and managed theatres in London; in our own day, Andrew Lloyd Webber (Baron Lloyd-Webber of Sydmonton, listed as the eighty-seventh richest Briton in 2006), is the composer of a number of hit musicals and founder of The Really Useful Theatre Company, which owns a number of West End theatres in London, as well as companies holding the musical rights, publishing, making recordings and films of his theatrical productions.

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Cultural entrepreneurship  195 In art, Rembrandt van Rijn, dealt in art, ran a studio and made and sold etchings of his works but, nevertheless, became bankrupt; Peter Paul Rubens, who in addition to his prodigious commissions as an artist, ran a pay-on-entry workshop, dealt in art and pioneered print making of his works, for which he trained a number of engravers, from all of which he became very rich; similarly, in the twentieth century, Andy Warhol produced silk-screen prints on a commercial scale in the Factory in addition to original works of art and other undertakings, from all of which he became very rich. In music, the Italian opera impresarii (taken from impresa meaning enterprise or undertaking) commissioned new works (opera) from librettists (often well-known poets) and composers such as Bellini, Donizetti and Rossini (to name only a few that are still well known), made all the arrangements for producing them including hiring the singers, musicians, the costumes and sets, for which they had to put up considerable sums of money, and then toured them all around Italy and Europe and from Moscow to New York. This form of organisation carried on from around the mid-eighteenth century for well over 100 years until they were in effect put out of business by the music publisher, Giulio Ricordi, another superb cultural entrepreneur. Richard Wagner, who in addition to writing the libretti and music for his operas, revolutionised the production of opera though theatre design, conducting and dramaturgy. Richard D’Oyly Carte not only founded an opera company and commissioned Gilbert and Sullivan to write operettas for it, he also ran a concert agency (representing the singer Patti and the author Oscar Wilde) and, with the profits, financed the building of the Savoy Theatre and Hotel. Sergei Diaghilev, created the company Ballet Russes, organised its tours, commissioned a roster of ­composers – Debussy, Ravel, Satie, Prokofiev and most famously Stravinsky – hired Fokine as choreographer, legendary dancers such as Nijinski and Pavlova, and kept the company going until his death in 1929. Turning to the cultural industries, Walt Disney was an actor (the original voice of Mickey Mouse), animator, screenwriter and probably the best-known film producer and director in the world; in 2008, the Walt Disney Company had gross revenues of just under US$40 billion. In the Netherlands, Joop van den Ende, the Dutch billionaire theatre producer and media tycoon was co-founder of Endemol (and owner of the television rights to Batman among others); John de Mol, his partner in the enterprise, has the distinction of having invented the Big Brother and Deal or No Deal reality television formats, and has become very rich as a result. Also, let us not forget Steven Spielberg, film director and producer, and master of the modern blockbuster movie. Some of these people were artists who supplemented their own artistic work with other entrepreneurial activities; they were individuals and innovators in their arts. Others were mainly in the cultural business. They are all very well known and some, though not all, became rich. We could mention many, many more. However, where do we stop? Is Bill Gates a cultural entrepreneur because he created software, or Richard Branson because he started record companies and radio stations?

CONCLUSIONS In summary and to reiterate, an entrepreneur is not just a manager, although he or she may do a great deal of managing, since management may be hired in the labour market;

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196  Handbook of cultural economics nor is he or she a coordinator of production because, again, industrial engineering is available for hire in the marketplace; nor is he or she a capitalist, since capital funds can be borrowed at the going rate of interest in the credit market. Thus what characterises any form of entrepreneurship is the very quality that is the modus vivendi of dynamic change in an economy. Unless we empty the word entrepreneurial of all meaning, we must hang on to its distinguishing characteristics, namely, novelty of action, leadership, in the sense of being ahead of the pack, wealth-creating and individuality. It is difficult to see how large institutions and mammoth corporate entities can be both innovative and trail-blazing. A cultural entrepreneur is an innovator, usually but not necessarily an individual, who generates revenue from a novel cultural activity. Cultural entrepreneurs do much more than manage the activity; typically they discover it and exploit its revenue potentialities. They have the one quality that cannot be bought or hired, namely, alertness to revenuegenerating arbitrage, involving new products, new materials or new processes, or all of these in some combination.

SEE ALSO: Chapter 9: Business models; Chapter 15: Creativity; Chapter 19: Cultural districts.

REFERENCES Acheson, K., C. Maule and E. Filleul (1996), ‘Cultural entrepreneurship and the Banff Television Festival’, Journal of Cultural Economics, 20 (4), 321–39. Baumol, W.J. (1990), ‘Entrepreneurship: productive, unproductive, and destructive’, Journal of Political Economy, 98 (5), 893–921. Blaug, M. (1998), ‘Entrepreneurship in the history of economic thought’, in P. Boetke, I. Kirzner and M. Rizzo (eds), Advances in Austrian Economics, London: Jai Press, pp. 217–39. Cantillon, R. (1755), An Essay on Economic Theory, repr. 2010, Auburn, AL: Ludwig von Mises Institute. Global Center for Cultural Entrepreneurship (2010), website, accessed June 2010 at www.culturalentrepreneur. org. Mill, J.S. (1848), Principles of Political Economy with Some of their Applications to Social Philosophy, vol. 1, London: John W. Parker. Schumpeter, J. (1934), The Theory of Economic Development, Cambridge, MA: Harvard University Press. Swedberg, R. (2006), ‘The cultural entrepreneur and the creative industries: beginning in Vienna’, Journal of Cultural Economics, 30 (4), 243–62. Van der Ploeg, F. (2006) ‘The making of cultural policy: a European perspective’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1183–221.

FURTHER READING Blaug (1998) provides a detailed account and analysis of the development of entrepreneurship in the history of economic thought, and the website of the Global Center for Cultural Entrepreneurship (2010) spells out the features and tasks of cultural entrepreneurship.

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22.  Cultural statistics David Throsby

Statistics covering the volume and value of cultural output, levels of employment, cultural consumption and participation, public and private funding and so on are required for purposes such as: ●

describing the size of the cultural sector, its place in the economy and society, and the nature and extent of its functioning; ●● underpinning evidence-based policy formulation which depends both on raw data and on relevant analysis of those data; ●● monitoring and evaluation of the success or otherwise of cultural policies and programmes while they are being implemented or after they have been completed; and ● comparing various items of data using intra-nationally or internationally compar­ able statistics to assist, for example, in the benchmarking of performance standards. Cultural statistics that are useful for these purposes can be derived from three sources. First, official government statistical agencies that routinely gather and publish data on the economy and society are a major source of information about the arts and culture. The data they provide may occur as a subset of more general statistical collections, such as censuses, national accounts and workforce surveys, or they may be put together specifically for the arts and culture sector, perhaps by specialised units devoted to cultural statistics. Second, a number of independent bodies collect data of various types that may be relevant for policy purposes; for example, cultural observatories, university research institutes and private consultants carry out surveys, while national and international industry bodies and non-governmental organisations (NGOs) gather data from their members. Third, several international organisations publish data of relevance to the arts and culture, most notably the United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute of Statistics (UIS) which has a primary responsibility to collate and publish cultural statistics from the member states of its parent body. Other bodies such as the World Trade Organization and the World Tourism Organization include some reference to cultural goods and services in their statistical collections. The range of data types covered by the overarching term cultural statistics is very wide. This chapter discusses these various types and areas of application, paying particular attention to matters of definition and classification.

CULTURAL INDUSTRIES Statistical compilations for the cultural industries face two problems. The first is a definitional problem, raising questions such as: which industries are included? Are they creative or cultural industries? What product classifications are used? The specific industries regarded 197

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198  Handbook of cultural economics as either cultural or creative that are identified within national systems vary between countries, although there is broad agreement that the cultural industries include the arts and heritage, film, broadcasting and print media, audio-visual industries, publishing and design. Nevertheless countries differ in their interpretation of how far the terms cultural or creative extend, and, as a result, international comparisons of such statistics as the cultural industries’ contribution to gross domestic product (GDP) can be problematical. The second problem is to define the data series of interest for policy or other purposes. Conventional economic data that are routinely collected for all industries include gross value of production, contribution to GDP or gross national product (GNP), value added, fixed capital formation, and wholesale and retail prices, as well as trade and employment statistics. Data on these variables for the cultural industries can be extracted from the economy-wide statistics by imposing whatever cultural industry classification scheme is in use. It may then be possible to carry out inter-industry analyses at a macroeconomic level to examine the relationships between the cultural sector and the rest of the economy. Researchers undertaking these investigations use input–output analysis, computable general equilibrium models or a variety of other econometric methods.

INTERNATIONAL TRADE IN CULTURAL GOODS AND SERVICES Statistics on cultural trade have to rely on a workable product classification system rather than on industrial or other classifications, since the concern is with the actual movement of identifiable goods and services across national borders. Generally, the product classification systems in use do not display cultural goods or services as an identifiable category. Hence compilation of statistics on cultural trade has to rely on extracting the relevant numbers for the individual products covered by the particular definition of cultural goods and services in use, as is the case with the industry data discussed previously. The audio-visual industries give rise to a particular difficulty in measuring cultural trade. In earlier years, international transactions relating to movies or music, for example, could be readily observed since they involved the export and import of physical commodities – reels of film, cassette tapes and compact discs. With the advent of the Internet, trade in audio-visual product occurs increasingly across the World Wide Web; the material is transmitted in electronic form, as is payment for rights, royalties, and so on. Systematic tracking of these flows by national statistical agencies is generally not possible, so estimates of the volume and value of this trade have to be assembled from other sources, for example, from data provided by collecting societies which are responsible for the collection and distribution of copyright revenues. These data vary in their quality and coverage. Thus compiling a fully comprehensive and accurate statistical picture of cultural trade in all its various forms is almost impossible.

CULTURAL EMPLOYMENT Once again, issues of definition are raised when labour force statistics for the cultural sector are being derived. Questions arise such as: what is a cultural occupation? How is

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Cultural statistics  199 the creative workforce to be delineated? The answers to these questions are not as straightforward as it may appear. For example, a cultural worker could be defined as someone who works in a cultural industry, whether the work that person does is cultural (producing cultural output, such as writing poetry or acting) or non-cultural (such as selling tickets for a theatre company). Alternatively, a cultural worker could be more narrowly defined, for example, by limiting this category to artists or other creative workers. Thus a cultural occupation can be defined by reference not to the industry of employment, but to the nature of the work that occupation entails. In this case it may make for clearer definition to identify creative occupations instead of cultural occupations, since this terminology is related to a more easily recognisable input (creativity) than to a less easily observed output (culture). Even so, the designation of a set of creative occupations from the International Standard Classification of Occupations (ISCO) is not a simple matter, since it depends on how far the adjective ‘creative’ is deemed to extend. Therefore, different countries use different approaches to measuring cultural employment, the creative workforce or other similar categories. An illuminating representation of employment data for the cultural sector can be obtained by cross-tabulating creative/non-creative occupations against a cultural/noncultural industry classification for any given jurisdiction, to yield a two-by-two matrix in which three of the quadrants are of particular interest. This is the trident model of cultural labour market statistics, which allows an estimate of both creative and non-creative employment in the cultural sector, as well as of the numbers of creative workers who find employment in the rest of the economy. Adoption of this methodology depends on having an appropriate means for classifying which occupations are deemed to be creative.

ARTISTS Data about artists can be derived from two main sources. The first main data source, a population or labour force census, provides the most accurate information available on the size and characteristics of the population of workers within specific occupational categories. Given that in most countries’ censuses, standard occupational classifications are adopted which include various identifiable types of artists, in some cases down to quite a fine level of occupational disaggregation, these statistics have been useful in studying the extent and nature of the artistic workforce. However, they suffer from several important drawbacks. First, in most cases the allocation of an individual respondent to a job category is based on their main job at the moment of the census or survey; it is well understood that this procedure will overlook many genuine professional artists who are forced to take other work as a means of supporting their artistic practice, and who are therefore working at some other main job at the time of the data collection. Secondly, the categorisation of artist in these statistical collections does not distinguish professional from amateur; while it may be reasonable to assume professional status is attached to someone who declares their main job to be an artist, there is no way of knowing if these individuals would meet more refined criteria for professionalism. Thirdly, there may be problems in respondents’ understanding of what artist means as a job category when the data collection is based on self-evaluation. Finally, the descriptive data collected via censuses may be very limited in their capacity to enable analysis of the types of issues of

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200  Handbook of cultural economics interest to economic and sociological researchers. For example, economists are usually concerned to identify time allocation and corresponding earnings from arts work and from non-arts work, and even this two-way classification does not go far enough for many purposes. Income statistics for artists derived from census returns are thus problematical for economic analysis, and researchers who use census data to analyse the income position of artists, are inevitably limited in the conclusions they can draw. The second main data source comprises special-purpose surveys. Targeted surveys of artists can identify part-time as well as full-time workers, including those temporarily not working, and hence more accurate estimates of the size of artist populations can be obtained than are usually possible from a general census. If the category of interest in a particular study is professional artists, filters can be used to screen out amateurs from the sample or, in a broader study aimed at covering a range of types of practice, appropriate questions can be included to establish precisely the occupational status of respondents. The definition of artist is controllable by the researcher instead of being provided by census requirements or by self-evaluation. Most significantly, the quality and extent of data obtainable can be expected to be much richer in a specially targeted survey than in a general data collection, since the survey instrument is custom-designed to answer the precise questions of interest to the researcher. In particular, the researcher can match both time allocation and income data to what has become a standard classification of the three labour markets that professional artists supply: the market for their primary creative work; the market for arts-related work, such as teaching in their art form, which uses their creative skills and talents but does not yield original output; and the non-arts market to which artists must often turn in order to earn a survival income. Despite their attractiveness, however, there are some problems with sample surveys. First, the usefulness of their results for purposes of inference depends critically on the researcher’s capacity to identify the artist population of interest and to draw a statistically valid random sample from it. For some occupations, identifying the artist population may be relatively straightforward. For example, in many countries, actors or musicians tend to be unionised; therefore, with the cooperation of the union concerned, a researcher may be able to obtain a reasonably complete list of professional practitioners, together with contact details, from which to draw a sample. In other artistic occupations, however, such centralised lists may not exist, and a researcher may have to rely on building up a database by putting together lists from various sources and eliminating duplication. Even so, it may still be difficult to establish the overall size of the relevant artist population by these means, since the extent of those not included in the population list may not be readily estimated. In these circumstances, the use of techniques such as network sampling or respondent-driven sampling may enable extension of the sample to those groups not on the original list. A further problem with sample surveys as a methodology for deriving data about artists is that they are generally costly to administer. The ideal approach in this type of survey is via a personal interview with the artist, conducted either face to face or by telephone; the connection that can be established between interviewer and subject by this means can be expected to engage the artist’s interest directly and engender the trust that is necessary if sensitive information, for example about income, is to be disclosed. This is especially relevant since the derivation of reliable financial data is usually an important motivation for the survey. However, the cost of a personal approach may prove prohibitive if desired sample sizes are large. For this reason, an increasing use of more cost-effective methods

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Cultural statistics  201 such as online surveys is likely to be seen in the future. As experience in their application accumulates, it can be expected that these types of data collection procedures will be able to be further refined.

DEMAND FOR CULTURAL GOODS The volume and value of purchases by consumers of cultural goods and services are recorded in a variety of ways. These statistics may be obtained via household expenditure data or collected for specific categories of goods by commercial firms or by trade or industry associations. Examples of the latter include: ●

art market data collected and made available (usually at a price) by sales monitoring organisations; for instance, a wealth of data is available on the prices of artworks sold at auction by the major auction houses; ●● record industry data on sales of music in various formats collected by the International Federation of the Phonographic Industry (IFPI); these data include estimates of levels of piracy (sales of illegally copied music) in various countries; and ● data collected by publishers’ associations in various countries on the numbers and prices of different categories of books, magazines and newspapers sold. In some cases, special-purpose surveys of cultural consumption are undertaken by statistical agencies which provide a wide range of statistics on the artistic and cultural goods and services purchased by consumers. Cultural consumption can be tracked via household expenditure surveys, either carried out across all types of expenditure of which cultural spending is a part, or focused specifically on consumption of the arts and culture. Either way, consumer expenditure surveys – a standard means of regular data collection employed by most official statistical ­agencies – can yield a great deal of information about individual and household spending on culture in all its forms. Nevertheless, international comparisons of such statistics may be problematical; while data for particular items of expenditure may be compared, aggregate concepts such as total cultural spending will depend on the classification schemes used for cultural goods and services, which may or may not be comparable between countries.

ATTENDANCE AND PARTICIPATION The generic terms participation or involvement of people in the arts and culture cover a range of activities from passive attendance as an audience at a concert or a theatrical performance to active engagement in acting, dancing, creative writing, painting, musical performance, filmmaking, and so on. In surveys concerned with these latter activities, it is assumed they are undertaken voluntarily and on a non-professional basis for pleasure rather than reward. Despite the apparent clarity of a definition of participation along these lines, it remains a concept of some fuzziness, especially if international comparisons are involved. Nevertheless, sidestepping questions such as how active are apparently

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202  Handbook of cultural economics passive cultural pursuits such as reading or going to the opera, we can draw a pragmatic distinction between: ●

attendance as measured by surveys of audiences at cultural institutions or tabulated by the institutions themselves; ●● readership as indicated by surveys of book, magazine and newspaper purchases, library borrowings, and so on; ●● viewing and listening as assessed by television and radio ratings, and so on; ●● access to online cultural consumption that may be streamed, or downloaded and consumed subsequently, as measured by Internet tracking and other services; and ● creative involvement in active artistic and cultural activities of any type, such as writing a novel, singing in a choir, or painting landscapes, as documented in specialpurpose surveys. All these types of data, and more, can be gathered together under the generic heading of participation studies, of which there are many in existence.

CULTURAL FUNDING The implementation of cultural policy in all its many guises entails direct and indirect expenditure by government, the levels of which are reported in various ways in national accounting data. Although standardised formats exist according to which national governments present their accounts, there are many variations in detail between countries as to what is counted as cultural if, indeed, that adjective is used at all. Moreover it is not just at the national level that public funding of the arts and culture is important. Sub-national levels of government (states, counties, municipalities, cities, and so on) also provide funds to support the arts and culture through subsidies, grants, capital and operating allocations to cultural institutions, investment allowances, tax breaks, and so on. The formality and rigour by which these expenditures are recorded and published differ widely between jurisdictions, and in some countries it is difficult or impossible to aggregate cultural funding statistics across all tiers of government to obtain a comprehensive national picture. These variations both within and between countries make international comparisons of cultural funding extremely hazardous. Yet comparing the level of cultural funding per head is a favourite pastime in many quarters, even to the extent of constructing league tables of countries ranked in order of their apparent commitment to arts and cultural support. These comparative statistics suffer from three particular problems. First, as noted repeatedly in this chapter, different countries use different classification systems to assemble their data. Second, if the comparisons focus only on public-sector outlays, they neglect to account for what is likely to be a significant component of direct cultural support, namely, private finance given to artists and cultural organisations, either under sponsorship agreements or as no-strings-attached philanthropic donations. Finally, comparative statistics may fail to account for the cost to the public purse of indirect support measures such as the tax concessions allowed to donors for making gifts to the arts in cash or in kind. In some countries the tax revenue forgone via these concessions exceeds the cost to the budget of direct public expenditure on the arts.

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Cultural statistics  203

CULTURAL INDICATORS Indicators are statistics which go beyond simply describing some phenomenon. They are intended to imply something more; for example, to be used in conjunction with other data to monitor or evaluate some circumstance or process. They occupy an intermediate position between raw data, on the one hand, and analysis, on the other; that is, between the supply of information in the form of primary statistics and the demand for information for purposes of analysis and policy-making. Indicators can be either quantitative or qualitative in nature. Examples include: ●

a suite of statistics gathered together to indicate levels of cultural participation or enjoyment in the community or the population; ●● performance indicators for cultural institutions to indicate their success or otherwise in achieving designated goals; ●● quality-of-life indicators to demonstrate the artistic or cultural ambience of a city or region, or the cultural vitality of communities; ●● various data that can be taken as indicators of cultural development in a developing country; and ● indicators of cultural value for some artistic or cultural phenomenon, to be used when direct measures of cultural value are not available. A great deal of effort has gone into devising workable procedures for constructing and utilising indicators of various types, including cultural indicators. There is general agreement that good indicators should be firmly grounded in theory, linked to policy practice, and be relevant, unambiguous, measurable and easily understood.

SATELLITE ACCOUNTS FOR CULTURE Satellite accounts provide a representation of national accounting data for a particular field that is more detailed than that which is available from the normal national accounts. They in effect expand the System of National Accounts (SNA) that is used as a basis in most countries for the construction of statistics measuring aggregate economic activity, such as gross value of production, national income, capital transactions and foreign trade. Satellite accounts provide information on a range of macroeconomic data for a particular sector with greater product and industry specificity than would otherwise be available. Currently, the main areas of the economy for which satellite accounts have been put together are tourism and the environment, both sectors which are not represented in the national accounts by a single industry, but instead are made up of a number of interlinked areas of economic activity. The satellite accounts bring these disparate areas together into a single comprehensive framework, and allow more accuracy in estimating statistics such as the contribution of the sector to GDP, value added and employment. It is apparent that the cultural sector has the same conglomerate structure, and thus the idea of developing satellite accounts for culture arose, beginning more than 30 years ago with research carried out in Colombia under the auspices of the Convenio Andrés Bello, and complemented by developments in Europe, particularly at Statistics Finland. Since

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204  Handbook of cultural economics then, cultural satellite accounts have begun to appear in a number of countries, including in the United States and Australia, as well as in Latin America and Europe. A major project undertaken by the UIS is providing an overview of the area and a set of guidelines for statistical agencies interested in constructing a set of culture satellite accounts for their own economies. Given the wealth of reliable data that satellite accounts can provide, there can be no doubt that statistical bureaus and cultural agencies around the world are increasingly likely to turn to their application in deriving cultural statistics in the future.

CONCLUSION: PROVIDING A FRAMEWORK FOR CULTURAL STATISTICS There are a number of international standard classifications which provide individual countries with a template for the design of their own classification systems for statistics covering a range of economic variables, including industry, occupation and commodity classifications. In the specialised field of cultural statistics, a framework was put forward in 1986 by UNESCO that was intended to provide some consistency across jurisdictions in national statistical collections for the arts and culture. The framework guided the development of cultural statistics collections in many countries over a number of years. However, the social, economic and technological changes that have occurred since the 1980s have prompted the development of a new framework for cultural statistics by the UIS. The framework is not intended to be a blueprint that every country will follow, since different aspects of cultural statistics are of different importance in different countries. Instead it provides a coherent and consistent basis on which national systems of cultural statistics can be developed. To the extent that the framework is utilised in different jurisdictions, we can hope in future that stronger, more reliable and more internationally comparable cultural statistics will result. Finally, in any consideration of cultural statistics, it must be borne in mind that data are not collected just for their own sake, but to inform discussion and to enable analysis of the size, structure, interrelationships, causal connections, and so on, that characterise the cultural sector. The validity of these discussions and the strength of these analyses will depend critically on the quality of the statistics on which they are based, imposing a major responsibility on collection agencies to provide comprehensive and reliable statistics for the variety of users that they serve.

SEE ALSO: Chapter 5: Artists’ labour markets; Chapter 30: Google Trends data; Chapter 35: International trade; Chapter 45: Performance indicators; Chapter 52: Ratings, reviews and recommendations.

REFERENCES Heckathorn, D.D. and C.J. Cameron (2017), ‘Network sampling: from snowball and multiplicity to respondentdriven sampling’, Annual Review of Sociology, 43 (1), 101–19.

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Cultural statistics  205 Higgs, P.L. and S.D. Cunningham (2016), ‘Creative industries mapping: where have we come from and where are we going?’, in J.D. Potts (ed.), The Economics of Creative Industries, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 843–66. Madden, C. (2005a), ‘Indicators for arts and cultural policy: a global perspective’, Cultural Trends, 14 (3), 217–47. Madden, C. (2005b), ‘Cross-country comparisons of cultural statistics: issues and good practice’, Cultural Trends, 14 (4), 299–316. McCaughey, C. (2005), Comparisons of Arts Funding in Selected Countries: Preliminary Findings, Ottawa: Canada Council for the Arts. Mikić, H. (2012), Measuring the Economic Contribution of Cultural Industries: A Review and Assessment of Current Methodological Approaches, Montreal: UNESCO Institute for Statistics. Pattanaik, P. (1998), ‘Cultural indicators of well-being, some conceptual issues, in United Nations Educational, Scientific and Cultural Organization (UNESCO)’, World Culture Report: Culture, Creativity and Markets, Paris: UNESCO, pp. 333–40. Schuster, J.M. (1996), ‘The performance of performance indicators in the arts’, Nonprofit Management and Leadership, 7 (3), 253–69. Schuster, J.M. (2003), ‘Informing cultural policy – data, statistics, and meaning’, in S. Bernier and D. Lievesley (eds), Proceedings of the International Symposium on Culture Statistics: Montréal, 21 to 23 October 2002, Montreal: Government of Quebec, pp. 41–61. Schuster, J.M. (2007), ‘Participation studies and cross-national comparison: proliferation, prudence, and possibility’, Cultural Trends, 16 (2), 99–196. Throsby, D. (2010), The Economics of Cultural Policy, Cambridge: Cambridge University Press, ch. 14. Throsby, D. and K. Petetskaya (2017) Making Art Work: An Economic Study of Professional Artists in Australia, Sydney: Australia Council for the Arts. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2014), Culture for Development Indicators: Methodology Manual, Paris: UNESCO. United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics (2009), The 2009 UNESCO Framework for Cultural Statistics, Montreal: UIS.

FURTHER READING This chapter is an abridged and edited version of Chapter 14 ‘Cultural statistics’ in Throsby (2010). International comparisons of cultural industry classifications are contained in Mikić (2012); the perils and possibilities in making cross-national comparisons of cultural statistics are discussed in Madden (2005b), McCaughey (2005) and Schuster (2007). The trident model of cultural employment is outlined in Higgs and Cunningham (2016). An illustration of a comprehensive survey of practising professional artists is contained in Throsby and Petetskaya (2017); respondent-driven techniques and other sampling methods of use in some types of artist survey are reviewed in Heckathorn and Cameron (2017). For discussions of cultural indicators, see Schuster (1996, 2003), Pattanaik (1998) and Madden (2005a); an extensive example of the construction of cultural indicators is in UNESCO (2014). For details of the UNESCO Institute for Statistics’s (UIS’s) work on satellite accounts for culture, go to http://uis.unesco.org/en/topic/culture-satellite-account (accessed 6 May 2019). The 2009 UIS Framework for Cultural Statistics is described in detail in UNESCO Institute for Statistics (2009).

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23.  Cultural value Jen D. Snowball

While most people accept that the arts have value for society, not all would agree that this value is measurable, or that it should be measured. This chapter describes the types of value that the arts can provide and how at least some aspects of their value might be quantified.

WHY QUANTIFY THE VALUE OF THE ARTS AT ALL? One of the questions often asked of cultural economists is why we need to put a monetary value on the arts at all. Is it not possible to accept that the arts are valuable and so just agree to fund them publicly? If governments had unlimited funds, then this would certainly be enough, but in reality, limited public resources have to be allocated to all types of competing, and equally valid, needs, like education and healthcare. All funding decisions thus have an opportunity cost – the next best alternative foregone. That is, money spent on culture is money not available to be spent on anything else. In this scenario, the question is not simply one of whether to fund the arts or not, but of whether to fund the arts or something else. A related issue is which arts to fund. Thirty years ago, there was a general consensus that what should be funded was high culture – largely represented by European art forms, such as opera and ballet and fine art forms identified by experts – while popular culture was funded through the market by ticket sales and merchandising. Today, there is much less agreement on what constitutes culture or art. Puppet shows, street theatre and installations are considered just as valid as more traditional art forms. Expert valuations can help, but since publicly funded arts are paid for by the public, there is a growing need to take into account public sentiment about what makes up culture and the arts, and how they should be funded. Policy-makers are obliged to make funding decisions with the information to hand, whether it is quantitative or qualitative. The advantage of quantitative information is that it can be used to compare the benefits to society of various projects in order to make a socially efficient choice between them. Qualitative valuations are more difficult to compare, but may also have a role to play in measuring longer-term, socially constructed cultural values. The problem is how we quantify the benefits of culture to society so that the best decisions possible can be made. Measuring cultural value is often contentious, since most measurement techniques measure only part of the value. In general, they can be divided into stated preference methods (such as willingness to pay studies, subjective well-being studies and conjoint analysis), or revealed preference methods that make use of market prices (such as cultural satellite accounts, travel cost methods, hedonic pricing and the spatial analysis of cultural economic geography). 206

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Cultural value  207

INSTRUMENTAL AND INTRINSIC VALUES The arts have broadly two types of values: instrumental and intrinsic. Intrinsic value is the unique value of the arts themselves; it reflects the purpose of producing art in the first place. Instrumental values are those things that arise as side effects of the arts; not the main aim of the artistic endeavour, but nevertheless valuable. For example, the aim of a performing arts festival may be to celebrate the arts and culture of a particular region and to encourage artistic collaboration between local and international performers, to entertain, delight and inform audiences, and to lead to more and better quality productions – the intrinsic value of the festival. Side effects might include visitors coming to the region and spending on, for example, accommodation and food, job creation for providers of such services, spending to improve infrastructure and so on – regarded as instrumental values. Some artists, scholars and policy-makers suggest that the arts should not be quantified. This largely stems from a tendency of some studies to focus on the instrumental values of the arts and not on the intrinsic values. Instrumental values are often captured by some market transaction, with its value measured in terms of price, and are thus much easier to quantify than intrinsic values. By using well-tested methods, such as economic impact studies, a monetary value could be put on something like an arts festival, a museum, a library or a cultural heritage site. These measurements of impact became popular because of their ability to produce a single monetary amount which could be used, often effectively, for the promotion of a particular event or institution and to argue for public or private funds. Not surprisingly, however, there were vehement objections to such studies because the intrinsic value of the arts, their reason for existence in the first place, was completely excluded. One of the most popular methods for measuring the impact of a festival or cultural event on a host economy is the economic impact method. All events attract new money into the impact region (which could be a town, city, municipality or province) and create direct and indirect impacts. Direct impact is the result of the spending of visitors on goods and services, for example, accommodation, transport, food and drinks, and tickets. The indirect and induced impacts occur through the re-spending of the initial financial injection in the area and are commonly referred to as the multiplier effect. Economic impact studies attempt to answer the question, ‘If the event had not taken place, what would the loss of economic activity to the impact area have been?’ An economic impact study thus calculates all the additional economic activity that takes place in the region as a result of the event or festival. Economic impact studies work best as a valuation method when large numbers of tourists from outside the impact area come specifically to attend that festival or event. This is because normal expenditure by local residents should not be included, since their spending is likely to have occurred regardless of the event. The same applies to sponsorship from inside the impact area, since it is likely that, even if the event had not taken place, this money would still have been spent in the impact area on something else (Crompton et al. 2001; Crompton 2006; Snowball 2008). However, Warnick et al. (2015) argue that the spending of local residents and those who are not in the area primarily for the event (casuals) could still be included in a measure of the economic significance of the event.

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208  Handbook of cultural economics An interesting development in measuring the economic value of culture at a national level is the rise of the cultural and creative industries (CCIs) discourse. Various frameworks for defining the CCIs at a national level exist, but one of the most common is the United Nations Educational, Scientific and Cultural Organization (UNESCO) Framework for Cultural Statistics (FCS) (2009). The FCS defines the cultural industries in broad terms, including both the traditional, often non-profit sectors (such as museums, experimental theatre, libraries, music and dance), and the more commercial sectors that make use of cultural content (such as graphic design, advertising, podcasting and video games). The FCS divides the cultural industries into six main sections, or domains: cultural and natural heritage; performance and celebration; visual arts and crafts; books and press; audio-visual and interactive media; and design and creative services. Each domain includes all the cultural activities, goods and services related to that sector. Running across all the domains are transversal domains: intangible cultural heritage; education and training; and archiving and preserving. The real value in the FCS, however, is that it explains how to measure the economic value of the cultural industries using existing national-level data, such as the Standard Industrial Classification (SIC) and the International Standard Classification of Occupations (ISCO). The FCS thus allows us to estimate the size of the CCIs to gross domestic product (GDP) and employment creation at a national level, and (to a certain extent) compare these figures internationally, and track changes over time. The FCS has also helped to develop cultural satellite accounts, which use the system of national accounts that every country has to track the cultural sector’s GDP contribution and growth rates. Some authors have welcomed this approach to cultural valuation, arguing that the UNESCO’s FCS has helped to harmonise methods of cultural sector valuation so that international comparisons can be made, as well as tracking the sector over time in relation to overall economic growth and policy interventions. However, others have been far more critical of combining the traditional (or core) cultural sector with the more commercial periphery. A simple definition of the cultural industries is that they produce goods and services with symbolic value, while the creative industries produce goods and services that can be protected by intellectual property laws. Garnham (2005), for example, argued early on that the focus on the economic contributions of the cultural sector was simply an attempt by government departments of arts and culture to reposition themselves from being politically less important ‘ministries of fun’ to being seen as more serious contributors to national imperatives of economic growth and job creation. By putting the cultural and creative sectors in one category, their overall economic impact looks larger, but mostly owing to the contribution of the fast-growing areas in the audio-visual and interactive media, and design and creative services domains that include areas such as computer services and software development. In a paper produced for the National Endowment for Science, Technology and the Arts (NESTA), Bakhshi and Cunningham (2016) also object to the cultural and creative grouping, arguing that they need different policy interventions. Parts of the non-profit cultural industries are unlikely ever to be financially self-sustaining, and will always require public support. They produce goods and services that have intrinsic and symbolic value to society, beyond their financial impact, and often have a non-profit business model. The creative industries, however, are more productively seen as part of the knowledge economy, engaged in innovation, research and development, and content creation.

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Cultural value  209 Instead of financial public support, they require industrial policy-type support, related to enabling risk-taking and leveraging copyright. Bohm and Land (2008, p. 5) track the rise in interest of a new set of public instrumental values associated with arts and culture: ‘Creativity and innovation; Education, training, skills and employability, Social inclusion and community cohesion and (linked to this last category) Human and social capital’. These are also non-market values that can, perhaps indirectly, lead to economic growth, job creation and increased productivity. While not unproblematic to measure, these values are easier to track (using, for example, sets of cultural indicators) than the purely intrinsic values. A danger of representing the value of culture using only instrumental values is that these same effects might be provided equally well by other, non-cultural, industries. If opening a local supermarket creates more jobs than an arts festival, should the government subsidise the supermarket instead? If the mining sector has a greater effect on economic growth than the cultural industries, should public spending be focused on mining instead of culture? The answers in both cases are no: culture and the arts are not primarily about creating jobs or economic growth. If they ceased to be funded and no longer existed, not only the jobs and growth would be lost, but also their unique intrinsic values that could not be provided by other industries. As Seaman (1987, p. 54) notes, ‘Arts proponents are involved in a dangerous game when they resort to economic impact studies to prove their value. In a sense, they are choosing to play one of their weakest cards [that is, instrumental values], while holding back their aces [intrinsic values]’. Yet, it is often through the measurement of instrumental benefits that the value of the arts is represented because such studies are based on accepted research methods and rely on revealed preference data (for example, consumption behaviour or travel undertaken). More recently, social media has also provided a rich source of data in order to track what people do (their revealed preferences in cultural consumption or participation), instead of relying on stated preferences (what people say they do or value). For example, Lazrak et al. (2014) use data on the price of listed buildings in the historic Dutch area of Zaanstad to find indicators of the value of cultural heritage for cities. This valuation method is referred to as hedonic pricing, and is an indirect revealed preference method. The premise is that if a listed house (which has some historical cultural value) sells for more than a non-listed (modern) house, then (controlling for individual property characteristics, such as the number of rooms or size, traffic in the area, population density, distance from the city centre and so on) the difference in the price must represent an indirect measure of the value of the cultural heritage embodied in the listed house. Lazrak et al. (2014) examined the market price of listed (historical) buildings compared with those buildings not listed, and found that buyers are willing to pay an additional 26.9 per cent for a listed building (controlling for other property and location characteristics). They also show how we can use geographical information systems (GIS) data to measure the impact of historical neighbourhoods on the price of non-listed buildings nearby – a measure of the social value of heritage buildings. They find that modern houses do sell for more if they are in proximity to listed heritage buildings – 0.28 per cent for each additional listed building within a 50-metre radius. The finding provides evidence that the presence of heritage buildings provides some positive externalities (or spillovers) for the public, as well as private benefits for homeowners.

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210  Handbook of cultural economics Following the theories of Florida (2002) on the relationship between ‘the creative class’ and economic growth rates of cities, the field of cultural economic geography has emerged. This research often makes use of GIS mapping to combine economic and social data with information on the type and number of CCIs in particular locations in order to explore relationships between them. For example, Drummond and Snowball (2019) used census data to construct a socio-economic status index for rural municipalities in a particular district in South Africa. This was then combined with data on the number and type of CCIs in each municipality. Findings generally showed that those areas with higher socio-economic welfare were also those with a higher number of CCIs. While causality could not be determined (and is probably bi-directional), the findings are important for regional cultural policy development that seeks to use the cultural sector as a pathway to local economic development. These results could provide a rationale for regional cultural funding, but note that it relies solely on the economic instrumental values of the cultural sector, and not on any of their intrinsic, or even social, values. Some arts proponents argue that the arts are a special class of goods and services, and thus should be exempt from market valuations. However, it is not true that there is no possible way of measuring intrinsic value: Economics does offer effective non-market valuation methods which can go some way towards capturing this value. Contingent valuation (CV) methods use surveys to ask large samples of people about their consumption of cultural activities and whether they would be willing to pay (usually through an increase in taxes) to support them. While initially regarded with some scepticism, CV has become an accepted and widely used valuation technique that has been applied, not only to just about any cultural product one can think of, but also in other fields, such as environmental economics. For example, Tanguy and Kumar (2019) used a willingness to pay (WTP) study to determine the value of public art installation in a smart-city context. They aimed to determine to what extent people in two areas of London were willing to pay for public art initiatives, what factors influenced such values, and what the economic value of such projects is. The WTP method was chosen because public art is, by its nature, non-rivalrous (that is, its use by one person does not diminish its use by others) and non-excludable (once it has been provided, it is not feasible to restrict access through, for example, ticket purchases). The researchers conducted 469 interviews at the sites of the public arts installations. Their findings show that 83 per cent of people were willing to pay to support more public art installations in their area, with the average WTP being £4.73. Factors that increased WTP were living locally, agreeing that public art increased their well-being, and being a frequent visitor to art museums and galleries. However, even those who were not frequent art visitors were willing to pay something towards public art (Tanguy and Kumar 2019). A surprising finding of many of these studies is that it is not only those people who attend arts events, museums or heritage sites who are willing to pay to preserve or expand them; many non-users are willing to do so as well. This is because, in addition to the private benefits that the arts provide to people who have bought a ticket, they also provide public benefits to society at large.

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Cultural value  211

CULTURE AS A PUBLIC GOOD WITH LONGER-TERM, SOCIALLY CONSTRUCTED VALUE One of the most compelling arguments for the use of government funds to support the arts is their public-good nature. Public goods are special because, once they have been provided, they benefit not only their purchaser, but also the whole society. It has been argued that the arts can enhance national identity and pride and international prestige, provide ongoing education for children and adults, offer a critique of social policy, foster personal development, integrate individuals into society and encourage experimentation and the entrepreneurship that drives economic growth. It is thus not only those who purchase tickets to cultural events or who visit museums and heritage sites who benefit through their direct use values, but also people who do not directly consume the arts. While this is positive for society, it may lead to market failure and the under-provision of cultural goods since those who provide these goods are not able to recoup their value completely through market sales. A characteristic of public goods is that they are not completely appropriable by their supplier or by their purchaser. Therefore, the supply of cultural goods is likely to be below the socially optimal level, and the argument is that public (government) funds should be used to correct this by providing support to suppliers. Moving away from measuring the instrumental economic impact of arts and culture, measures of subjective well-being (also sometimes referred to as happiness studies) have been used to determine the effect of cultural consumption and participation on quality of life. This is a social survey valuation method that asks respondents to score their satisfaction with their overall quality of life and with various aspects of it (health, relationships, safety, community, and so on) on Likert scales. Subjective well-being measures can be seen as a proxy for the utility provided by various attributes and activities. Quality-of-life surveys include information on other respondent characteristics, such as demographic variables (age, income, race and gender), and activities, such as work, participation in community projects, arts and arts-related activities, sport, politics and leisure. The impacts of these variables on people’s self-rated quality of life can then be determined using regression analysis. Various authors (Michalos and Kahlke 2008; Wheatley and Bickerton 2017) have demonstrated that participation in arts and culture activities, particularly active and regular participation, have a statistically significant positive impact on overall quality of life, and on satisfaction with leisure time specifically. However, they also caution that the cause-and-effect mechanisms are not well understood, so a simplistic assumption that more art equals more happiness may be missing important parts of the story, such as the different motivations for attendance or participation, and the accessibility of arts, culture and heritage resources. It may also be that large cultural events or festivals may decrease life satisfaction. Research on the impact on the quality of life of people in European cities that had hosted the European Capital of Culture event showed that, although the economic impact on the city was positive, life satisfaction decreased, especially for lower income and education groups (Steiner et al. 2015). So, while one measure of value was rising, another was falling. Results were explained by noting the negative externalities often associated with large-scale events (rising prices, and increased congestion and crime). While those local

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212  Handbook of cultural economics residents who could afford to attend some of the cultural offerings would have had positive experiences to offset the negative externalities, lower-income groups were less likely to attend the cultural events but more likely to be negatively affected by rising prices, crime and congestion. This demonstrates the difficulty of combining different measures of cultural value – in this case, revealed preference methods (economic impact, measuring the instrumental value) and stated preference methods (quality of life, measuring intrinsic value). A potential problem with even the non-market valuation methods suggested previously is that they are based on random utility theory (RUT) which concerns perceptions of value by individuals. While RUT can take into account intrinsic values, it does so by creating an imaginary market in which individual people signal their value through their WTP. Klamer (2003), as well as many other economists, finds this approach problematic for cultural goods. He argues that individual ownership and valuation of culture makes little sense, since these values are constructed by society and can be changed. Throsby (1999) first introduced the idea of ‘cultural capital’, defined as a ‘long lasting store of value’ providing a stream of benefits to individuals and groups (Throsby 2001, p. 44). The concept is closely related to the intrinsic value of the arts – unique values provided by the art form itself. While economic or ordinary capital generated by arts and culture (the instrumental benefits) could also be supplied by other industries, cultural capital is that part of the value of culture that can only be provided by culture itself. As with other forms of capital, cultural capital can decay if it is not protected and enhanced, thus also eroding the stream of benefits it might have provided to future generations. Klamer (2002) argues that cultural capital should be included as part of a nation’s or individual’s wealth. Cultural capital may impact positively on (or underpin) other parts of the economy through, for example, developing creativity and experimentation, helping to develop a sense of identity and encouraging social cohesion. In modern economies, creativity and entrepreneurship are highly prized and often conceived as drivers of growth, as suggested by Florida (2002). Another form of capital that can arise from the arts and culture is social capital, related to the generation of social values, such as friendship and trust, and, at a national level, how a country is perceived by the outside world (cultural diplomacy). This type of capital is finding more acceptance with the recent revitalisation of institutional economics, which gives renewed importance to the role of socio-institutional networks in stimulating economic growth. Holden (2009, p. 453) gives an example of how culture can impact on foreign relations: ‘The way that a museum deals with objects from another country; or the fact that Israeli and Palestinian musicians can play together . . . become significant way beyond questions of aesthetics or artistic quality.’ These reasons for providing public support for the arts and culture are perhaps more compelling than those provided by individual non-market valuation methods (CV) or short-term financial impacts (economic impact studies). However, they are much more difficult to measure, and any attempt at measurement is likely to be qualitative and thus not directly comparable with other projects. Does this mean that they should not be measured? Take, for example, the National Arts Festival in South Africa. The festival was started in 1974 as an annual event, originally to celebrate the English culture of British settlers who came to South Africa in 1820. However, it quickly developed into a much more multicultural African festival and,

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Cultural value  213 during the dark days of Apartheid, played a significant role in resistance to government policies that deliberately sought to exclude and undermine the culture and art of black South Africans. The festival helped to maintain diverse cultural capital, built new cultural capital, provided a platform for political and social resistance and awareness, and was a forum for the judging (valuation) of South African art and culture by artists, agents and audiences. These values are unlikely to be captured by any market or non-market valuation method. An interesting trend in CV studies is the development and use of multidimensional valuation strategies. For example, the UK’s Cultural Value project was established in 2012 as a counter-response to a growing focus on the instrumental value of culture, which was particularly used to demonstrate value in order to obtain public funding (Crossick and Kaszynska 2014). The project deliberately focused on intrinsic value and the development of valuation indicators that start with ‘people’s experience of arts and culture, rather than secondary benefits that follow’ (Crossick and Kaszynska 2014, p. 123). Incorporating some of the ideas and themes from the Cultural Value project, the South African Cultural Observatory developed ‘A framework for the monitoring and valuation of publicly funded arts, culture and heritage’ (SACO 2016). The framework identified five value themes, linked to indicators and valuation methods (Figure 23.1) and was based on a review of the theory of cultural value, international best practice, and existing research on cultural valuations and valuation methods. It advances the idea that valuation should take a broad approach and be directly linked to the aims of the arts event or the institution itself (including social and intrinsic values) as well as providing quantitative information on instrumental values. As Brown and Novak-Leonard (2013, p. 231) note: ‘Impact measurement, broadly defined, may play a growing role in arts

Human capital and professional capacity building

Audience development and education

Inclusive economic growth

Cultural value

Social cohesion and community development

Reflective and engaged citizens

Source:  SACO (2016).

Figure 23.1  Cultural value themes identified in the SACO monitoring and evaluation framework

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214  Handbook of cultural economics policy in future years. The challenge lies in aggregating the individual level impacts in some fashion so as to help frame and inform a policy-level understanding of the public value of the arts.’ To conclude, culture provides many forms of value, some of which are easily measured in the market (the instrumental values) and some of which (intrinsic values) are much more of a challenge to quantify. However, it is not true that economic valuation of culture includes only instrumental values and is unaware of, or entirely unable to measure, intrinsic worth. The important thing to remember is that any one valuation method will only ever capture part of the value of culture, and a completely quantitative valuation is probably not possible. However, when difficult decisions about public (and private) funding allocations have to be made, some measures of the value of culture to individuals and society may be a very useful and powerful tool.

SEE ALSO: Chapter 10: Contingent valuation; Chapter 18: Cultural capital; Chapter 27: Economic impact of the arts.

REFERENCES Bakhshi, H. and S. Cunningham (2016), ‘Cultural policy in the time of the creative industries’, Nesta Provocation, London, accessed 10 November 2016 at https://www.nesta.org.uk/sites/default/files/cultural_ policy_in_the_time_of_the_creative_industries_.pdf. Bohm, S. and C. Land (2008), ‘No measure for culture? Value in the new economy’, accessed 13 November 2016 at http://repository.essex.ac.uk/1261/1/no_measure_for_culture_pre_pub.pdf. Brown, A. and J. Novak-Leonard (2013), ‘Measuring the intrinsic impacts of arts attendance’, Cultural Trends, 22 (3), 223‒33. Crompton, J. (2006), ‘Economic impact studies: instruments for political shenanigans?’, Journal of Travel Research, 45 (1), 67–82. Crompton, J., S. Lee and T. Schuster (2001), ‘A guide for undertaking economic impact studies: the Springfest example’, Journal of Travel Research, 40 (1) 79–87. Crossick, G. and P. Kaszynska (2014), ‘Under construction: towards a framework for cultural value’, Cultural Trends, 23 (2), 120–31. Drummond, F. and J. Snowball (2019), ‘Cultural clusters as a local economic development strategy in rural, small town areas: the Sarah Baartman District in South Africa’, Bulletin of Geography: Socio-Economic Series, 43, 107–19. Florida, R. (2002), The Rise of the Creative Class: And How It’s Transforming Work, Leisure, Community and Everyday Life, New York: Basic Books. Garnham, N. (2005), ‘From cultural to creative industries’, International Journal of Cultural Policy, 11 (1), 15‒29. Holden, J. (2009), ‘How we value arts and culture’, Asia Pacific Journal of Arts and Cultural Management, 6 (2), 447–56. Hutter, M. and D. Throsby (eds) (2008), Beyond Price: Value in Culture, Economics, and the Arts, Cambridge and New York: Cambridge University Press. Kabanda, P. (2018), The Creative Wealth of Nations, Cambridge: Cambridge University Press. Klamer, A. (2002), ‘Accounting for social and cultural values’, De Economist, 150 (4), 453–73. Klamer, A. (2003), ‘A pragmatic view on values in economics’, Journal of Economic Methodology, 10 (2), 1–24. Lazrak, F., P. Nijkamp, P. Rietveld and J. Rouwendel (2014), ‘The market value of cultural heritage in urban areas: an application of spatial hedonic pricing’, Journal of Geographical Systems, 16 (1), 89–114. Michalos, A.C. and P.M. Kahlke (2008), ‘Impact of arts-related activities on the perceived quality of life’, Social Indicators Research, 89 (2), 193–258. Rizzo, I. and A. Mignosa (eds) (2013), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar.

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Cultural value  215 Seaman, B.A. (1987), ‘Arts impact studies: a fashionable excess?’, in A.J. Radich (ed.), Economic Impact of the Arts: A Sourcebook, Washington, DC: National Conference of State Legislatures, pp. 43–76. Snowball, J. (2008), Measuring the Value of Culture: Methods and Examples in Cultural Economics, Berlin and Heidelberg: Springer-Verlag. South African Cultural Observatory (SACO) (2016), ‘A framework for the monitoring and evaluation of publicly funded arts, culture and heritage’, report commissioned from J. Snowball by the South African Cultural Observatory, accessed 18 November 2019at https://www.southafricanculturalobservatory.org.za/. Steiner, L., B. Frey and S. Hotz (2015), ‘European Capitals of Culture and life satisfaction’, Urban Studies, 52 (2), 374‒94. Tanguy, M. and V. Kumar (2019), ‘Measuring the extent to which Londoners are willing to pay for public art in their city’, Technological Forecasting and Social Change, 142 (May), 301–11. Throsby, D. (1999), ‘Cultural capital’, Journal of Cultural Economics, 23 (1), 3–12. Throsby, D. (2001), Economics and Culture, Cambridge: Cambridge University Press. Towse, R. (2014), An Advanced Introduction to Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2009), Framework for Cultural Statistics, accessed 7 December 2019 at http://www.uis.unesco.org/culture/Pages/framework-cultural-statis​ tics.aspx. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2015), Festival Statistics: Key Concepts and Current Practices, accessed 7 December 2019 at: http://www.unesco.org/new/en/media-services/ single-view/news/festival_statistics_key_concepts_and_current_practices/. Warnick, R., D. Bojanic and F. Xu (2015), ‘Using trade market analysis techniques to refine measurements for economic impact analysis of special events’, Journal of Travel Research, 54 (1), 52–65. Wheatley, D. and C. Bickerton (2017), ‘Subjective well-being and engagement in the arts, culture and sport’, Journal of Cultural Economics, 41 (1), 23–45.

FURTHER READING Beyond Price: Value in Culture, Economics and the Arts (Hutter and Throsby 2011) and Snowball (2008) discuss the theories of cultural value and the various ways in which cultural values can be measured, with examples of applications to cultural goods. An Advanced Introduction to Cultural Economics by Towse (2014) has a chapter on cultural festivals, including economic impact studies. A UNESCO (2015) report, Festival Statistics: Key Concepts and Current Practices, is also useful for those interested in festival valuation methods. The Handbook of the Economics of Cultural Heritage (Rizzo and Mignosa 2013) has a section (part 8) on the values and evaluation methods specifically for cultural heritage. The Creative Wealth of Nations (Kabanda 2018) discusses cultural value more broadly in a macroeconomic context, including the arts and education, international trade statistics and cultural tourism.

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24.  Demand

Jordi McKenzie and Sunny Y. Shin

This chapter reviews some of the main themes that studies of demand for cultural goods and services (hereafter, cultural products) have examined over recent years. In doing so, the intention is not only to review well-established features of demand that characterise cultural products but also to discuss less familiar issues that are increasingly being considered by researchers. In particular, these include (but are not limited to) the inherent uncertainty of demand for cultural products, the implications of globalisation for cultural products, and the impact of digitisation on consumption of cultural products more generally. Before doing so, however, it is useful to provide a definition of context. By cultural products, we refer to the broad range of products produced by cultural industries. These include, albeit not exhaustively, performing arts (for example, concerts), visual arts (for example, paintings), literary arts (for example, novels), as well as more mainstream cultural products intended for mass consumption, such as movies, television, music or books.1 However, we leave discussions about specifics of demand for visual arts (such as paintings, sculptures and other collectibles) for other chapters of this volume, as demand for these products follows a different conceptual model due to buyers’ non-hedonic motivation. It is not necessarily true that all cultural products are inherently different from ordinary products. Furthermore, it is also not true that all cultural products share the same fundamental characteristics which give rise to the particular features of demand we discuss in this chapter. With these caveats in mind, the chapter highlights some of the main directions that research into demand for cultural products have taken, without suggesting that these apply to the entirety of the cultural product spectrum. Researchers of cultural industries understand well that a one-size-fits-all approach to studying demand for cultural products makes no sense. In taking this approach, we also note that we have not covered all aspects of demand for cultural products and offer the disclaimer that this chapter is a selected review of demand for cultural products, rather than an exhaustive review of the literature. Furthermore, while we have attempted to cover a broad range of cultural products, our review necessarily leans towards cultural products that have had more research applications related to the themes we discuss. This is not to suggest certain categories of cultural products are more deserving of attention, but that for various reasons (for example, data availability) some types of cultural product have simply generated more research. We also believe that the specific features of demand of the cultural products we do discuss often apply more broadly across the spectrum of cultural products. The rest of this chapter is structured as follows. We first review some well-established themes that earlier demand studies have considered, in particular those that relate to the broad (or aggregate) demand for a specific type (or category) of cultural product, such as performing arts. We then turn our attention to demand for individual products within these categories. Given the implicit high level of differentiation between competing 216

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Demand  217 cultural products of a given type (for example, movies), how consumers make decisions between alternatives becomes an important question. In particular, we discuss (1) information asymmetry faced by consumers unable to judge quality prior to consumption, (2) demand for superstar products versus niche products, (3) demand for domestic versus imported cultural products (and implications for cultural policy), and (4) the broader impacts of digitisation on cultural consumption. In the final section we summarise and conclude.

ESTIMATION OF DEMAND AND CONSUMPTION CAPITAL Demand for cultural products can be viewed in many respects just like demand for ordinary products. That is, demand responds to prices (own and related) and income in the usual ways, and obeys other axioms associated with neoclassical consumer theory. Indeed, many of the earlier studies of demand investigated basic but necessary questions concerning such properties. However, researchers also realised there were some inherently distinct features of cultural products that made them different to other products and worthy of special attention. Basic microeconomics teaches us that demand is willingness (and ability) to consume a good or service. While these conditions are reasonable when considering the majority of consumer products, cultural economists have long known that those who are willing and able to consume high culture are not generally representatives of the wider population. Consumers of high culture (such as opera, theatre and classical music) are typically of higher socio-economic status with generally higher levels of income and education. Similar consumer profiles have been found across countries with a small variance in the performing arts (Seaman 2006). Even in the context of cinema, Collins and Hand (2005) find cinema-going increases in socio-economic status. The main objective of demand analysis is to provide estimates of (price and income) elasticities, and there is a well-established body of research in this area within cultural economics. By standard assumptions, cultural products are likely to be a luxury (or non-necessity) implying demand would be expected to be both price and income elastic. However, Seaman (2006), in his extensive review on demand for performing arts, reports mixed estimates of price and income elasticities and identifies issues in interpretation and data aggregation levels as a potential explanation of the mixed evidence. As better data sets and econometrics techniques develop, this area continues to be fruitful for research. Cultural economists have also long stressed the experiential aspect of consumption as a defining feature of demand for many cultural products. Related research has focused on acquired tastes derived from experiential consumption, as well as (potentially) increasing utility derived from repeated consumption. The origin of this latter idea is Stigler and Becker’s (1977) theory of rational addiction, which proposes that each consumption experience adds consumption capital that affects future consumption. Lévy-Garboua and Montmarquette (1996) develop a related model where consumers develop tastes through a process of learning by consuming such that each experience provides (positive or negative) information, which would be reflected in the future consumption decision.2 There have been numerous other studies based on similar models. Although specifics vary, they share a common structure in that demand is a function of consumption capital ­accumulated

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218  Handbook of cultural economics through previous consumption experiences. While not universal, many empirical studies have found positive effects of consumption capital, such as early exposure to the arts (or related education) on future cultural consumption (for example, Lévy-Garboua and Montmarquette 1996; Cameron 1999; Sisto and Zanola 2004, 2010). However, a notable consideration regarding the rational addiction theory of demand for cultural products is homogeneity versus heterogeneity in consumers’ preferences. In its basic form, Stigler and Becker’s (1977) model assumes preferences as given and identical across consumers. In this context, the theory explains the evolution of consumption only based on external conditions, which has led to some criticism of the model being applied to demand for cultural products. For example, Blaug (2001) considers the elitist profile of consumers for the arts itself as direct evidence of heterogeneous tastes among consumers.3 A more modern group of demand studies with origins in empirical industrial organisation have applied models specifically developed to capture heterogeneity among ­consumers to cultural products. In the context of the demand for movies, Davis (2006), Moul (2007), Einav (2007) and de Roos and McKenzie (2014) have all applied discrete choice (logit) models of demand that permit consumer heterogeneity. Other recent studies of demand have considered heterogeneous tastes by identifying latent classes of consumers using survey data (Ateca-Amestoy 2008; Grisolía and Willis 2012; Ateca-Amestoy and Prieto-Rodríguez 2013; Baldin and Bille 2018), as well stated-preference methods using choice experiments (Grisolía and Willis 2016; McKenzie et al. 2019). Beyond simply capturing (and identifying) heterogeneous types of consumers, demand studies such as these allow more refined estimation of elasticities than those presented in earlier studies.

DEMAND UNDER UNCERTAINTY AND INFORMATION ASYMMETRY Consumption of many cultural products comes in the form of experience. That is, the quality (hence utility) are largely uncertain prior to consumption. As a result, consumers face an asymmetric-information problem they attempt to solve by seeking quality-related information prior to consumption. In addition, many cultural products are characterised by high levels of product differentiation and short product cycles, which implies high search costs for quality-related information. This said, demand for any specific cultural product depends on the amount and type information that the consumer is able to access. Uncertainty permeates not only consumption but also the ability of producers to predict consumption. Whereas consumers are uncertain about product quality, producers are uncertain about demand for their products. When large up-front investments are required (for example, movie production), there has to be a reasonable expectation that the final product will generate sufficient demand to recoup the investment, or even earn a profit. Ostensibly, however, ‘nobody knows’ how consumers will judge the quality of a new cultural product, making demand highly unpredictable (Caves 2000). It is almost impossible for the producer of a cultural product to overcome such uncertainty. Gatekeepers in cultural industries have long understood the inherent challenges arising from demand uncertainty and have sought various ways to signal quality to consumers. The most obvious strategy is advertising (broadly defined), providing potential consumers with a set of information signals about quality.4 For example, producers in the performing

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Demand  219 arts and audio-visual industries may employ the services of a star as a signal of quality (see, for example, De Vany and Walls 1999, 2004; Ravid 1999; Elberse 2007; Han and Ravid 2019). The effect of a star on demand for a product has been considered in many empirical studies but findings are mixed potentially owing to varying ways of measuring star power (McKenzie 2012). The producers may also choose to produce an adaptation or franchise product, which similarly serves as a signal of quality for the uncertain consumer. For example, sequel films are reported to perform better in relation to box office revenue when compared with non-sequel films, although they do not perform as well as their parent films (Basuroy and Chatterjee 2008; Dhar et al. 2012). Quality-related information provided by suppliers does not entirely resolve the asymmetric information problem. Faced with remaining uncertainty, consumers will consult other sources of information – primarily in the form of professional or industry certification of some type (for example, critics reviews or awards/nominations) and/ or the opinions of other consumers (such as traditional word of mouth or online user reviews) – to assist consumption decisions. Empirical studies generally agree on the positive correlation between a favourable expert review and demand (or commercial success) of a cultural product (for example, Abbé-Decarroux 1994; Eliashberg and Shugan 1997; Reinstein and Snyder 2005; Berger et al. 2010). The role of awards and nominations in cultural industries has been found to be a strong predictor of sales in empirical studies conducted for various art forms; for example, Ashworth et al. (2010) for novels, Boyle and Chiou (2009) for musicals, Nelson et al. (2001) for movies, Ginsburgh (2003) for movies, books and music, and Ponzo and Scoppa (2015) for books. Other consumers’ opinions are another source of information to which the consumer can turn in order to obtain quality-related information. The importance of word of mouth (or user reviews in the online world) in the success of cultural products has been studied extensively in both marketing and management literature and has increasingly been recognised in cultural economics. It has also been noted that the emergence of online social networks has altered the way in which information transmission occurs, and research interest has been increasingly focused on consumers’ online activities (for example, Chevalier and Mayzlin 2006; Duan et al. 2008; Oh et al. 2017). By observing user scores and reviews, this approach permits direct observation of volume and valence of (online) information transmission. This contrasts with (interpersonal) word-of-moth studies where information transmission has generally been inferred from analysing sales dynamics within a broader model of demand (for example, De Vany and Walls 1996; Moul 2007).

DEMAND FOR SUPERSTARS VERSUS NICHES For cultural products with demand largely dependent on information transmission, there are infinite possible ways a product’s lifecycle may evolve. The complex dynamics give rise to large variance in demand outcomes; so much so that sales distributions of many cultural products tend to exhibit unusual properties that do not resemble the normal distribution in any way. Notably, superstar products reside many standard deviations above the mean (often more than ten), which leads to significantly right-skewed distributions. Sometimes referred to as the ‘winner-take-all’ effect (Frank and Cook 1995), the phenomenon has

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220  Handbook of cultural economics been widely discussed in scholarly works on films (for example, Walls 2010; FernandezBlanco et al. 2013), recorded music (for example, Strobl and Tucker 2000; Connolly and Krueger 2006; Pitt 2010) and books (for example, Gaffeo et al. 2008; Berger et al. 2010).5 It has also been studied in other cultural industries, including performing arts (Kulmatitskiy et al. 2016), visual arts (Candela et al. 2016) and video games (Cox 2014). On first inspection one might assume the winner-take-all distribution is simply due to a higher general quality of superstar products relative to those of more mediocre appeal, and that consumers have simply made rational choices based on ex ante quality judgement. However, researchers argue otherwise for at least three reasons. First, a superstar product does not necessarily need to be of significantly greater quality to become a superstar. The seminal contribution regarding this idea is Rosen (1981, p. 846) who explains how small differences in artists’ talent translate to enormous differences in earnings because ‘lesser talent often is a poor substitute for greater talent’. While this work was primarily concerned with artists’ income, a similar principle can be applied to cultural products (McKenzie and Smirnov 2018). Rosen’s theory is that a consumer given the choice between two similar cultural products with a small (but non-zero) difference in quality will almost always select the product of higher quality. In this way, small differences in quality translate to large differences in eventual demand. The second possible reason why superstar products are not necessarily of significantly higher quality is that consumers may follow others’ decisions, ignoring their own quality signals. In this respect, small differences in quality (or signals of quality) again become amplified, but by a process of path dependency in consumption. For example, consumers may ‘herd’ (Banerjee 1992) towards bestsellers because they believe bestsellers possess qualities that they are not (yet) aware of. Relatedly, consumers may choose a bestseller over another with mediocre sales owing to an information-cascade effect (Bikhchandani et al. 1992) if their own (subjective) quality judgement between two products is close. The theoretical predictions implied by these seminal contributions have been empirically examined by a number of researchers (for example, De Vany and Lee 2001; Moretti 2011; Cabral and Natividad 2016). The third reason superstar products may not arise from differences in quality alone relates to many cultural goods that are subject to network externalities (Rohlfs 1974). People are inherently social, and consumers receive utility not only from consuming the cultural product itself, but also from consuming the shared experience of consumption with others. This implies utility increases as the number of consumers consuming the same product increases, which implies a similar dynamic to those discussed previously but for entirely different reasons. In another seminal contribution, Adler (1985) argues that superstars need not be the most talented because consumers’ choice is also rooted in the desire to discuss with other individuals. In a recent empirical study, Gilchrist and Sands (2016) observe network effects in the (theatrical) performance of films, in addition to social-learning effects such those discussed previously. Given these arguments, the winner-take-all outcomes observed in cultural industries can arise as a result of information transmission and/or network externality effects, rather than as a result of (significant) quality differences. This phenomenon can be traced back to the asymmetry of information and the inherent uncertainty of the experiential aspect of a cultural product. In this way, the nobody-knows and winner-take-all principles are intimately connected.

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Demand  221 However, while the winner-takes-all model has proved enduring over time and across industries, the rise of digitisation (and associated cost reductions in production and distribution) has led to a phenomenon that is potentially at odds with this well-established result. Popularly known as the ‘long-tail’ theory, Anderson (2006) stressed the increasing importance of niche products altering the shape of sales distributions of digitised products such as recorded music and movies. His argument can be understood in two parts. First, many of the niche products that would have not been displayed in brick-andmortar stores now can occupy a space in the online market with unlimited virtual shelf space, such as Amazon.com or iTunes, which elongates the tail of sales rankings (that is, more low-ranked products). Second, consumers facing lower search costs, and tailored recommendations would then migrate from superstar products to niche products, which would attenuate the skew (and heavy right tail) of sales distribution. The idea is compelling as emergence and consumption of long-tail products implies an improvement in consumer surplus and potentially market efficiency. It is particularly appealing to many cultural economists as the long-tail products could also suggest an improvement in cultural diversity and not just an increase in product diversity. Research examining the long-tail hypothesis against the theory of superstar products, or the effect of increased product variety on the market in general, has been growing since the introduction of the idea. The first part of the long-tail theory is easy to confirm observing data and no study denies that online shelves carry much higher number of products in comparison to brick-and-mortar stores. Related studies confirm and measure consumer benefits derived from increased product availability (Brynjolfsson et al. 2003, 2011; Aguiar and Waldfogel 2018a). However, the jury is still not entirely convinced with the second part of the long-tail story. Despite the increased number of choices available to consumers, a number of researchers have observed that sales are still increasingly concentrated towards superstar products (Elberse and Oberholzer-Gee 2008; Kumar et al. 2014; Benghozi and Benhamou 2019). One possible explanation that supports the winner-takes-all model, relates to the way in which information is shared in a digital world. Social media in particular has transformed the way in which people interact and share information about cultural products. In this environment, people recommend and discuss cultural products and derive utility from these interactions. While network effects have always existed, the digital age has almost certainly increased the relevance of these interactions for a product’s ultimate success. We continue a discussion of digitisation below.

GLOBALISATION, CULTURAL DISCOUNTING AND POLICY IMPLICATIONS Although the long tail offers consumers more variety than ever before (both within and across classes of cultural products), how much these niche products are valued by consumers is not known a priori. This may be especially true if the products residing in the long tail are foreign and additionally subject to a cultural-discount effect. Cultural discounting refers to the tendency for consumers to value the products from unfamiliar cultures less than those more familiar cultures. The term was originally coined by Hoskins and Mirus (1988) in explaining US dominance in the television programme industry.

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222  Handbook of cultural economics Cultural discounting can be interpreted as a trade barrier inherent on the demand side and is regarded as a peculiarity in international trade of cultural products (Iapadre 2014). It is not conventionally discussed within the boundary of demand for cultural products, but separately within the topic of international trade. However, we believe it deserves some discussion in this chapter because it is inherently a demand issue and an important determinant of demand for individual cultural products, especially given the rapidly growing relevance of imported cultural products in the era of globalisation and digitisation. Cultural discounting is a concept related to consumers’ preferences and is therefore difficult to measure directly. Empirical studies typically infer the existence of cultural discount by observing revealed preference outcomes. For example, Lee (2006) examines the performance of Hollywood films in Hong Kong and finds that film genres subject to lower cultural discount (such as science fiction) perform better than those subject to higher cultural discount (such as comedies). Moon et al. (2015), using South Korean data, find that consumers have a lower expectation and lesser knowledge prior to the release of a foreign film in comparison with a domestic film. An important feature of cultural discounting is asymmetry, which is the phenomenon that the appreciation of cultures between two countries is not necessarily mutual. For example, it could be reasonably argued that American consumers discount Australian cultural products more than Australian consumers discount American cultural products. The asymmetric nature of cultural discounting has been proposed as a potential explanation of why the global consumption of arts and entertainment has concentrated towards English-speaking and/or Anglo-American cultures (Hoskins and Mirus 1988; Shin and McKenzie 2019). Related studies proposed a couple of conjectures of how consumers came to apply lower cultural discount rates for the more dominant cultures, which relate to the discussions of previous sections. Schulze (1999), following the theory of rational addiction, notes that the asymmetric cultural discount can be a result of the historically asymmetric exposure of consumers between American and non-American cultural products. Another explanation is found in Rauch and Trindade (2009) who explain the demand concentration towards products from dominant cultural products based on consumption network externalities, through which consumers receive more utility from consuming a product reflecting dominant and popular cultures. The idea that cultural discount can evolve through exposure to certain cultural products and network externalities presents one argument in favour of policy support for domestic cultural production. It is often argued that cultural products represent an example of merit goods. A merit good is deemed to hold value for society even if the market may fail to provide it at an efficient level. In many countries, public support for the arts and creative industries exists to allow citizens to benefit from provision of cultural products that might otherwise not be provided. In some industries, for example, television and film, this support enables local producers to create content that may not be privately efficient, with forces such as (asymmetric) cultural discounting working against them. Although arguments in favour of this type of support are compelling, the form of such support and the metrics by which to evaluate its effectiveness are less clear. See, for example, Jansen (2005), Fernández-Blanco and Gil (2012), Teti et al. (2014) and McKenzie et al. (2019).

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Demand  223

DIGITAL DISRUPTION AND DEMAND FOR CULTURAL PRODUCTS The digital revolution has transformed (and continues to transform) cultural industries in various ways. In industries such as music, television and film, production and distribution costs have fallen significantly, allowing new content producers to enter the domain that historically was protected by gatekeepers. While the supply of cultural products in these industries has undeniably increased (Waldfogel 2017), digitisation has in parallel changed the way in which consumers access this content. This has implication for understanding demand for cultural products more generally. Since the arrival of the Internet, new technologies and platforms have also emerged and dramatically altered how consumers engage with cultural content. In the music industry, iTunes paved the way before streaming services such as Pandora and Spotify redefined how consumers enjoy music (Aguiar and Waldfogel 2018b). In the television and film industries, Netflix and other video-on-demand services have created challenges for traditional terrestrial television, as well as movie cinemas (McKenzie et al. 2019). In the book industry, the arrival of e-books and devices such as the Kindle have similarly challenged the traditional model, in this case print publication (Chen et al. 2018). All these disruptions have implications for the quantity and type of cultural products being consumed. Beyond the (intra-industry) digital substitutes for traditional forms of cultural products, new types of cultural products have arrived as a direct result of the digital renaissance. In particular, social media and online gaming provide alternative ways for consumers to spend leisure time that may previously have been spent on other forms of cultural consumption. While the consumer has more alternatives than ever before, producers of cultural products competing in the digital space are having to stay responsive to the rapidly evolving landscape. To the extent that these new products also (perhaps weakly) substitute ‘higher’ forms of cultural consumption (for example, theatre or opera), the digital revolution is potentially impacting demand for cultural products indirectly as well.

CONCLUDING REMARKS Demand studies on cultural industries have been evolving. Earlier studies in cultural economics explored basic but necessary demand-related questions such as profiles of consumers, and price and income elasticities, mainly focusing on estimation of demand for a category of products, such as performing arts or cinema. Other early studies highlighted the experiential aspect of consumption and the cumulative nature of consumption capital as defining idiosyncrasies of cultural demand. More recently, demand studies on cultural industries have evolved with researchers generally more focused on single (differentiated) cultural products instead of broad categories of cultural products. This has been achieved by applying wider conceptual models related to information asymmetry, superstar theory and cultural discounting with increasingly more sophisticated econometric techniques. This evolution has also benefited from increasing availability of micro-level data sets on sales transactions of cultural products. This has also enabled cultural industries to be more attractive to researchers in cognate (sub)-disciplines, such as industrial organisation, marketing and management.

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224  Handbook of cultural economics

NOTES 1. In some contexts, in the past, only the latter are referred to as cultural industries. 2. See Lévy-Garboua and Montmarquette (2011) for more detailed discussion on the theories of rational addiction and learning by consuming. 3. Also see Cowen (2002). 4. Throsby (1990) and Abbé-Decarroux (1994) are the examples of earlier demand studies that explore the role of consumers’ perceived quality on demand using prior-consumption information such as cast, genres, mass/niche appeal and so on. 5. See also Walls (2014) for superstar effects in movies, music and books.

SEE ALSO: Chapter 23: Cultural value; Chapter 25: Digital piracy; Chapter 44: Participation; Chapter 49: Pricing the arts.

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Demand  225 Caves, R.E. (2000), Creative Industries: Contracts between Art and Commerce, Cambridge, MA: Harvard University Press. Chen, H., Y.J. Hu and M.D. Smith (2018), ‘The impact of e-book distribution on print sales: analysis of a natural experiment’, Management Science, 65 (1), 19–31. Chevalier, J.A. and D. Mayzlin (2006), ‘The effect of word of mouth on sales: online book reviews’, Journal of Marketing Research, 43 (3), 345–54. Collins, A. and C. Hand (2005), ‘Analyzing moviegoing demand: an individual-level cross-sectional approach’, Managerial and Decision Economics, 26 (5), 319–30. Connolly, M. and A.B. Krueger (2006), ‘Rockonomics: the economics of popular music’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 667–719. Cowen, T. (2002), ‘Are all tastes constant and identical?’, Journal of Economic Behavior & Organization, 11 (1), 127–35. Cox, J. (2014), ‘What makes a blockbuster video game? An empirical analysis of US sales data’, Managerial and Decision Economics, 35 (3), 189–98. Davis, P. (2006), ‘Spatial competition in retail markets: movie theaters’, RAND Journal of Economics, 37 (4), 964–82. De Roos, N. and J. McKenzie (2014), ‘Cheap Tuesdays and the demand for cinema’, International Journal of Industrial Organization, 33 (1), 93–109. De Vany, A. and C. Lee (2001), ‘Quality signals in information cascades and the dynamics of the distribution of motion picture box office revenues’, Journal of Economic Dynamics and Control, 25 (3–4), 593–614. De Vany, A. and W.D. Walls (1996), ‘Bose-Einstein dynamics and adaptive contracting in the motion picture industry’, Economic Journal, 106 (439), 1493–514. De Vany, A. and W.D. Walls (1999), ‘Uncertainty in the movie industry: does star power reduce the terror of the box office?’, Journal of Cultural Economics, 23 (4), 285–318. De Vany, A.S. and W.D. Walls (2004), ‘Motion picture profit, the stable Paretian hypothesis, and the curse of the superstar’, Journal of Economic Dynamics & Control, 28 (6), 1035–57. Dhar, T., G. Sun and C.B. Weinberg (2012), ‘The long-term box office performance of sequel movies’, Marketing Letters, 23 (1), 13–29. Duan, W., B. Gu and A.B. Whinston (2008), ‘The dynamics of online word-of-mouth and product sales-an empirical investigation of the movie industry’, Journal of Retailing, 84 (2), 233–42. Einav, L. (2007), ‘Seasonality in the U.S. motion picture industry’, RAND Journal of Economics, 38 (1), 127–45. Elberse, A. (2007), ‘The power of stars: do star actors drive the success of movies?’, Journal of Marketing, 71 (4), 102–20. Elberse, A. and F. Oberholzer-Gee (2008), ‘Superstars and underdogs: an examination of the long-tail phenomenon in video sales’, Working Paper No. 07-015, Harvard Business School, Boston, MA. Eliashberg, J. and S.M. Shugan (1997), ‘Film critics: influencers or predictors?’, Journal of Marketing, 61 (2), 68–78. Fernández-Blanco, V. and R. Gil (2012), ‘Underneath the red carpet: government intervention in the Spanish movie industry’, Journal of Media Economics, 25 (1), 54–72. Fernandez-Blanco, V., L. Orea and J. Prieto-Rodríguez (2013), ‘Endogeneity and measurement errors when estimating demand functions with average prices: an example from the movie market’, Empirical Economics, 44 (3), 1477–96. Frank, R.H. and P.J. Cook (1995), The Winner-Take-All Society, New York: Penguin Books. Gaffeo, E., A.E. Scorcu and L. Vici (2008), ‘Demand distribution dynamics in creative industries: the market for books in Italy’, Information Economics and Policy, 20 (3), 257–68. Gilchrist, D.S. and E.G. Sands (2016), ‘Something to talk about: social spillovers in movie consumption’, Journal of Political Economy, 124 (5), 1339–82. Ginsburgh, V.A. (2003), ‘Awards, success and aesthetic quality in the arts’, Journal of Economic Perspectives, 17 (2), 99–111. Grisolía, J.M. and K.G. Willis (2012), ‘A latent class model of theatre demand’, Journal of Cultural Economics, 36 (2), 113–39. Grisolía, J.M. and K.G. Willis (2016), ‘Consumer choice of theatrical productions: a combined revealed ­preference – stated preference approach’, Empirical Economics, 50 (3), 933–57. Han, S. and S.A. Ravid (2019), ‘Star turnover and the value of human capital – evidence from Broadway shows’, Management Science, doi: 10.1287/mnsc.2018.3177. Hoskins, C. and R. Mirus (1988), ‘Reasons for the US dominance of the international trade in television programmes’, Media, Culture & Society, 10 (4), 499–515. Iapadre, P.L. (2014), ‘Cultural products in the international trading system’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsterdam: North-Holland, pp. 381–409.

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226  Handbook of cultural economics Jansen, C. (2005), ‘The performance of German motion pictures, profits and subsidies: some empirical evidence’, Journal of Cultural Economics, 29 (3), 191–212. Kulmatitskiy, N., J.S. Simonoff, L.M. Nygren, J. Cao and K. Nygren (2016), ‘Survival of Broadway shows: an empirical investigation of recent trends’, Communications in Statistics: Case Studies, Data Analysis and Applications, 1 (2), 114–24. Kumar, A., M.D. Smith and R. Telang (2014), ‘Information discovery and the long tail of motion picture content’, MIS Quarterly, 38 (4), 1057–78. Lee, F.L.F. (2006), ‘Cultural discount and cross-culture predictability: examining the box office performance of American movies in Hong Kong’, Journal of Media Economics, 19 (4), 259–78. Lévy-Garboua, L. and C. Montmarquette (1996), ‘A microeconometric study of theatre demand’, Journal of Cultural Economics, 20 (1), 25–50. Lévy-Garboua, L. and C. Montmarquette (2011), ‘Demand’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 177–89. McKenzie, J. (2012), ‘The economics of movies: a literature survey’, Journal of Economic Surveys, 26 (1), 42–70. McKenzie, J. and V. Smirnov (2018), ‘Blockbusters and market expansion: evidence from the motion picture industry’, Journal of Cultural Economics, 42 (2), 341–52. McKenzie, J., C. Rossiter and S.Y. Shin (2019), ‘For love or money? Assessing outcomes from direct public investment in film’, International Journal of Cultural Policy, doi: 10.1080/10286632.2018.1554652. McKenzie, J., P. Crosby, J. Cox and A. Collins (2019), ‘Experimental evidence on demand for “on-demand” entertainment’, Journal of Economic Behavior & Organization, 161 (C), 98–113. Moon, S., B.L. Bayus, Y. Yi and J. Kim (2015), ‘Local consumers’ reception of imported and domestic movies in the Korean movie market’, Journal of Cultural Economics, 39 (1), 99–121. Moretti, E. (2011), ‘Social learning and peer effects in consumption: evidence from movie sales’, Review of Economic Studies, 78 (1), 356–93. Moul, C.C. (2007), ‘Measuring word of mouth’s impact on theatrical movie admissions’, Journal of Economics & Management Strategy, 16 (4), 859–92. Nelson, R.A., M.R. Donihue, D.M. Waldman and C. Wheaton (2001), ‘What’s an Oscar worth ?’, Economic Inquiry, 39 (1), 1–16. Oh, C., Y. Roumani, J.K. Nwankpa and H.F. Hu (2017), ‘Beyond likes and tweets: consumer engagement behavior and movie box office in social media’, Information and Management, 54 (1), 25–37. Pitt, I.L. (2010), ‘Superstar effects on royalty income in a performing rights organization’, Journal of Cultural Economics, 34 (3), 219–36. Ponzo, M. and V. Scoppa (2015), ‘Experts’ awards and economic success: evidence from an Italian literary prize’, Journal of Cultural Economics, 39 (4), 341–67. Rauch, J.E. and V. Trindade (2009), ‘Neckties in the tropics: a model of international trade and cultural diversity’, Canadian Journal of Economics, 42 (3), 809–43. Ravid, S.A. (1999), ‘Information, blockbusters, and stars: a study of the film industry’, Journal of Business, 72 (4), 463–92. Reinstein, D.A. and C.M. Snyder (2005), ‘The influence of expert reviews on consumer demand for experience goods: a case study of movie critics’, Journal of Industrial Economics, 53 (1), 27–51. Rohlfs, J. (1974), ‘A theory of interdependent demand for a communications service’, Bell Journal of Economics and Management Science, 5 (1), 16–37. Rosen, S. (1981), ‘The economics of superstars’, American Economic Review, 71 (5), 845–58. Schulze, G.G. (1999), ‘International trade in art’, Journal of Cultural Economics, 23 (1), 109–36. Seaman, B.A. (2006), ‘Empirical studies of demand for the performing arts’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 415–72. Shin, S.Y. and J. McKenzie (2019), ‘Asymmetric cultural discounting and pattern of trade in cultural products: empirical evidence in motion pictures’, The World Economy, 42 (11), 3350–67. Sisto, A. and R. Zanola (2004), ‘Rational addiction to cinema? A dynamic panel analysis of European countries’, Working Paper No. 41, Universita Del Piemonte Orientale, Italy. Sisto, A. and R. Zanola (2010), ‘Cinema attendance in Europe’, Applied Economics Letters, 17 (5), 515–17. Stigler, G.J. and G.S. Becker (1977), ‘De Gustibus Non Est Disputandum’, American Economic Review, 67 (2), 76–90. Strobl, E.A. and C. Tucker (2000), ‘The dynamics of chart success in the U.K. pre-recorded popular music industry’, Journal of Cultural Economics, 24 (2), 113–34. Teti, E., A. Collins and J. Sedgwick (2014), ‘An offer they couldn’t refuse (but probably should have): the ineffectiveness of Italian state subsidies to movie-making’, Public Money and Management, 34 (3), 181–8. Throsby, D. (1990), ‘Perception of quality in demand for the theatre’, Journal of Cultural Economics, 14 (1), 65–82. Throsby, D. (1994), ‘The production and consumption of the arts: a view of cultural economics’, Journal of Economic Literature, 32 (1), 1–29.

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Demand  227 Waldfogel, J. (2017), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214. Walls, W.D. (2010), ‘Superstars and heavy tails in recorded entertainment: empirical analysis of the market for DVDs’, Journal of Cultural Economics, 34 (4), 261–79. Walls, W.D. (2014), ‘Bestsellers and blockbusters: movies, music, and books’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsetrdam: North-Holland, pp. 185–213.

FURTHER READING Throsby (1994) is a classic discussion on consumption (and production) in cultural industries. Seaman (2006) provides a thorough and extensive review of empirical studies on demand for performing arts. McKenzie (2012) surveys the film literature, which provides a detailed review of the role of quality-related information on demand. Walls (2014) reviews theories of bestsellers and blockbusters and their applications to movies, music and books.

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25.  Digital piracy Jordi McKenzie

Digital piracy can be defined as the unlawful reproduction of digital content, such as music, television, film, books and software. Although prior to the arrival of Napster in 1999 digital piracy had existed in other forms (compact disc burners, for example), the creation of peer-to-peer (P2P) file-sharing technology took the unlawful activity to a new level. With hindsight, this technological breakthrough marked a significant moment in the history of the content industries. Napster and successor P2P services made vast collections of digital content (in particular, music) available to anyone with a satisfactory Internet connection. As broadband Internet speeds increased and file-sharing technologies evolved, digital piracy was already having significant impacts on music industry revenues and was threatening other content industries’ revenues as well. The disruption created by digital piracy did not go unnoticed by academics. Indeed, much has been written on the topic by scholars from various disciplines. Economists have featured prominently in this discourse, applying the tools of their trade to questions concerning the impact on legal markets, as well assessment of policy responses. While there have been a number of theoretical contributions related to digital piracy (for example, see Peitz and Waelbroeck 2006; Ahn and Shin 2010; Alcalá and González-Maestre 2010; Banerjee and Chatterjee 2010; Cho and Ahn 2010; Choi et al. 2010; Herings et al. 2010; Marti 2010; Minniti and Vergari 2010; Thomes 2013; Gans 2015; Darmon and Le Texier 2016), the most interesting questions can only be answered definitively with careful empirical analyses. The remainder of this chapter therefore focuses primarily on these studies.

IN SEARCH OF SALES DISPLACEMENT Many of the early studies set about asking the most obvious question regarding potential sales displacement effects resulting from digital piracy. Primarily focused on the music industry, these studies employed a variety of data and empirical approaches to address this question.1 While some used product-level sales data with contemporaneous measurement of piracy activity (for example, Bhattacharjee et al. 2007; Oberholzer-Gee and Strumpf 2007; McKenzie 2009; Lee 2018), others employed proxies for piracy (for example, Internet penetration or computer ownership) at more aggregated levels. This has been achieved using cross-sectional methods (for example, Peitz and Waelbroeck 2004; Zentner 2005), time-series methods (for example, Stevans and Sessions 2005) and combinations of the two (for example, Hui and Png 2003; Michel 2006; Liebowitz 2008; Mortimer et al. 2012). Another body of work employed individual-level survey data to estimate sales displacement effects (for example, Zentner 2006; Rob and Waldfogel 2006; Bounie et al. 2007; Anderson and Frenz 2010; Waldfogel 2010; Bai and Waldfogel 2012; Hong 2013). Related 228

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Digital piracy  229 research also used survey data to describe demographic characteristics of individuals partaking in piracy activity (for example, Gopal et al. 2006; Cox et al. 2010; Cox and Collins 2014). Finally, other recent studies have made use of different forms of (individual-level) observational data to investigate sales displacement (for example, Aguiar and Martens 2016; Aguiar 2017). Largely owing to the relative difference in typical music file sizes compared with those of typical television or film file sizes, digital piracy in the early years was more focused on music content. As a consequence, the music industry suffered revenue declines that were not observed in other content industries after the arrival of P2P technologies. To some degree, the dramatic fall in music industry revenues probably explains the skew of academic research towards this industry. However, with the emergence of BitTorrent coupled with increasing Internet speeds and download capacities, unlawfully sourced television and film have since become increasingly accessible to Internet pirates. Researchers have subsequently considered similar questions about the effects of piracy in the television and/ or film industries to those previously studied in the context of the music industry. Consistent with the literature on sales displacement arising from music piracy, some studies considering television or film industries have used product-level data (for example, De Vany and Walls 2007; McKenzie and Walls 2016), while others have pursued a timeseries or cross-sectional approach using proxies for piracy (for example, Smith and Telang 2010; Walls 2008). Also, in parallel with music piracy literature, a number of studies have used individual-level (survey) and stated-preference techniques to investigate questions concerning sales displacement effects (for example, Hennig-Thurau et al. 2007; Rob and Waldfogel 2007; McKenzie et al. 2019; Rojas and Briceño 2019).

THE ENDOGENEITY PROBLEM While the theoretical potential for piracy to stimulate sales via a promotion effect was acknowledged in many of the early studies, with a few exceptions most found some evidence of a displacement effect. Researchers also quickly realised they faced a non-trivial empirical challenge when attempting to establish a causal relationship between piracy and sales at both the product and individual (consumer) levels. This challenge extends from unobserved heterogeneity between lawful and unlawful consumption. It exists at the product level owing to products that are popular in terms of sales are also likely to be popular with (illegal) downloaders. It also exists with individual-level (survey) data, given consumers who purchase more legal content might also partake in more illegal consumption. Whether using data at the product or individual level, left untreated this endogeneity induces a (positive) bias on sales displacement estimates, leading to invalid causal inference. While standard remedial measures, such as fixed effects and/or instrumental variables, have been routinely applied (as permitted by data and context), recent studies have demonstrated the inherent challenges of identifying sales-displacement effects using product-level data (Aguiar and Waldfogel 2018a). The most promising approach to measuring industry-level displacement effects of digital piracy is generally accepted to be at the aggregated level (not the product level) providing a decent measure (or proxy) for overall piracy levels is available.

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NATURAL EXPERIMENTS Given the challenges in identifying causal relationships between digital piracy and sales, researchers have sought alternate (and often creative) approaches to studying the same question. In particular, a number of studies have made use of quasi-experimental data to identify relationships of interest pertaining to substitution between lawful and unlawful consumption. Some studies of this type have exploited policy events (for example, Danaher et al. 2014; Adermon and Liang 2014; Orme 2014; McKenzie 2017), while others have used supply-side interruptions related to file-sharing services (for example, Danaher et al. 2010; Danaher and Smith 2014; Hammond 2014; Aguiar et al. 2018; Peukert et al. 2017). While some studies have found sales increases from the imposition of anti-piracy policies and/or supply-side interruptions, other studies have found no such impacts or, if they do exist, only in the short term. Although conceptually policy and supply-side approaches provide an appealing way to examine (potential) substitution between lawful and unlawful modes of consumption, their success in this respect is subject to caveats. In the case of the policy-event studies, the implicit assumption is that the policy is viewed as effective and that pirates do not simply circumvent it by using a more sophisticated approach to illicit consumption (using virtual private network software to mask an Internet Protocol address, for example). Given the efficacy of widely used graduated-response policies (for example, HADOPI in France) has been called into question by a number of scholars (for example, Arnold et al. 2014; Giblin 2014) it is not obvious how internet pirates perceive the effectiveness of antipiracy laws more generally, which implies difficulties using a policy approach to identify substitution effects between lawful and unlawful consumption. Similar issues exist for the supply-side studies exploiting a disruption in a file-sharing service to identify sales effects. If Internet pirates simply substitute to another service, then it would be difficult to detect a relationship between piracy and sales.

WELFARE IMPLICATIONS While it is now widely accepted that piracy harms sales, there is also the perverse result that, in the short run, welfare increases as a direct result of piracy (for an exposition of this result, see Waldfogel 2012a). The intuition is that in addition to a direct transfer of surplus from producers (that is, music rights holders) to consumers (that is, pirates) accessing free content, there is also additional surplus created from consumption that would not have occurred in the legal market (assuming the consumer’s willingness to pay was above zero but below price). The conversion of what was formerly dead-weight loss to consumer surplus implies overall surplus expands. Consumers benefit from illegal piracy, whereas producers suffer, but overall total welfare nonetheless increases as the gains to consumers outweigh the losses to producers. This simple analysis, however, assumes a static (short-run) framework. With falling revenues and profits, eventually creators of music would cease supplying new music. The long-run implications of piracy are a significant decline in the supply of new music. Has there been any evidence of such an effect? In a series of papers, Waldfogel (2011, 2012b, 2012c, 2016, 2017) provides compelling evidence that the answer to this question is a

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Digital piracy  231 firm no. Handke (2006, 2012) and Bourreau et al. (2013) provide similar evidence using German and French music industry data, respectively. What explains this seemingly counter-intuitive finding? While technological progress had given rise to new ways of consuming content illegally, advances in technology were simultaneously having significant impacts on the supply side of the market. In particular, digitisation was reducing costs associated with both production and distribution, making it easier than ever for creators to produce, distribute and promote their content.

STREAMING SAVES THE DAY . . . FOR NOW Ultimately another technological disruption on the supply side would again change the fortunes of the content industries, and in particular the music industry. The rise of streaming services – for example, Spotify in the music industry and Netflix in the television and film industries – have provided consumers with almost endless supplies of content at relatively affordable (monthly subscription) rates. In both the music and television/film industries it has also been observed that piracy levels have fallen as consumers embrace the new legal forms of consumption (for example, Godinho et al. 2017; Aguiar and Waldfogel 2018a). Moreover, these services have facilitated distribution of increasing quantities of high-quality content (for example, Waldfogel 2017; Aguiar and Waldfogel 2018b). Is streaming the saviour of the content industries and, if so, should we expect to see continuing declines in piracy? Well perhaps in the short term, but if history holds any lessons, the next technological disruption could be upon us soon, and it is never certain what form it might take. Even as the fortunes of the music industry appear to be significantly more optimistic than just a few years ago, a new type of piracy threatens the streaming model and has rights holders concerned again. Known as stream ripping, the technology allows users to convert a file being streamed into one that can be kept permanently. Unlike file-sharing services, stream-ripping services do not share copyrighted content, making it difficult to prosecute under traditional copyright laws. In the context of the television and film industries, illegal Internet Protocol television (IPTV) presents another emerging threat as it blurs the lines between illegal and legal subscription models by providing users access to (illegal) premium content (such as live sport) for a small subscription fee. In addition to IPTV, increasingly popular software (and hardware) services such as Kodi allow access to large libraries of on-demand film and television content if users install (illegal) third-party add-ons. While both IPTV and Kodi are entirely legal in themselves, both have been manipulated by developers to allow users access to various forms of content unlawfully without compensating rights holders. As with stream ripping, this presents significant challenges for copyright law enforcement. Another significant concern is block chain. While many are excited about the prospects this technology holds for the content industries (digital rights management, for example), there are others who hold concerns the decentralised nature of block-chain technology could provide the perfect platform for large-scale piracy, if corrupted. Although beyond the scope of this chapter, the threat of piracy from new and evolving technologies remain real and significant.

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NOTE 1. Dejean (2009), Waldfogel (2012a), Smith and Telang (2012) and Liebowitz (2016) provide useful surveys on the (early) empirical studies of media piracy.

SEE ALSO: Chapter 12: Copyright; Chapter 26: Digitization in the cultural industries; Chapter 40: Music industry; Chapter 47: Platforms.

REFERENCES Adermon, A. and C.-Y. Liang (2014), ‘Piracy and music sales: the effects of an anti-piracy law’, Journal of Economic Behavior & Organization, 105 (C), 90–106. Aguiar, L. (2017), ‘Let the music play? Free streaming and its effects on digital music consumption’, Information Economics and Policy, 41 (December), 1–14. Aguiar, L. and B. Martens (2016), ‘Digital music consumption on the Internet: evidence from clickstream data’, Information Economics and Policy, 34 (March), 27–43. Aguiar, L. and J. Waldfogel (2018a), ‘As streaming reaches flood stage, does it stimulate or depress music sales?’, International Journal of Industrial Organization, 57 (July), 278–307. Aguiar, L. and J. Waldfogel (2018b), ‘Quality predictability and the welfare benefits from new products: evidence from the digitization of recorded music’, Journal of Political Economy, 126 (2), 492–524. Aguiar, L., J. Claussen and C. Peukert (2018), ‘Catch me if you can: effectiveness and consequences of online copyright enforcement’, Information Systems Research, 29 (3), 656–78. Ahn, I. and I. Shin (2010), ‘On the optimal level of protection in DRM’, Information Economics and Policy, 22 (4), 341–53. Alcalá, F. and M. González-Maestre (2010), ‘Copying, superstars, and artistic creation’, Information Economics and Policy, 22 (4), 365–78. Andersen, B. and M. Frenz (2010), ‘Don’t blame the P2P file-sharers: the impact of free music downloads on the purchase of music CDs in Canada’, Journal of Evolutionary Economics, 20 (5), 715–40. Arnold, M.A., E. Darmon, S. Dejean and T. Penard (2014), ‘Graduated response policy and the behavior of digital pirates: evidence from the French three-strike (HADOPI) law’, unpublished manuscript, accessed 6 December 2019 at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2380522. Bai, J. and J. Waldfogel (2012), ‘Movie piracy and sales displacement in two samples of Chinese consumers’, Information Economics and Policy, 24 (3–4), 187–96. Banerjee, D. and I. Chatterjee (2010), ‘The impact of piracy on innovation in the presence of technological and market uncertainty’, Information Economics and Policy, 22 (4), 391–7. Bhattacharjee, S., R.D. Gopal, K. Lertwachara, J.R. Marsden and R. Telang (2007), ‘The effect of digital sharing technologies on music markets: a survival analysis of albums on ranking charts’, Management Science, 53 (9), 1359–74. Bounie, D., M. Bourreau and P. Waelbroeck (2007), ‘Pirates or explorers? Analysis of music consumption in French graduate schools’, Brussels Economic Review, 50 (2), 167–92. Bourreau, M., M. Gensollen, F. Moreau and P. Waelbroeck (2013), ‘“Selling less of more?” The impact of digitization on record companies’, Journal of Cultural Economics, 37 (3), 327–46. Cho, W.-Y. and B.-H. Ahn (2010), ‘Versioning of information goods under the threat of piracy’, Information Economics and Policy, 22 (4), 332–40. Choi, P., S.H. Bae and J. Jun (2010), ‘Digital piracy and firms’ strategic interactions: the effects of public copy protection and DRM similarity’, Information Economics and Policy, 22 (4), 354–64. Cox, J. and A. Collins (2014), ‘Sailing in the same ship? Differences in factors motivating piracy of music and movie content’, Journal of Behavioral and Experimental Economics, 50 (June), 70–76. Cox, J., A. Collins and S. Drinkwater (2010), ‘Seeders, leechers and social norms: evidence from the market for illicit digital downloading’, Information Economics and Policy, 22 (4), 299–305. Danaher, B. and M.D. Smith (2014), ‘Gone in 60 seconds: the impact of the Megaupload shutdown on movie sales’, International Journal of Industrial Organization, 33 (C), 1–8. Danaher, B., S. Dhanasobhon, M.D. Smith and R. Telang (2010), ‘Converting pirates without cannibalizing

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Digital piracy  233 purchasers: the impact of digital distribution on physical sales and internet piracy’, Marketing Science, 29 (6), 1138–51. Danaher, B., M.D. Smith, R. Telang and S. Chen (2014), ‘The effect of graduated response anti-piracy laws on music sales: evidence from an event study in France’, Journal of Industrial Economics, 62 (3), 541–53. Darmon, E. and T. Le Texier (2016), ‘Private or public law enforcement? The case of digital anti-piracy policies with illegal non-monitored behaviors’, Review of Network Economics, 15 (4), 169–210. Dejean, S. (2009), ‘What can we learn from empirical studies about piracy?’, CESifo Economic Studies, 55 (2), 326–52. De Vany, A.S. and W.D. Walls (2007), ‘Estimating the effects of movie piracy on box-office revenue’, Review of Industrial Organization, 30 (4), 291–301. Gans, J.S (2015), ‘“Selling out” and the impact of music piracy on artist entry’, Information Economics and Policy, 32 (C), 58–64. Giblin, R. (2014), ‘Evaluating graduated response’, Columbia Journal of Law & the Arts, 37 (2), 147–209. Godinho de Matos, M., P. Ferreira and M.D. Smith (2017), ‘The effect of subscription video-on-demand on  piracy: evidence from a household-level randomized experiment’, Management Science, 64 (12), 5610–30. Gopal, R.D., S. Bhattacharjee and G.L. Sanders (2006), ‘Do artists benefit from online music sharing?’, Journal of Business, 79 (3), 1503–33. Hammond, R.G. (2014), ‘Profit leak? Pre-release file sharing and the music industry’, Southern Economic Journal, 81 (2), 387–408. Handke, C.W. (2006), ‘Plain destruction or creative destruction? Copyright erosion and the evolution of the record industry’, Review of Economic Research on Copyright Issues, 3 (2), 29–51. Handke, C.W. (2012), ‘Digital copying and the supply of sound recordings’, Information Economics and Policy, 24 (1), 15–29. Hennig-Thurau, T., V. Henning and H. Sattler (2007), ‘Consumer file sharing of motion pictures’, Journal of Marketing, 71 (4), 1–18. Hennig-Thurau, T. and M.B. Houston (2018), Entertainment Science: Data Analytics and Practical Theory for Movies, Games, Books, and Music, Cham: Springer. Herings, P.J.-J., R. Peeters and M.S. Yang (2010), ‘Competition against peer-to-peer networks’, Information Economics and Policy, 22 (4), 315–31. Hui, K.-L. and I. Png (2003), ‘Piracy and the legitimate demand for recorded music’, Contributions in Economic Analysis & Policy, 2 (1), art. 11. Hong, S.-H. (2013), ‘Measuring the effect of Napster on recorded music sales: difference-in-differences estimates under compositional changes’, Journal of Applied Econometrics, 28 (2), 297–324. Lee, J.F. (2018), ‘Purchase, pirate, publicize: private-network music sharing and market album sales’, Information Economics and Policy, 42 (March), 35–55. Liebowitz, S.J. (2008), ‘Testing file sharing’s impact on music album sales in cities’, Management Science, 54 (4), 852–9. Liebowitz, S.J. (2016), ‘How much of the decline in sound recording sales is due to file-sharing?’, Journal of Cultural Economics, 40 (1), 13–28. Martı, F. (2010), ‘Avoiding commercial piracy’, Information Economics and Policy, 22 (4), 398–408. McKenzie, J. (2009), ‘Illegal music downloading and its impact on legitimate sales: Australian empirical evidence’, Australian Economic Papers, 48 (4), 296–307. McKenzie, J. (2017), ‘Graduated response policies to digital piracy: do they increase box office revenues of movies?’, Information Economics and Policy, 38 (C), 1–11. McKenzie, J. and W.D. Walls (2016), ‘File sharing and film revenues: estimates of sales displacement at the box office’, The BE Journal of Economic Analysis & Policy, 16 (1), 25–57. McKenzie, J., P. Crosby, J. Cox and A. Collins (2019), ‘Experimental evidence on demand for “on-demand” entertainment’, Journal of Economic Behavior & Organization, 161, 98–113. Michel, N.J. (2006), ‘The impact of digital file sharing on the music industry: an empirical analysis’, Topics in Economic Analysis & Policy, 6 (1), art. 18. Minniti, A. and C. Vergari (2010), ‘Turning piracy into profits: a theoretical investigation’, Information Economics and Policy, 22 (4), 379–90. Mortimer, J.H., C. Nosko and A. Sorensen (2012), ‘Supply responses to digital distribution: recorded music and live performances’, Information Economics and Policy, 24 (1), 3–14. Oberholzer-Gee, F. and K. Strumpf (2007), ‘The effect of file sharing on record sales: an empirical analysis’, Journal of Political Economy, 115 (1), 1–42. Orme, T. (2014), ‘The short-and long-term effectiveness of anti-piracy laws and enforcement actions’, Journal of Cultural Economics, 38 (4), 351–68. Peitz, M. and P. Waelbroeck (2004), ‘The effect of Internet piracy on CD sales: cross-section evidence’, Review of Economic Research on Copyright Issues, 1 (2), 71–9.

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234  Handbook of cultural economics Peitz, M. and P. Waelbroeck (2006), ‘Why the music industry may gain from free downloading – the role of sampling’, International Journal of Industrial Organization, 24 (5), 907–13. Peukert, C., J. Claussen and T. Kretschmer (2017), ‘Piracy and box office movie revenues: evidence from Megaupload’, International Journal of Industrial Organization, 52 (May), 188–215. Rob, R. and J. Waldfogel (2006), ‘Piracy on the high C’s: music downloading, sales displacement, and social welfare in a sample of college students’, Journal of Law and Economics, 49 (1), 29–62. Rob, R. and J. Waldfogel (2007), ‘Piracy on the silver screen’, Journal of Industrial Economics, 55 (3), 379–95. Rojas, C. and A. Briceño (2019), ‘The effects of piracy on competition: evidence from subscription TV’, International Journal of Industrial Organization, 63 (March), 18–43. Smith, M.D. and R. Telang (2010), ‘Piracy or promotion? The impact of broadband Internet penetration on DVD sales’, Information Economics and Policy, 22 (4), 289–98. Smith, M.D. and R. Telang (2012), ‘Assessing the academic literature regarding the impact of media piracy on sales’, unpublished manuscript, accessed 6 December 2019 at https://papers.ssrn.com/sol3/papers.cfm?abstract​ _id=2380522. Stevans, L.K. and D.N. Sessions (2005), ‘An empirical investigation into the effect of music downloading on the consumer expenditure of recorded music: a time series approach’, Journal of Consumer Policy, 28 (3), 311–24. Thomes, T.P. (2013), ‘An economic analysis of online streaming music services’, Information Economics and Policy, 25 (2), 81–91. Waldfogel, J. (2010), ‘Music file sharing and sales displacement in the iTunes era’, Information Economics and Policy, 22 (4), 306–14. Waldfogel, J. (2011), ‘Bye, bye, Miss American Pie? The supply of new recorded music since Napster’, NBER Working Paper No. 16882, National Bureau of Economic Research, Cambridge, MA. Waldfogel, J. (2012a), ‘Music piracy and its effects on demand, supply, and welfare’, Innovation Policy and the Economy, 12 (1), 91–110. Waldfogel, J. (2012b), ‘Copyright research in the digital age: moving from piracy to the supply of new products’, American Economic Review, 102 (3), 337–42. Waldfogel, J. (2012c), ‘Copyright protection, technological change, and the quality of new products: evidence from recorded music since Napster’, Journal of Law and Economics, 55 (4), 715–40. Waldfogel, J. (2016), ‘Cinematic explosion: new products, unpredictability and realized quality in the digital era’, Journal of Industrial Economics, 64 (4), 755–72. Waldfogel, J. (2017), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214. Waldfogel, J. (2018), Digital Renaissance: What Data and Economics Tell Us about the Future of Popular Culture, Princeton, NJ: Princeton University Press. Walls, W.D. (2008), ‘Cross-country analysis of movie piracy’, Applied Economics, 40 (5), 625–32. Zentner, A. (2005), ‘File sharing and international sales of copyrighted music: an empirical analysis with a panel of countries’, The BE Journal of Economic Analysis & Policy, 5 (1), 1–17. Zentner, A. (2006), ‘Measuring the effect of music downloads on music purchases’, Journal of Law and Economics, 49 (1), 63–90.

FURTHER READING Beyond the papers covered in this review, the interested reader can find extended discussions of piracy and related issues in Hennig-Thurau and Houston (2018) and Waldfogel (2018).

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26.  Digitization in the cultural industries Joel Waldfogel

The word digitization means many things, but for the cultural industries it reflects two distinct phenomena: piracy (and therefore reduced revenue), and reduction in the costs of production, promotion and distribution (with the potential to offset the effects of piracy). Digitization has therefore also given rise to a third phenomenon which we label unfiltered production: cost reduction enables cultural production without the control of the traditional gatekeeping intermediaries – for example, publishing houses and record labels – and so threatens, if creative activity is not undone by piracy, to overwhelm the consuming public with large amounts of low-quality products. The goal of this chapter is to briefly describe what has happened to creative output in music, movies, books and television in the wake of digitization. The brief treatment here summarizes longer descriptions in my 2017 Journal of Economic Perspectives article and, especially, my 2018 book, Digital Renaissance: What Data and Economics Tell Us about the Future of Popular Culture. Readers interested in full lists of references to underlying research are directed to Waldfogel (2017a, 2018).

TWO FACES OF DIGITIZATION The arrival of Napster brought the first face of digitization, unpaid consumption via digital piracy, to the cultural industries. Following 1999, recorded-music industry revenue began a long slide, in which revenue was halved in about a decade. The threat of piracy loomed for other products, but the music industry faced the challenge first. If digitization had brought nothing other than a reduction in revenue, then we would have expected a corresponding decline in cultural production. However, digitization also brought new technologies that reduced the costs of bringing new cultural products to market. In music, for example, production no longer required an expensive studio but could instead be accomplished with inexpensive hardware and software (an iPhone or a Mac with Garageband). Distribution no longer required physical product and distribution arrangements with record stores, but could instead be achieved by inexpensively making your own songs available on iTunes, YouTube and, later, Spotify. Promotion, while still challenging, no longer required placement on the radio and could instead be accomplished by having some fans discover your music and then communicate their discoveries to friends. Digitization-induced cost reductions were not limited to recorded music. Around 2005, the appearance of low-cost digital cameras capable of cinema-quality recording revolutionized independent film-making. Anyone so inclined could make a movie. Shortly thereafter, with the appearance of streaming platforms such as Amazon and Netflix, the bottleneck of theatrical distribution was broken. The US theatrical distribution system 235

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236  Handbook of cultural economics had been able to accommodate just a few hundred movies in broad release annually. When any Internet-connected device became an exhibition venue, many movies that would not have been viable candidates for theatrical distribution could now inexpensively find audiences large enough to cover their modest production costs. The impact of digitization on the book market has been even more profound. Book publishing has traditionally been controlled by cultural elites at major publishing houses. They sifted through submissions, many from agents, and chose to invest their editorial nurture and marketing budgets in relatively few. With the arrival of Amazon’s Kindle device and publishing platform, authors had a way to distribute their work directly to consumers. Gatekeepers could no longer thwart their efforts, although much work would now be able to come to market without the steady guiding hand of editors, or even proofreaders. Cory Doctorow worried about an ‘open slush pile’ of self-published novels (Flood 2015).

OUTPUT MEASURES Output of the creative industries – the number of new works produced and released each year – has grown substantially in the years since digitization. Numbers are difficult to obtain, but available data clearly indicate substantial increases in the number of new products released annually in books, music, movies and television. We can look at sources such as Musicbrainz, an open-source, user-generated database of musical recordings, or Nielsen Sound Scan, to see that the number of new musical recordings grew by about a factor of three between 2000 and 2010. It is possible to obtain data on the number of recordings added to Spotify by year for recent years, and 2017 saw the addition of roughly 950 000 new recordings to the service. Not all of these recordings were newly recorded, but this large number of songs ingested gives a sense of the volume of new work being created. Documenting the number of new books is in principle easy but in practice difficult. Traditionally, new books obtained an international standard book number (ISBN), but while traditional publishers still obtain ISBNs for their books, self-published electronic books at Amazon do not necessarily have these numbers. Quantifying the number of new books is complicated by, first, that each edition of the same book receives a different ISBN number and, second, that new print-on-demand releases of old books now out of copyright also receives their own new ISBNs. Despite all these complications, it is clear that the number of new titles has risen sharply in the digital era. For example, the number of self-published electronic books rose from about 10 000 to about 150 000 between 2008 and 2012 (Waldfogel and Reimers 2015; Waldfogel 2017a). The growth of movies and television is in some ways easier to document, largely because obsessive fans maintain databases, such as the Internet Movie Database (IMDb) which documents movies and television show production, as well as epguides.com, which provides a catalog of aired programming. These sources show roughly a tenfold increase in the numbers of new movies and television shows produced between 2005 and 2015 (Waldfogel 2016, 2017b).

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Digitization in the cultural industries  237

OUTPUT AND QUALITY IN AN UNFILTERED WORLD Despite some challenges in obtaining specific numbers, digitization has brought increases in the numbers of new creative products brought to market. Growing numbers of new products in an unfiltered world would not necessarily lead to an improved experience for consumers. Whether it does, depends substantially on the predictability of new product quality. To see how this works, consider a stylized world in which product quality is entirely predictable at the time of the investment decision (when the book, movie or musical composition is being pitched to an investing gatekeeper). In that fully predictable world, a reduction in costs, in relation to revenue, would reduce the threshold for greenlighting proposed projects. However, owing to perfect predictability, all the newly available products would be less appealing than the lowest-quality products previously made available. The new products enabled by digitization with perfect predictability would enhance the consumer experience, but only modestly. In the real world, the appeal of potential new products is far from perfectly predictable. Indeed, William Goldman (2012), who wrote Butch Cassidy and the Sundance Kid, as well as the Princess Bride, argued that ‘NOBODY KNOWS ANYTHING’ about which Hollywood movies would succeed. Academic assessments, such as Caves (2000), reach similar conclusions. This leads to the practical question: what happens to the quality of new products available to consumers when there is growth in new products, and quality or appeal to consumers is unpredictable? A great deal of the new work will be unappealing to consumers, but some of the newly available work – owing to unpredictability – will end up in the right tail of sales distributions. That is, some of the newly available work, which would not have made it to market absent digitization, will end up among the most popular products with consumers. With suitable definitions of the types of products made possible by digitization, we can test this prediction. Testing requires empirical measures of products made possible with digitization but which would not have been released in its absence, which I have termed ex ante losers. The structures of the respective creative industries provide reasonable ways of measuring the number of ex ante losers. In music, it is songs that appear on independent record labels or self-released by artists. In books, it is products that first come to market as self-published works. In movies, it is the movies produced by entities other than the major Hollywood studios; and in television it is serialized video programming not delivered by the traditional distribution channels (broadcast networks or established premium cable networks such as HBO). The prediction that ex ante losers make up a growing, and eventually substantial, share of successful new products is borne out sharply in data on music, books, movies and television. Between 2000 and 2010, the share of independent record label music among the Billboard 200 (the weekly list of the top-selling albums in the US), rises from about 13 to nearly 40 percent. In books, the share of the USA Today weekly top 150 bestselling titles accounted for by works that originally came to market as self-published works rises from zero to roughly 10 percent between 2008 and 2012. In the romance category, the originally self-published share of titles tops 40 percent. In movies, the films produced by independent, instead of major Hollywood, studios play the role of ex ante losers. Documenting the share of revenue accounted for by ex ante loser movies is complicated by only box office revenue being easy to observe. Given the

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238  Handbook of cultural economics important role of non-theatrical distribution for digitally enabled movies, this complication means that the independent share of box office revenue will tend to understate the importance of the new movies. Still, the independent share of US box office revenue rose from 20 percent to 40 percent between 2000 and 2012 (Waldfogel 2016). Also, while I cannot observe total revenue for all movies, I can observe a measure of attention, the number of movies rating a movie at IMDb. Using this measure, I can document that the share of attention garnered by independent movies rose from 15 percent to 30 percent between 2005 and 2015 (Waldfogel 2018). As in movies, revenue data are not available for television shows. It is instead possible to obtain different measures of success, such as whether US shows are nominated for, or win, Emmy Awards. As recently as 2000, these awards were dominated by traditional broadcast networks (ABC, CBS, NBC and Fox) as well as, since about 2000, HBO, a premium cable channel. The years since 2010 have seen growth in content released by basic cable channels (such as AMC and FX) as well as purely digital distributors, chiefly Netflix and Amazon. The share of award nominations accounted for by the traditional players fell from 90 percent to less than 40 percent between 1985 and 2015. In 2018, Netflix alone received 112 Emmy nominations, compared with 108 for HBO (Gilbert 2018).

GOOD NEW VINTAGES The new digitally enabled products in all these categories now account for growing and large shares of the currently successful products. That ex ante losers now end up among the ex post commercial winners is a necessary, but not sufficient, condition for a digital renaissance. The evidence further needed to support a conclusion that digitization has led to the creation and discovery of good products is evidence that the new crops of products are good compared with the old. Broadly, I have two ways to compare the quality of new products, that is, those produced after digitization, with that of older crops of products. The first method relies on critical assessments, in particular multi-year ‘best of’ lists. Perhaps the most famous example is Rolling Stone’s 500 best albums of all time. If we assign each of those albums to the years in which they were released, we get a time series showing the evolution of the number of very good products – those whose quality in the eyes of some critics exceed a common threshold. By assembling many critical ‘best of’ lists, I can construct a music quality index covering a long period, including the years after digitization (and its devastating effect on recorded music revenue). What this process shows is that music quality rose from 1960 to 1970, then fell in the years to 1980 (Waldfogel 2012). Following 1999, when revenue collapsed, the index held steady, neither rising nor falling. The absence of a decline stands in contrast to the revenue trends. We might have expected talented musicians to stop producing in the face of sharply curtailed revenue. The second broad approach to measuring the evolution of vintage quality relies directly on choice behavior, in particular consumers’ choice of products from different vintages. The question is, after accounting for depreciation – here the extent to which products of different ages are typically used – are some vintages used more than others? If so, then the vintages that are used more, conditional on their ages, are more useful. Applying this idea requires data on usage by calendar year and vintage, which is not generally or easily

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Digitization in the cultural industries  239 obtained. It is possible to obtain this type of data on sales of recorded music as well as radio airplay (see Waldfogel 2012; Aguiar and Waldfogel 2016). Specifically, I define st,v as the share of year t consumption that is accounted for by products of vintage v. I then regress the log of st,v on dummies for age (which is measured as t – v), as well as dummies for vintage. The coefficients on the vintage dummies then serve as an index of vintage quality. Using these approaches, I find that that vintage quality rises from 1960 to 1970, falls to 1980, and is relatively stable through 1999. Thereafter, as digitization arrives, and even as revenue falls sharply in the wake of Napster, the quality index rises. That is, vintages of music produced after 1999 get used more, given their age, than do the vintages produced in the decade leading up to digitization. I take this as evidence that consumers find the new music, produced during the period of digitization, to be good and useful. Data on movie usage by time and vintage are not systematically available, but I can obtain information on television broadcast of movies on US premium channels. I can see what share of the movies on, say, HBO or Showtime or Cinemax, were originally produced in each previous year. If I take these to be rough measures of consumption, then I can implement the same usage-based approach I employ in music (see Waldfogel 2016). This approach reveals that movie vintage quality rose steadily from 1975 to about 2005 and has remained high since then. I do not have data on book or television show usage by year and vintage, and therefore rely on other types of information on the quality of recent versus earlier vintages. Two such sources are critic and lay-user ratings of television shows, at Metacritic and IMDb, respectively. In Waldfogel (2017b) I document that the ratings of the shows that critics and users like best have risen over time, an observation which is consistent with the idea that when creators make more new products, i.e. more ‘draws from the urn,’ a larger range of quality outcomes ensues. What tends to matter for consumers is the quality of the best material.

CONCLUSION Upon its arrival, digitization connoted mainly threats, of lost revenue and lost control, a world in which professional creators and intermediaries would no longer be able to finance continued investment, and consumers would, at best, find themselves awash in low-quality amateur products. What has happened instead is a large growth in creative activity which, even if it contains an ‘open slush pile’ of unappealing work, also includes a substantial amount of work which (1) would not have come to market under the system prevailing prior to digitization and (2) consumers value highly. That is, despite early reports to the contrary, it appears that we are experiencing a digital renaissance.

SEE ALSO: Chapter 8: Broadcasting; Chapter 14: Creative industries; Chapter 38: Motion-picture industry; Chapter 40: Music industry; Chapter 47: Platforms; Chapter 57: Video game industry.

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240  Handbook of cultural economics

REFERENCES Aguiar, L. and J. Waldfogel (2016), ‘Even the losers get lucky sometimes: new products and the evolution of music quality since Napster’, Information Economics and Policy, 34 (March), 1–15. Caves, R.E. (2000), Creative Industries: Contracts between Art and Commerce, Cambridge, MA: Harvard University Press. Flood, A. (2015), ‘Authonomy writing community closed by HarperCollins’, Guardian, 20 August, accessed at www.theguardian.com/books/2015/aug/20/authonomy-writing-community-closed-by-harpercollins, accessed December 9, 2019. Gilbert, S. (2018), ‘Emmy nominations 2018: Netflix takes over’, Atlantic, 12 July, accessed at www.theatlantic.com/ entertainment/archive/2018/07/emmy-nominations-2018-netflix-hbo/565046/, accessed December 9, 2019. Goldman, W. (2012), Adventures in the Screen Trade, New York: Grand Central. Waldfogel, J. (2012), ‘Copyright protection, technological change, and the quality of new products: evidence from recorded music since Napster’, Journal of Law and Economics, 55 (4), 715–40. Waldfogel, J. (2016), ‘Cinematic explosion: new products, unpredictabilty and realized quality in the digital era’, Journal of Industrial Economics, 64 (4), 755–72. Waldfogel, J. (2017a), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214. Waldfogel, J. (2017b), ‘The random long tail and the golden age of television’, Innovation Policy and the Economy, 17 (1), 1–25. Waldfogel, J. (2018), Digital Renaissance: What Data and Economics Tell Us about the Future of Popular Culture, Princeton, NJ: Princeton University Press. Waldfogel, J. and I. Reimers (2015), ‘Storming the gatekeepers: digital disintermediation in the market for books’, Information Economics and Policy, 31 (June), 47–58.

FURTHER READING For the long read, see Waldfogel (2018) which has a full account of digitization in the music movies, television and books industries. For the shorter read, see Waldfogel (2017a).

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27.  Economic impact of the arts Bruce A. Seaman

How might one answer the question: ‘What is the economic value of the Chicago Symphony Orchestra to the city of Chicago?’ This type of question has many variations. The cultural asset need not be a single organization but instead a whole sector, such as the arts industry in Chicago. The geographical area in which to measure this economic impact need not be a city boundary, but an entire metropolitan area, several counties, a state or a region (or nation). The focus of the inquiry can also be a single event or series of events, such as the Mozart Festival in Salzburg, the Boston Pops summer concert series in Tanglewood or Mardi Gras in Rio de Janeiro. Almost identical issues are raised when the concept of a cultural asset is expanded to include sports instead of arts-related subjects, and the comparison of those two sectors continues to be of great interest to practitioners and academicians (see Crompton 1995; Seaman 2006b).

INTRODUCTION TO THE PROBLEM AND ANALYTICAL METHODS Special challenges exist in the case of cultural assets that are non-market goods, for which the exclusion of non-payers is largely infeasible or impractical (for example, icons such as the French language, the Kiwi as the symbol of New Zealand, the Brandenburg Gate or the Grand Canyon). While almost all cultural assets have non-market features, these cultural icons generate especially limited market data that can be used in the valuation process. However, economics does have analytical options in even the most problematic cases. An important revealed preference approach to this dilemma measures travel costs incurred to specific locations, while the hedonic price approach attempts to isolate the value of living near cultural amenities as capitalized into housing prices. Stated preference approaches include contingent valuation, willingness to pay and choice experiments, and share the essential feature of exploring how various hypothetical attributes of the object of study are valued via direct questioning of individuals under controlled experimental conditions (see Snowball 2008). The methodology followed in economic impact studies is a revealed preference approach that attempts to identify the incremental output, income, employment and tax revenues generated in a specified region by new spending stimulated by the existence or expansion of an organization or an event. However, since the preponderance of these studies are ex ante predictions of such impacts rather than ex post examinations of the evidence for such impacts, there are elements of stated preference theory in the attempt to identify what visitors are willing to spend and whether their visit to a region was primarily owing to the existence of event X or institution Y. When key data used in the study is linked to surveys of visitors and possibly local vendors, the studies are partly ex post empirically based even if no econometric estimation is performed. 241

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242  Handbook of cultural economics Regardless of specific methodology, an overriding tension remains between instrumentalist and intrinsic impacts of the arts. The past 50 years have seen the relentless rise of instrumentalist thinking, with economic impact studies being a prime and controversial example owing to their potential for abuse and misinterpretation (see Seaman 1987 [1997]; Crompton 1995). Owing in part to those controversies, there has been a notable backlash against instrumentalism despite the continued popularity of economic impact studies.1 This backlash has taken several notable forms. McCarthy et al. (2004) attempt to reframe the debate and plea for arts advocates to move away from an emphasis on economic growth (and even on improved student test scores) and to return to their original passion for stressing more fundamental rewards (some potentially measurable), such as pleasure, captivation, cognitive growth, creation of social bonds and expression of communal meaning. The Arts Council of England launched a 2006 public inquiry that led to a call for a more balanced approach between a return on investment (public value) standard to tax financed arts funding and one that recognized also the importance of enriching arts experiences (see Bunting 2008). When the Museum of Modern Art (MoMA) commissioned a study claiming that its reopening would create a two-year $2 billion spending impact, $650 million in New York City incomes, $50 million in local tax revenue and more than 4000 jobs, two economists called this ‘creative accounting’ (Hassett and Swagel 2006). Yet, as supporters of MoMA’s contributions to culture and enlightenment, those economists defended the notion that the average New York resident was willing to pay the $11.25 per capita required to fund the $90 million annual tax-financed direct and indirect subsidies bestowed upon that museum, based upon its ability to create joy and make New York a special place.2

TYPES OF ECONOMIC IMPACTS There are three broad categories of the economic impact of a cultural asset. First, there is the consumption value, including the value received by users (those who actually attend events or performances) and non-users. The most observable use value is total expenditures on tickets. However, there are other consumption values that are not easily captured by suppliers, such as consumer surplus (the difference between the maximum that someone would pay for a given quantity of the good and the actual amount that they pay to suppliers) and any necessary travel and related expenditure directly related to the consumption of the good. Even those who never attend cultural events or visit cultural institutions can derive non-use consumption value as reflected in their potential willingness to pay for the option of being a direct future consumer, through the indirect prestige or quality-of-life benefits they receive from the existence of cultural assets in their community, or through their interest in preserving those assets for their heirs (bequest value). Second, there are potential long-run increases in productivity and economic development linked to the cultural asset. As noted previously, these might be measured by hedonic values reflected in increases in property values and rents in a community with desirable cultural amenities (which also generate additional local tax revenues used to enhance local public services important for development), or reduced business labor expenses resulting from workers willing to accept lower wages in locations having these cultural amenities (hence encouraging business expansion). More direct productivity benefits resulting from

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Economic impact of the arts  243 the educational value of cultural goods are frequently mentioned, but difficult to verify. While these types of longer-run effects are linked to the consumption value of the assets, they can generate potentially measurable economic impacts on the real economy in the form of expanded population and economic growth. Richard Florida (2002) argues that firms and jobs follow the relocation of highly mobile creative people (rather than people relocating to jobs and industries) who are initially attracted to tolerant and creative cities. While this argument has been enthusiastically adopted by arts advocates eager to claim the arts as vital to a city becoming creative and hence an engine of long-term economic growth, the Florida argument has been subject to considerable criticism. The connection between the arts and the Florida indicia for a creative city are tenuous, the definition of creativity seems most closely linked to high income regardless of occupation, and the empirical relationship between highly ranked creative cities and rapid economic (or population) growth has not been consistently established, and at times has been strongly negative (see, for example, MacGillis 2010). Third, there are the primarily short-run net increases in economic activity (as measured in output, income, jobs and tax revenues) related to the net injections of new spending into the region as a direct consequence of the cultural asset. The total impact includes the longer-run multiplier effects of this new spending. These economic impacts are summarized in equation (27.1): Total impact (TI) 5 Consumption impact (C) 1 Long-run growth impact (LRG) 1 Short-run spending impact (SRS) (27.1)

METHODOLOGICAL APPROACHES RELATED TO TYPES OF IMPACTS It is useful to think of each of these three impacts as being addressed by particular methodologies. The term economic impact study is most commonly reserved for the conventional approach that focuses on the third type of impact – the short-run effects of spending generated by the cultural asset. To many casual observers, and most arts advocates, this is the only imaginable type of economic impact and the term economic is uniquely reserved for what they believe to be the highly measurable jobs, income and tax revenues linked to their organization or event. The non-survey (revealed preference) willingness-to-pay methods such as the hedonic market approach that estimates the complex market values linked to housing, land and labor market compensating differentials is most applicable to measuring the long-term economic growth impacts, the second of the three impacts. The contingent valuation (stated preference) survey methodology (CVM) attempts to capture the non-market consumption benefits linked to use value (consumer surplus) and non-use value (option, existence, prestige and bequest benefits), while the travel cost method is a more traditional approach to measuring that part of consumption (use) value not captured by the suppliers of the attraction being visited. Each of these approaches has strengths and weaknesses. The use of the results of any of these valuation approaches to justify expanded government support for the cultural sector (a frequent claim of arts proponents) is limited by the inherently partial equilibrium

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244  Handbook of cultural economics nature of these studies, which generally fail to consider the costs as well as the benefits, and cannot provide a ranking of all the possible public-sector investment projects that could make competing claims upon the public purse. Hence the finding that a cultural asset generates significant economic benefits is, at best, a necessary but not sufficient condition for justifying tax-financed support. Furthermore, to the extent that these benefits confirm the potential for additional earned income (by expanded use of price discrimination strategies to capture more user consumer surplus) or reveal the magnitude of public benefits that would motivate more business and individual non-profit contributions, the case for tax-financing could even be weakened.

CONVENTIONAL ECONOMIC IMPACT MODELS (EIM): BACKGROUND AND VARIATIONS The EIM approach remains the most common valuation method in the arts (although the CVM approach and its variants are generally more academically respectable and have exploded in popularity among arts economists). The intellectual foundations for economic impact models can be traced to the work of Wassily Leontief and John Maynard Keynes in the 1930s. Leontief’s inter-industry analysis generated input–output tables designed to reflect the relationships among the various sectors of the economy. His work is the inspiration for both the regional input–output modeling system (RIMS II), developed by the US Bureau of Economic Analysis and the IMPLAN software and databases supplied by the Minnesota IMPLAN Group (MIG, Inc.), which are the primary sources of the state and industry specific multipliers used in most US-based EIM studies, and the multipliers developed for other countries, such as the Australian Bureau of Statistics’ multipliers for culture-related industries (distributed by the Cultural Ministers Council) and industry multipliers from the input–output analytical tables for the United Kingdom (Office for National Statistics). Keynes’s emphasis on income and expenditure flows as key determinants of at least short-run real output variations also popularized the concept of multiplier analysis and the search for demand-based sources of economic vitality, which is fundamental to the export-base orientation of the EIM approach. As with the broader macroeconomic debate regarding demand-focused Keynesian models, fluctuations in outside demand will affect local economic activity, even if more fundamental determinants of long-term growth are often linked to labor productivity, infrastructure quality, the effect of industry structure on innovation and other more supply-orientated factors. Therefore, even if the arts can be portrayed as a basic export industry (usually a significant challenge), their role in long-run economic growth would not be established via conventional economic impact studies (see Seaman 1987 [1997]). Conceptually, a sophisticated economic impact study (SEIM) of X should attempt to answer the question: ‘How much would short-run economic activity decline in a specific region if X were no longer to exist?’ A thorough input–output model combined with a scrupulous analysis of the data designed to identify the accurate direct economic impact would ideally be used to address this question since it could (1) distinguish between net injections into the region from tourists or other external sources (typically named the primary direct impact) and diversions of local spending; (2) identify immediate leakages

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Economic impact of the arts  245 from the local region by carefully identifying all vendors and spending flows (with the amount of spending retained locally through at least one round sometimes named the capture rate); (3) properly identify any ancillary spending by those tourists or other external sources that are uniquely the result of the existence of X (often but not always named the induced direct impact); and (4) utilize multipliers that reflect the actual interdependencies among specific economic sectors and the size and degree of self-sufficiency of the target region so that all of the subsequent indirect impacts (both primary indirect and induced indirect impacts) can be properly measured.3 This type of an economic impact study would measure the total impact (whether in output, earnings or employment, and there are distinct multipliers for each) as in equation (27.2): Total impact 5 Direct impacts 1 Indirect impacts 5 Direct impacts 3 Multiplier (27.2) However, this is a difficult standard to meet, is costly to produce and must be distinguished from more modest economic impact studies that do little more than document the financial magnitudes of some sector or activity in the spirit of national income accounting. The term satellite account was developed by the United Nations to measure the size of economic sectors not already defined in national accounts as industries, and led many countries to focus attention on how exactly to define the arts sector as well as related sectors such as tourism. These sector-size studies are in the same spirit as other naive economic impact models (NEIMs), such as the census method which simply uses the aggregate budget of an organization, its total ticket revenues and possible capital expenditures without any adjustments to separate net injections from diversions of spending, and then typically applies average multipliers that do not adjust for the nature of the asset being evaluated or for the size and degree of self-sufficiency of the relevant region. A third low-cost EIM alternative that seems inexplicably more prevalent in the US is the online economic impact calculator. While not always focused on the arts (airports, boating, animal agriculture, public libraries and general tourism are particular variations), the first of these low-cost EIMs originally extrapolated from the findings of the unprecedented 1992 effort by the National Association of Local Arts Agencies (NALAA) to study the impact of diverse arts organizations in 33 different communities in 22 states (in cooperation with economists at Davidson-Peterson Associates). This has evolved into the Arts & Economic Prosperity calculator, and a fifth companion written national report (1994, 2002, 2007, 2010 and 2015) based most recently on 341 diverse American communities and regions across all states (Americans for the Arts 2015). Other arts-focused and more regionally specific online calculators are the Greater Philadelphia Cultural Alliance economic impact calculator (in cooperation with local economists), and the Georgia Arts (GAARTS) impact calculator focused on cultural organizations created by the current author for the Georgia Council for the Arts (in 2008), with an expanded Georgia calculator now in use in South Africa.4 The City of Boulder, Colorado is an example of a regional online calculator directly derived from the Americans for the Arts’ ‘Arts & Prosperity’ calculator, which they named the ‘Boulder Arts & Economic Prosperity 5 Study Calculators’. Despite the relative technical and analytical sophistication of some of those online calculators, they cannot substitute for case-by-case detailed studies (and there is always a

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246  Handbook of cultural economics warning to this effect to users). Everitt (2009) provides a critical review of the ‘Arts and prosperity III’ 2007 study, and there is one particular feature of the related Americans for the Arts online calculator that is especially troubling: the direct translation of an organization’s total expenses into a component of the expenditure impact on the community without any apparent adjustment for the origin of those funds (local or non-local) and the uses of those funds (the degree of local capture). This gives user organizations the entirely false impression that their own budgets are the minimum relevant local economic impacts, and dangerously focuses their attention on how big a multiplier effect can mechanically be applied to their budgets instead of on whether they are having any net incremental impact.5 Also, compared with more state-specific online calculators, the Arts & Economic Prosperity calculator has the natural disadvantage (despite its link to underlying carefully carried out surveys of target organizations and regions) of not being able to fully incorporate county-specific multipliers, local options sales tax rates, the relevant state sales tax rate, and the relative populations of counties versus municipalities that are usually important in dividing sales tax revenues among local jurisdictions.

FURTHER EVALUATION AND RECENT DEVELOPMENTS The residents of any local region will annually be exposed to numerous economic impact claims. It is unsurprising that general skepticism (or total indifference) will meet the simultaneous assertion that non-profit arts and cultural organizations have added $765 million per year to the local economy, the local sports sector has added another $1.25 ­billion, while other industries (or organizations) from A to Z weigh in with their own impact claims. Is it correct to presume that these claims are always systematic overstatements? It is important to realize that in terms of equation (27.1), the short-run spending impact (SRS), which is the focus of conventional economic impact studies, is only one of the three components of the total impact. Therefore, assuming away interdependencies among those three components (including the consumption and long-run growth impacts), a correct derivation of the short-run spending impact would itself be an understatement of the total impact. Thus, even if a naive study overstates the true short-run economic impact, that overstatement can conceivably be a more accurate measure of the true total impact than a more sophisticated impact study. Seaman (2006a) examines the specific circumstances under which a NEIM might consequently be right for the wrong reasons. Seaman (2006a) also poses the question: ‘When more than one methodology is used to measure economic impact, are those separate results complements or substitutes?’ That is, if a contingent valuation study is performed together with an economic impact study, should those separate results be summed to obtain the relevant total economic impact? The answer depends critically on whether those two methods are measuring entirely different aspects of economic impact. That would be the case if, for example, contingent valuation only was capturing the user and non-user consumption impacts in equation (27.1), while economic impact exclusively was measuring the short-term spending impacts in that same equation. However, as an alternative possibility, people’s stated willingness to pay for the expansion of an arts organization, or the sponsorship of a local arts event, may not be independent of their expectations regarding the resulting increases in output, incomes, employment and tax revenues (even if small in magnitude). This creates the

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Economic impact of the arts  247 distinct ­possibility of double counting if the CVM impact is added to the EIM impact, since those two approaches are likely to be at least partial substitutes.6 Snowball (2008, p. 223) reports finding just this type of substitution effect between willingness-to-pay results in at least one of her South African case studies, especially among low-income residents. Alberini and Longo (2006, pp. 288–9) combine a travel cost approach with contingent valuation methods in their study of the value of heritage sites, but those two methods are solely complementary inasmuch as they utilize travel cost to measure the value of sites based on actual observed visitor trips given existing attributes of those sites, and by contrast they use contingent valuation to estimate expected future trips under hypothetical conditions linked to changes in those attributes. They also observe the travel cost method is only capable of measuring use values for those who visit a site and cannot measure non-use values of the site to those who wish to conserve them but do not or cannot visit them. To the extent that CVMs can estimate those non-use values, the results from the travel cost method and the CVM would again not be overlapping. Ignoring those complications and returning to our focus solely on the short-run spending impacts as measured by economic impact studies, the aggregate of all EIM studies will invariably be an overstatement of the net additional regional economic activity that would not otherwise occur. There are two reasons for this: (1) the mix of all reported EIM results will include some combination of inflated NEIMs such as size or census studies and sophisticated accurate models (SEIM); and (2) those cases in which the local economic impact in terms of net increased output, earnings and employment is $0 (as would be the case if the local arts sector had no export component and only served local residents, or did have external funding sources but a 0 percent capture rate, hence changing at best the composition but not the size of the local economy) will never be reported publicly (at least not by industry sponsors). As regards any individual study, what are the critical types of errors, and to what extent have modern SEIM studies succeeded in avoiding them? Seven broad types of errors are identified and, where applicable, selected examples of studies that provide notable improvements in study design to limit those errors are briefly identified in the following list. 1.  Direct base (spending diversion) error: the failure to subtract local sources of funds and non-local uses (or recipients) of funds from the budgets of the subject entities; this also requires the estimation both of displacement effects and non-local vendor capture effects linked to spending by attendees of arts events and festivals. 2.  Induced (ancillary spending) base error: the erroneous attribution of all hotel, restaurant, retail and other spending by non-local arts consumers to the existence of those arts organizations or arts events. 3.  Multiplier (indirect impact) error: the failure to adapt the multiplier to the specific region, including the failure to recognize that smaller, less self-sufficient regions that are likely to have more net injections of non-local spending also have smaller multipliers owing to more extensive spending leakages. 4.  Supply constraint (crowding-out) error: especially relevant to large tourist events than to arts organizations, the failure to consider whether the local transportation and hospitality infrastructure could simultaneously absorb the influx of arts event visitors as well as the normal flow of tourists to the local region.

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248  Handbook of cultural economics 5.  Aggregation error: the simple summation of incremental impacts from smaller jurisdictions, such as counties, into a total statewide economic impact without adjusting for the circumstance that what was a net injection of new activity into a smaller region by non-local visitors may not be a net injection into the larger region when those same visitors to a smaller region are residents of the larger region. 6.  Ex post verification error: the failure to verify, if possible, whether any observed closures of local arts organizations or temporary interruptions of activity owing to labor disputes have had any adverse economic effects consistent with prior economic impact claims, or whether econometric testing can isolate the beneficial effects on taxable sales, employment or incomes in relevant time periods linked to an event. 7.  Policy interpretation (partial versus general equilibrium) error: the incorrect presumption that a positive economic impact is a sufficient condition to make a claim for government support without considering the opportunity costs of diverting that support from other potentially higher rate of return public sector investments. Economic impact studies by professional economists generally limit the first three of these technical errors, and sometimes can limit all of them. A study of the 1999 Eurovision Song Contest in Israel (Fleischer and Felsenstein 2002) conceptually ties the usual short-run spending effects to theoretically important economic surplus concepts (consumer, producer and government) and uses a balance of payments approach to provide a more complete cost–benefit analysis. Two studies that do an especially good job of avoiding the induced base error are the Kentucky study (Thompson et al. 1998) and the Renoir and Barnes art exhibit study (Stanley et al. 2000). The latter documents with special clarity the importance of carefully adjusting visitor spending for the ‘primary purpose of visiting a local region’ (in this case Ontario and Quebec) (Stanley et al. 2000, pp. 246–7). From a total base of C$67 million in spending by visitors to the Renoir Exhibit in 1995, various downward adjustments eventually yielded only C$8 million (11.9 percent) in ‘new money brought into the province which would not otherwise have been spent there’ (Stanley et al. 2000, pp. 247–8). The policy interpretation error is primarily committed by sponsors of these types of studies and other arts advocates, despite warnings by economists, and this error is not limited to EIM studies but is also equally common in CVM and other methodologies. The two issues that are frequently addressed by economists in sports contexts, but rarely in arts impact studies, are the potential supply constraint and the ex post verification errors (see Seaman 2006b). Sports economists often come close to arguing that the incremental economic impact of a city hosting a major sporting event, or an entire professional sports team, approaches zero. This is generally linked to extreme skepticism that a normal-sized city (for example, Tampa Bay, Florida) could absorb the claimed 100 000 additional visitors to a mega-event such as the Super Bowl without fully displacing all other tourists over that time period, stressing supply constraints and crowding-out. These arguments can sometimes be shown to be overstated since the significant advance notices of major events of this type should allow normal events and visits to be rescheduled instead of permanently canceled. Usually, time-switching is cited by critics of economic impact studies when no adjustment is made for those who would have visited city X in September, but shift that visit to March to correspond with some scheduled arts or sporting event (see Crompton 1995, p. 27). However, in this case, the ability to delay visits to less crowded periods significantly weakens the supply constraint criticism.

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Economic impact of the arts  249 The most notable analytical advances are the increasingly sophisticated econometric studies undertaken primarily by sports economists for ex post verification of ex ante impact claims. For example, Baade et al. (2008) provide a useful survey as well as new results focused on taxable sales, while Porter and Fletcher (2008) examine the 1996 Summer Olympics and the 2002 Winter Olympics. There are increasing numbers of these studies alleging that past historical experience has failed to reveal significant changes in the level of local economic activity in years (weeks or months) in which a city has hosted various mega-events. While technical issues can always be raised about such estimations, these ex post sports studies are generally consistent with earlier empirical studies finding that work stoppages in professional football and baseball had no notable impact on the economies of cities with those sports franchises, and that the departure of professional basketball teams had no discernible impact on the economies of host cities in the following years. This is not to deny that fans of those teams were not upset, or did not lose consumption or other economic value, but that the traditional measures of economic impact were not registering those effects. An especially interesting debate regarding econometric impact studies concerned the employment effects of the 1996 Atlanta Summer Olympics, with two related studies finding significant and lingering beneficial employment effects of the Olympic Games in some geographical areas in the US state of Georgia (Hotchkiss et al. 2003, 2015), with the second of these studies being a response to methodological criticisms of the first study raised by Fedderson and Maennig (2013). Despite the very significant challenge that this econometric sports literature presents to economic impact claims, not only in sports but by extension also in the arts/cultural sector, the technical issues that are raised are not trivial. Skepticism is warranted as to whether these studies have proven that nearly all regional economic impact claims should be adjusted by moving the decimal point one place to the left (a common assertion by sports economists, who would argue that if a mega-sports event or tournament is claimed to have generated $105.87 million in local economic impact, that figure is more likely to be no more than $10.587 million). Admirably, even prominent sports economists who have conducted such econometric studies have highlighted these issues, most notably Robert Baumann and Victor A. Matheson (2011) in their ‘Estimating economic impact using ex post econometric analysis: cautionary tales’. There are two key threshold issues in econometric studies of economic impact. The first is the ‘needle in a haystack’ problem (together with long-standing debates about economic versus statistical significance) of whether econometric analysis, regardless of sophistication, can isolate the unique impact of events/organizations/­ facilities having impacts that are not trivial in absolute dollar terms, but that are very small as a percentage of regional gross domestic product (typically a small fraction of 1 percent). The second key threshold issue is the most defensible time period over which to try to measure these impacts. By definition, multiplier effects extend over multiple time periods and, as noted previously, rational consumer behavior would anticipate that visitors shift their timing of visiting a region in order to avoid peak periods when previously announced events could cause local crowding issues. This suggests that the crowding-out problem that plays a central role in the rationalization of weak econometric impact results is unlikely to be sufficiently significant to explain those results (an argument that might be named Godzilla crowding out; see Seaman and Price Elton 2016).

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250  Handbook of cultural economics While recognizing both problems (especially the time-period issue), Baumann and Matheson (2011) focus their attention on more technical challenges, including: (1) the need to simultaneously control for city and time effects, a problem that limits the number and types of events that can be studied; (2) limitations to which first differences and percentage change dependent variables can adequately control for unit root problems; (3) limitations to which fixed effects and dummy variables can solve key econometric challenges without creating other problems; (4) more generally, solutions to the autocorrelation problem may not be feasible; (5) the omitted variables problem causes such a spurious correlation challenge that a well-specified model is critical; and (6) instrumental variables and general methods and moments models are necessary to address critical endogeneity issues. A suggestion to possibly address these econometric issues is to use synthetic control methods (for example, Seaman and Price Elton 2016). An example is Islam’s (2019) attempt to move away from panel regression procedures and substitute a case study approach using synthetic control techniques in the context of local sports teams and facilities, focusing on the effect of National Football League (NFL) expansion into three cities in the US. His finding that the presence of a sports franchise ‘does not significantly affect the time path of employment’ (Islam 2019, p. 242) would seem to reinforce the widespread econometric skepticism about economic impact. However, even ex ante studies and non-econometric ex post studies of franchises/teams/organizations (in contrast to mega-events and the construction impacts of facilities) have generally found very limited regional economic impacts, largely owing to limited direct impacts from non-local spending injections (since the fan bases are primarily local) and a significant part of team spending is not captured locally when paid to players who do not live in the region. Hence, this result does not fundamentally challenge there being non-trivial economic impacts from hosting arts festivals (sports tournaments) even if the spending economic impact of a local orchestra (football team) is limited. With a very notable econometric exception (discussed below), similar systematic ex post attempts to verify any of the ex ante claims made in arts economic impact studies are still rare (Skinner 2006 was a preliminary but very limited attempt), despite the threat of actor and other television and movie industry strikes always generating fearful claims as to the dire consequences for the economy of Southern California (with similar claims made regarding Broadway and New York City). Also, sometimes there are non-econometric ex post verifications focused on seeing whether pre-opening predictions about attendance were actually observed, or where zip code or other location tracing data are available, whether the geographic distribution of visitors was as expected. In the arts case, the exception to this dearth of ex post econometric testing is the study of the ex ante versus ex post analysis of the impacts on Maribor, Slovenia, of being a European Capital of Culture (Srakar and Vecco 2017). This research utilized surveys and stratified sampling methods as part of a detailed ex ante impact study focused on both visitor and direct budgetary non-local injections, incorporating defensible adjustments and parameters, and found 2012 output impacts of between €88.0 million and €105.7 million (value added of between €42.3 million and €51.5 million), and total number of employment impacts ranging from 1007 to 1132. In their econometric ex post analysis, the size of the economic impact linked to tourism arrivals and overnight stays (including foreign tourists) was large and statistically significant for the city of Maribor itself, but no effects were found for five

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Economic impact of the arts  251 partner cities. Their econometric employment results were enigmatic, suggesting negative impacts (not totally unheard of, but still relatively rare, in sports studies), but more likely due to an inability to fully separate the negative effects of the ongoing financial crisis (important in Slovenia in 2012), as well as economic and political turmoil in Maribor in 2012, in contrast to any positive incremental effects of being the Capital of Culture. They do not totally discount the possibility that crowding-out could have been an issue, but also recognize that econometric modeling inadequacies can plague these types of econometric studies. Another important result in the Srakar and Vecco Maribor study was linked to CVMs (with the sample evenly split between Maribor and its partner cities, and other locations in Slovenia), demonstrating a ‘large willingness-to-pay for continuing the project after its finish in a reduced, 25%, yearly size’, consistent with a mean individual willingness to pay of €13.80 and a three year aggregated value of €68.4 million (Srakar and Vecco 2017, p. 205). Similar contingent valuation studies continue often to demonstrate notable economic impacts even when output, income and employment impacts are more problematic. This also holds true for sports. For example, deBoer et al. (2019) found that after-the-event willingness to pay (WTP) to host a large international sports event is even higher than before-the-event valuations (specifically, for the second largest cycling event in the world, Giro d’Italia in 2016, held in the Gelderland region of the Netherlands). DeBoer et al. (2019, p. 159) found that the percentage of residents with positive WTP increased from 29.7 percent to 39.3 percent immediately after the event, with individual WTP increasing from €3.58 to €4.45, and with aggregate valuation hence increasing from €5.8 million to €7.1 million. Although those valuations are relatively small compared with the Maribor contingent valuation results, the Giro d’Italia is a three-week event compared with the Maribor case of being a cultural capital for an entire year. In summary, insightful future research and the debate on economic impacts will continue to focus on these ex ante versus ex post methodologies, as well as the relationships among the alternative measurement approaches, and the reasons for any differing results in the similar entertainment/cultural sectors of arts versus sports.

NOTES 1. In the United States alone, the National Assembly of State Arts Agencies identifies 45 economic impact studies between 2005 and 2009. Previous surveys identified as many as 250 of this type of American studies between 1973 and 1993, but their popularity is hardly limited to the United States. 2. When interviewed for his own opinion, William Baumol took the diplomatic route by conceding to doubts that any one of the numerous outstanding New York arts organizations could itself generate such impacts, but also defending the general instrumentalist point that ‘taken together, the cultural institutions . . . are really the key attraction of visitors to the city’ and ‘together with the financial center, are among the primary ingredients in the city’s prosperity’ (in Taylor 2006, pp. 89–90). Schwester (2007) provides an excellent example regarding sports stadiums where he finds support for public subsidies only stemming from ‘nonpecuniary, public good externalities’ rather than their insignificant effects on local jobs or incomes. 3. Inconsistent terminology for indirect and induced effects (with both combined sometimes called secondary effects) can be frustrating. For example, the multiplier effects are sometimes called the induced effects, and some popular regional accounting system models such as IMPLAN generate Type 1 multipliers to refer to indirect inter-industry supply relationships and Type 3 multipliers to refer to multiple rounds of induced re-spending of household incomes linked to increases in both direct and indirect spending. In that case, the Type 3 multiplier would be the final multiplier to apply to the direct impact (see equation (27.2) in this chapter).

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252  Handbook of cultural economics 4. The author has also created a more complicated but still user-friendly four-worksheet spreadsheet economic-impact model focused on cultural events and festivals as distinct from established organizations. Named Georgia Economic Model of Developmental Events (GEMODE), the user is asked to input data in a limited number of cells of the spreadsheet, and the formulas in the model generate the results. In collaboration with Jen Snowball of Rhodes University, Grahamstown, this model was adapted in 2017 for application to South Africa, and is now in widespread use as the South African Festival Economic Impact Calculator (SAFEIC), a free online resource for local South African communities that is also supported by the South African government. 5. For example, a recently completed state-wide study of the economic impact of the arts on the state of Georgia that inserted survey data from arts organizations into the GAARTS calculator generated a result that while the combined annual revenues of the surveyed organizations was $722 million, the incremental economic impact on the state was $387 million. This disparity is often very difficult to explain to arts personnel. See Atlanta Business Chronicle (22 January 2010, article by Maria Saporta). 6. One of the few studies to report valuation results using both economic impact and contingent valuation methods is ‘Arts and the Kentucky economy’ (Thompson et al. 1998). They added their contingent valuation result to their economic impact result to obtain a total impact result, hence implicitly assuming that those two methods were purely complementary.

SEE ALSO: Chapter 10: Contingent valuation; Chapter 13: Cost of production; Chapter 22: Cultural statistics; Chapter 23: Cultural value; Chapter 24: Demand; Chapter 45: Performance indicators; Chapter 58: Welfare economics.

REFERENCES Alberini, A. and A. Longo (2006), ‘Combining the travel cost and contingent behavior methods to value cultural heritage sites: evidence from Armenia’, Journal of Cultural Economics, 30 (4), 287–304. Americans for the Arts (2015), ‘Americans for the Arts prosperity 5 report’, brochure, Americans for the Arts, Washington, DC, accessed 13 December 2019 at https://www.americansforthearts.org/sites/default/files/aep5/ PDF_Files/ARTS_Brochure_Mockup.pdf. Baade, R.A., R. Baumann and V.A. Matheson (2008), ‘Selling the game: estimating the economic impact of professional sports through taxable sales’, Southern Economic Journal, 74 (3), 794–810. Baumann, R. and V.A. Matheson (2011), ‘Estimating economic impact using ex post econometric analysis: cautionary tales’, Working Paper No. 11-12, International Association of Sports Economists/North American Association of Sports Economists, accessed 13 December 2019 at http://college.holycross.edu/RePEc/spe/ MathesonBaumann_Econometrics.pdf. Bunting, C. (2008), ‘What instrumentalism? A public perception of value’, Cultural Trends, 17 (4), 323–8. Crompton, J.L. (1995), ‘Economic impact analysis of sports facilities and events: eleven sources of misapplication’, Journal of Sports Management, 9 (January), 14–35. DeBoer, W.I.J., R.H. Koning and J.O. Mierau (2019), ‘Ex ante and ex post willingness to pay for hosting a large international sports event’, Journal of Sports Economics, 20 (2), 159–76. Everitt, S. (2009), ‘Arts and economic prosperity III: a review’, Cultural Trends, 18 (4), 315–21. Feddersesn, A. and W. Maennig (2013), ‘Employment effects of the Olympic Games in Atlanta 1996 reconsidered’, International Journal of Sports Finance, 8 (2), 95–111. Fleischer, A. and D. Felsenstein (2002), ‘Cost-benefit analysis using economic surpluses: a case study of a televised event’, Journal of Cultural Economics, 26 (May), 139–56. Florida, R. (2002), The Rise of the Creative Class, New York: Basic Books. Hassett, K. and P. Swagel (2006), ‘Creative accounting: MoMA’s economic impact study: a museum’s value to the city’, Wall Street Journal, 30 August. Hotchkiss, J.L., R.E. Moore and F. Rios-Avila (2015), ‘Reevaluation of the employment impact of the 1996 Summer Olympic Games’, Southern Economic Journal, 81 (3), 619–32. Hotchkiss, J.L, R.E. Moore and S.M. Zobay (2003), ‘The impact of the 1996 Summer Olympic Games on employment and wages in Georgia’, Southern Economic Journal, 69 (3), 691–704. Islam, M.Q. (2019), ‘Local development effects of sports facilities and sports teams: case studies using synthetic control methods’, Journal of Sports Economics, 20 (2), 242–60.

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Economic impact of the arts  253 MacGillis, A. (2010), ‘The ruse of the creative class’, American Prospect, 4 January. McCarthy, K.F., E.H. Ondaatje, L. Zakaras and A. Brooks (2004), Gifts of the Muse: Reframing the Debate about the Benefits of the Arts, Santa Monica, CA: RAND Corporation. Porter, P.K. and D. Fletcher (2008), ‘The economic impact of the Olympic Games: ex ante predictions and ex post reality’, Journal of Sport Management, 22 (4), 470–86. Saporta, M. (2010), ‘Study: arts worth $387 million to the state’, Atlanta Business Chronicle, 22 January. Schwester, R.W. (2007), ‘An examination of the public good externalities of professional athletic venues: justifications for public financing?’, Public Budgeting & Finance, 27 (3), 89–109. Seaman, B.A. (1987), ‘Arts impact studies: a fashionable excess’, in A. Radich (ed.), Economic Impact of the Arts: A Sourcebook, Washington, DC: National Conference of State Legislatures, pp. 43–76, repr. 1997 in R. Towse (ed.), Cultural Economics: The Arts, the Heritage and the Media Industries, vol. 2, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Seaman, B.A. (2006a), ‘The relationship among regional economic impact models: contingent valuation versus economic impact in the case of cultural assets’, Andrew Young School of Policy Studies Research Paper No. 07-05, accessed 17 April 2019 at http://ssrn.com/abstract=975773. Seaman, B.A. (2006b). ‘The supply constraint problem in economic impact analysis: an arts/sports disparity’, Andrew Young School of Policy Studies Research Paper No. 07-04, accessed 17 April 2019 at SSRN: http:// ssrn.com/abstract=975770. Seaman, B.A. and J.J. Price Elton (2016), ‘How reliable are ex post econometric studies of regional economic impacts?’, PowerPoint presentation at the Nineteenth International Conference of the Association for Cultural Economics International, Valladolid, Spain, 21–24 June. Skinner, S.J. (2006), ‘Estimating the real growth effects of blockbuster art exhibits: a time series approach’, Journal of Cultural Economics, 30 (June), 109–25. Snowball, J.D. (2008), Measuring the Value of Culture: Methods and Examples in Cultural Economics, Berlin and Heidelberg: Springer-Verlag. Srakar, A. and M. Vecco (2017), ‘Ex ante versus ex-post: comparison of the effects of the European Capital of Culture Maribor 2012 on tourism and employment’, Journal of Cultural Economics, 41 (2), 197–2014. Stanley, D., J. Rogers, S. Smeltzer and L. Perron (2000), ‘Win, place or show; gauging the economic success of the Renoir and Barnes art exhibits’, Journal of Cultural Economics, 24 (3), 243–55. Taylor, K. (2006), ‘Study says Museum of Modern Art boosts economy – and possibly tourism, too’, The New York Sun, accessed 13 December 2019 at https://www.nysun.com/new-york/study-says-museum-of-modern-artboosts​-economy/36731/. Thompson, E., M.C. Berger and S.N. Allen (1998), ‘Arts and the Kentucky economy’, working paper, Center for Business and Economic Research, University of Kentucky, February.

FURTHER READING Snowball (2008) provides a readable and technically enlightening description and comparative evaluation of economic impact, contingent valuation, willingness to pay and choice experiment methods. Alberini and Longo (2006) combine travel cost (measuring actual use value) and contingent valuation (measuring hypothetical future use value) methods in valuing heritage sites, while Seaman (2006a) explores the theoretical relationships between contingent valuation and economic impact methodologies. Seaman (1987) and Crompton (1995) provide detailed descriptions of the potential abuse of economic analysis in economic impact studies. Baade et al. (2008) address the gap between the optimistic results generated by ex ante economic impact studies in sports and the dismal findings from ex post econometric studies, while Skinner (2006) provides a preliminary ex post analysis (of blockbuster art exhibits) and suggests some consistency with what might have been a simplified ex ante set of predictions. Srakar and Vecco’s (2017) more sophisticated study of not only ex ante versus econometric ex post output and employment impacts, but also contingent valuation impacts is an important contribution. Seaman (2006b) documents the substantially greater emphasis on community supply constraints in sports impact studies compared with arts studies (consistent with ex post sports studies generally finding de minimis regional impacts).

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28.  Event cinema

Allègre L. Hadida

The term event cinema, sometimes referred to as alternative content cinema or livecast, refers to the capture and transmission (customarily known as broadcast) in digital cinemas, generally in real time (live), of performances and events. They include opera (for example, Giacomo Puccini’s Tosca at The Met: Live in HD), theatre (for example, William Shakespeare’s Hamlet at National Theatre Live), concert (for example, ‘One Direction Live’ and ‘Take That: Greatest Hits Live’), ballet (for example, Pyotr Illyich Tchaikovsky’s The Nutcracker at Bolshoi Ballet in Cinema), musical theatre (for example, Billy Elliot Live), museum exhibitions (for example, ‘Van Gogh and Japan’ at the Van Gogh Museum), lectures (for example, ‘Margaret Atwood: Live’), gaming (for example, League of Legends Championships), sport (for example, the football World Cup Final) and television specials (for example, ‘Dr Who 50th Anniversary Episode’). Event cinema performances and events typically consist in a one-off, live broadcast followed by one or several encore broadcasts of the most popular content. Few studies in cultural economics thus far have addressed the nature, challenges and opportunities of event cinema. Among them, two Arts Council England commissioned reports stand out. Tuck and Abrahams (2015) provide an evidence-based review of this nascent format and its impact on the broader arts and cultural sectors, and Karpf Reidy et al. (2016) analyse how cultural producers and audiences react to event cinema and other forms of digital distribution, including online streaming and downloading, and television broadcasting. Barker (2013) also offers an account of the first few years of event cinema, and Bakhshi and Throsby (2014) and Bakhshi and Whitby (2014) examine how the National Theatre Live (NT Live) broadcasts increase audiences at the National Theatre. In classical music, Petrie et al. (2012) investigate the pilot programme of concerts streamed live online and to participating mixed-arts venues by a leading network of UK classical orchestras, venues and technology partners.

A SHORT HISTORY OF EVENT CINEMA BY Experience, the world’s leading global distributor of alternative content to cinemas, was launched in 2003 with the release of David Bowie’s album Reality with a performance and questions and answers screened live to over 50 000 fans in cinemas in 26 countries. This first event cinema broadcast resulted in the album debuting on top of the worldwide charts (www.byexperience.net/about, accessed 10 April 2019). The Metropolitan Opera (Met) at the Lincoln Center in New York City, which had pioneered live radio simulcasts in 1910 and live public television opera performances in 1977, partnered with BY Experience to launch The Met: Live in HD in December 2006 (www.metopera.org/about/ the-met/, accessed 10 April 2019). Two years later, more people: 254

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Event cinema  255 watch the Met Opera in movie theaters that in the opera house itself (around 850 000). Presumably many of the attendees will graduate from watching the opera in a movie theater to experiencing it at the Metropolitan Opera House. And finally, the HD program is public relations bonanza. The performances are covered by the local media in cities around the world as if the operas were actually held in those locales. The press clip file of the Met now has grown from magazine thickness to that of a telephone book. (Rosen 2008 [2017])

The success of The Met: Live in HD led Nicholas Hytner, then Director of the National Theatre in London, to consider expanding this model to theatre. In the summer of 2008, University of Cambridge Judge Business School MBA candidate David Sabel undertook a feasibility study to this effect under the supervision of the author of this chapter. Soon after, Sabel became the first NT Live producer. The advantages of theatre over opera as event cinema content are as follows. First, theatre is generally seen as less exclusive than opera. Second, theatre offers the opportunity to tap into the Hollywood A-list for talent, thus increasing the visibility of the productions and the awareness of audiences of broadcast theatre plays compared with operas, which performers, with the exception of a few stars, tend to be less familiar to general audiences. As a case in point, NT Live’s first-ever broadcast in June 2009 featured Dame Helen Mirren as Phèdre, and Benedict Cumberbatch starred as William Shakespeare’s Hamlet and in Nick Dear’s Frankenstein in the 2010–11 second season. The choice to include these productions in the NT Live programme was made partly to increase cinema exhibitors’ and audiences’ awareness of the new format and to motivate filmgoers familiar with these cinema A-listers to attend NT Live broadcasts. Third, theatre plays tend to be more familiar across media than opera libretti and scores, with books regularly made into plays (for example, Terry Pratchett’s Nation) and plays regularly made into movies (for example, Tom Stoppard’s Rosencrantz and Guildenstern Are Dead). The complexity and cost of production per broadcast also tend to be higher for opera at around £1 million versus £400 000 for theatre, excluding the opportunity costs of cordoning off entire rows of seats for camera use on the day of the live capture. This higher cost is mostly owing to the larger number of opera performers on stage and the combination of music, acting and singing. Even so, the words-based nature of theatre requires a higher level of viewers’ attention and increases the difficulty of transferring broadcasts to non-native speaking countries, leading NT Live and other event cinema providers to use subtitles in some markets. Under David Sabel’s and Emma Keith’s leadership, NT Live, which became profitable in the 2013–14 season (The National Theatre 2014), became a market leader in the UK and revolutionized the approach to recorded theatre by moving away from the traditional model of working fixed cameras ‘around a normal paying audience in the theatre that night’ (Sabel, quoted in Schutt 2010, p. 5) to creating a more dynamic experience with travelling cameras taking up, and therefore offering, the best seats in the house to cinema audiences.

PERFORMANCE Event cinema providers and artist managers identify months in advance which performances and events are best suited to being broadcast. Rehearsals and screen tests are carried out to select the best camera positions and angles, and to make sure that existing elements of the stage set, costumes and make up are well rendered by high definition (HD)

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256  Handbook of cultural economics cameras on large cinema screens. Alternatively, they may be modified to look good on camera and switched back to their previous condition after the broadcast. For instance, several props which details could not effectively be captured in HD over a dark stage background were dyed prior to the NT Live broadcast of the 2016 Donmar Warehouse production of Christopher Hampton’s Dangerous Liaisons, and a prosthetic mask was made to hide lead actor Lucian Msamati’s face microphone from the eagle eye of the HD cameras used to capture the 2017 NT Live production of Peter Shaffer’s Amadeus. On the day of the broadcast, several HD cameras carefully positioned in the audience and on stage, or (in the case of sports or gaming events) on the playing field, capture the action using a variety of angles and shots to give cinema audiences a unique viewing experience. Event cinema directors also customarily provide added value during intervals, including backstage tours, interviews with playwrights, stage directors or choreographers, and short documentaries. Event cinema has been steadily growing since its beginnings in 2003. It accounts for 1 to 3 per cent of the overall cinema box office worldwide in 2019, corresponding to over £1 billion (www.eventcinemaassociation.org/, accessed 12 April 2019). In the UK, concert overtook theatre in box office gross takings for the first time in the 2018–19 season, with these two categories accounting for box office revenues of £7.27 million and £6.64 million (25.7 per cent and 23.6 per cent of UK event cinema box office gross), respectively (internal NT Live data in 2019). While advances in HD cameras, screen capture and satellite broadcasting secured the viability of event cinema, the growth of the format rests on the proliferation of digital cinema screens: at the end of 2018, 97 per cent of all cinema screens worldwide, including all USA and Canada, Europe, Middle East and Africa (EMEA) and Latin America screens, were digital (MPAA 2019). The switch from analogue to digital proved costly to independent movie theatres and chains, with many of them unable to afford on their own the £50 000 to £75 000 average cost of a digital projector. Public support offered to purchase and install these projectors accelerated this transformation in many countries, including the UK.

EVENT CINEMA AS A PARTIAL CURE TO THE ‘COST DISEASE’ As explained in Chapter 46 in this volume, the performing arts are exemplars of a nonproductive industry. They suffer from an inherent ‘cost disease’ caused by the widening of the income gap between what may reasonably be charged at the box office and the rising costs of production. Lower attendance, owing in part to the growth of other cultural and leisure activities, including cinema, television and, more recently, online streaming and social media, also affects revenues. The performing arts are therefore condemned to decline and, eventually, disappear (Baumol and Bowen 1966). While Baumol and Bowen’s (1966) analysis is still valid, their conclusion ought to be nuanced (see Chapter 46 in this volume). Among other factors, the Internet and social media enable better dissemination of information on upcoming performances and events. For instance, the Brooklyn Academy of Music (BAM) sets an example of best digital practice. The BAM keeps its spectators up to date by sending them extensive information on a specific show prior to their attendance, including a teacher’s study guide in preparation for

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Event cinema  257 school trips, at little extra cost since the BAM owns the data (www.nyc-arts.org/organiza​ tions/347/brooklyn-academy-of-music-bam, accessed 8 April 2019). Furthermore, the screen-to-stage pattern, which emerged as a reversal of the more traditional stage-to-screen model, increases audience awareness and attendance through brand or character recognition. Disney on Broadway launched this trend in 1994 with a stage adaptation of Gary Trousdale’s and Kirk Wise’s 1991 animated film Beauty and the Beast, which then went back from stage to screen with Bill Condon’s eponymous 2017 feature film. Event cinema opens up a new technology-enabled ‘stage-to-screen’ pattern, as live and encore cinema broadcasts substantially expand audience numbers and earnings beyond the physical walls of the performing arts venue (see Chapter 46 in this volume). This is particularly significant at a time when television screenings of stage performances are increasingly few and far between (Sanderson 2019). Even so, the stage-to-screen model of event cinema raises economic and philosophical concerns akin to those formalized by Walter Benjamin in 1935.

EVENT CINEMA IN THE AGE OF MECHANICAL REPRODUCTION Benjamin (1935 [1969]) claims that mechanical reproduction such as that allowed by movie cameras has compromised the work of art’s presence in time and space: it has removed its sacred aura to replace it with politics. Cinema spectators no longer have to engage in a pilgrimage to see a work of art in its fixed place; they can experience it from the comfort of their local movie theatre. Technology has made cultural consumption less valuable by reducing the time and effort invested in it. The pilgrimage to the museum, historical site or cultural venue is removed from the event cinema experience as well, since the latter allows spectators, for instance, to experience a private visit of the British Museum’s major Pompeii and Herculaneum exhibition (Pompeii Live at the British Museum) in cinemas worldwide instead of having to travel to London and purchase a ticket to the exhibition to see it. Film actors have also lost their sacred aura to technology by allowing the immediate, organic rapport theatre actors have with audiences to become mediated by the camera acting as an extraneous accessory (Benjamin 1935 [1969]). The stage actor’s sacred aura has been replaced by the screen actor’s personality, making the latter akin to an artefact manufactured in a factory. Performing to a live audience or to a camera requires different sets of skills, which become blurred in an event cinema performing arts broadcast during which performers must do both simultaneously. Even though multiple seats are customarily lost to cameras on the evening of a live broadcast, providers still make sure that a substantial audience is at the venue for the performers to engage with. Also, HD camera close-ups capture the tiniest changes in an opera singer’s or a stage actor’s face and body language, even though they remain largely invisible to most spectators in the venue where the performance or event is captured. Performers have different reactions to this dual challenge. Ralph Fiennes and Sophie Okonedo, the two leads in the 2019 NT Live production of William Shakespeare’s Anthony and Cleopatra, reportedly found the cameras distracting and detrimental to their performances and engagement with the live audience on the evening of the broadcast

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258  Handbook of cultural economics (Sanderson 2019). In contrast, many performers find the dual presence of live audience and cameras stimulating. One London stage actor commented to the author of this chapter that he felt ‘more heightened’ when on stage for a live broadcast than for a regular performance. Live audiences also tend to be very engaged on the day of the broadcast, partly because they know they are on camera and taking part in a unique experience. Working with experienced cinema directors such as Sam Mendes and with actors equally at ease performing to a live audience and to a camera, including Sally Field, Bill Pullman and Gillian Anderson, largely contributes to the success of event cinema, as their star power and charisma on stage transfers to the cinema screen. The experiences of live and screen audiences also differ. According to Benjamin (1935 [1969]), just as a painter uses his or her brushes to remain at a distance to reality and a surgeon uses his or her instruments to work on a patient, camera operators use their equipment to penetrate deeply into the fabric of reality. The camera serves as director, dictating audiences where to look by giving them access to ‘multiple fragments’ rather than ‘the performance as an integral whole’ (Benjamin 1935 [1969], pp. 14, 9). As a result, screen audiences connect to the camera, not the actor. In the age of mechanical reproduction, everyone becomes an expert: every reader can be a writer, and every spectator can be a movie extra – or, in the case of event cinema, a live audience member, a gamer or an in-person museum visitor on the day of the capture. The audience has consequently become an absent-minded examiner, and society as a whole has shifted from concentration to distraction (Benjamin 1935 [1969]). Interestingly, existing research on NT Live audiences tends to disprove this last assertion, as audiences watching the performances in cinemas report being engaged (Schutt 2010), often to the point of applauding during the curtain call (Barker 2013) and tweeting their appreciation before and after the show. The following quote partly explains why: The experience of watching an HD live telecast of the Met Opera is remarkable. In many ways it is an improvement over seeing the opera in person. Heresy? No, not really. To start with, the close-ups of the singers on the screen are simply not available in the opera house. Also unique are the live interviews with the performers during intermissions; many are caught just as the curtain falls and they head backstage. Or they’re interviewed in their dressing rooms. And the specially produced documentaries shown during intermission – for example, how the opera was rehearsed – are insightful. Moreover, the high-definition images, color, and sound are all at the highest level. (Rosen 2008 [2017])

IS EVENT CINEMA A THREAT TO LIVE VENUES? A pervasive concern at the inception of event cinema was that audiences might be lured away from live venues and would substitute attending a performance or event in person for a broadcast in a nearby cinema. This could happen in two ways. First, event cinema could cannibalize the live audiences of the performing arts venues that take part in the broadcasts. Second, event cinema broadcasts from leading national operas, theatres and concert halls could substitute for regional performing arts venues by eating into their audiences, and eventually leading to their closure (Youngs 2014). Cultural economics research has demonstrated that those two apprehensions are largely unfounded.

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Event cinema  259 The Met has experienced a halo effect, as increases in the number of HD cinemas broadcasting The Met: Live in HD operas led to more in-person attendance at the Met, more subscriptions and more donations (Schutt 2010). Cultural economics studies and surveys carried out in the UK similarly conclude that live performances and event cinema neither compete nor substitute each other; they are complementary (Bakhshi and Throsby 2014). Event cinema neither displaces live attendance in theatres, nor does it seem to contract the touring market of theatre organizations (Karpf Reidy et al. 2016). Instead, event cinema offers theatres additional marketing opportunities, leads to renewed interest in the rest of their repertoire and makes them appear accessible to younger audiences, who are also often new to theatre as an art form (Bakhshi and Whitby 2014; Tuck and Abrahams 2015; Karpf Reidy et al. 2016). These results align with observations made in other cultural sectors, including classical music (Petrie et al. 2012). Event cinema also allows the National Theatre to fulfil its mission to ‘reach the widest possible audience’ (www. nationaltheatre.org.uk/about-the-national-theatre, accessed 10 April 2019) by meeting spectators in local cinemas near where they live. Most audience members consider live theatre to be more engaging than event cinema (Karpf Reidy et al. 2016). Consequently, they place a premium on the live experience in the actual venue, or in the words of Nicholas Hytner, on ‘the irreducible thrill of being in the room at the same time’ (Hemming 2017). Nevertheless, audiences typically perceive event cinema as a distinct and novel experience. They attend event cinema broadcasts because the corresponding live performances are sold out, and because they are closer to home, less time-consuming and less expensive than attending live performances (Karpf Reidy et al. 2016).

THE FUTURE OF EVENT CINEMA Event cinema redefines the boundaries of live performances and mainstream cinema. In the strategy terminology of Kim and Mauborgne (2005, 2017), the Met, the National Theatre and other leading event cinema providers have contributed to creating a blue ocean of uncontested market space with a new format at the intersection of live performances and events and cinema. As of February 2020, BY Experience had orchestrated the satellite distribution of over 250 unique live HD digital events to over 3000 cinemas and performing arts centres in more than 75 countries (www.byexperience.net/about, accessed 3 February 2020). NT Live, the first of 43 UK event cinema distributors in market share, similarly leverage their expertise in digital capture and broadcasting by offering their services to other venues, thus lowering the barriers to entry into event cinema for smaller or less technologically able theatres. NT Live went from four full-length productions broadcast from the National Theatre to 309 screens worldwide (including 84 in the UK) in their first season, to ten full-length productions broadcast from several venues, including the Nottingham Playhouse and The Old Vic, to more than 2500 screens (including over 700 in the UK) in 65 different countries in their 2018–19 season (http:// ntlive.nationaltheatre.org.uk/, accessed 10 April 2019). Three major challenges stand in the way of further expansion. First, event cinema is still unfamiliar to many exhibitors and spectators, and industry organizations such as the Event Cinema Association in the UK have been set up to raise awareness to the format.

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260  Handbook of cultural economics Other barriers to attendance include inconvenient timing and lack of viewing locations, particularly in rural areas (Karpf Reidy et al. 2016). Second, many live performance organizations still consider digital as an afterthought, and tend to neglect the difficulties that may arise in the future with the ownership and management of intellectual property rights across formats and channels. To prevent such complications and to generate substantial revenues as they expand to event cinema and other digital formats, including online streaming and downloading, live-performance organizations need to build digital rights management into their business model and event cinema into their programming from the outset. Third, technical issues may arise during live broadcasts and prevent cinema audiences from fully engaging with the experience. Even so, they become increasingly scarce as satellite transmission and broadcasting knowhow improve. Cinema audiences are also encouraged to tweet and signal them as they arise, thus assuring an immediate response from the movie theatre or the event cinema distributor. The success of event cinema has led traditional performing arts organizations to diversify into feature film production. The National Theatre, for instance, used NT Live’s partner network of independent cinema chains worldwide to launch Rufus Norris’s London Road, a 2015 live theatre/film hybrid adapted from a musical by Adam Cork and Alecky Blythe. The success of event cinema has also triggered renewed interest in performing arts broadcasting across multiple channels, thus generating an increase in competition for viewership. Bespoke digital platforms have emerged, including for instance Digital Theatre and Marquee.tv, respectively founded in 2009 and 2016 to offer on-demand access to dance, opera and theatre performances. Generalist streaming service Netflix has also streamed comedy stand-ups and concerts recorded live, including Springsteen on Broadway in December 2018, and started producing and capturing performing arts for the small screen with a first filmed theatre play in 2019 (Snow 2019). Such initiatives could raise audiences’ awareness to digital arts content and create positive spillover effects for both event cinema and the performing arts. The market for event cinema does not seem to have reached saturation yet. Not all projects are suitable for digital capture and streaming, and event cinema providers are still experimenting with content, formats and platforms. On-demand in schools and education services and consumer distribution across formats (including video-on-demand and subscription-based services) feature among the avenues they actively pursue. Virtual reality, three-dimensional, and augmented reality capture and rendition also look promising, notably for sport, dance and museum exhibitions. Advances to these technologies may lead event cinema providers to extend participatory theatre experiments beyond their location, by allowing, for instance, cinema audiences to vote live for specific outcomes and directions in an interactive play’s narrative together with live audiences in the venue. This could be achieved, for example, when staging and broadcasting live plays, such as, in 2015, Ferdinand von Schirach’s Terror, during which the audience are the jury on the trial of a fighter pilot who shot down a plane carrying 164 people to stop it crashing into a stadium containing 70 000 people. Virtual and augmented reality technologies may also enable future audiences to experience from their cinema seat the form of epic storytelling only possible in person and on site thus far by the immersive, location-specific plays produced by companies such as Punchdrunk and Third Rail Projects. Ultimately, event cinema is still a young form, which presents excellent opportunities for content and format innovation across arts organizations and cultural sectors, and for new research in cultural economics.

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Event cinema  261

SEE ALSO: Chapter 37: Media economics and regulation; Chapter 46: Performing arts; Chapter 47: Platforms.

REFERENCES Bakhshi, H. and D. Throsby (2014), ‘Digital complements or substitutes? A quasi-field experiment from the Royal National Theatre’, Journal of Cultural Economics, 38 (1), 1–8. Bakhshi, H. and A. Whitby (2014), ‘Estimating the impact of live simulcast on theatre attendance: an application to London’s National Theatre’, NESTA Working Paper No. 14/04, NESTA, London. Barker, M. (2013), Live to Your Local Cinema: The Remarkable Rise of Livecasting, London: Palgrave Macmillan. Baumol, W.J. and W.G. Bowen (1966), Performing Arts: The Economic Dilemma, Cambridge, MA: Twentieth Century Fund. Benjamin, W. (1935), ‘The work of art in the age of mechanical reproduction’, repr. 1969 in H. Arendt (ed.), Illuminations, New York: Schocken, pp. 217–51. Hemming, S. (2017), ‘Nicholas Hytner: you don’t find The History Boys by devoting yourself to Shakespeare’, Financial Times, 6 October, accessed 12 April 2019 at https://www.ft.com/content/2a38f8d0-a8f1-11e7-ab66-21cc87a2edde. Karpf Reidy, B., B. Schutt, D. Abramson and A. Durski (2016), ‘From live-to-digital: understanding the impact of digital developments in theatre on audiences, production and distribution’, AEA Consulting report for Arts Council England, UK Theatre and Society of London Theatre. Kim, W.C. and R. Mauborgne (2005), Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant, Boston, MA: Harvard Business School Press. Kim, W.C. and R. Mauborgne (2017), Blue Ocean Shift: Beyond Competing – Proven Steps to Inspire Confidence and Seize New Growth, Paris: Hachette Books. Motion Picture Association of America (MPAA) (2019), 2018 THEME (Theatrical Home Entertainment Market Environment) Report, Los Angeles, CA: Motion Picture Association of America. Petrie, M., A.L. Hadida, B. Schutt, S. Barakat and A.B. Cruz (2012), ‘A smooth sea never made a skilled sailor: DERO project, research findings & insights’, NESTA, London. Rosen, B. (2008), ‘The Metropolitan Opera – turnaround case study’, Huffington Post, 18 June, updated 6 December 2017, accessed 6 April 2019 at www.huffpost.com/entry/the-metropolitan-opera_b_107924. Sanderson, D. (2019), ‘Filming Shakespeare on stage has a tragic flaw: actors hate it’, The Times, 14 January. Schutt, B. (2010), ‘The work of art in the age of technological reproduction: the National Theatre goes to the movies’, Cambridge Judge Business School, University of Cambridge, The Case Centre, case ref. no. 310-221-1. Snow, G. (2019), ‘Netflix unveils plans to adapt theatre for on-demand platform’, The Stage, 30 January, accessed 2 February 2019 at www.thestage.co.uk/news/2019/netflix-plans-theatre-demand/. The National Theatre (2014), Annual Report, London: National Theatre. Tuck, F. and M. Abrahams (2015), ‘Understanding the impact of event cinema, an evidence review’, Trends Business Research (TBR) research and business intelligence report for the Arts Council England and the British Film Institute. Youngs, I. (2014), ‘Sir Alan Ayckbourn voices fears over theatre screenings’, BBC News Online, 11 June, accessed 8 October 2019 at www.bbc.com/news/entertainment-arts-27761568.

FURTHER READING More detailed analyses of event cinema from the point of view of cultural economics are provided in Karpf Reidy’s et al. (2016) comprehensive report, which also comprises six case studies of arts organizations having experienced live-to-digital shifts in recent years. Walter Benjamin’s (1935 [1969]) essay is a fascinating read as well. Its discussion of societies’ shift from concentration to distraction, in particular, appears timely in the current age of social media and constant digital interruptions.

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29.  Festivals

Bruno S. Frey

The oldest contemporary music festival is the Three Choirs Festival in Gloucester, Hereford and Worcester, dating back to 1724, followed by the Handel Festivals in Westminster Abbey. Among the most acclaimed European music festivals are the Bayreuther Festspiele (since 1876), the Glyndebourne Festival, the Salzburger Festspiele and the Spoleto Festival of the Two Worlds. Other famous festivals take place, for instance, in Edinburgh, Avignon, Aix-en-Provence, Würzburg, Lucerne, Verona and Bregenz. Most European cities or regions today have a festival of opera, theatre, cinema or some other form of art. A particular festival may embody a number of different types of performances and may take place in diverse locations (Saayman and Saayman 2006), such as open air, in historic stadiums, in churches, on the water, in city squares or in public parks. It has been estimated that there are between 1000 and 2000 music festivals per year in Europe alone. This chapter focuses on music festivals. However, most arguments also apply to other types of festivals. The emphasis is on Europe, where most festivals are located. In Europe a substantial number of artistic activities take place in publicly run venues, such as opera houses, theatres and concert halls. The situation in America is different. In the US a larger part of established artistic supply is privately organized, and therefore there is less need to organize festivals in addition. A great deal of the literature on festivals has been devoted to calculating the impact effects, that is, the multiplier effects generated by festivals on regional economic activity. In contrast, this text looks at the functioning of festivals themselves. It is useful to distinguish the various factors on the demand side from those on the supply side (see also Peacock 2006).

DEMAND FOR FESTIVALS It is useful to distinguish five reasons why people attend festivals: 1.  Incomes have risen. The large increase in real disposable income since World War II has enabled people to spend more money on vacation and cultural entertainment. Similar to other cultural events, festivals benefit from an income elasticity of demand larger than one. 2.  Attendance costs are lower. Many festival performances take place during the holiday season, so that attending provides a welcome chance for entertainment at little or no time opportunity cost. Also, travel costs have fallen. Consequently, the incentive for individuals to combine holidays and culture has steadily increased. 3.  Transaction costs are lower. A considerable barrier to attending artistic performances in a traditional venue is the effort involved in obtaining the tickets. In contrast, tickets for festivals are often provided by the same travel agency that takes the entire holiday bookings, and hence no additional effort is needed on the part of the visitor. 262

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Festivals  263 4.  Particular groups derive monetary advantages. The recording industry finds festivals an excellent opportunity to market compact discs, tapes and videos. The same holds for artists under contract, who can be placed in the limelight of an often very large number of spectators. Corporate sponsors can advertise their products and brand names more prominently than in regular concerts and opera performances. 5.  Politicians can seek popularity. Politicians can project themselves as patrons of the arts (with taxpayers’ money). They profit from the large amount of media attention associated with the opening nights and gala performances of well-known festivals.

SUPPLY OF FESTIVALS Four major incentives determine the organization of festivals: 1.  The cost of hiring artists and other employees is lower. Musical festivals can supply performances more cheaply than regular concert halls and opera houses can. Most employees (administrative, technical and artistic staff) have their main and permanent occupation at a concert hall or opera house paying their fixed costs (old age pension, health insurance, holidays, and so on). Festivals can often be run with a small number of permanently employed staff. Most participants (in particular the artists and the technical personnel) are employed for a limited period only and can therefore be hired at comparatively low cost. This does not mean that a festival’s artists and employees are badly paid; quite the opposite may be true. 2.  The cost of renting artistic venues is low. Festivals normally use existing structures of a permanent concert hall or opera house, since they are not used during the festival, or they take place in the open (often historical sites) or in churches. In any case, these venues can often be rented at a low price or even free of charge. 3.  Many restrictions are avoided. Established music venues have increasingly been burdened by a straitjacket of regulations making it difficult, if not impossible, for enterprising conductors and other musicians to reach their artistic and personal goals. One type of restriction is imposed by government. In Europe, most venues are either under close scrutiny or are part of the public administration, with all the consequences of very restricted bureaucratic flexibility and muted incentives. Festivals, in contrast, are often privately organized. The directors are freer to pursue a policy conforming to their own artistic ideas. It is easier to hire superstars, who in turn attract many visitors and allow high entrance fees. As festivals are designed for a short season, often only one or two weeks, there is almost no permanent employment, so that restrictions on hiring and firing are less relevant. The organizers may choose the form of collaboration with sponsors and recording companies best meeting their needs. They can use the revenue as they see fit, including to engage in new artistic endeavors. Other types of restrictions on established venues are imposed by trade unions. In addition to closely regulating salaries, they tend to strongly restrict working hours. As festivals hire people to perform specific services over a limited period of time, trade union restrictions apply less, if at all, compared with other types of music venue. Their influence is further reduced by the possibility of substituting ­professionals with volunteers to some extent.

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264  Handbook of cultural economics 4.  Artistic ossification is overcome. Many established concert and opera venues have lost their flexibility over time. Taste, particularly of the season ticket holders in these establishments, is normally conservative. By specializing in particular types of music, festivals offer the possibility of breaking new artistic ground by performing more modern programs.

FESTIVALS IN THE FUTURE Several determinants identified for the growth of music festivals also apply to other types of festivals, and even beyond to the visual arts in general. Art museums have also benefited from the rise in the demand for culture, and they also have been subject to government and trade union restrictions. Indeed, some of the major museums have become ossified, as the collection presented may not be changed in any way for historical reasons (this even applies to the hanging of paintings in a collection). Moreover, many such museums are not given the necessary funds to acquire additional art objects. In order to overcome these restrictions, enterprising museum directors arrange special exhibitions, with which they can pursue their artistic goals, gain prominence in the art world and attract large crowds. Blockbuster exhibitions are similar to festivals and have become major tourist attractions. Music festivals are an art form in constant flux. We may consider them a festival cycle. Festivals are typically created as the result of private initiative without government intervention. They often work against the publicly subsidized and regulated concert and opera activities. The temptation for the organizers to accept subsidies from public sources is strong, however, so that, over time, governmental involvement tends to increase. As subsidies are given only if official regulations are observed, the festivals tend to become ossified too. This provides arts entrepreneurs with incentives to create spinoffs to the established festivals in an attempt to regain discretionary power. After some time, these festivals acquire momentum of their own, thus restarting the festival cycle. Festivals may be interpreted as a welcome effort to overcome the cost disease, according to which live cultural performances face increasing deficits because their wage costs rise constantly, while there is little scope for an increase in productivity. Switching to festivals with lower wage and capital costs and higher income from recording firms and corporate sponsors, constitutes a shift towards live performances with better chances of survival. The steadily increasing number of festivals suggests that they are alive and well.

SEE ALSO: Chapter 19: Cultural districts; Chapter 27: Economic impact of the arts; Chapter 46: Performing arts.

REFERENCES Dwyer, L. and L. Jago (2015), ‘Economic evaluation of special events: challenges for the future’, in I. Yeoman, M. Robertson, U. McMahon-Beattie, E. Backer and K.A. Smith (eds), The Future of Events & Festivals, Abingdon: Routledge, pp. 99–115.

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Festivals  265 Frey, B.S. (1986), ‘The Salzburg Festival: an economic point of view’, Journal of Cultural Economics, 10 (2), 27–44, repr. 1990 in B.S. Frey and W.W. Pommerehne, Muses and Markets: Explorations in the Economics of the Arts, Oxford: Blackwell, pp. 49–60. Frey, B.S. (1994), ‘The economics of musical festivals’, Journal of Cultural Economics, 18 (1), 29–39. Frey, B.S. (1996), ‘Has Baumol’s cost disease disappeared in the performing arts?’, Ricerche Economiche, 50 (2), 173–82. Frey, B.S. and I. Vautravers-Busenhart (2000), ‘Special exhibitions and festivals: culture’s booming path to glory’, in B.S. Frey (ed.), Arts & Economics. Analysis & Cultural Policy, Berlin: Springer, pp. 67–93. Galeotti, G. (1992), ‘Riflettori sull’Iposcenio: Elementi per un’Analisi Economica del Festival di Spoleto’ (‘Spotlight on the understage area: elements for the economic analysis of the Spoleto Festival’), in G. Brosio and W. Santagata (eds), Rapporto sull’Economia delle Arti e dello Spettacolo in Italia, Turin: Fondazione Agnelli, pp. 125–47. Peacock, A. (2006), ‘The arts and economic policy’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: Elsevier/North-Holland, pp. 1123–40. Rizzo, I. and R. Towse (eds) (2016), The Artful Economist: A New Look at Cultural Economics, Cham: Springer International. Saayman, M. and A. Saayman (2006), ‘Does the location of arts festivals matter for the economic impact?’, Papers in Regional Science, 85 (4), 569–84. Tohmo, T. (2005), ‘Economic impacts of cultural events on local economies: an input-output analysis of the Kaustinen Folk Music Festival’, Tourism Economics, 11 (3), 431–51.

FURTHER READING This text follows partly Frey (1994). A general analysis of festivals from the viewpoint of cultural economics is provided in Rizzo and Towse (2016). Specific festivals are discussed in Galeotti (1992) and in Frey (1986 [1990]). Impact effects of festivals are calculated, for example, in Tohmo (2005). The relationship of festivals to special exhibitions is the subject of Frey and Vautravers-Busenhart (2000). For the cost disease see Frey (1996). A theoretical outlook can be found in Dwyer and Jago (2015).

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30.  Google Trends data

Olivier Gergaud and Victor Ginsburgh

In Europe, and to some extent, in many countries, cultural events, such as music or theatre festivals, European Capitals of Culture, and why not the Olympic Games or Wimbledon, benefit from public and private subsidies. The organizers have to show that what they have in mind will break even, or better, make profits. The costs and benefits from the event have usually to be reported to those who subsidized it, and from time to time these reports are made public, from which it is possible to realize that the methods used to compute the benefits are flawed, for two reasons. First, there are three types of visitor, and not all of them should be counted as adding value: 1. L  ocals, who would probably have spent more or less the same locally if the special event had not taken place (going to a restaurant, drinking wine in local bars, visiting a museum or going to a local concert). 2. Visitors from the surrounding neighbourhood and the country, who may have contributed to the city where the event took place but not to the gross domestic product (GDP) of the country. 3. Foreigners, whose expenses (only their local value added) contribute to the city, the region and the country. Visitors of types (2) and (3) may increase the revenues of the local population, but not necessarily of the region, and very rarely of the population in the rest of the country. We can even take a further step, and suggest that the expenses of visitors from the country itself should not be counted. Indeed, they do not increase the country’s GDP. So the only receipts that are worth counting are those coming from other (neighbouring or distant) countries, otherwise the event is just a beggar-your-neighbour, or even a steal-from-yourneighbour game. The types of visitor should at least be accounted separately: Cheating on numbers does not help and, to paraphrase Diamond and Hausman (1994), no number is better than a number that is wrong. The second reason is that the number of visitors may be difficult to assess. This is not the case when attending a specific event where entry tickets are needed (concerts, theatres, and so on). However, it is so with festivals or other comparable events (such as the Olympic Games and the European Capitals of Culture) that last for days or weeks during which guests go from one event to the other, and may need to be lodged and fed. We suggest using Google Trends which counts the clicks of people who look for information concerned with the cultural project to prepare their visit, though some may not come, but this hardly biases the results. Google Trends also collects their geographical origin. Although Google Trends cannot produce a full ex post evaluation, it contributes to an estimate of whether the project attracted visitors and it helps in correcting exaggerated receipts. 266

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Google Trends data  267 The view taken is, however, also extremely narrow, since it considers neither the cultural benefits of those who visit the city, nor of those who live in or close to the city where the event takes place. There are three elements that contribute to the impact of a cultural project: 1.  the monetary contribution of visitors, 2.  the welfare gains (or losses, such as additional pollution and noise, traffic jams) of those who live close enough as well as those of visitors, and 3.  the possible local long-term effects (new or upgraded museums, concert halls, green areas, roads, newly painted or restored house fronts, and so on). The short-term welfare gains and the long-term effects are very difficult to measure. We therefore restrict our discussion to the immediate monetary contributions of visitors, which is what is usually considered in ex post evaluations. Monetary effects are very often summarized by an expense multiplier R/I, where R and I respectively represent monetary receipts from visitors and investments in the project. Investments are in principle easy for the organizer to measure, and consist in private or public subsidies. However, with the exception of additional entry tickets to museums or to special events, such as concerts, exhibitions, additional overnight stays in hotels which consist mainly of local wages and profits, most receipts are not measured in terms of value added. This is much more complicated for other commodities that may be imported from other regions of the country or from foreign countries. Only the value added of the glass of wine sold in a bar during a festival in Dublin or Brussels should be accounted for, not the price paid by the visitor. Here also, the receipts are exaggerated if R contains costs and value added is borne elsewhere. There is thus the danger of exaggerating receipts in three ways: overestimating the total number of visitors, including the expenses of locals and accounting for the full price paid by the visitor instead of only the value added. Ad hoc methods used by experts without expertise often forget to do this, or do it only partially, since they have to convince donors that the event will be, or has been, successful.1

USUAL EVALUATION METHODS Several methods have been and are still used to evaluate the opportunity of creating cultural events, or to measure their fallouts: input–output analysis and computable general equilibrium models, time-series analysis, natural and randomized experiments, contingent valuation and surveys. Input–Output Analysis and Computable General Equilibrium Models The oldest approach is input–output analysis using national or regional input–output tables in which estimates of final demands are injected, and sector multiplier effects are recovered. This may work for events that have large national or even international effects, such as the Olympic Games, but in smaller events, such as music festivals, the effects are small, even unnoticeable, and country-wide or regional input–output tables would not help much. Computable general equilibrium models suffer from similar problems.2

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268  Handbook of cultural economics Time-Series Econometrics Time-series econometrics is used only rarely, both because of lack of data, and of events that are again too small to make it possible to discern the blip produced by the event in aggregate time series, or to decide whether the blip is just noise. The idea is to collect time series before, during and after the event, and compare the three periods.3 Natural Experiments A natural experiment is the result of an unexpected event that makes it possible to compare the behaviour of agents in normal times (the control situation) with the behaviour during or after the event considered to have changed the situation (the treatment). The 2003 Avignon theatre festival is one of these cases. Just before the festival was poised to start, and although everything was ready to run the show, it was cancelled because actors went on strike. Comparing what happened during 2003 with other years provides estimates of what got lost in 2003, but also of what the festival generates in normal times.4 The Avignon case uses the control and the treatment at different moments in time, but we can also apply the technique to events that could have been organized in different locations A, B, C and D that were candidates, while only one is submitted to the treatment; the Olympic games took place in city B while A, C and D play the role of controls, since they (hopefully) had the same basic characteristics as B. This is an essential request. Indeed, locations and populations should be as close as possible to each other.5 Randomized Experiments Natural experiments are rare, or they may not exist when they are needed. Randomized experiments were invented long ago by psychologists and are mostly used in the pharmaceutical industry where individuals are randomly allocated between those who receive the new drug (treatment) and those who receive a placebo (control). The problem is again making sure that the control and treatment groups are endowed with identical characteristics, and have no contacts with each other.6 Contingent Valuation, Willingness to Pay and Willingness to Accept Contingent valuation (CV), willingness to pay (WTP) and willingness to accept (WTA) are without doubt the methods that cultural economists prefer. Willingness to pay roughly consists in asking consumers (or producers) how much they would be willing to pay to avoid a negative or to accept a positive outcome; WTA goes for compensation, and asks agents how much they would like to be paid to accept a negative outcome, or how much they would be likely to pay to enjoy a positive outcome. See the special issue of the Journal of Cultural Economics edited by Schuster (2003) as well as Carson’s (2011) 7500 entries on the subject. Diamond and Hausman (1994, p. 45) ask whether ‘some number [is] better than no number’. Hausman (2012, p. 54) suggests that CV is not only dubious, it is hopeless as well. The debate seems therefore far from being closed. Hausman’s conclusion is utterly pessimistic: ‘I do not expect that proponents and opponents of CV will ever agree. Some bad ideas in economics and econometrics maintain a surprising viability.’

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Google Trends data  269 Surveys Surveys invariably come up with very positive results. The reason is that in most cases the event cannot be organized without subsidies, and private and public donors both have to be convinced that the event will be, is or was a profitable operation. Running surveys should not be criticized per se, but there is much to say against the way their results are used. Collecting VAT Receipts In most European countries Value Added Tax (VAT) is collected at least every month, but most events do not last during a full month, or take place between, say, 20 July and 10 August. In addition, the data are often very difficult to obtain from the tax ­administration. Those who organize events should be in touch with tax collectors, long before the event takes place, to make sure that the collection is organized in a way that can be used to examine the results a couple of weeks before, during and after the event. Summary Natural experiments as well as well-designed random experiments and analysis of time series are superior to all other methods, and should be used whenever possible. All other methods are weak (for example, input–output analysis since it can hardly capture small effects, such as those of a music festival) or strongly biased by the questions and answers used in CV, WTP or WTA, as well as in surveys: ‘I am willing to pay $100’ is not the same as ‘Here is my $100’. Collecting and analysing the receipts of the VAT, especially if they can be distinguished by type of outlet (hotels, restaurants, taxis, bars and coffee shops, tourist shops, other shops, and so on) would be extremely helpful. They could easily be adjusted by taking into account the origin of the visitor (city, region or foreign country) to assess the economic short-term monetary effects of the event.

GOOGLE TRENDS Google Trends (GT) provides a simple method using the number of clicks by those who look for information on events or destinations, and have been classifying possible visitors according to their origin since 2004. Although not every click will be followed by a visit, we can assume that this does not bias the final results. Note that repeated searches from the same person over a short period of time are eliminated. Many papers have been published during the past few years on the statistical possibilities offered by GT and the large correlation coefficients obtained by comparing observed numbers (when they exist) and Google clicks. In 2005, 64 per cent of travellers were using research engines before, during and after their tourist visit (Zheng and Gretzel 2010). This number is probably much larger nowadays. Choi and Varian (2012) were the first to use GT data to predict the number of tourist arrivals in Hong Kong.7 However, there are two problems. The data are provided under the form of normalized indices which take the value 100 for the largest number of clicks searching for a given

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270  Handbook of cultural economics destination and introduced by the citizens of a specific country, region or city.8 This makes it difficult, although not impossible,9 to compare the number of visitors between different events. The second problem is that we have to search using several keywords to make sure that we cover as much as possible (but nothing that is irrelevant). For the Bayreuth Wagner Festival, for example, we have to type ‘Bayreuth Festival 1 Bayreuther Festspiele 1 Bayreuth Wagner 1 Wagner Festival 1 Wagner Festspiel – Richard Wagner’, where the plus sign adds and the minus sign subtracts the information. Our experience suggests it is best to try as many words as possible, using several languages, but also using the minus sign to try to avoid duplications.

THE EXAMPLE OF FRENCH MUSICAL FESTIVALS Table 30.1 shows that even for important French music festivals, many clicks originate from other regions or cities within the country. Although some visits are quite important, especially for the well-known festival in Aix-en-Provence, these can be considered as beggar-thy-neighbour effects: what visitors spend in Aix-en-Provence is not spent in Auvergne (26) or Burgundy (18). Table 30.1  Google visitors at French musical festivals Aix-enProvence Alsace Aquitaine Auvergne Brittany Burgundy Ile de France Languedoc-Roussillon Lorraine Midi-Pyrénées Nord-Pas de Calais Picardie Poitou-Charentes Provence C. d’Azur Rhône-Alpes

9 26 8 18 23 19

Beaune

La Roque d’Anthéron

Orange

Saintes

Strasbourg 100

100 9

19

28 79

7

11

13 8 100 38

10

100

100 43

4

100

5 2 3

Note:  Location of festivals and French region in which the festival takes place are in italic; the largest number of visitors is 100, others are relative to 100.

THE EXAMPLE OF EUROPEAN CAPITALS OF CULTURE, 2011–16 In 1985, the European Union (EU) decided to nominate one European Capital of Culture (ECC) each year for a period of one year during which cultural events with a

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Google Trends data  271 strong pan-European dimension should be organized. Since 2001, two cities located in EU member states are chosen. Our results describe what happened in 11 ECCs during the period 2011–16, dropping 2017 and 2018, since we wanted to also analyse the two years that followed the event: Guimarães (Portugal, in 2012), Košice (Slovakia, in 2013), Maribor (Slovenia, in 2012), Marseille (France, in 2013), Plzeň (Czech Republic, in 2015), Riga (Latvia, in 2014), San Sebastián (Spain, in 2016), Tallinn (Estonia, in 2011), Turku (Finland, in 2011), Umeå (Sweden, in 2014) and Wrocław (Poland, in 2016). There are thus two cities every year, with the exception of 2015 where we dropped Mons (Belgium), keeping only Plzeň. (Mons was problematic since it has two names in Belgium: Mons in French and Bergen in Flemish. Bergen in Flemish also means mountains, and this would have collected millions of clicks that have nothing to do with the city. Bergen is also the name of a city in Norway. Note that even Plzeň (Pilsen) was problematic since there exists a beer that carries the same name.) We collected GT scores for each ECC over a period of eight years: five years before the event, the year of the event and two years following the event. For instance, Guimarães, an ECC in 2012, is followed between 2007 and 2014, while we observe clicks about Wrocław (ECC in 2016) between 2011 and 2018. Normalized clicks for each ECC are accounted for by restricting our queries to the travel category suggested by GT, using as keyword the name of the city, followed by the words ‘city in ***’, where *** is the name of the country, for instance, ‘Košice – city in Slovakia’. By doing so, we could avoid dealing with too much unrelated information. The clicks are summarized in Table 30A.1 in the Appendix to this chapter for each destination. As can be checked in column 2, Guimarães received clicks from 19 countries out of 72,10 between 2007 and 2014, with a score of 100 in Portugal, four from Angola and two from Brazil. All others are ,1. Clicks to Wrocław during the years 2011–18 come from ten countries, with a score of 100 from Poland (where Wroclaw is located) and a score of ,1 from all other countries. The most visited city is San Sebastián (column 8) which obtained at least a score of 2 from 29 countries, including a score of 25 from Puerto Rico, 93 from Spain and 100 from Andorra, which is not located in Spain, but in the Pyrenees, on the border between Spain and France. Marseille comes second with 22 countries of origin, including Reunion Island (a French island in the Indian Ocean) with a score of 70 and France with 100. The large number of small scores and zeros show that, although ECCs are largely subsidized by their own country as well as by the EU, other countries, including their European neighbours, are not very eager to show up. This clearly means that the GDP of the nominated country is hardly affected. The numbers in Table 30A.1, in the Appendix, are cumulated over eight years for each ECC and may therefore miss the peak year during which the event takes place, as well as the two years (before and after) that surround the event. To check for this issue, we ran two regressions, one for national clicks only (within the country in which the ECC takes place) and worldwide clicks (which unfortunately also include national clicks). The regressions are specified using eight dummy variables for years (five years before to two years after) and 11 dummies for the cities where the event was organized. The regression equation based on 88 observations (8 years 3 11 cities) is specified as:

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N ti 5 β t 1 α i 1 γ 1 εti ,(30.1)

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272  Handbook of cultural economics Table 30.2  Main determinants of GT clicks in 11 ECCs (2011–16) Time dummies Intercept Four years   before ECC Three years   before ECC Two years   before ECC One year   before ECC ECC year One year   after ECC Two years   after ECC

National

Worldwide

ECC dummies

39.984*** (3.268) 21.970 (3.098) 3.341 (2.962) 3.061 (2.331) 6.538** (2.551) 8.939*** (2.481) 8.331*** (2.693) 10.912*** (3.587)

62.262*** (3.756) 1.189 (3.621) 1.500 (3.451) 0.826 (3.218) 1.136 (3.368) 2.841 (3.487) 0.545 (3.884) 20.304 (3.700)

Guimarães

National

0.000 2 Košice 29.865** (3.864) Maribor 3.042 (2.530) Marseille 1.875 (2.695) Plzeň 1.462 (3.094) Riga 9.448*** (2.883) San Sebastián 2.552 (2.757) Tallinn 24.344 (4.499) Turku 5.740* (2.926) Umeå 1.760 (2.900) Wrocław 37.927*** (3.492) R-squared 0.825 No. of observations 88

Worldwide 0.000 2 22.885** (3.400) 211.156*** (3.302) 1.646 (3.230) 2.759 (4.102) 21.031 (3.463) 28.271** (3.923) 3.365 (3.707) 27.667* (3.885) 28.896 (3.963) 14.083*** (4.191) 0.694 88

Note:  Robust standard errors in brackets; *** p ,0.01; ** p ,0.05; * p ,0.10.

where Nti is the number of GT clicks in year t (t 5 25, 24, . . ., 0, 1, 2),11 for ECC i (i 5 Guimarães, . . ., Wrocław); eti is the error term. The parameters bt and ai pick up the differences between the reference year (year 5 before the event) and the excluded ECC (Guimarães). The estimated coefficients thus represent the difference between the regression intercept g which is common to all cities and years. The result of both regressions (national and worldwide clicks) are reproduced in Table 30.2. The estimated parameters can be interpreted as follows. In the left side of Table 30.2, the intercepts give the average number of clicks, both national and worldwide. They are very significantly positive and different from zero and national clicks (40.0/100) are smaller than worldwide clicks (62.3/100). The time and ECC dummies provide the additional effects, which can be positive or negative. Very few are significantly different from zero, which means that there is very often no additional effect. Four time dummies are positive: The national excitement starts one year before, increases during the event to some nine additional points (40 1 8.9), and lasts for two more years reaching 40 1 10.9. We do not know whether this positive effect lasts for longer periods. No additional worldwide time effect is significantly different from zero.

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Google Trends data  273 The right-hand side of Table 30.2 shows the ECC effects for Guimarães, the reference ECC in both regressions. At the national level, Riga (19.4) and Wrocław (137.9) are the only ECCs that generated a strong positive surplus, but the opposite occurred with Košice (29.9). Worldwide effects are usually negative or equal to zero, with the exception of Wrocław (although the effect contains the large increase, of 37.9, in Poland itself). Global effects on cities should include the sum of the time and the city dummies. Let us take Riga in its active year as an example. At the national level, the time effect is equal to 8.9 (time effect – ECC year) 1 9.4 (ECC effect), that is, 18.3 points. The worldwide effect on Wrocław is 8.9 1 14.1, that is, 23 points. The joint national effect on Košice, however, is negative (8.9 – 9.9).

FINAL REMARKS As long as serious econometric methods such as natural or well-designed random experiments, or time-series methods, are not used on relevant data (VAT receipts, for example), GT could play an important role. It is easy to use, costs some time but no money, and the results are easy to understand. It is in no way sufficient to cover the various aspects of artistic events, but it can help tempering the enthusiasm of professional experts who, for two neighbouring ECCs, Lille (France, in 2004) and Mons (Belgium, in 2015) discovered an expense multiplier of the order of five or six, even before the year of the event.12

NOTES  1.  2.  3.  4.  5.  6.  7.  8.  9. 10. 11. 12.

See Crompton (2006) and Crompton and McKay (1994). See Humphreys and Plummer (1995) and Matheson (2008). See Skinner (2006), Plaza (2006) and Plaza et al. (2011). See Brodaty (2017). See Billings and Holladay (2012). See Greene et al. (2014) and Lattarulo et al. (2017). See also Robbins et al. (2018), Jun et al. (2018) for many other references. For more details and how to use the website, see https://support.google.com/trends/?hl=en#topic=6248052 (accessed 1 March 2019). Indeed, it is impossible to run more than five different queries at the same time. There are 72 countries which gave at least one click to one of the 11 ECCs considered during the eight-year observation period. Zero represents the year during which the event takes place. For details, see Gergaud and Ginsburgh (2017) and Gergaud et al. (2017).

SEE ALSO: Chapter 2: Art auctions; Chapter 22: Cultural statistics; Chapter 52: Ratings, reviews and recommendations.

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274  Handbook of cultural economics

REFERENCES Billings, S. and J.S. Holladay (2012), ‘Should cities go for the gold? The long-term impact of hosting the Olympics’, Economic Inquiry, 50 (3), 754–72. Brodaty, T. (2017), ‘Annulations des festivals d’Avignon et d’Aix-en-Provence en 2003: des catastrophes économiques locales?’ (‘Cancellations of the Avignon and Aix-en-Provence festivals in 2003: local economic disasters?’), in Y. Nicolas and O. Gergaud (eds), Evaluer les politiques publiques de la culture, Paris: Ministère de la Culture. Carson, R. (2011), Contingent Valuation: A Comprehensive Bibliography and History, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Choi, H. and H. Varian (2012), ‘Predicting the present with Google Trends’, Economic Record, 88 (S1), 2–9. Crompton, J. (2006), ‘Economic impact studies: instruments for political shenanigans?’, Journal of Travel Research, 45 (1), 67–82. Crompton, J. and S. McKay (1994), ‘Measuring the economic impact of festivals and events: some myths, misapplications and ethical dilemmas’, Festival Management and Event Tourism, 2 (1), 33–43. Diamond, P. and J. Hausman (1994), ‘Contingent valuation: is some number better than no number?’, Journal of Economic Perspectives, 8 (4), 45–64. Frey, B.S. and I. Busenhart (1996), ‘Special Exhibitions and Festivals’, in V. Ginsburgh and P.-M. Menger (eds), Economics of the Arts: Selected Essays, Amsterdam: North-Holland, pp. 275–302. Gergaud, O. and V. Ginsburgh (2017), ‘Measuring the economic effects of cultural events with special emphasis on music festivals’, in V. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU, Cham: Springer, pp. 337–53. Gergaud, O., V. Ginsburgh and Y. Nicolas (2017), ‘Google Trends: un outil pour l’évaluation économique d’événements culturels?’ (‘Google Trends: A tool that helps assessing economic aspects of cultural events’), in Y. Nicolas and O. Gergaud, Evaluer les politiques publiques de la culture, Paris: Ministère de la Culture. Greene J., B. Kisida and D. Bowen (2014), ‘The educational value of field trips’, Education Next, 14 (1), 79–86. Hausman, J. (2012), ‘Contingent valuation: from dubious to hopeless’, Journal of Economic Perspectives, 26 (4), 43–56. Humphreys, J. and M. Plummer (1995), ‘The economic impact on the state of Georgia of hosting the 1996 Summer Olympic Games’, Executive summary, Selig Center for Economic Growth, Terry College of Business, University of Georgia, Athens, GA. Jun, S.-P., H.S. Yoo and S. Choi (2018), ‘Ten years of research change using Google Trends: from the perspective of big data utilizations and applications’, Technological Forecasting & Social Change, 130 (May), 69–87. Lattarulo P., M. Mariani and L. Razzolini (2017), ‘Nudging museums attendance: a field experiment with high school teens’, Journal of Cultural Economics, 41 (3), 259–77. Matheson, V. (2008), ‘Mega-events: the effect of the world biggest events on local, regional and national economies’, in D. Howard and B. Humphrey (eds), The Business of Sports, Westport, CT: Praeger, pp. 81–99. Maugham, C. and F. Bianchini (2004), ‘The economic and social impact of cultural festivals in the East Midlands of England: final report’, Arts Council England, Birmingham. Négrier, E., A. Djakouane and M.-T. Jourda (2010), Les publics des festivals (Festival Audiences), Paris: Editions Michel de Maule et France Festivals. Ormerod, P., R. Nyman and A. Bentley (2014), ‘Nowcasting economic and social data: when and why search engine data fails, an illustration’, accessed 3 March 2019 at https://arxiv.org/abs/1408.0699. Plaza, B. (2006), ‘The return on investment of the Guggenheim Museum Bilbao’, International Journal of Urban and Regional Research, 30 (2), 452–67. Plaza B., A. Gonzalez-Flores and C. Galvez-Galvez (2011), ‘Testing the employment impact of the Guggenheim Museum Bilbao via tourism satellite accounts’, Tourism Economics, 17 (1), 223–9. Rabin, C.P. (1990), Music Festivals in America, Great Barrington, MA: Berkshire Traveller Press. Robbins G., D. Choi and J. Joven (2018), ‘Google Trends and genius lyrics: the bright side of dark places’, accessed 3 March 2019 at https://bit.ly/38ys1qV. Rolfe, H. (1992), Arts Festivals in the U.K., London: Policy Studies Institute. Schuster, M. (ed.) (2003), ‘Contingent valuation in cultural economics’, Journal of Cultural Economics, 27 (3–4), 155–285. Silverstovs, B. and D. Wochner (2018), ‘Google Trends and reality: do the proportions match? Appraising the informational value of online search behaviour: evidence from Swiss tourism’, Journal of Economic Behavior & Organization, 145 (January), 1–23. Skinner, S. (2006), ‘Estimating the real growth effects of blockbuster art exhibits: a time series approach’, Journal of Cultural Economics, 30 (2), 109–25. Steiner, L., B. Frey and S. Hotz (2013), ‘European capitals of culture and life satisfaction’, Working Paper No. 117, Department of Economics, University of Zurich, accessed 3 March 2019 at http://ssrn.com/abstract=2251904.

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Google Trends data  275 Zheng, X. and U. Gretzel (2010), ‘Role of social media in online travel information search’, Tourism Management, 31 (2), 179–88.

FURTHER READING On Google Trends: the papers by Choi and Varian (2012) almost started the subject and are of course worth reading. Jun et al. (2018) give a nice summary on the ten last years of research. Ormerod et al. (2014) show that the search engine may also fail. See also a recent paper by Silverstovs and Wochner (2018) on tourism in Switzerland.   On festivals and other events: see Frey and Busenhart (1996), Négrier et al. (2010), Rabin (1990), Rolfe (1992) and Maugham and Bianchini (2004) on festivals in France, the US and the UK and Steiner et al. (2013) on European capitals.

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276

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Google visits from: Algeria Andorra Angola Argentina Australia Austria Belarus Belgium Bosnia & Herzegovina Brazil Bulgaria Canada Chile China Colombia Costa Rica Croatia Cyprus Czechia Denmark Ecuador Egypt El Salvador Estonia Finland

,1 ,1

2

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Guimarães Košice Maribor Marseille Plzeň Riga S Sebastián Tallinn Turku Umeå Wrocław Portugal Slovakia Slovenia France Czech Rep. Latvia Spain Estonia Finland Sweden Poland 2012 2013 2012 2013 2015 2014 2016 2011 2011 2014 2016

Table 30A.1  Google visitors to European Capitals of Culture, 2011–16

APPENDIX

277

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France Georgia Germany Greece Guatemala Hungary India Iraq Ireland Israel Italy Japan Kazakhstan Kenya Latvia Lithuania Luxembourg Macedonia Mexico Morocco Netherlands Norway Peru Philippines Poland Portugal Puerto Rico Romania Russia Reunion Serbia Singapore Slovakia 100 ,1

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278

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Note:  European Capitals of Culture (and countries in which the capitals are located) are in italic; largest number of visitors is 100, others are relative to 100.

Slovenia South Korea Spain Sweden Switzerland Thailand Tunisia Turkey Ukraine United Kingdom United States Uruguay Venezuela Vietnam

Guimarães Košice Maribor Marseille Plzeň Riga S Sebastián Tallinn Turku Umeå Wrocław Portugal Slovakia Slovenia France Czech Rep. Latvia Spain Estonia Finland Sweden Poland 2012 2013 2012 2013 2015 2014 2016 2011 2011 2014 2016

Table 30A.1  (continued)

31.  Heritage

Françoise Benhamou

The economics of the built cultural heritage has a particular status in the field of cultural economics. Heritage goods share some characteristics with other cultural goods, especially uniqueness and their perception as merit goods. They differ also from other cultural goods owing to durability and irreversibility; if a historical building is transformed or destroyed, it cannot be re-created or restored in its initial shape. From this viewpoint, heritage economics is close to environmental economics. They share a preoccupation with sustainability, and the existence of an international demand linked to tourism (see the 2017 special issue of the Journal of Cultural Economics on tourism and culture) and to the idea the corpus of heritage that exists belongs to all people. They also share the risks linked with climate degradation and pollution, on one hand, and geopolitical upheaval on the other. Heritage goods generate mixed feelings among researchers. Publications are not so numerous, probably owing to many methodological difficulties: empirical issues lack data, and comparative studies are limited by the very specificity of national situations. Moreover, there is a soft consensus in favour of public regulation, while subsidisation is criticised for its inefficiency.

DEFINITION Heritage includes different forms of cultural capital ‘which embodies the community’s value of its social, historical, or cultural dimension’ (Throsby 1997, p. 15). In this chapter we only emphasise the question of built heritage, in the restrictive sense of immovable heritage, including archaeological sites, historical buildings and historic urban centres (or some part of them). A minimal definition would identify the built heritage as the buildings and monuments inherited from the past, with a cultural or historical dimension justifying their preservation for next generations, but also contemporary monuments whose symbolic or cultural value is high, such as houses or buildings designed by international elite architects. Even in this sense, heritage includes a large range of goods, whose definition changes over time and space, and depends on the variety of dimensions (symbolic, cultural, national identity oriented, social, and so on) included in the concept (Chastel 1986). Therefore, heritage is a social construction whose boundaries are unstable and blurred, with a threefold source of extensions: historical additions, enlarging the concept of heritage towards additional items (gardens, industrial buildings, and so on) and to the intangible value of tangible assets. This last aspect can be considered as capital value (Rizzo and Throsby 2006). It also deals with trademarks and property rights that derive from heritage. Finally, tangible heritage has an intangible dimension that may justify the use of trademarks as a way to create value. For example, the Chateau de Chambord in the Loire Valley in France has created a brand protected by property rights and sells wine and other goods named Chateau de Chambord. 279

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280  Handbook of cultural economics Peacock (1995 [1997], p. 195) argues in favour of a Beckerian definition of heritage as ‘an intangible service increasing the utility of consumers, in which historic buildings and artefacts are inputs’. The definition recognises the existence of substitutes for goods that share some characteristics in common. This conception presents the advantage of including services offered through new technologies, provided that the consumer c­ onsiders a visit through the Internet as a satisfying substitute for real use. Evrard and Krebs (2018) insist on the low level of substitutability because of the high value of authenticity for visitors (see also Borowiecki et al. 2016). An institutional definition (the official listing of historical buildings) is the opposite of a more informal definition (what art historians or citizens think should be kept and preserved). Different institutional definitions of heritage also may be distinguished, depending on the level of the administration in charge of them: from a small city mayor deciding to undertake restoration of a little rural church, to an international organisation such as the United Nations Educational, Scientific and Cultural Organization (UNESCO) providing lists of artefacts that it considers to be the basis of an international human patrimony (Frey et al. 2011; Bertacchini and Saccone 2012; Wuepper and Patry 2017). In 2010, the World Heritage list included 890 properties that UNESCO considered to have outstanding universal value. Those goods share some characteristics of global public goods: decision-making involves many countries in the process of conserving. Their symbolic value reaches beyond one country and one generation (Frey and Pamini 2009). Local or national authorities may be in opposition with international demand. Contrary to Klamer and Throsby (2000), preservation is never obvious, as we have seen in 2001 with the Taliban’s destruction of Afghanistan’s giant sculptures, but also with the recurrent debate about the spoliation and restitution of parts of monuments, for example, the Parthenon friezes and their display in the British Museum, or with the controversial question of destroying or preserving urban centres built in the 1950s (Hoffman 2006). At the end of 2017, President of France, Emmanuel Macron, declared in Ouagadougou that ‘within five years, conditions will be met for temporary or definitive restitution of African heritage’ (Macron 2017). A highly controversial report by Savoy and Sarr (2018) notes that at least 90 000 works of art from sub-Saharan Africa are found in major European public collections, and proposes making an inventory and a transfer of the majority of the claimed works.

CHARACTERISTICS OF CULTURAL HERITAGE Cultural monuments and buildings may be privately or publicly owned. Whatever their status, they have public good characteristics. First, indivisibility generally prevails: the consumption of publicly owned goods is potentially identical for all consumers provided that the monuments – especially their façades – represent joint, non-rival goods. Nevertheless, congestion may occur for overcrowded monuments, putting them at risk: degradation, especially for superstar sites or monuments (for example, Venice, Mont Saint Michel, the Statue of Liberty, the Leaning Tower of Pisa and Angkor Wat), threatens buildings that attract too many visitors. For these monuments, reputation increases with the number of users, creating network externalities. Benhamou and Thesmar (2011) suggest slightly increasing the tourist tax on hotel rooms and allocating that revenue to heritage, in order

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Heritage  281 to internalise the positive externalities of heritage for the industry of tourism and to compensate for the deterioration of heritage due to mass tourism. Secondly, externalities are a source of market failure: heritage constitutes a legacy to be passed on to future generations (bequest value); heritage also confers benefits on individual citizens, who have not contributed to their production or preservation; and many economists emphasise the spillover effects of historical monuments for local activities and tourism. Moreover, excludability is not always possible or desirable. Greffe (2003) addresses the question of whether or not to price (when possible). He analyses the management of sites and buildings and price discrimination policies emphasising the lack of clarity that results from the large variety of policies. Those characteristics constitute a strong argument for public funding in order to correct market failure, and for the impossibility of grounding the choice of preservation solely on market forces (Mossetto 1994; Koboldt 1997).

THE MARKET VALUE OF HISTORICAL BUILDINGS: SOME METHODOLOGICAL QUESTIONS One of the greatest methodological difficulties is the evaluation of demand and supply. Tools are available to evaluate heritage demand and willingness to pay. Contingent valuation methods value consumer preferences that people place on heritage. Different biases are inherent to this survey-based methodology, especially free-riding, that can be explained by the collectively owned nature of certain goods as described previously. Referenda have the advantage of combining the evaluation of competing alternatives with democratic decisions. They are routinely undertaken in Switzerland (Frey 1997). The travel cost method is based on the hypothesis that the cost of travel (including time opportunity cost) to heritage sites is a satisfactory proxy for visitors’ willingness to pay. However, this method underestimates demand by excluding non-users. A proxy of the market value of historical buildings is the property rental. It may greatly differ from their scientific value (as the object of study) and communication value (the social significance of heritage, its aesthetic and commercial value); a property with zero market value except the land (for example, a country church) can have very great heritage value. Heritage goods have both option and existence value. Option value is defined by what the non-user is ready to pay in order to preserve the possibility of benefit from an asset in the future. Existence value is obvious when individuals gain utility from the mere existence of cultural goods that they do not directly consume. The hedonic pricing method is theoretically much more convincing. According to this method, a building is considered to be a bundle of characteristics. It estimates the differences in the value of buildings with a set of identical characteristics, but located in two different areas (listed and non-listed), considering that the price of a property can be viewed as the sum of the shadow prices of its characteristics. Unfortunately, many difficulties arise for the estimation of hedonic prices (Stabler 1995). It has been suggested that the utility of preserving the past increases with the age of consumers, especially during rapid social and economic change, when national identities seem threatened by changes. Therefore, the intensity of demand varies according to a series of factors: access, revenues, price and age.

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282  Handbook of cultural economics Costs of restoration and upkeep are high since listing implies the hiring of skilled labour and the use of rare, and hence expensive, building materials (Benhamou 1996). These costs increase with the stock of heritage. Arguably, nobody can anticipate the test of time. This uncertainty implies the broadest preservation policy possible, taking into account that current preferences of consumers may differ markedly from future preferences. However, the vast financial burden of preservation imposes the need to select a set of buildings among the large variety of possibilities and claims. Two types of criteria coexist: objective criteria, such as the age of the building, its state of conservation and the emergency; and subjective criteria, such as the definition of experts, who give the imprimatur to heritage goods. With subjective criteria, there is a risk of a conventional and self-referential process (Throsby 2001), given that criteria are not well established and may be imposed by experts for their own benefit. Regulators have their own preference functions which they impose on the public; in such a case, regulatory capture, as for other public utilities, leads to an oversupply of heritage.

REGULATIONS When the stock of cultural items is large, the marginal value of a specific item is low (Hutter 1997; Netzer 1998); this is an explanation of the low level of preservation in Italy. The problem is probably merely caused by the huge costs of preservation in this country. Throsby (2001) makes the contrast between soft and hard regulations. Soft regulations open up the possibility of relatively large tax incentives and subsidisation, or simple agreements, while hard regulations include enforceable legal restrictions on use, exchange and transformation. Listing requires owners to conform with a series of constraints that range from restrictions on alteration and demolition, and supervision of works by public experts, to the requirement that the work is undertaken by approved contractors. Moreover, in many countries, inheritance tax deductions are submitted on the opening to the public of the property during a defined period. Therefore regulation creates an incentive to reveal the existence of heritage goods and to provide services to the public. However, regulation also creates an incentive to apply for subsidies: moral hazard occurs, creating a collective propensity to produce more heritage than would be preserved in a free-market situation (Benhamou 1996). Individuals asymmetrically weight losses and gains for heritage, and therefore have a natural propensity to apply for preservation. Social costs of preservation may be much higher than is socially desirable. Theoretically, bestowing on a monument a mark of architectural quality has a contradictory effect on its market value. However, a study conducted in the UK in 1993 does not find any substantial change in the commercial value. Creigh-Tyte (2000) compares returns of listed and unlisted office properties over the period 1980–95. He concludes that the value of listed properties built before 1974 matches or exceeds their unlisted equivalents. Moreover, the oldest (pre-1945) listed properties slightly exceed the return on all property. Unfortunately, data collected in this survey only concern offices and not residential buildings. Listing gives birth to a twofold contrasted effect on value: higher value because of symbolic significance versus lower value because of a loss resulting from the opportunity costs of constraints and delays. Subsidies may compensate for it.

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Heritage  283 An alternative way of analysing the question of the effects of listing on market value consists in taking into account property rights allocation. Different individuals may own distinct attributes of the same commodity (Barzel 1997). Thus, among the multiple attributes of a historical building, some belong to the private owner, and others have to be shared with the public, since they are a part of the national collective heritage. Therefore, restrictions on the owner’s behaviour are imposed in order to protect the rights of the other citizens, and public authorities capture a part of the property rights because of the inherent heritage quality of the property. The state and the owners share the responsibility for restoring registered monuments, as is observed in most countries. Sable and King (2001) identify a double public good feature: historical assets enter into household utility functions and contribute to the public externality of ‘shared experience’. This shared experience leads to a public concern and may legitimate regulations. The twofold nature argument applies better to façades than to interiors; the idea to preserve only the façades gave birth to a very questionable preservation choice named façadism, consisting in preserving the integrity of façades and freely reorganising the interiors, with owners free to adapt their properties to modern life. Art historians generally criticise such an exercise, considering that it implies a loss of cultural value. This question of quality is emphasised by Mossetto and Vecco (2001), who show that people wish to keep heritage almost unchanged for centuries, as in the case of Venice, in such a way that conservation costs grow almost continuously. Re-use responds to cost concerns but it is always susceptible to threatening the historical quality of a site. As in the Baumolian cost disease case for the performing arts, economising on costs may lead to a decrease in quality. An interesting debate concerns the degree of restoration. Are identical reproductions of the past stimulating solutions, or should we leave unchanged the architectural transformations made at different periods? The well-known architectural theory of Viollet Le Duc relies on the idea of mixing history with modernity (Leniaud 1994). This question is close to that of inalienability. When historical buildings are publicly owned, are there any possibilities to apply market forces in order to diminish the burden of preservation for taxpayers? The same issue concerns some works of art in the storage of public museums (de-accessioning). From this viewpoint the question of the preservation of non-movable heritage (providing fixed-location services) shares many aspects with movable artefacts. Peacock (1998) denies the existence of inalienable rights for the preservation of buildings that that would lead each generation to preserve a stock of heritage equivalent to that which it has inherited. This intertemporal redistribution issue relies on the assumption that future consumers will cover the costs of such an accumulation. He adds that there are no grounds that justify ‘[forcing] present generations, especially in poor countries, to make the implied sacrifices in terms of the alternative use of resources in the expectation – which could be falsified – that future generations will perceive extra-benefits from a bequest of historical artefacts at the expense of other forms of physical capital’ (Peacock 1995 [1997], p. 229). The question is more complicated when taking into account the international concern for the preservation of other countries’ heritage. According to Netzer (1998), there are cases in which foreigners are ready to contribute to preservation, because of option, existence or bequest values. International demand for heritage services in many poor countries is undersupplied when financing preservation depends only on the national decision-making process.

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284  Handbook of cultural economics

PRIVATE VERSUS PUBLIC, LOCAL VERSUS CENTRAL A large part of cultural heritage remains in private hands. Mossetto (1994) notes the existence of three different levels for the extent of preservation: re-use, (partial) restoration and preservation. In the first two, the market works adequately, while public regulation is unavoidable at the third level. One of the specific problems is the risk linked to the first two cases: without any intervention, heritage may be radically transformed and its long-term value reduced by the loss of its historical characteristics. Privatisation is often presented as a solution in order to limit public expenditure. Whatever the case, public funding may be in addition to private financing. Public funding helps listed buildings’ owners to undertake work and preserve the property as a whole. Therefore, private and public financing do not conflict. There are private altruistic solutions, in the case of non-profit institutions in charge of heritage (for example, the National Trust in England and in Scotland) and friends’ associations. Another form of private altruism relies on the proportion of voluntary labour in this field. The National Lottery has been mainly developed in the UK, which contributes to heritage financing, with the burden on taxpayers being reduced by people who like to gamble, leading to a regressive effect (Peacock 1995 [1997]). This model exists in Italy (and has done since 1997) and in France (since 2018) with different arrangements. The final structure of financing depends on the context, the nature and extent of externalities. Some debates emphasise a second opposition between local and central support. For Peacock, devolution towards funding by regional and local authorities would increase individual involvement in the decision-making process. However, the legitimacy of devolution depends on the type of monument concerned. A case study of Sicily shows that devolution does not diminish the gap between local voter preferences and those of policy-makers: while administrative responsibility relies on local authorities, funds still come from central authorities (Rizzo 2002).

FINAL REMARKS The economics of built heritage does not live in a ghetto only concerned with the question of preserving the past. Economists help policy-makers to find appropriate solutions when intellectual property rights intervene in the decision process. For example, they discuss that every image of the Pyramide du Louvre designed by Pei provides royalties to its architect. Economists value the way digitalisation increases the market value of monuments, by enlarging the circle of their potential users (as in the record industry for the performing arts). Economists have to undertake more studies on the impact of regulation on supply and demand behaviours in relation to heritage. They also have to undertake more studies on the impact of regulation on supply and demand behaviours in relation to heritage in a context of globalisation and digitisation. Digitisation enables improved access and information by creating informational cascades (Bikhchandani et al. 1992), as with the video clip released in 2018 in the Louvre by Beyoncé and Jay-Z, ‘Apes**t’, which achieved a 150 million view count within one year, and the museum launched a 90-minute ‘Jay-Z and Beyoncé at the Louvre’ tour. Technologies make the visit less intimidating and make it possible to

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Heritage  285 gather virtually scattered works (Benhamou 2019). They are a tool for preserving the memory of destroyed places (Martinez 2015). Many stimulating avenues for further research are still open in this field.

SEE ALSO: Chapter 10: Contingent valuation; Chapter 23: Cultural value; Chapter 33: Intangible cultural heritage; Chapter 48: Political economy; Chapter 53: Regulation of heritage.

REFERENCES Barzel, Y. (1997), Economic Analysis of Property Rights, Cambridge: Cambridge University Press. Benhamou, F. (1996), ‘Is increased public spending for the preservation of historic monuments inevitable? The French case’, Journal of Cultural Economics, 20 (2), 115–31. Benhamou, F. (2019), Economie du patrimoine culturel (Economics of Cultural Heritage), 2nd edn, Paris: La Découverte. Benhamou, F. and D. Thesmar (2011), Valoriser le patrimoine culturel de la France (Enhance the Cultural Heritage of France), Paris: La Documentation française. Bertacchini, E.E. and D. Saccone (2012) ‘Toward a political economy of world heritage’, Journal of Cultural Economics, 36 (4), 327–52. Bikhchandani, S., D. Hirshleifer and I. Welch (1992), ‘A theory of fads, fashion, custom, and cultural change as informational cascades’, Journal of Political Economy, 100 (5), 992–1026. Borowiecki, K.J., N. Forbes and A. Fresa (eds) (2016), Cultural Heritage in a Changing World, Springer, accessed 12 December 2019 at https://link.springer.com/content/pdf/10.1007%2F978-3-319-29544-2.pdf. Chastel, A. (1986), ‘La notion de patrimoine’ (‘The notion of heritage’), in P. Nora (ed.), Les Lieux de Mémoire, 2 vols, Paris: Gallimard, pp. 405–50. Creigh-Tyte, S.W. (2000), ‘The built heritage: some British experience’, Recherches Economiques de Louvain, 66 (2), 213–30. Evrard, L. and A. Krebs (2018), ‘The authenticity of the museum experience in the digital age: the case of the Louvre’, Journal of Cultural Economics, 42 (3), 353–63. Frey, B.S. (1997), ‘The evaluation of cultural heritage. Some critical issues’, in M. Hutter and I. Rizzo (eds), Economic Perspectives on Cultural Heritage, London: Macmillan, pp. 31–49. Frey, B.S. and P. Pamini, (2009), ‘Making world heritage truly global: the Culture Certificate Scheme’, Working Paper No. 419, Institute for Empirical Research in Economics, Zurich. Frey, B.S., P. Pamini and L. Steiner (2011), ‘What determines the World Heritage list? An econometric analysis’, working paper, University of Zurich. Greffe, X. (2003), La Valorisation Economique du Patrimoine (Economic Valuation of Heritage), Paris: La Documentation française. Hoffman, B.T. (ed.) (2006), Art and Cultural Heritage: Law, Policy, and Practice, Cambridge: Cambridge University Press. Hutter, M. (1997), ‘Economic perspectives on cultural heritage: an introduction’, in M. Hutter and I. Rizzo (eds), Economic Perspectives on Cultural Heritage, London: Macmillan, pp. 3–10. Journal of Cultural Economics (2017), ‘Economics of cultural tourism’, Journal of Cultural Economics, 41 (May), special issue. Klamer, A. and D. Throsby (2000), ‘Paying for the past: the economics of cultural heritage’, World Culture Report, Paris: UNESCO, pp. 130–45. Koboldt, C. (1997), ‘Optimizing the use of cultural heritage’, in M. Hutter and I. Rizzo (eds), Economic Perspectives on Cultural Heritage, New York: St Martin’s Press, pp. 50–73. Leniaud, J.-M. (1994), Viollet-le-Duc ou les Délires du Système (Viollet-le-Duc or the Deliriums of the System), Paris: Mengès. Macron, E. (2017), speech at the ‘Presentation of the Savoy/Sarr report on restitution of African heritage’, Palais de l’Elysée, 23 November, accessed 12 December 2019 at https://www.elysee.fr/emmanuel-macron/2018/11/23/ remise-du-rapport-savoy-sarr-sur-la-restitution-du-patrimoine-africain. Martinez, J.L. (2015), ‘Cinquante propositions françaises pour protéger le patrimoine de l’humanité’ (‘Fifty French proposals to protect the heritage of humanity’), Rapport au Président de la République, Paris.

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286  Handbook of cultural economics Mossetto, G. (1994), ‘The economic dilemma of heritage preservation’, in A. Peacock and I. Rizzo (eds), Cultural Economics and Cultural Policies, Dordrecht: Kluwer Academic, pp. 81–96. Mossetto, G. and M. Vecco (2001), Economia del Patrimonio Monumentale (Economics of Monumental Heritage), Venice: ICARE, Universita Ca’ Foscari. Netzer, D. (1998), ‘International aspects of heritage policies’, in A. Peacock (ed.), Does the Past Have a Future? The Political Economy of Heritage, London: Institute of Economic Affairs, pp. 135–54. Peacock, A. (1995), ‘A future to the past: the political economy of heritage’, Proceedings of the British Academy, 87, repr. 1997 in R. Towse (ed.) Cultural Economics: the Arts, the Heritage and the Media Industries, vol. 1, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 189–243. Peacock, A. (ed.) (1998), Does the Past Have a Future? The Political Economy of Heritage, London: Institute of Economic Affairs. Rizzo, I. (2002), ‘Heritage conservation: the role of heritage authorities’, in I. Rizzo and R. Towse (eds), The Economics of the Heritage: A Study in the Political Economy of Culture in Sicily, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 31–47. Rizzo, I. and D. Throsby (2006), ‘Cultural heritage: economic analysis and public policy’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 983–1016. Rizzo, I. and R. Towse (eds) (2002), The Economics of Heritage: A Study in the Political Economy of Culture in Sicily, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Sable, K.A. and R.W. King (2001), ‘The double public good: a conceptual framework for “shared experience” values associated with heritage conservation’, Journal of Cultural Economics, 25 (2), 75–89. Savoy, B. and F. Sarr (2018), ‘Rapport sur la restitution du patrimoine culturel africain. Vers une nouvelle éthique relationelle’ (‘The restitution of African cultural heritage. Towards a new relational ethics’), accessed 12 December 2019 at https://www.icom-musees.fr/ressources/rapport-sur-la-restitution-du-patrimoine​ -culturel-africain-vers-une-nouvelle-ethique. Stabler, M. (1995), ‘Research in progress on the economic and social value of conservation’, in P. Burman (ed.), The Economics of Architectural Conservation, York: Institute of Advanced Architectural Studies, pp. 33–50. Throsby, D. (1997), ‘Seven questions in the economics of cultural heritage’, in M. Hutter and I. Rizzo (eds), Economic Perspectives on Cultural Heritage, London: Macmillan, pp. 13–30. Throsby, D. (2001), Economics and Culture, Cambridge: Cambridge University Press. Wuepper, D. and M. Patry (2017), ‘The World Heritage list: which sites promote the brand? A big data spatial econometrics approach’, Journal of Cultural Economics, 41 (1), 1–21.

FURTHER READING General analyses of heritage from the point of view of cultural economics are provided in Rizzo and Throsby (2006). Specific analyses are discussed in Rizzo and Towse (2002) and in Hoffman (2006). For contingent valuation studies, see volume 27 of the Journal of Cultural Economics, 2003.

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32.  Information goods Michael Hutter

Information goods constitute a diverse category of commodities. Among these, we find written reports, bundled and sold as newspapers, and educational or scientific content, sold as books or subscriptions to journals. We also find computer software, digital programs for all types of symbolic and material tasks, and vast networks of infrastructure that enable the transfer and multiplication of information parcels. Cultural goods also belong to this category. They consist of symbolic content that enables players to stimulate their minds into a distinct experience of encounter or immersion. This description fits products from all branches of the creative industries: works of visual art, music, literature, film, the narratives of heritage goods, the aesthetic vocabularies of architecture, design, fashion and advertising, the formats of broadcasting, and videogames.

FUNDAMENTAL PROPERTIES OF INFORMATION GOODS Distinguishing three types of information goods brings some order to this multitude: goods of a first type are demanded for their value in providing external information about some aspect of the past, present or future world – for example, newspapers and scientific content. Goods of a second type are demanded for their abilities in processing information – for transporting signals around the globe, converting, applying and storing them. Goods of a third type are demanded for their power to arrange symbols – words, colored shapes and sounds – in ways that stimulate internal information, or experiences, in the minds of fiction readers, fashion followers, film watchers or video gamers. There exist hybrid forms as well; for example, advertising products try to combine the utility value of external information with the aesthetic appeal of internal information. In economic theory, information has been treated as the counterpart of uncertainty. Basic neoclassical market models assume complete information. Uncertainty implies a lack of information about some features of future price formation (Stiglitz 2000). External information products generate such missing information. In their performance, they make use of information-processing devices. The producers of both types of goods aim for zero uncertainty, or perfect reliability. Uncertainty is a state to be avoided. For internal information goods, however, uncertainty is a positive value. Positive uncertainty values the new, the unpredictable (Andersson and Andersson 2006). Minds are stimulated into surprising imaginations, suspenseful fictions and inventive narratives (Hutter 2011). Producers compete with new variations and new interpretations of known cultural goods. Consumers develop skills of decoding and appreciating these creations (Scitovsky 1986). Despite their differences in construction and purpose, all information goods consist of symbols, signals and signifiers – the semantic elements of information (Shapiro and Varian 1999). In consequence, they have common characteristics: easy access, abundance of copies 287

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288  Handbook of cultural economics and variations, and networks of attachment between those agents who share information. Over the past centuries, institutions have evolved that respond to these characteristics.

ACCESS The efficiency of market transactions depends heavily on the effective definition and enforcement of private property rights. Property rights relating to specific information bundles or content are notoriously difficult to establish. The difficulties grow with the availability of cheap and effective means of digital reproduction and distribution. Access, not property, becomes the basic institutional condition of the information economy (Rifkin 1998). The analytical reason for this shift lies in the public goods nature of information products. Public goods are characterized by non-rivalry in consumption. Information is eminently non-rival because it is generated and stored in every individual’s consciousness, first on the level of present experience and then on the level of retrievable memory. Public goods are also non-excludable. Because of these properties, public goods are often provided by a community or state agency, as is the case with security and education. If access can be sufficiently impeded, information products turn into private goods that are sold at profitable prices. Exclusion can be accomplished through soundproof walls, through the use of proprietary carrier media, like books and compact discs (CDs), or through encryption. Exclusion erodes, however, if means are found that permit access to the original information bundle despite the artificial barriers erected by the producers or their agents. Legal norms are social barriers that complement technical barriers. Various forms of temporary intellectual property rights have been developed over the past centuries, such as patents, copyrights, licenses and trademarks. Currently, intellectual property rights protect access to information goods ranging from software codes to data banks (Towse and Holzhauer 2002; Hutter 2018). Intellectual property rights accomplish a bigger task than enforcing the effects of material barriers. Perfect exclusion is not the socially desirable solution since it prohibits the collective benefits of information dissemination: valuable information that could be used at no cost is kept not only from the market, but also from free distribution in sharing networks. In addition, competition for unanticipated innovations needs a regulatory environment that allows open access to current information processing and content. In markets for information goods, where natural monopoly is the technologically dominant market structure, change takes the form of successful challenge through products with superior, or at least new, features (Ottolia and Wielsch 2004). The political aim of the intellectual property rights is therefore the maintenance of equilibrium between the interests of the creator-producers and the interests of those who might use textbooks, digital applications (apps) or streamed movies. In consequence, copyright is constructed as a temporary monopoly, and it is constrained by rules that permit fair use for non-commercial purposes. However, it makes sense for rights holders to allocate resources to rent-seeking activities, such as the extension of the protection period and stiffer penalties for infringement. Accordingly, the duration of copyright protection under US law has expanded from 28 years previously, to currently up to 95 years after the

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Information goods  289 death of the author. Despite these efforts, strategies of sharing or of pirated appropriation persist. They can even be shown to be quality increasing (Lahiri and Dey 2013). The nature of information leads to a further difficulty with the property concept adopted from the material world. Information signals are connected to some meaning, to some content. Such content may be another information product, such as the signals transmitting a movie, or a fraction thereof, as in the case of quotations, samples and references. Connectedness is essential for information. New information only has meaning in its relationship to previous information. Yet, distributed claims to authorship are incompatible with the separateness of physical property. Legal rulings that favor the isolated private property interpretation of information goods inevitably restrict the access to, or even the production of, new and surprising content connections. The immateriality of access rights has already led to vast changes in pricing strategies and even to changes in the legal architecture of enterprises. Access no longer demands physical ownership, and therefore alternatives to the purchase of goods become advantageous. Flat rates for periods of access have been introduced, and software packages are rented out at rates that correspond to the level and duration of access quality. Owing to their perfect mobility, intellectual property rights have become the central profit center for major providers of information-processing goods. The rights of the copyright- or patent-holding legal entity are registered in the one country where the profits gained in all countries are taxed at the lowest rate.

ABUNDANCE Market exchange depends to a high degree on the condition of scarcity. Buyers gain access to an object or a service that is not equally available to everybody who wants to use it. Prices then allocate a scarce amount of the good to its users. Under conditions of abundance, scarcity disappears. Information goods are produced through the duplication process of copying, not through assemblage or transformation of material resources. An original information bundle – a text or a performance – is recorded, and the recording can be duplicated endlessly. Therefore, the major cost of production is incurred at the beginning, while the variable cost of copying and distributing approaches zero in the case of electronic reproduction. This cost structure is familiar from material network goods, such as railroad tracks or electricity lines: The expensive infrastructure has to be installed first, but its subsequent use is inexpensive. The result is a natural monopoly; the cost advantage of a singular producer allows prices well above the expenses for the initial investment. However, the production of information differs significantly from the production of infrastructure networks. These industries benefit from economies of scale, but they eventually reach a point at which congestion, and thus scarcity, sets in. They also use material resources to build and maintain the network, so that at least some of the inputs are bound to become scarce. Copy industries, by contrast, can reproduce at zero cost indefinitely and will never be affected by decreasing factor productivity or increasing cost owing to factor scarcity (Kelly 1998). If copies cost next to nothing and if the demand for specific goods, particularly internal information goods, is uncertain, then producers will flood the market with such products.

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290  Handbook of cultural economics The supply of cultural goods is characterized by a further type of abundance. Variations of positive uncertainty, as in book and film plots, melodies or touristic events, make these products attractive to consumers who look for new thrills, illusions and amazements. Nobody knows which of these variations, created by a multitude of creator-producers, will be successful. In addition, self-satisfaction is generated by the very act of creating new information products, be it in science, art or entertainment. The incentives for continuous variation and for pleasurable production combine to create an oversupply of cultural goods (Throsby and Hollister 2003). When flooding is the dominant strategy, access to consumers’ attention becomes scarce (Franck 2019). The probability of success can be increased through advertising and publicity. If the success of a good depends on these expenditures, a strategy of intensive promotion will be chosen. In most branches of the experience economy, where a wide public must be informed about the launching of a new product, marketing budgets are larger than production budgets. A fundamental technology of dealing with abundance is the establishment of value hierarchies. Valuation practices permit the selection of few, thus scarce, goods from the total pool of available experience goods. Valuation institutions have evolved, complete with formalized competitions, ratings and other devices (Karpik 2010). Those who pass judgments have accumulated reputation capital in the respective branches – a type of information capital that cannot be bought because its authority depends on the presumed independence of the branch-specific value scale. The new techniques of digital recording and distribution have lowered even further the cost barrier for abundance strategies. Scarcity continues to exist, however, for those information products whose position in the value hierarchy makes them attractive to expanding circles of users..

ATTACHMENT Standard economic theory assumes clear distinctions, between individuals as well as between units of production and consumption. In the information economy, however, distinctions rival with attachments. Information parcels are connected through references and repetitions, and those who either send or receive information are attached with each other through networks that communicate in a shared language. Networks are, by definition, agglomerated combinations of links and nodes. The links consist in shared meaning, but also in stronger attachments, such as shared experiences or reciprocal commitments. Production is mostly organized in networks with shifting motley crews (Caves 2000). The most striking effects of attachment, however, take place on the consumption side. First, there is the effect of network externalities: as users connect with a growing number of communication partners, the utility of the network grows at the rate U 5 n (n – 1). Growth ceases only when the individual utility derived from the potential attachment to distant individuals reaches zero. The network effect explains the exponential increase in historical demand for all of the major communication media currently in use. It provides an explanation for the prevalence of traffic-dominating platforms in markets for information goods.

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Information goods  291 Secondly, the attachment between communicating individuals leads to a ‘social contagion’ effect within networks for internal information goods (Kretschmer et al. 1999). Since content quality of new goods is uncertain, individuals talk about their experiences. Social contacts allow for positive, exponential feedback (Potts et al. 2008). Goods that are preferred by a critical number of community members lead to preferential attachment by other members and thus to superstar markets (Barabási 2001). The distribution of rewards, measured in units of attention, copies or revenues, follows an asymmetric Pareto distribution, with almost all of the rewards allotted to a few of the available entries. Under this type of distribution, the mean value of rewards is much higher than the median value, and thus misrepresents the competitive situation. This pattern of peaks and long tails (Anderson 2006) is typical for the creative industries. Social contagion effects weaken when fresh information about new products is fed into the communication channels. Its effects run like waves, with short-lived peaks, through the population of those who pay attention to the new entries in a specific genre of experience. Thirdly, users often contribute information content to a community because they value the reaction of others to their contribution. The user becomes a prosumer who earns attention and recognition from other community members. In some cases, for example in the scientific field, the attention desired is restricted to a very small circle of peers, yet the effect on the utility of users is sufficiently strong to invest resources in order to maintain and increase attention flow and reputation status. In other fields, the low cost of digital recording and processing technology has enabled amateurs to produce information goods that are as successful as those produced by professionals. These activities are noncommercial, carried out in peer-to-peer communities and driven by personal engagement. They endanger the revenues of professionals and are therefore under competitive attack, usually through claims of copyright infringement.

CONCLUSIONS Access, abundance and attachment are essential features of information goods. The markets that have formed around the three types of information goods correspond to these features. External information goods reduce negative uncertainty through methods of knowledge agglomeration, logic, experimental proof and various other forms of investigation. However, they might also be used as a means to experience the thrill of discovery, and the exciting search for new interpretations in the material and the intellectual world. Patents and copyrights regulate access to valuable content, while other content is transmitted in the public domain. Those who produce new discoveries and interpretations gain attention and prestige in specialized circles that have established their own valuation procedures. Valuation hierarchies solve the problem of abundance by determining the demand for specific new discoveries and new interpretations. Information processing takes place in infrastructures for distribution and storage, and in algorithmic programs that allow transition between different information networks, languages and protocols. Vertical layers of information network architecture permit a modularization of products tailored to the successive layers (Ottolia and Wielsch 2004).

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292  Handbook of cultural economics Uncertainty is a negative property in these markets, producers aim for perfect reliability and precision of all connections and translations. Single networks that link users of certain information layers are most efficient, and the network effects for participants are strong. End-users buy subscriptions to access information infrastructures and they rent connecting applications, but they do not need to own parts of them to be able to consume them. Since most of the networks and their products are private property, the owners are able to gain monopolistic profits (Andersson and Andersson 2006). Cultural goods provide information to all the senses that enable consumers to enjoy experiences. Access to these public goods is contested, as traditional notions of privately owned property bundles are confronted with notions of distributed and interlocking property claims. Works and events that gain attention and prestige stimulate copious reproduction and an abundance of variations. They gain prestige through institutions that allow those who hold reputation capital to attribute and assess value to old and new products in their taste community. Cultural goods are therefore particularly prone to develop asymmetrical distributions of rewards.

SEE ALSO: Chapter 11: Contract theory and information goods; Chapter 15: Creativity; Chapter 16: Criticism; Chapter 18: Cultural capital; Chapter 52: Ratings, reviews and recommendations.

REFERENCES Anderson, C. (2006), The Long Tail: Why the Future of Business Is Selling Less of More, New York: Hyperion. Andersson, A.E. and D.E. Andersson (2006), The Economics of Experiences, the Arts and Entertainment, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Barabási, A.-L. (2001), Linked: The New Science of Networks, Cambridge: Perseus. Caves, R.E. (2000), Creative Industries: Contracts between Art and Commerce, Cambridge, MA: Harvard University Press. Franck, G. (2019), ‘The economy of attention’, Journal of Sociology, 55 (1), 8–19. Hutter, M. (2011), ‘Infinite surprises: on the stabilization of value in the creative industries’, in J. Beckert and P. Aspers (eds), The Worth of Goods: Valuation and Pricing in the Economy, London: Oxford University Press, pp. 201–22. Hutter, M. (2018), ‘Postscriptum: analyzing property rights in the age of digital transactions’, Munich Social Science Review, New Series, 1, 5–16. Karpik, L. (2010), Valuing the Unique: The Economics of Singularities, Princeton, NJ: Princeton University Press. Kelly, K. (1998), New Rules for the New Economy: 10 Radical Strategies for a Connected World, New York: Penguin. Kretschmer, M., G.M. Klimis and C.J. Choi (1999), ‘Increasing returns and social contagion in cultural industries’, British Journal of Management, 10 (S1), pp. 61–72. Lahiri, A. and D. Dey (2013), ‘Effects of piracy on quality of information goods’, Management Science, 59 (1), 245–64. Ottolia, A. and D. Wielsch (2004), ‘Mapping the information environment: legal aspects of modularization and digitalization’, Yale Journal of Law and Technology, 6 (1), 174–276. Potts, J., S. Cunningham, J. Hartley and P. Ormerod (2008), ‘Social network markets: a new definition of the creative industries’, Journal of Cultural Economics, 23 (3), 167–85. Rifkin, J. (1998), The Age of Access, New York: Tarcher. Scitovsky, T. (1986), ‘How to bring joy into economics’, in T. Scitovsky (ed.), Human Desire and Economic Satisfaction. Essays on the Frontiers of Economics, Brighton: Wheatsheaf Books, pp. 183–203.

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Information goods  293 Shapiro, C. and H. Varian (1999), Information Rules: A Strategic Guide to the Network Economy, Boston, MA: Harvard Business School Press. Stiglitz, J.E. (2000), ‘The contribution of the economics of information to twentieth century economics’, Quarterly Journal of Economics, 115 (4), 1441–78. Throsby, D. and V. Hollister (2003), Don’t Give Up Your Day Job: An Economic Study of Professional Artists in Australia, Sydney: Australia Council. Towse, R. and R.W. Holzhauer (eds) (2002), The Economics of Intellectual Property, Cheltenham, UK and Northampton, MA, USA: Edward Elgar.

FURTHER READING Economic theory is expanded by two works: Andersson and Andersson (2006) explore the consequences of monopolistic competition in markets for information and experience goods; Karpik (2010) starts from the premise that lack of information about new and unknown products is the normal rather than the exceptional case, and investigates strategies that generate reliable information about expected consumption value.

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33.  Intangible cultural heritage Tiziana Cuccia

An official definition of intangible cultural heritage (ICH) has been introduced by the United Nations Educational, Scientific and Cultural Organization (UNESCO) in Article 2.1 of the Convention for the Safeguarding of the Intangible Cultural Heritage, signed in 2003 (UNESCO 2003). For the purposes of this Convention, intangible cultural heritage means ‘the practices, representations, expressions, knowledge, skills – as well as the instruments, objects, artefacts and cultural spaces associated therewith – that communities, groups and, in some cases, individuals recognize as part of their cultural heritage’. This definition covers a very large range of material and immaterial expressions of local cultures that fall under the following domains: ‘oral traditions and expressions, including language as a vehicle of the intangible cultural heritage; performing arts; social practices, rituals and festive events; knowledge and practices concerning nature and the universe; traditional craftsmanship’ (UNESCO 2003, Art. 2.2). Material instruments and goods are protected not for themselves but as essential inputs or final outputs of the idiosyncratic immaterial culture. What deserves protection is the immaterial culture in which local communities are rooted. The adopted definition of culture is an anthropological definition that includes those expressions of local tacit knowledge which are difficult to transmit through codified procedures, and protected by intellectual property rights. Intangible cultural heritage (ICH) is also known as living cultural heritage to underline the difference from tangible cultural heritage (TCH) represented by the monuments and all artefacts of outstanding universal value that we inherited from past generations and have to preserve for future generations. With ICH, what is transmitted from generation to generation is not an artefact in itself but the skills that it incorporates; the individuals who own such skills are the main means of transmission. However, their behaviour and actions are not neutral, since individuals reinterpret their past memories and culture with their eyes, and are influenced by the environment where they live. Hence, ICH could be more depletable than TCH, particularly in a globalized context. In this chapter, the main differences between ICH and TCH are examined, referring to the UNESCO approach on which the Convention Concerning the Protection of the World Cultural and Natural Heritage and the Convention for the Safeguarding of the Intangible Cultural Heritage are rooted. Following an economic approach, ICH is interpreted as a local common good. We discuss what threatens ICH, and the role that ICH can play as driver of creativity and innovation, and as expression of cultural diversity. Finally, we deal with the effectiveness of the UNESCO interventions for the ICH safeguarding.

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INTANGIBLE HERITAGE VERSUS WORLD CULTURAL AND NATURAL HERITAGE The Convention for the Safeguarding of the Intangible Cultural Heritage, signed in 2003 by the state parties in UNESCO, differs from the Convention Concerning the Protection of the World Cultural and Natural Heritage signed more than 30 years earlier (UNESCO 1972) for two main aspects: the object to protect, and the subjects mainly entitled to value the object to protect. The object of the Convention Concerning the Protection of the World Cultural and Natural Heritage comprehends natural heritage (that is, natural features, geological and physiographical formations and natural sites) and cultural heritage (that is, monuments, groups of buildings and sites). To deserve this international recognition, natural and cultural heritage has to be of outstanding universal value in relation to history, art or science. The universal value must be recognized by the international community of experts who certificate the artefact uniqueness and authenticity. The 1972 Convention testifies to the increasing interest of the international community, at that time, in sustainable development issues; the 2003 Convention testifies to the increasing awareness by the international community of the risks of globalization in the twenty-first century. In the three decades that separate these two conventions, different categories of cultural and natural heritage have been included in the World Heritage List (WHL): at the beginning, single monuments, historical centres and specific natural attractions were included; more recently, areas with different cities and monuments characterized by a common architectural style (for example, the Jesuit Missions of the Guaranis, between Brazil and Argentina, or the Baroque area of Valdinoto in South-Eastern Sicily in Italy), natural areas and landscapes (such as the Dolomites in Italy) and areas characterized by immaterial cultural endowment (for example, the vineyard landscapes in the Loire Valley in France, Tokaj in Hungary and Langhe-Roero and Monferrato in Piedmont, Italy) (Cellini and Cuccia 2016). The sites included in the WHL can be outstanding artefacts or examples of human interaction with the natural environment that deserve to become archetypes. Their cultural value is more ethnological and anthropological than aesthetic; however, they must have a physical or tangible dimension. For instance, the immaterial culture expressed by architects sharing a common style, and by vine growers sharing the ancient art of winemaking in the case of the recognition of the site Langhe-Roero and Monferrato has been recognized potentially as of outstanding universal value but only inside the material expression of their knowledge (savoir-faire) (World Heritage Committee 2014). The increasing interest of UNESCO in the preservation of the immaterial culture is testified by the programmes launched by UNESCO since the 1990s. The Living Human Treasures programme, launched in 1993, grants official recognition to persons who possess a very high degree of knowledge and skills that are expressions of the living cultural traditions and the creative genius of local communities. The Proclamation of Masterpieces of Oral and Intangible Heritage of Humanity, launched in 1998, aims to raise awareness in local communities and to recognize the importance of oral and intangible heritage, and the need to safeguard and revitalize it, establishing national inventories and providing legal and administrative measures for the protection of intangible heritage.1

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296  Handbook of cultural economics Both programmes were discontinued in 2003 when the Convention on the Safeguarding of the Intangible Cultural Heritage came into force, and all the recognitions have been included in the Representative List of the Intangible Cultural Heritage of Humanity. They show the new sensibility that was spreading in UNESCO: ‘The tangible can only be interpreted through the intangible’ (Perez de Cuellar 1996, p. 34). Therefore, the object of the 2003 Convention on the Safeguarding of the Intangible Cultural Heritage is human creativity itself that can be expressed in many different ways; its outstanding value first has to be recognized by the local community that identifies itself with these expressions. In summary, the recognition process of TCH (natural resources and monuments) to be inscribed in the WHL is based more on a top-down approach, compared with the recognition process of ICH, where local communities choose the expressions of the localized skills that better represent themselves. The only limit that local communities must respect is to select practices or expressions of ICH compatible with existing international human rights, as well as with the requirements of mutual respect among communities, groups and individuals, and with a sustainable development path.

THE SAFEGUARDING OF ICH: AN ECONOMIC APPROACH From an ethical viewpoint, we could say that every expression of localized culture deserves to be preserved as an expression of human genius; from an economic point of view, the problem is determining the optimal level of preservation that maximizes the social welfare, taking into account that any choice has to meet budget constraints. In the more than 500 expressions of intangible heritage coming from 122 countries that are actually inscribed in the Representative List of Cultural Intangible Heritage of Humanity, many different expressions of human creativity are considered. On the one hand there are ancient techniques and practices such as the art of dry-stone walling, traditional violin craftsmanship, the Mediterranean diet and the Neapolitan pizzaiolo, and art expressions such as music and dancing (reggae, meringue, flamenco, and so on), that contribute to produce goods and performing arts that are traded in the market. On the other hand there are ritual dances, festivals, carnivals and religious celebration that require the participation of local communities and are representative of their culture. These different expressions of human creativity share the limited role that the market mechanism can play in their preservation and valorization. The market price can express only the use value of the workers that possess the knowledge on intangible heritage, or on the products and services, such as violins and pizza, that are realized according to cultural traditions. However, the total economic value of these products and services include other components – the option value and the non-use or intrinsic value – that cannot be expressed in the market price. To take into account the option value, that is the willingness to pay of individuals for a potential use in the future of ICH for their own utility and/or for the utility of the future generations, the market price should include a premium to ensure against an irreversible future loss of ICH. The premium depends on the individual capacity to anticipate the future relevance of ICH. If no one knows, for example, the future potential uses of traditional Chinese medicines or theatrical African masks, no premium will be expressed, unless a no-regret criterion is adopted. For example, no one could know that the ancient

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Intangible cultural heritage  297 African theatrical masks would have become a source of inspiration for the cubism arts at the beginning of the twentieth century (for example, for Picasso and Braque). The intrinsic value or the existence value of ICH is a non-use value that implies value judgements: individuals appreciate ICH per se as an expression of their localized cultural identity. Religious celebrations and annual popular events, such as festivals and carnivals, can create a positive social atmosphere, an intangible capital that can provide generalized positive tangible effects, and can help individuals to live and enjoy life together; that is, they can contribute to the creation of social capital. The intrinsic or non-use value is a public-good component (non-rival and not-excludable) of ICH that cannot be expressed by the market price. Therefore, the market price is lower than the total economic value of ICH. In the short and medium runs, this causes an under-provision of ICH as regards the social welfare maximizing quantity. In the long run, ICH could even disappear, owing to the lack of practitioners or who consider cultivating ICH useless, and to free-rider behaviours from individuals and firms that misuse ICH merely for commercial purposes without contributing to safeguard it. Since this loss damages present and future generations, public intervention is required to promote ICH preservation and to underline its economic value in an increasingly globalized world. Moreover, some endogenous mechanisms negatively influencing the survival of ICH are operative in the long run, and these are explained in the subsequent section.

WHY COULD ICH DISAPPEAR? Every time ICH is used as input of a production process, it renovates itself, and this renovation process can either contribute to a natural updating and enrichment of the previous intangible cultural endowment or to the deterioration of the stock of ICH previously accumulated. However, as ICH can be considered a renewable resource, similar to forestry and fishery, it has to reproduce itself, in order to survive. Thus, ICH should not go below a minimum quantitative and qualitative threshold to ensure it is able to reproduce its original essence. Social and economic interactions can influence traditional practices and rituals in different, sometimes opposite, ways: respecting their ancient spirit and looking for more contemporary applications of them, or losing their main essence, exploiting them in standardized processes of mass production of goods and services, or even completely abandoning them for cultivating skills more appreciated in the labour market. A language, which is an example of ICH and a means of transmission of ICH, will not survive unless individuals speak and transmit it from generation to generation. However, this can depend on the number of individuals who speak it: the more individuals speak it, the lower the probability that the language disappears. Under a minimum level of individuals who speak it, the survival of the language is seriously threatened. The same can apply also to the bundle of tacit knowledge on which a traditional craftsmanship is based; the body of knowledge can be transmitted from one generation to another, often from parents to their children, only if they share the same environment and the environment continues to value these artefacts. If the environment does not appreciate the artefacts or if young people emigrate from the rural area where their parents live to urban centres, where different skills are required, that knowledge could disappear forever.

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298  Handbook of cultural economics Therefore, the main threats to the ICH can be listed as follows. First, ICH is mostly ephemeral, and this feature makes it particularly vulnerable. Secondly, international integrated production processes carried on by transnational firms try to incorporate localized ICH in the continuous process of innovation and differentiation of products and services supplied, but (inevitably) simply mimic it, and are not able to interpret the true idiosyncratic content of ICH, causing its irreversible loss. Thirdly, the living communities themselves give up their own local knowledge and tradition to learn some set of skills allowing them to increase productivity. We can explain the declining number of practitioners involved in activities based on localized ICH according to a dynamic economic process resembling what is known as the Baumol disease (Baumol and Bowen 1966). The labour productivity of artisans involved in localized productions grows more slowly than the labour productivity of workers in manufacturing. This slower pace, owing to lower productivity, can cause lower salaries and lower labour supply in the sector based on local ICH or a growth of wages higher than labour productivity in this sector, leading to increasing prices of the products based on local ICH. In both cases, the risk arises that products based on local ICH and the ICH incorporated in the products can disappear owing to, respectively, a shortage of labour supply or a shortage of demand. The loss could be irreversible. Both TCH and ICH run the risk of over-exploitation and irreversible deterioration, typical of common goods. However, TCH are mainly preserved for their global common good nature, as they help to preserve the masterpieces of humankind; ICH has mainly a local common-good nature. Its over-exploitation is caused by intra-generational rivalry that misuses it by incorporating local ICH into standardized production process of goods and services without recognizing any property rights of the local community that possesses ICH. Moreover, current over-exploitation causes irreversible damage to the future generations of local communities, which, with the loss of ICH, lose pieces of their identity and a tranche of local knowledge that could be better used in future local productions. The economic concepts we refer to can offer policy-makers useful advice about the appropriate policy instruments to adopt to preserve and value ICH. The common good nature of ICH, the under-estimate of its market value (if a market value exists) and the slow rate of growth of labour productivity in local production based on ICH could justify public intervention. In this case, public policies can be based on a number of different tools: different forms of regulation of ICH codifying the peculiar aspects of ICH; market mechanisms such as subsidies to the producers of ICH goods or services and/or to the consumers of ICH products or services; and appropriate design of common property rights (for example, geographical indicators) attributed to local producers of goods based on ICH. It is disputable what layer of government can better design and implement policy measures. Local administrations can better supervise their intangible cultural endowments than can higher layers of government; however, they could be tempted to adopt a myopic view and favour over-exploitation and misuse of local ICH. The intervention of an international organization such as UNESCO could avoid the potential drift of local policy-makers, but its enforcement power is weak, as we explain in the next section.

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Intangible cultural heritage  299

ICH AND CULTURAL DIVERSITY The role of UNESCO in the safeguarding of worldwide ICH aims to protect not specific ICH items per se but the infinite varieties of ICH that, as a whole, are expression of worldwide cultural diversity. Cultural diversity is a global common good, that is threatened by globalization that occurs, owing, on the one hand, to cultural standardization and homogenization of consumers’ demand and, on the other, to the standardization of the production processes and the deprivation of local communities of their distinctive ICH. Local individual items of ICH run the risk of becoming obsolete or being improperly incorporated into standardized products. Worldwide, each expression of ICH contributes to the creation of cultural diversity. The UNESCO Universal Declaration on Cultural Diversity, adopted in 2001 (UNESCO 2001, Art. 1), compares the safeguarding of cultural diversity with the safeguarding of biological biodiversity: ‘cultural diversity is as necessary for humankind as biodiversity is for nature’. Using a metaphor, each ICH is like a library book whose value increases as the number and the variety of books it contains increase (Metrick and Weitzamn 1998, p. 23). To justify the safeguarding of cultural diversity, we can return to the total economic value concept, and to an evolutionary economics approach. Cultural diversity that comes directly from localized ICH has a use value in the market system as it contributes to differentiation of products and services. For instance, a large part of commercial music is inspired by ethnic rhythms showing how the contamination of different cultures is able to generate a successful melting pot for creative expression (as UNESCO Director-General Koichiro Matsuura defines ICH). Social customs and rituals are tourism attractions: if they were the same all over the world, travelling would be a less interesting way of spending our leisure time. Therefore, it is in the interest of the market system that cultural diversity survives (Beck 1999). Postmodern consumers’ demands push producers of goods and services in this direction: consumers choose products and services to buy not only for their functions but for their symbolic value. Consumption has a relational value and it is also a way for consumers to differentiate themselves in the market and in their social relationships (Greffe 2002). However, consumers’ choices are not sufficient to guarantee the social optimal quantity, quality and variety of ICH. Use value is not the only component of the economic value of cultural diversity. In an evolutionary economics approach, cultural diversity can be seen as a systemic and resilient property of the socio-economic community, just as biodiversity is seen as a systemic and resilient property of biological systems. The option value of cultural diversity expresses how it allows socio-economic systems to strengthen their capacity of adaptation to exogenous shocks. ‘Cultural variation and diversity are the precondition for cultural crossover and creation of “new cultural species” which may be able to respond to new selection pressures’ (Matutinovic 2001, p. 242). Current and future use values consist of adaptation to different environments, avoidance of head-to-head competition, efficient use of available resources and providing a range of responses to new selection pressures. Moreover, if cultural diversity declines below a certain threshold, extreme consequences may occur. The Noah’s ark problem (from the Bible, that renders a vivid image of the core problem) suggests that a priority list for maximizing social welfare and the degree of diversity

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300  Handbook of cultural economics under a budget constraint can be based on a cost-effectiveness approach that takes into account the direct benefits from each species (for example, each expression of ICH) and the indirect benefits from the overall diversity of genes (for example, the set of different expressions of ICH). Four criteria are suggested to select the species to preserve and to rank a scale of priority: (1) the distinctiveness of a species, that is, its degree of uniqueness; (2) the direct utility of a species; (3) the probability of survival of a species; and (4) the cost of recovery intervention. These general criteria can be adapted to selection of ICH to be included in the Representative List, at least for the first three criteria reported in the UNESCO Convention (there is no official mention of the cost of the recovery projects) (UNESCO 2005). Intangible cultural heritage representativeness corresponds to the distinctiveness of the species; survivability corresponds to the level of risk of disappearing that each ICH expression runs; and other aspects (for example, means of affirming the cultural identity, excellence in the application of idiosyncratic skills and technical qualities) correspond to different elements contributing to direct and indirect utility. We do not know which criteria count more in the selection of ICH to be included in the Representative List. Furthermore, we cannot disregard that other political economy determinants could influence the choice. It has been proven for the UNESCO WHL, which selects natural and tangible cultural heritage, that political economy considerations do matter. For instance, the composition of the UNESCO Commission and the country of origin of the members of the Commission are relevant (Frey and Steiner 2011, 2013; Bertacchini and Saccone 2012). However, the distribution across continents of UNESCO ICH expressions seem more even compared with TCH, probably because the Convention was signed in a period when the Western-centric vision of culture in UNESCO was almost overcome and new emergent economies gained importance in international scenarios.

ICH AND CREATIVITY Creativity is a driver of innovation. Stimulating creativity is a complex process that only partially depends on the talent of individuals; instead, it involves the society as a whole. Under the UNESCO programme Living Human Treasures, which complements the ICH UNESCO listing, individuals who possess a very high degree of the tacit knowledge and skills required for performing or creating specific elements of the ICH, are selected as a testimony of their living cultural traditions and of the creative genius of local groups, communities and individuals. However, the recognition of individuals is neither a necessary nor a sufficient condition: creativity has a social component also. These people must live in an appropriate social ecosystem where they can transmit their knowledge to the new generation and contribute together to find new expressions of the ICH, that respects its origin and the community where it comes from, but at the same time are able to satisfy new needs (Cominelli and Greffe 2012). The common-good characteristics and the key role that ICH can play as driver of innovation require some forms of public intervention at different layers of government. The UNESCO, as an international organization, intervenes to preserve the bundle of ICH as a

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Intangible cultural heritage  301 whole to respond to the final opportunity to preserve culture diversity; its instruments are listing ICH and supervising the national and local policies. Policy-makers at the national level are responsible for the selection of the expressions of ICH that better represent the country to submit to UNESCO, but we cannot ignore that the selection could be based more on the local political power than on the degree of distinctiveness of local ICH within the national context. Local policy-makers are mainly responsible for the safeguarding of ICH and they have to do more than the inventories of ICH. They should be aware of the economic value of localized ICH and support cooperation among the individuals that have this specific knowledge. Local policy-makers should support the institution of private consortia to establish the characteristics of the localized ICH that must be preserved and to select new potential applications of ICH that do not betray its roots. These consortia can adopt geographical indicators to introduce intellectual property rights that signal the authentic origin of the products that incorporate ICH. The creation of institutional ‘cultural districts’ (Santagata 2006) in a circumscribed geographical area (region, municipality or quarter) could contribute to create the proper environment to enhance social-creativity processes.

SOME REMARKS ON POLICY INTERVENTIONS The safeguarding of ICH is more difficult than the preservation of TCH. In the latter, people can discuss the type of the restoration that better respects the original architecture; in the former, it is really difficult to distinguish the natural evolution of this vivid input of production from a stereotypical reproduction that depletes localized ICH. In the UNESCO Convention for the Safeguarding of the Intangible Cultural Heritage the term safeguarding is appropriately preferred to preserving, adopted by the UNESCO Convention on World Cultural and Natural Heritage. Indeed, the role UNESCO intends to play is just to help local communities be aware of their cultural identity, identifying the core elements of their ICH, and creating inventories at national level, in order to evaluate if the natural evolution of ICH still respects the expectations of creators and bearers, even after a period of time (Lenzerini 2011). The listing method adopted by UNESCO could be criticized in the case of ICH, as no ranking among ICH expressions is acceptable and there cannot be an exhaustive taxonomy; the listing can be acceptable only in terms of safeguarding cultural diversity as a whole. However, the enforcement power of UNESCO action in the preservation of both TCH and ICH is not very strong. No financial support is given to the tangible and intangible heritage inscribed in the lists (the WHL and the Representative List of ICH), except in exceptional cases, and not for a significant amount. As far as the TCH is concerned, the effectiveness of the inscription in the WHL has been studied, both regarding the protection of the sites and the contribution to the economic growth of the area where sites are located, with the focus on tourism attractiveness. The results are not unequivocal (see the recent and comprehensive meta-analysis by Yang et al. 2019). The value added of a UNESCO site depends on the local capacity to exploit it, and exploitation is not always sustainable. Inclusion in the UNESCO WHL is sometimes counterproductive, as it enhances damage from mass tourism; the enforcement capacity of UNESCO cannot avoid such a negative result, even if the management plan

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302  Handbook of cultural economics required to add a site to the list has to be founded on environmental and socially sustainable development plans, and periodical checks are provided. As far as the ICH is concerned, to the best of my knowledge, no empirical study has been carried out to estimate the effectiveness of inscription in the Representative List for the safeguarding of ICH and the promotion of local development based on ICH. Consider also that the inscription in the Representative List of ICH does not affect the rights and obligations of state parties deriving from any international instrument relating to intellectual property rights (Article 3 of the Convention). Therefore, UNESCO safeguarding action does not interfere with the international action of the World Intellectual Property Organization (WIPO, the specialized agency of the United Nations devoted to promote creativity and the protection of intellectual property throughout the world). Nor can the protection of ICH be seen as an effective tool to protect human rights, even if sometimes judgments adopted by regional Courts of Human Rights have interpreted the loss of ICH as a threaten to human rights (Lenzerini 2011, p. 115). The United Nations Educational, Scientific and Cultural Organization provides state parties with guidance on best practices for the ICH safeguard (including legal safeguarding measures, if necessary), and offers technical assistance to establish national inventories. It monitors the national and local safeguarding plans for the ICH inscribed in the Representative List through the reports that the states periodically (every six years after the inscription) have to present; however, a defaulting state party cannot be penalized. It also delegates the management of ICH to state parties, even if more decentralized layers of government (that is, regions, provinces and municipalities) have to be involved too. The main purpose of the Representative List is to increase the visibility of ICH and to make local communities aware of the importance of safeguarding ICH, from cultural and economic perspectives. Until now, the interest of policy-makers has been more focused on the inclusion of a site or a landscape in the WHL, whose logo is more visible and more easily recognizable for tourism purposes, compared with that of the Representative List of ICH. However, in the long run, ICH as driver of innovation can interconnect and benefit larger parts of a community. For this reason, the increasing attention attached by UNESCO to ICH is understandable; national and local governments have to become aware of its importance, and to invest in this source of creativity.

NOTE 1. Other UNESCO programmes in the field of ICH concern endangered languages and traditional music of the world.

SEE ALSO: Chapter 10: Contingent valuation; Chapter 20: Cultural diversity; Chapter 31: Heritage; Chapter 48: Political economy; Chapter 53: Regulation of heritage.

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Intangible cultural heritage  303

REFERENCES Baumol, W.J. and W.G. Bowen (1966), Performing Arts: The Economic Dilemma, New York: Twentieth Century Fund. Beck, U. (1999), What is Globalization? Cambridge: Polity Press. Bertacchini E. and D. Saccone (2012), ‘Toward a political economy of World Heritage’, Journal of Cultural Economics, 36 (4), 5–24. Cellini, R. and T. Cuccia (2016), ‘UNESCO sites as public goods: comparative experiences in Italy’, Revista de Economia Contemporanea, 20 (3), 553–69. Cominelli, F. and X. Greffe (2012), ‘Intangible cultural heritage: safeguarding for creativity’, City, Culture and Society, 3 (4), 245–50. Frey, B.S. and L. Steiner (2011), ‘World Heritage list: does it make sense?’, International Journal of Cultural Policy, 17 (5), 555–73. Frey, B.S. and L. Steiner (2013), ‘World heritage list’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 171–86. Greffe, X. (2002), Arts and Artists from an Economic Perspective, Paris: UNESCO. Lazzaretti, L. and P. Cooke (eds) (2018), The Role of Art and Culture for Regional and Urban Resilience, Abingdon: Routledge. Lenzerini, F. (2011), ‘Intangible cultural heritage: the living culture of peoples’, European Journal of International Law, 22 (1), 101–20. Matutinovic, I. (2001), ‘The aspects and the role of diversity in socioeconomic systems: an evolutionary perspective’, Ecological Economics, 39 (2), 239–56. Metrick, A. and M.L. Weitzman (1998), ‘Conflicts and choices in biodiversity preservation’, Journal of Economic Perspectives, 12 (3), 21–34. Perez de Cuellar, J. (1996), Our Creative Diversity: Report of the World Commission on Culture and Development, Paris: UNESCO, accessed 13 December 2019 at https://digitallibrary.un.org/record/195002. Santagata, W. (2006), ‘Cultural districts, property rights and sustainable economic growth’, in V. Ginsburgh and D. Throsby (eds), Handbook on the Economics of Art and Culture, Amsterdam: Elsevier Science NorthHolland, pp. 1100–119. United Nations Educational, Scientific and Cultural Organization (UNESCO) (1972), Convention Concerning the Protection of the World Cultural and Natural Heritage, Paris: UNESCO, accessed 13 December 2019 at http://whc.unesco.org/en/conventiontext. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2001), ‘Universal Declaration on Cultural Diversity’, 2 November, UNESCO, Paris, accessed 13 December 2019 at http://portal.unesco.org/en/ ev.php-URL_ID=13179&URL_DO=DO_TOPIC&URL_SECTION=201.html. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2003), Convention for the Safeguarding of the Intangible Cultural Heritage, Paris: UNESCO, accessed 13 December 2019 at https://ich. UNESCO.org/en/convention. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2005), ‘Criteria for inscription on the lists established by the 2003 Convention for the Safeguarding of the Intangible Cultural Heritage’, report of the Expert Meeting, 5–6 December, accessed 13 December 2019 at https://ich.unesco.org/doc/src/00035-EN. pdf. World Heritage Committee (2014), ‘Vineyard landscape of Piedmont: Langhe-Roero and Monferrato’, Paris: UNESCO, accessed at http://whc.UNESCO.org/en/list/1390. Yang Y., L. Xue and T.E. Jones (2019), ‘Tourism-enhancing effect of World Heritage Sites: panacea or placebo? A meta-analysis’, Annals of Tourism Research, 75 (1), 29–41.

FURTHER READING To deepen the knowledge of the different and interconnected expressions and practices that are considered as ICH, see the ICH section of the UNESCO website (https://ich.UNESCO.org). To enhance the role that ICH has played, in the years of the Great Recession, as driver of resilience processes at the regional and urban level, see Lazzaretti and Cooke (2018). To connect the safeguarding of ICH with the creation of cultural districts and the proper institutional framework able to combine preservation and innovation of local ICH, see Santagata (2006).

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34.  Intermediaries

Paolo Di Caro, Luigi Di Gaetano and Isidoro Mazza

Intermediation is common in many markets. Intermediaries help to solve different problems that may hinder the matching between demand and supply. In the art market, galleries act as intermediaries between collectors (buyers) and artists (sellers). They have specific functions that improve market efficiency. First, they contribute to reduce the knowledge gaps that buyers may have, owing to lack of time and/or expertise, regarding the qualities of artists’ productions.1 Secondly, they reduce inspection and transaction costs that buyers should bear if they had to buy directly from artists. Thirdly, galleries reduce uncertainties about the future of the artists they represent. By reinvesting their profits, galleries build on their reputation, signalling continuance of their activity to buyers and, therefore, a steady support that contributes to the success of their artists. In order to gain insight into the way galleries operate, it is important to realize that they are intermediaries in the two-sided art market, which is characterized by network externalities: members on one side have preferences (generally positive) regarding the number of users on the other side. The existence of the cross-side network effect is evident, although inadequately explored in the economic literature on the art market. Artists are interested in dealing with galleries with many collectors, and collectors want to deal with galleries that have a roster of sought-after artists, both emerging and established. The increasing returns to scale deriving from the network effects explain the premium that more important galleries tend to charge on the work of artists they represent. Studying the strategies followed by the galleries to build a network helps to shed light on debated issues in the art world, most notably pricing. In view of the network, galleries choose a price structure instead of a price for the level of their services. This chapter highlights the role of galleries as intermediaries between artists and buyers and how they can become market-makers. It refers, among the art dealers, mainly to commercial galleries who select, represent and promote a set of artists.

ART GALLERIES AS INTERMEDIARIES There is a substantial amount of studies investigating transactions in the art market. Quantitative analysis has focused on auction sales providing important insights into the determinants of prices (Mei and Moses 2002; Ashenfelter and Graddy 2003, 2006; Ginsburgh et al. 2006; Mandel 2009; Goetzmann et al. 2011; Renneboog and Spaenjers 2013). Owing to the diffuse lack of data concerning private deals, the economic analysis of the activities and impact of art galleries in the market has been relatively neglected. This remains an important lacuna of the literature, notwithstanding recent and growing attention (Candela et al. 2012; Etro and Pagani 2012; Prinz et al. 2015; Di Caro et al. 2019; Di Gaetano et al. 2019). Yet, dealers have traditionally played a prominent role in 304

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Intermediaries  305 the art market, contributing to the success of previously unknown artists, satisfying the desire of collectors, and promoting trade of cultural and creative goods. In the past two decades, the importance of commercial galleries has grown massively. We have observed a proliferation of art fairs across the world, while a number of galleries have become multinationals with lavish offices and exhibition spaces in different continents, able to sustain stardoms and fads. An economic examination of the functions and determinants of success of art galleries is, therefore, fundamental to our comprehension of the evolution and performance of the art market. The relevance of intermediation by art galleries can be understood by observing the specific features of the art market, where symmetric and complete information are rare (Caves 2000). The quality of an artwork is difficult to ascertain, especially in the contemporary art market, and because, unlike in the past, its relationship with aesthetics and technique is dubious. Moreover, the spread of digital and industrial production in artistic practices has reduced the cost of reproduction and increased the uncertainty of buyers. A prospective buyer who considers the acquisition of an artwork from one of the many artists who have not yet built an adequate curriculum cannot exploit potential quality signals such as gallery shows, institutional exhibitions, media coverage and price. In this situation, there are two problems of asymmetric information that buyers face. A first problem arises because a buyer does not have information sufficient to ascertain, to some extent, the quality of an artist. In order to lessen this information gap, a buyer should spend a substantial amount of resources to build expertise to discern quality and to cover searching and transaction costs to find and acquire artworks of quality. In this framework of asymmetric information, where consumption goods show qualitative uncertainty (Akerlof 1970; Ginsburgh 2003), demand for an intermediary (Viscusi 1978) arises to deal with the agency problems generated by the art market (Caves 2006). As noted by Di Caro et al. (2019), who were building on Biglaiser (1993) and Biglaiser and Friedman (1994), art galleries operating as intermediaries between artists and buyers increase the welfare of both. Thus, galleries improve the efficiency of the market. Moreover, galleries can be instrumental in sorting artists according to their talent, which is likely to be private information. In a model including both adverse selection and moral hazard, Di Gaetano et al. (2019) show that the more innovative artists are more likely be found in prominent galleries, even when they are not particularly productive, because they will be able to charge a premium for their innovation, which would be unlikely in smaller galleries having less wealthy clients. This is consistent with the common observation that superstar artists (who tend to combine innovation with productivity) are generally to be found in top galleries with high market power, while smaller galleries rely upon young, promising artists. A second problem, deriving from asymmetric information, is that galleries can be informed about the quality or talent of artists, but this does not imply they will necessarily convey this information to buyers. Indeed, galleries may misrepresent the quality of an artist or withhold valuable information (for example, about the artist’s lifestyle or commitment). This problem can be mitigated by the importance of reputation for the gallery. Reputation is vital in a market where there is a relatively limited number of buyers who periodically meet for exhibitions and fairs.2 Reputation can be based on different aspects and can be built in different ways. For example, collectors would be interested in knowing that a gallery is committed to continue its work of selection and support of artists and will

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306  Handbook of cultural economics not propose artists’ whose practice has not been adequately scrutinized. This implies that the gallery will at some point avoid monetizing the acquired reputation by not honouring agreements with artists and collectors and misrepresenting information about the future of the gallery itself. A gallery, however, will have an incentive to honour its commitment if it charges a price sufficiently higher than the competitive gallery’s price, as it will lose a stream of profits higher than the gain from not honouring its commitment. Moreover, Klein and Leffler (1981) show that the profits gained by this quality-assuring price, which will increase with quality, will have to be invested in sunk firm-specific investments, such as those on assets representing the firm’s brand name. In this way, potential competitors will be cut out of the market. This may explain why a gallery is willing to spend substantially more on a show production and opening parties than it expects to earn from that show; or why a gallery may decide to spend a considerable amount of money for a lavish and large booth while about the same number of works on show could be displayed with a much lower expenditure. Galleries operating as intermediaries are also interested in their reputation since it reinforces their role as information suppliers and contributes to determine the prominence of a gallery in the art market. Prinz et al. (2015) reveal how galleries can become marketmakers, owing to their ability to be innovative at predicting future trends. In particular, if a gallery made long-term investments in innovative artists who later become successful, that gallery will acquire a unique reputation since it was investing in those artists before they became famous. Thus, if the intrinsic value of artworks depends on collective aesthetic taste, collectors observing the success of a gallery above the mean success level will consider that information more valuable than their own taste. A gallery that manages to be innovative can trigger an information cascade where success breeds success.3 Interestingly, the initial successful investment in innovation creates a signal that the gallery is able to forecast future successful trends, and the gallery’s choices will be followed by curators, collectors, other galleries and, even, artists themselves. Thus the gallery would be able to determine self-fulfilling prophecies about future trends through the selection it makes.

INTERMEDIARIES IN A TWO-SIDED ART MARKET Defining galleries as platforms in a two-sided market is an interesting framework with which to analyse the role of intermediaries in the art market. A two-sided market is characterized by the presence of cross-externalities (indirect network effects), that is, when a group of agents’ utility in a certain market depends on the consumption of the same service (or good) by other agents (Caillaud and Jullien 2003; Rochet and Tirole 2003, 2004, 2006; Armstrong 2006; Armstrong and Wright 2007). When an artist chooses a gallery in which to be displayed, he or she will take into account the number of potential buyers using the same platform, in addition to the fee he or she should pay to the gallery. That is, the choice regarding the platform (gallery) depends on the opposite network size. Since the dimension of one side of the platform is affected by the price charged to that side, the utility for an agent in a two-sided market depends on both prices. In addition to indirect network effects, it is useful to consider also direct network effects (also known as same-side effects), that is, when the utility of an agent on one side of the

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Intermediaries  307 platform depends on the number of agents on the same side of the market. For instance the number of artists displayed in a gallery may (positively or negatively) affect the utility of other artists. For example, displaying artists that are of the same school may create a stronger presence on the artistic scene and create value for the artists (positive direct network effects). Alternatively, artists may be negatively affected by the presence of other artists in the same gallery owing to lower opportunities to sell their artwork (negative direct network effects). Therefore, galleries have to define a price structure that considers direct and indirect network effects. Note that the presence of indirect network effects influences the pricing structure of a platform, that is, since the size of one side of the platform affects the other side, a lower price in one side of the platform positively affects the other side of the platform. There is a cross-subsidy between sides of the platform, that is, a gallery lowers the fee or compensation on one side to internalize the positive membership externality for the opposite side. In general, considering pricing strategies in two-sided markets, every platform provider will try to balance prices in order to encourage take-up on both sides, which means that the prices charged to each side are jointly determined. For the strategy of a platform, therefore, the structure of prices matters as much as their level. There are a broader range of examples when considering galleries as platforms. Major collectors may receive a discount larger than others, or receive benefits (free hotel room, visits, champagne breakfast, and so on) because (1) the more influential the buyers, the more attractive a gallery (positive indirect network effects), and (2) influential collectors will attract other buyers (positive direct network effects). Also, galleries can implement projects at a loss to have important artists at display and attract more collectors. An important outcome is that prices may turn out to be negative when indirect network externality is sufficiently strong. In relation to galleries, this is the case of benefits and perks for artists and main collectors. A question that arises concerns the particular features of intermediaries in the art market. We believe that galleries may have a role when asymmetric information on the artists arises. When considering galleries as a platform, therefore, network externalities do not relate only to the number of artists but also to quality. Also, since the price of artworks could be a signal of quality, the price structure should take into account these effects. However, if – on one side of the platform – the level of prices cannot be too low (since it would be a signal of bad quality), this will affect the price on the other side of the platform. As regards competing galleries, it is necessary to analyse multi-homing, that is, where a platform is not exclusive and adoption of two or more platforms by users is allowed. This is commonly the situation for collectors, who can shop in more than one gallery, and could apply to artists as well (depending on the presence of exclusivity). In a two-sided market, multi-homing on one side of the platform affects competition on the other side. When single-homing prevails on one side of the market (for example, if exclusivity contracts for artists are commonly established in the market), there is stronger competition between platforms on the other side of the market. For example, galleries tend to attract more influential collectors in order to attract artists who will sign exclusive contracts. However, if multi-homing is also common for the artists, galleries can exert more competition to attract artists. Taking into account these various effects leads to several scenarios regarding the dynamic of galleries as platforms.

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308  Handbook of cultural economics Regarding indirect network effects (positive effects owing to the greater number of artists and collectors), if a gallery increases the number of artists displayed without attracting collectors, it may experience a phase of stagnation and decline since the price structure should compensate for there being no returns from the collector side and there is a congestion of artists. Artists tend to leave the gallery owing to no sales and negative direct effects (crowding out). This is a weak indirect network effect that is unable to attract collectors. When a gallery increases the number of artists but only a few of them attract collectors, two outcomes are possible, depending on the ability of galleries to maintain highly attractive artists. Successful medium- and large-sized galleries are able to attract and maintain highly appreciated artists, while the lack of this ability leads to the decline of galleries. When a gallery successfully attracts enough collectors after increasing its artists, it triggers an upward spiral that leads to the success of the gallery.

CONCLUDING REMARKS This chapter has shown the relevance of the function of intermediary that galleries perform in the art market. The economic literature reviewed here, although restricted, provides useful insights to improve our understanding of the functioning of the art market. In a framework where buyers are poorly informed about the quality of artists and there are search and transaction costs, the intermediation of galleries acting as quality certifiers can benefit both artists and collectors. In this context, it is highlighted how reputation and innovation have a crucial role for the success of galleries. In particular, economic analysis shows how innovative artists tend to concentrate in top galleries and how their early discovery can endogenously generate the power of galleries to influence future market trends. This analysis sheds light on the reasons why galleries are influential in the success of artists, as empirical observation indicates (Fraiberger et al. 2018). Further research is needed to better understand the strategies that galleries follow in the determination of prices. We suggest that a variety of interesting results can be found by the application of the theory developed from the study of two-sided markets.

NOTES 1. Quality is considered an elusive concept in art, especially when we deal with contemporary visual art. Yet, artists, critics and experts commonly refer to some unwritten paradigm. It is then possible that quality is certified by institutional exhibitions, or through the recognition of experts (for example, curators, critics and galleries), although there is evidence that they may be fallible judges (Ginsburgh 2003). Discussing how quality is defined or ascertained goes beyond the scope of this chapter. The underlying assumption here is that, through investments in the accumulation of human capital (Towse 2006), experts can ascertain and eventually attest quality. 2. Art collectors are often eager to share their views and experiences. There is also a company, Larry’s List, which supplies interviews and collects data concerning contemporary art collectors. 3. Prinz et al. (2015) note the similarity of this outcome to that determined by the preferential attachment process in networks. For a network analysis linking the galleries and the artists participating in Art Basel, see Baia Curioni et al. (2015).

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SEE ALSO: Chapter 2: Art auctions; Chapter 3: Art dealers; Chapter 47: Platforms.

REFERENCES Akerlof, G.A. (1970), ‘The market for lemons: quality uncertainty and the market mechanism’, Quarterly Journal of Economics, 84 (3), 488–500. Armstrong, M. (2006), ‘Competition in two-sided markets’, RAND Journal of Economics, 37 (3), 668–91. Armstrong, M. and J. Wright (2007), ‘Two-sided markets, competitive bottlenecks and exclusive contracts’, Economic Theory, 32 (2), 353–80. Ashenfelter, O. and K. Graddy (2003), ‘Auctions and the price of art’, Journal of Economic Literature, 41 (3), 763–87. Ashenfelter, O. and K. Graddy (2006), ‘Art auctions’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 909–45. Baia Curioni, S., L. Forti and L. Leone (2015), ‘Making visible: artists and galleries in the global art system’, in O. Velthuis and S. Baia Curioni (eds), Cosmopolitan Canvases: The Globalization of Markets for Contemporary Art, Oxford: Oxford University Press, pp. 55–77. Biglaiser, G. (1993), ‘Middlemen as experts’, RAND Journal of Economics, 24 (2), 212–23. Biglaiser, G. and J.W. Friedman (1994), ‘Middlemen as guarantors of quality’, International Journal of Industrial Organization, 12 (4), 509–31. Caillaud, B. and B. Jullien (2003), ‘Chicken & egg: competition among intermediation service providers’, RAND Journal of Economics, 34 (2), 309–28. Candela, G., M. Castellani and P. Pattitoni (2012), ‘Tribal art market: signs and signals’, Journal of Cultural Economics, 36 (4), 289–308. Caves, R.E. (2000), Creative Industries: Contracts between Art and Commerce, Cambridge, MA: Harvard University Press. Caves, R.E. (2006), ‘Organization of arts and entertainment industries’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 533–66. Di Caro, P., K. Georgalos, I. Mazza and A. Schram (2019), ‘Art galleries as informed experts: an experimental study’, unpublished manuscript. Di Gaetano, L., I. Mazza and A. Mignosa (2019), ‘On the allocation of talents in the contemporary art market’, Journal of Cultural Economics, 43 (1), 121–43. Etro, F. and L. Pagani (2012), ‘The market for paintings in Italy during the seventeenth century’, Journal of Economic History, 72 (2), 423–47. Fraiberger, S.P., R. Sinatra, M. Resch, C. Riedl and A.L. Barabási (2018), ‘Quantifying reputation and success in art’, Science, 362 (6416), 825–9. Ginsburgh, V. (2003), ‘Awards, success and aesthetic quality in the arts’, Journal of Economic Perspectives, 17 (2), 99–111. Ginsburgh, V., J. Mei and M. Moses (2006), ‘The computation of prices indices’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 947–79. Goetzmann, W.N., L. Renneboog and C. Spaenjers (2011), ‘Art and money’, American Economic Review, 101 (3), 222–6. Klein, B. and K.B. Leffler (1981), ‘The role of market forces in assuring contractual performance’, Journal of Political Economy, 89 (4), 615–41. Mandel, B.R. (2009), ‘Art as an investment and conspicuous consumption good’, American Economic Review, 99 (4), 1653–63. Mei, J. and M. Moses (2002), ‘Art as an investment and the underperformance of masterpieces’, American Economic Review, 92 (5), 1656–68. Prinz, A., J. Piening and T. Ehrmann (2015), ‘The success of art galleries: a dynamic model with competition and information effects’, Journal of Cultural Economics, 39 (2), 153–76. Renneboog, L. and C. Spaenjers (2013), ‘Buying beauty: on prices and returns in the art market’, Management Science, 59 (1), 36–53. Rochet, J.-C. and J. Tirole (2003), ‘Platform competition in two-sided markets’, Journal of the European Economic Association, 1 (4), 990–1029. Rochet, J. and J. Tirole (2004), ‘Two-sided markets: an overview’, mimeo, IDEI University of Toulouse.

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310  Handbook of cultural economics Rochet, J.-C. and J. Tirole (2006), ‘Two-sided markets: a progress report’, RAND Journal of Economics, 37 (3), 645–67. Towse, R. (2006), ‘Human capital and artists’ labour markets’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 865–94. Viscusi, W.K. (1978), ‘Quality certification’, Bell Journal of Economics, 9 (1), 277–9.

FURTHER READING See Ashenfelter and Graddy (2006) on art auctions, Prinz et al. (2015) on galleries and Di Gaetano et al. (2019) on the talent in the contemporary art market.

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35.  International trade Günther G. Schulze

The market for cultural goods is arguably one of the most internationalized – Van Gogh’s paintings can be admired in New York, a large collection of Egyptian art is on display in Berlin, Isabel Allende’s and Thomas Mann’s books are popular in Europe and the Americas alike, the Beatles’ and Madonna’s compact discs (CDs) are sold throughout the world, and Hollywood movies have global coverage. Yet, this phenomenon is not uniform: The market share of American films in Europe is much higher than that of European films in the US and pop art had a larger influence on European culture than traditional Javanese paintings did. Why is that? What determines the pattern of trade in cultural goods? Trade theory explains why sellers (mostly producers) of certain goods reside in different jurisdictions to the buyers/consumers of these products. In order to understand the trade pattern, we need to know what determines the demand for foreign art and its supply, that is, what determines consumption for foreign art and under what conditions are the respective cultural goods produced. In both dimensions cultural goods are very different from most other goods.1

THE DEMAND FOR CULTURAL GOODS IN THE INTERNATIONAL MARKET The demand for cultural goods is characterized by the positive addiction in consumption of cultural goods. The idea goes back to Alfred Marshall who wrote: ‘It is therefore no exception to the law [of diminishing marginal utility] that the more good music a man hears, the stronger is his taste for it likely to become’ (Marshall 1891 [1962], p. 94). Marginal utility from cultural consumption increases with the ability to appreciate (a particular form of) cultural goods, which is a function of past consumption (Stigler and Becker 1977). In the course of consuming cultural goods, for example, enjoying Flemish painters or French films noir, art-specific consumption capital is built up. Marginal utility from cultural consumption increases with the accumulation of consumption capital and therefore rises over time. This leads to a shift in the demand for the specific cultural goods without a change in prices or income. There is ample empirical evidence for this addictive effect of art consumption (for example, Smith 1998). Becker (1996) distinguishes two components of consumption capital: personal capital, which is formed out of past consumption and other relevant individual experience,2 and social capital which represents the influence of others on a person’s utility, namely, the influence of peers or relevant others. Social capital can be influenced by individuals, only to a limited degree, by the choice of the social milieu they live in. Part of social capital is cultural capital (Throsby 1999) given for the individual. In the international context this notion of positive addiction has two implications: first, people value cultural goods from abroad less if they have not accumulated enough 311

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312  Handbook of cultural economics personal consumption capital for this unfamiliar art; social capital is similarly underdeveloped as their peers have not either. This cultural discount vis-à-vis domestic art limits the degree of trade – the closer (national) cultures are, the smaller the difference in the relevant consumption capital and, thus, the larger bilateral trade in art. This cultural discount can be asymmetric. One country can accumulate consumption capital for the other country’s culture, but the opposite need not be true (to the same extent). The more consumption capital is built up, the easier its further accumulation until foreign-originated cultural goods become part of the national culture. Trade levels go up and remain high. This describes the hysteresis effect in trade in cultural goods. These arguments imply that trade in art is a positive function of cultural proximity and that current trade is a positive function of past trade. However, this does not predict the pattern of trade in art; we need to look at the supply side in the international market for cultural goods.

THE SUPPLY OF CULTURAL GOODS: A CLASSIFICATION Cultural goods comprise heterogeneous products such as sculptures and statues, original paintings, CDs and digital versatile discs (DVDs), books, films for cinema and television, and prints. From an economic perspective they fall into two categories:3 unique cultural goods (for instance, original paintings and sculptures, and antiques) and reproducible cultural goods (recorded music and films, literature, and so on). Reproducible cultural goods are produced in two steps, the creative step in which the artist creates the blueprint (that is, the manuscript, the original recording or the master copy of the film) and the reproduction step in which the master copy is industrially copied under strongly increasing returns to scale and marketed.4 Artists (musicians, authors and actors) and the companies that reproduce the original work (music labels, publishers and film producers) need not reside in the same country, so there may be a first international transaction, an international art service, which is paid for in royalties or fees. The second international transaction takes place between the companies that industrially reproduce the original work and the consumers (the primary market).5 As these cultural goods are differentiated goods and are produced under strong scale economies (international) trade can be explained by a Dixit–Stiglitz type model of monopolistic competition (Wong 1995, ch. 6). In contrast, original paintings, sculptures, drawings and so on are produced in a single creative step without scale economies. They are unique and highly durable, and thus precious, which makes them a store of value and creates a strong secondary market, that is, a market between former and future consumers. The observable substantial price increases for these goods demonstrate that additions of the primary market to the secondary market’s stock are insufficient to satisfy rising demand for these collectors’ items and, thus, the secondary market dominates the primary market, partly also owing to low substitutability between the stock of old art objects and the new products. This makes international trade in works of art demand-determined, as both sellers and buyers are consumers and that distinguishes it from trade in most other products. The Creative Economy Outlook published by the United Nations Conference on Trade and Development (UNCTAD 2018) provides international trade figures for creative goods, a wider concept than cultural goods. According to this report, the value of world

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International trade  313 exports of creative industry goods and services increased from US$208 billion in 2002 to US$509 billion in 2015, growing dynamically at a rate of 7.3 percent per annum during the period 2003–15 (UNCTAD 2018, p. 20). Creative goods exports include design (62 percent of world exports), new media (8 percent), visual arts (11 percent), publishing (7 percent), audiovisuals (4 percent), art crafts (7 percent), and performing arts (1 percent) (UNCTAD 2018, p. 22). Yet the data have major shortcomings beyond the usual deficiencies of international trade data by product group, as a number of member states do not report trade in creative industries services, data for royalties that pertain exclusively to creative industries are unavailable owing to the non-availability of copyright statistics, and digitalized creative content traded via the Internet (music, films and books) is not recorded. Thus the above data will highly underestimate the trade volume in creative goods. Thus even though the report is the most recent available, its statistics are flawed as they include many activities that are not linked to cultural, but creative industries and it has important gaps for very dynamically developing markets for movies, music and literature.

TRADE IN UNIQUE ART Trade in unique art is demand driven and this demand in turn is a function of the income level as works of art are luxury goods. Demand also depends on cultural proximity, which should have a substantially stronger impact on the trade of works in art than on total trade. Schulze (2002) compares the pattern of trade in works of art with the total manufacturing trade pattern in a gravity model which links gross bilateral trade flows to the country sizes of both countries as measured by gross domestic product (GDP), the geographical distance between the two countries, the income levels (GPD per capita) and dummies for a common border, a common language and for countries that are members of the same trade bloc. These findings are consistent with the theoretical predictions: the effect of GDP per capita of the importing country is significantly stronger for works of art than for total trade indicating a higher income elasticity of demand. Also, the variables that capture cultural proximity – distance and a common language – exert a much stronger influence on trade in unique art than on total trade. People have closer ties to, and have built up more consumption capital for, nearby cultures; similarly a common language does not only facilitate cultural exchange but often is tied to a common (mostly colonial) history. It turns out that people trade five times as much work of art if they have a language in common, which is 2.5 times the factor for total trade.6

TRADE IN REPRODUCIBLE CULTURAL GOODS While trade in unique art establishes a particularity not only because of the special demand characteristics and therefore the importance of cultural proximity, but also because works of art are the only group of products where the secondary market dominates the primary market,7 the latter does not apply to reproducible art. For these goods, cultural discounts are similarly important and this refers to the different cultures

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314  Handbook of cultural economics of the artists (first production step) and the consumers, not the country of reproduction. Reproduction is characterized by strong scale economies – once a manuscript is written, it is cheap to reproduce additional copies of the book. This explains why (re-)production of a particular cultural good is concentrated in one location. Also, production of many cultural goods is characterized by strong economies of scope at the firm level as a substantial part of fixed costs are not tied to the production process of one particular product (a specific CD) only, but to producing similar products as such (CDs in general): production facilities (CD production plants) and distribution networks are efficient only if used for many similar products. This explains the existence of labels, film studios and publishing houses. In addition, there may be economies of scale at the industry level, which may be local, national or international, depending on the industry. Theoretical papers have analyzed the effect of trade in cultural goods on welfare and preference formation. In particular, they have called into question whether the commonly accepted free-trade postulate carries over to trade in (industrially produced) cultural products without qualification. Francois and van Ypersele (2002) show that a tariff for cultural products may be welfare improving if the good is produced under strong scale economies and there is strong heterogeneity of preferences in the countries involved in the trade. For instance, if France imposes a tariff on Hollywood movies, the market share of Hollywood movies declines, their prices rise and French films as well as independent American (auteur) movies gain a larger market share or become viable in their respective country. This may increase overall welfare in both countries if a number of consumers in France value French films more highly than the rest of their fellow citizens and, in the US, a number of consumers value non-Hollywood American films more highly than Hollywood movies while Hollywood movies are valued relatively similarly. The overall consumer rent goes up.8 Instead of assuming scale economies, Janeba (2007) analyzes trade effects in a standard Ricardian trade model with constant returns to scale, but assumes positive network externalities in the consumption of the cultural good: people are better off if more people consume the same cultural good as they do.9 He shows that under certain circumstances trade may reduce welfare of a country compared with autarky: since trade changes the relative price of the network goods, people may switch to the imported network good thereby making the consumers of the domestically produced cultural good worse off as price and user base of this good have deteriorated. A country’s welfare may (or may not) go down with free trade in cultural goods. Rauch and Trindade (2009) combine network externalities in consumption with scale economies in production. They show in a two-country model of differentiated cultural products that if the cultural discount is not too large and the difference in size is sufficiently great, the cultural products of the smaller country may disappear. Cultural globalization thus reinforces the home market effect of standard Helpman–Krugman type trade models. Increased cultural globalization – a reduction in the cultural discount – reduces the number of varieties of cultural goods, leading to higher network externalities; and the quality of future cultural products decreases as it is modeled to depend on the present number of varieties in the two countries, which are imperfect substitutes. Thus the welfare effects of globalization are ambiguous. Bala and Van Long (2005) use an evolutionary approach to analyze how preferences are shaped through generations as a consequence of relative scarcity or abundance of

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International trade  315 cultural goods and their resulting price level. They show that free trade between a large country and a small country with different stable preferences in autarky can lead to the extinction of the preferences of the small country. The small country will gradually lose its cultural identity; trade may bring about the demise of cultural diversity. Oliver et al. (2008) introduce a dynamic approach to the evolution of preferences that is based on a socialization mechanism and incorporates cultural identity as group externality – people meet randomly and derive utility from meeting someone from the same culture. They assume constant returns to scale production and thus their transmission channel is not characterized by the dominant economy/culture being able to offer its cultural product more cheaply after market integration, which would reveal a tendency for corner solutions. According to Oliver et al. (2008), factor endowments drive the preferences for cultural goods in the long run – people will have a preference for the good that is produced in abundance. Oliver et al. show that trade integration leads to cultures becoming more dissimilar across countries, but more homogenous within the country leading to cultural tensions within the countries. Social integration, on the contrary, leading to increased interactions between individuals of different countries, gives rise to cultural convergence in that the distribution of cultures becomes more similar across countries.10 Thus there is no general presumption that free trade in cultural goods is welfaredeteriorating – gains from trade may occur also with trade in cultural products – but the literature identifies a number of distinct situations in which unrestricted trade may reduce welfare compared with a situation that limits the trade in cultural products.11

TRADE IN MOVIES The movie industry may serve as an important example for reproducible art (De Vany 2006). Reproduction is characterized by economies of scale as it is easy to copy films. Production and marketing is characterized by scope economies as studios, marketing departments and distribution networks can serve production and especially financing and sale of many films at rapidly decreasing unit costs. Another reason is the high risk involved in film making – studios pool the risk and thus serve as insurance device, a function which capital markets may not fulfill equally well as knowledge is highly industryspecific. This explains the existence of the big studios. The making of the film itself requires highly specialized labor – actors, stuntmen/women, camera operators, stylists and the rest– for a very limited period of time, who make a living by working consecutively or even simultaneously on many movie productions, and for different studios. As flexibility and short-term availability are important, this creates a specialized localized labor market and thus local economies of scale at the industry level. This explains the existence of Hollywood and Bollywood (Bombay), that is, the concentration of the movies industry in one place in a country. The dominance of American films in the Western world is explained by the concurrence of scale economies and the demand characteristics for cultural goods. Since initially the cultural discount works both ways, and domestic films are preferred to foreign films, the film industry in the larger home market will have larger total sales as they face cultural discounts in the demand for their films for a smaller portion of the world market (Wildman and Siwek 1988; Frank 1993; Lee and Waterman 2007). Given strong scale economies in

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316  Handbook of cultural economics film production, this effect allows the larger country’s film industry to lower its prices or to increase its fixed costs and thereby try to enhance the quality of its products. Either way, it gains a competitive edge and enjoys a higher market penetration in the foreign countries than foreign films do in its home country. Market penetration in the foreign markets will build up consumption capital and reduce the cultural discount until, eventually, American films have become part of the European culture. The opposite does not hold to the same degree, and trade in films may become one-way transactions. Although this phenomenon is not uniform for all countries, empirical evidence is consistent with this theory. In 2017 the market shares for domestic films (based on number of movie theatre visitors) were 92 percent in the US, 93 percent in India, 54 percent in China, 24 percent in Germany, 18 percent in Italy, 37 percent in France, 10 percent in Hungary, 6 percent in Austria and an average of 31 percent for the 27 countries in the European Union (EU-27). The market sizes in movie attendances were 1240 million in the US, 1980 million in India and 1620 million in China, compared with 1027 million in the EU (Germany 122 million, Italy 99 million, France 209 million, Austria 15 million, Hungary 15 million, and so on; Berauer 2018, p. 81). The market shares in the EU market by country of origin of the film were 70 percent US films (including 4 percentage points US–EU co-productions), 28 percent EU films and 3 percent from the rest of the world (Berauer 2018, p. 79). These figures underline the importance of the size of the home market, scale economies and the endogenous – and asymmetric – nature of the cultural discounts. Marvasti and Canterbery (2005) estimate a specific gravity equation of US movie exports that conflates the role of national GDPs and distance, and studies the effect of language and trade barriers for which they construct two different measures. They show that the demand for protection of domestic films rises with cultural and geographic proximity. The effect of these trade barriers on motion picture trade is significant. Hanson and Xiang (2009) show the dominance of US films in Europe; over the period 1992 to 2002 they averaged a share of 69 percent of total box office receipts in Europe. Hanson and Xiang use a gravity type of equation to explain the relative dominance of US films in 19 European countries and find that dominance is larger for smaller countries, countries with lower linguistic distance and lower relative wages, and with higher trade barriers. Disdier et al. (2007) study trade in reproducible cultural products in general, and find using a gravity approach that common language and colonial history matter significantly more for cultural trade.

GOVERNMENT INTERVENTION IN THE INTERNATIONAL TRADE IN CULTURAL GOODS The observed trade patterns for both types of cultural goods are also partly a result of various government intervention. For instance, according to Article 36 of the Treaty of Rome, EU member states have the right to protect their national patrimony through export restrictions (embargos, export licensing and pre-emptive rights to purchase works of art to be exported) and they are free to define what they regard as their national patrimony. Value Added Tax (VAT) regulations may distort trade as well: within the EU, works of art are taxed at the margin (on the difference between purchasing and selling price) according to the origin principle, which disfavors high-VAT countries. On imports

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International trade  317 of works of art into the EU, the import VAT is levied mostly at reduced rates which differ substantially between countries, favoring low-tax countries such as the UK. The droit de suite entitles artists to a fraction of the gross selling price each time their works of art are resold. This right functions similarly to a turnover tax and thus may divert trade away from countries that enforce these resale royalty rights. The EU has decided on introducing a uniform droit de suite on a sliding scale with a derogation period of between five and ten years (Directive 2001/84/EC) whereas the important art markets Switzerland and the US do not have resale royalty rights. Finally, direct subsidies to art museums or indirect subsidies to art institutions and private individuals in the form of tax incentives (wealth and inheritance tax exemptions, income tax deductions for donations to art institutions and acceptance of art objects in lieu of tax payments) increase the incentive for residents to acquire or to hold art and thus distort trade. Government intervention in the movie industries is also frequent. This refers not only to direct subsidization of the domestic film industry (and in the form of lucrative awards), but also to local content requirements for national television.12 These measures increase the supply of, and the demand for, domestically produced films and therefore reduce imports and increase exports. To what extent government interventions distort trade is an empirical matter which to date remains largely unresolved.

NOTES  1. The following two sections draw on Schulze (1999). For normative issues of trade in cultural goods see, for example, van Hemel et al. (1996) and O’Hagan (1998, ch. 4.6). Iapadre (2014) provides an overview of issues surrounding international trade in cultural products.  2. This includes the interaction with others and it helps to explain the emergence of superstars (see Chapter 54 in this volume).  3. We disregard live performances such as concerts and plays, which are internationally tradable services if bands or theater companies tour abroad. We also disregard international cultural tourism, which is international trade in services as well.  4. The second step can be divided into functionally defined sub-steps (production, financing, marketing and distribution); see the ‘Trade in reproducible cultural goods’ section in this chapter.  5. This does not exclude possible intermediaries such as foreign publishers, so that the international trade can also take place between the producer and the foreign intermediary, and the subsequent sales are between this intermediary and a consumer.  6. The other results are that art trade rises more than proportionally with GDP, a common trade bloc increases trade significantly and a common border does not increase trade in addition to the proximity as measured by geographical distance.  7. The other exception is antiques and scientific collections which are in the same SITC category.  8. Belloc and Bowles (2017) show that differences in culture may give rise comparative advantages and thus to (gains from) trade.  9. See also Chapter 54, ‘Superstars’, in this volume for network externalities in art and culture. 10. In a related vein, Melitz (2007) shows how, in an integrated world, market forces tend to privilege translations from the dominant English into other languages, the consequence being reduced world literature production negative welfare effects for all countries involved. 11. See also Suranovic and Winthrop (2005, 2014). 12. For the Canadian case, see Acheson and Maule (1992); for Germany, see Perino and Schulze (2005).

SEE ALSO: Chapter 20: Cultural diversity; Chapter 38: Motion-picture industry; Chapter 54: Superstars.

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318  Handbook of cultural economics

REFERENCES Acheson, K. and C. Maule (1992), ‘Canadian content rules for television: misleading lessons for Europe’, Journal of Cultural Economics, 16 (1), 13–23. Bala, V. and N. Van Long (2005), ‘International trade and cultural diversity with preference selection’, European Journal of Political Economy, 21 (1), 143–62. Becker, G. (1996), Accounting for Tastes, Cambridge, MA: Harvard University Press. Belloc, M. and S. Bowles (2017), ‘Persistence and change in culture and institutions under autarchy, trade, and factor mobility’, American Economic Journal: Microeconomics, 9 (4), 245–76. Berauer, W. (2018), Filmstatistisches Jahrbuch 2018 (Film Statistical Yearbook 2018), Baden-Baden: Nomos. De Vany, A. (2006), ‘The movies’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 615–66. Disdier, A.-C., S. Tai, L. Fontagné and T. Mayer (2007), ‘Bilateral trade of cultural goods’, CEPII Working Paper No. 2007-20, Centre d’Etudes Prospectives et d’Informations Internationales, Paris. Francois, P. and T. van Ypersele (2002), ‘On the protection of cultural goods’, Journal of International Economics, 56 (2), 424–40. Frank, B. (1993), Zur Ökonomik der Filmindustrie (On the Economics of the Movie Industry), Hamburg: Steuerund Wirtschafts-verlag. Hanson, G. and C. Xiang (2009), ‘International trade in motion picture services’, in M. Reinsdorf and M. Slaughter (eds), International Trade in Services and Intangibles in the Era of Globalization, Chicago, IL: Chicago University Press, pp. 203–22. Iapadre, L. (2014), ‘Cultural products in the international trading system’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 2, Amsterdam: Elsevier, pp. 381–409. Janeba, E. (2007), ‘International trade and consumption network externalities’, European Economic Review, 51 (4), 781–803. Lee, S.-W. and D. Waterman (2007), ‘Theatrical feature film trade in the United States, Europe, and Japan since the 1950s: an empirical study of the home market effect’, Journal of Media Economics, 20 (3), 167–88. Marshall, A. (1891), Principles of Economics, 8th edn, 1962, London: Macmillan. Marvasti, A. and E.R. Canterbery (2005), ‘Cultural and other barriers to motion pictures trade’, Economic Inquiry, 43 (1), 39–54. Melitz, J. (2007), ‘The impact of English dominance on literature and welfare’, Journal of Economic Behavior & Organization, 64 (2), 193–215. O’Hagan, J. (1998), The State and the Arts, Cheltenham, UK and Lyme, NH, USA: Edward Elgar. Olivier, J., M. Thoenig and T. Verdier (2008), ‘Globalization and the dynamics of cultural identity’, Journal of International Economics, 76, 356–70. Perino, G. and G.G. Schulze (2005), ‘Competition, cultural autonomy and global governance: the audiovisual sector in Germany’, in P. Guerrieri, L. Iapadre and G. Koopmann (eds), Cultural Diversity and International Economic Integration: The Global Governance of the Audio-Visual Sector, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 52–95. Rauch, J.E. and V. Trindade (2009), ‘Neckties in the Tropics: a model of international trade and cultural diversity’, Canadian Journal of Economics, 42 (3), 809–43. Schulze, G. (1999), ‘International trade in art’, Journal of Cultural Economics, 23 (1–2), 109–36. Schulze, G. (2002), ‘International trade in art – a tale of cultural proximity and secondary markets’, University of Freiburg, revd manuscript. Smith, T. (1998), ‘The addiction to culture’, paper presented at the biannual meeting of the Association for Cultural Economics International, Barcelona, 14–17 June; also part of ‘Two essays on the economics of the arts: the demand for culture and the occupational mobility of artists’, unpublished PhD dissertation, University of Chicago, September 1998. Stigler, G. and G. Becker (1977), ‘De gustibus non est disputandum’, American Economic Review, 67 (2), 76–90. Suranovic, S. and R. Winthrop (2005), ‘Cultural effects of trade liberalization’, George Washington University, unpublished MS, EconWPA series International Trade no. 0511003, accessed 5 December 2019 at http://ideas. repec.org/p/wpa/wuwpit/0511003.html. Suranovic, S. and R. Winthrop (2014), ‘Trade liberalization and culture’, Global Economy Journal, 14 (1), 57–78. Throsby, D. (1999), ‘Cultural capital’, Journal of Cultural Economics, 23 (1–2), 3–12. United Nations Conference on Trade and Development (UNCTAD (2018), ‘Creative economy outlook – trends in international trade in creative industries’, United Nations Conference on Trade and Development, Geneva, accessed 12 June 2019 at https://unctad.org/en/PublicationsLibrary/ditcted2018d3_en.pdf. Van Hemel, A., H. Mommaas and C. Smithuijsen (1996), Trading Culture, Amsterdam: Boekman Foundation.

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International trade  319 Wildman, S. and S. Siwek (1988), International Trade in Films and Television Programs, Cambridge, MA: Ballinger. Wong, K. (1995), International Trade in Goods and Factor Mobility, Cambridge, MA: MIT Press.

FURTHER READING For an overview, see UNCTAD (2018); on international trade, see Schulze (1999); on international trade and cultural diversity, see Bala and Van Long (2005) and Raunch and Trindade (2009); on protection of cultural goods, see Francois and van Ypersele (2002).

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36.  Marketing the arts François Colbert

Traditional marketing theory maintains that a company seeks to fulfil an existing need among consumers in order to be successful. In the traditional model, the marketing components of the model must be considered as a sequence that starts in the market. The market is thus both the starting and the finishing point for this process. Although the marketing model for cultural enterprises contains the same components as this traditional marketing model, the marketing process for product-centred cultural enterprises is different. As Figure 36.1 shows, the process starts within the enterprise, in the product itself. The enterprise tries to decide which part of the market is likely to be interested in its product. Once potential customers are identified, the company will decide on the other three elements – price, place and promotion – as well as the elements of its service to clients. In this type of company, the process order would be: company (product)–information system–market–information system–company– residual marketing mix–customer service-market. The starting point is the product and the destination is the market. This product-to-client approach is typical of the not-for-profit arts sector. Therefore we can define cultural marketing as the art of reaching those market segments likely to be interested in the product while ­adjusting to the product the ­commercial variables – price, place and promotion – to put the ­product in contact with a sufficient number of consumers, providing a good customer service and reaching the objectives consistent with the mission of the cultural enterprise. Let us briefly examine the different components of this model. Company Mission

Information system

Product

1

Start Analysis Objectives Planning Implementation Monitoring

Market 2

4

Artistic product Spin-off product Customer service Experience

Consumers 3 Governments

Residual marketing mix Price Promotion

5 Place

Time Specificity of the company

6

Customer service

Private sector

Partners

Competition ‘Uncontrollable’ variables

Source:  Colbert et al. (2018).

Figure 36.1  The marketing culture and the arts model 320

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Marketing the arts  321

THE MARKET A market is a group of consumers expressing desires and needs for products, services or ideas (it can be an individual as well as another organization). In the arts, patrons’ needs can be diverse: educating oneself, being with friends or relatives, reviving the past (nostalgia), expressing its own identity to others, having fun, relaxing, living intense emotions, and so on. So, for the same work of art, different groups of patrons can attend for different reasons even though the art will be the cornerstone of the outing. A cultural organization may serve four different markets: (1) state, (2) donor/sponsor, (3) partners (distribution intermediaries, co-producers, distribution partners or presenters, and media people) and (4) the ultimate consumer. These are, in effect, distinct markets responding to different motivations and needing different marketing strategies. State State is used here to denote the different levels of government, federal, provincial and municipal (and the European Union), that support cultural enterprises in various ways. The state plays a dominant role in the cultural sector in most industrialized countries. Sometimes it acts as a consumer, or it may intervene, to varying degrees, in different guises – from simple partner to controlling the entire cultural sector of a nation. The level of state involvement is different depending on countries; the two extremes may be exemplified by countries such as the USA, where a small percentage of companies’ budgets in the performing arts comes from the different levels of government (from 0 to 10 per cent), while in Europe, in some countries, such as France or Germany, their respective governments’ contribution represents as much as 80 per cent of the total budget of symphonies or theatres. Sponsor/Donor There are two different groups in this market: sponsors and donors. For the former, the act is a business deal; for the latter, it is, in the case of an individual, an emotional commitment. Donations may be made by individuals, foundations or companies; however, sponsorships come mainly from companies. A donation is normally a philanthropic act, whereas sponsorship is a promotional initiative in exchange for publicity or advertising. Sponsorships are given according to advertising benefits calculated in advance. The corporate sponsor then judges the performance of the investment based on visibility and the number of consumers receiving the message. Donors provide disinterested assistance based on personal tastes and preferences. For a foundation, its mission and goals will determine the choice of a cause. Donors are rewarded by some form of recognition, but this does not usually motivate their philanthropic gesture. The Partners Market Although some companies sell their product directly to the ultimate consumer, many must use the services of an agent or intermediary. The distribution market comprises these agents or intermediaries. In the performing arts, for instance, the presenter is a

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322  Handbook of cultural economics distribution agent for a touring company. There is a distribution market in almost all cultural sectors. Other partners can be found in co-productions, whereas two or more entities invest together in one project (mounting an exhibition, co-creating a show or co-producing a film). Finally, artistic organizations make great efforts to get the media people to help them to reach the audience by talking about their event. The Consumer Market Surveys focusing on the socio-demographic profile of consumers of cultural products have been carried out in every Western country. These surveys have systematically and consistently revealed a strong polarization among audiences and consumers. They show that in the high art (symphonies, art museums or contemporary dance) companies mainly attract educated consumers who earn a salary above average and work as white-collar professionals, while popular culture draws upon a cross section of the entire population. Attendance rates at high-art performances are almost identical across all industrialized countries, with some variations attributable to the specific cultural heritage of given countries (for example, attendance is higher for opera in Italy and for classical music in Germany). Audiences in the arts are mainly female (Gainer 1993; Christin 2012). In dance, for example, we may find that as many as 70 per cent of the spectators are female; performing arts or museums participants are usually 55 per cent to 65 per cent females; in sports, it is the reverse: roughly two-thirds of the spectators are men. It has been suggested that the reason for this phenomenon resides in the way boys and girls are raised. Parental attitude (Gainer 1997; Colbert and Courchesne 2012) has a major impact on the preferences of children. Parents see boys as needing activities that will permit them to release their natural aggressiveness, while they see that, by nature, girls are more passive and emotional. These widely shared parental attitudes affect what activities adults will suggest to their children: playing the piano and taking ballet lessons for girls; playing sports for boys. These attitudes then act as social norms and define roles and preferences of the future adults. This does not mean that all parents push this kind of stereotype. However, parental attitude towards the arts is one of four elements that can affect future consumption of the arts. The three other documented elements are values transmitted by teachers, going to live art or museums when they are young and the practice of an art form as an amateur.

THE ENVIRONMENT A marketing strategy cannot be drawn up in a vacuum; many external restrictions affect the market and the firm. The environment is composed of two elements that constantly influence all organizations: competition, over which the company has no control except reacting to a move from a competitor; and macro-environmental variables, also known as uncontrollable variables, that is, demographic, cultural, economic, political–legal and technological. These variables are in constant evolution and affect all firms. Technology is a good example of a variable that has changed markets. Music and movies provide a very dramatic example of the impact of technology on a market. We can think of the advent of music streaming, or Netflix distribution and production of films for the global market.

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Marketing the arts  323 Those innovations have presented the consumer with an ever-increasing range of choices impacting directly the entire traditional sectors. The economic environment has also changed compared with the situation 60 years ago. Since the 1970s, the growth of the market, accompanied by an even stronger growth in the number of art organizations, has led to a deeply oversupplied market (Colbert 2009). Every year, new artists come out of training schools, new companies are created, but the growth of the market is currently very timid and cannot absorb all these new ventures. Competition is then fierce between the different players. New concepts, such as positioning, quality of service to the clientele or the use of information technology are envisaged by artistic groups to maintain or gain their place in the market (Ravanas 2008).

THE MARKETING INFORMATION SYSTEM (MIS) Marketing information systems rely on three key components: internal data; secondary data, published by private firms, government agencies or available through the Internet; and the data collected by the company itself. Internal data is all information available from within the firm itself. The firm’s accounting system provides more than financial analysis; it is a rich source of internal data for the marketing specialist. Front-line employees are also an interesting source of information since they see the consumers. The term secondary data is used to describe data published by public-sector agencies, such as a statistics bureau, arts council or ministry of culture, and private-sector firms that specialize in producing research reports. If the internal and secondary data together do not provide the information required in the decision-making process, it may be useful to gather primary data by using a survey or market study.

THE MARKETING MIX Every marketing strategy is composed of the same four components: product, price, place and promotion. Successful marketing depends on a skilful balance of these components and all firms aim at creating synergy through the combined strengths of all four. Synergy exists when the overall effect of several elements is greater than the sum of the effect of the elements taken separately. The components of the marketing mix are named controllable variables. Product The product is the centrepiece of any enterprise. This statement becomes particularly meaningful in the cultural sector, in which the product constitutes the starting point of any marketing activity. We use the term product in its broadest sense to mean a tangible good, a service, a cause or an idea. Product in the arts is associated with any result of the creative act – a performance, an exhibition, a record, a book or a television programme. We define a product as the set of benefits as they are perceived by the consumer. A product may be described by its technical dimension or symbolic value, yet, in the end,

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324  Handbook of cultural economics what the consumer buys is a set of benefits, real or imaginary. Consumers agree to invest money and effort in obtaining the product according to the importance of their needs and the resources available to them. Most cultural products may be defined as complex, especially when works produced require specific knowledge or rely on abstract notions that depend on the consumer’s ability to appreciate these concepts. Complexity becomes even greater when the consumer is unfamiliar with a particular type of product. The cultural or artistic sector does, nonetheless, include less complex products, such as work drawing on stereotypes known to most people or using very concrete concepts. These products are often labelled popular. To be consistent with their missions, most cultural companies must constantly launch new products without being able to pre-test them. The development and launching of a new product always involves a certain amount of risk for the producer, that is, risk of not satisfying the consumer, or of not meeting marketing objectives or corporate financial goals, and artistic risk. Moreover, once launched, most of a cultural product can no longer be changed. No artist or theme can be guaranteed success in advance. We can usually say that, in contemporary art, the risk is greater, whereas for a classic product that is well known by the public the risk is lower. Price Price is not only the monetary value attributed to a product. Price also includes the effort a consumer must expend in the act of buying and consuming the product, the risk perceived by the consumer and the time sacrificed to attend an event. Thus there is always a price to pay for a product, even when it is advertised as being free. The time dimension is an important element of a marketing strategy. The market for performing arts, for example, is composed of two types of consumers; those who have the means but not the time to go out, and those who have the time but not the means, seats are thus priced differently to catch the differences in the willingness or capacity to pay. However, theatres offer enhanced benefits for those who cannot afford to commit themselves ahead of time. They sell flexible subscriptions where the patron can change his or her pre-paid ticket for a particular night to an alternative evening; although, there is a premium to pay for this benefit (or privilege). For this kind of patron, money is not the problem; it is the busy life of an executive or of a professional that limits the time available for leisure. Place Place is composed of three elements: physical distribution, distribution channels and commercial venue. Physical distribution means the logistics of distributing the product, be it a theatrical tour or a book delivered from the publisher to the reading public. The distribution channel involves the relationships between the various agents within a channel; in an artistic example, the network from artist to producer to broadcaster. Finally, location is the physical place where a company sells its product. The location of a bookshop, cinema, hall, museum or even a traditional business must be carefully selected.

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Marketing the arts  325 Promotion Since a company must know which product is offered to whom, at what price and where, deciding on the promotion variable comes last. It must know beforehand the main characteristics of the target consumers and, in particular, the most convincing selling arguments for those consumers. The notions of advertising, promotion or marketing are often confused. The promotion variable comprises four distinct components: advertising, personal selling, sales promotions and public relations.

FIVE KEY CONCEPTS IN MARKETING Five important concepts constitute the foundations of any marketing strategy; they are: segmenting, targeting, positioning, differentiating and innovating. Segmentation can be defined as the process of subdividing a market into distinct subsets (segments) of customers who behave in the same way or have similar needs. Segmentation means distinguishing in a given market homogeneous subgroups of clients with similar consumption behaviour patterns, needs or desires, and that are sensitive to the same marketing mix components, but different from other subgroups. Having identified those segments in a market, the second concept is targeting, that is, choosing one segment in particular, and adopting a distinct marketing strategy to reach that segment and to try to involve those consumers in adopting the product. Positioning is the third key concept in marketing. It can be defined for the company either as an entity or for each of its products. Simply defined, positioning is the place occupied by the company or its product in the consumer’s mind or the place that it intends to occupy in the consumer’s mind. A brand is differentiated (the fourth concept) in the mind of the consumer if this consumer perceive the brand as being different. A brand can be perceived as different in a positive as well as in a negative sense, and can be so for the total brand or for one of its attributes. The fifth key concept, innovation, means to offer a change, something new that does not exist on the market. It could concern any element of the marketing strategy. In the arts, the artist is the person creating the product, and his or her work is by definition different from work produced by other artists. Thus, the company’s brand offering becomes different and distinct. Even if it is sometimes difficult to distinguish among themselves those five elements, it is useful to discuss these concepts because it can stimulate the strategic thoughts of the manager when reflecting upon the marketing strategy of the organization.

CUSTOMER SERVICE The current arts and culture sector is greatly influenced by social media, globalization, the ever-growing diversity of entertainment options, and brand loyalty or quality of customer service, since good customer service is perceived differently by different market

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326  Handbook of cultural economics segments (baby boomers versus millennials, for example). Customer service can be seen as a chain of elements that lead to satisfaction, repurchase intentions and loyalty (Colbert et al. 2018). Arts offer an experience to the patrons which generates emotion from the art itself, the quality of the peripheral services and the social interaction between clients. The art remains the focal point of an outing to a theatre or an exhibition, but the way patrons are welcomed or the easiness of buying tickets, the maintenance of the public space (such as bathrooms) or the friendliness of the staff can put the spectator in a good mood or, on the contrary, ruin his or her contact with the art presented. The satisfaction produced by an art work will also be influenced by the capacity of the consumer to understand and make sense of the artistic discourse. When in contact with a new work of art, the visitor will go through a cycle of appropriation, first looking at what is familiar, then researching what is new and, finally, making it part of his or her knowledge (Carù and Cova 2005). The more the theatre can facilitate this process, the better will be the satisfaction of the patron. Similarly, the pro-social values transmitted by the organization will be received positively, especially among the feminine clientele, enhancing the experience (Figure 36.2). When the total experience is positive, it induces trust in and involvement with the organization (Colbert and Dantas 2019). If this experience is negative, the level of tolerance of the patron may save the situation, otherwise it will negatively impact the spectator/ visitor and jeopardize his or her intention to come back (Obaidalahe et al. 2017). The product itself is not the responsibility of the marketing department. However, the manager can help to create the necessary environment favourable to the art developed by the artistic director or the curator.

Appropriation Core experience

Theatre’s value Co-creation

Involvement Service experience

Emotions

Pleasure Trust

Social experience

Tolerance to deception

Value

Satisfaction level Delight

Behaviour Repurchase

Outrage

Reject

Commitment Loyalty

Source:  Colbert and Dantas (2019).

Figure 36.2  Purchase–repurchase nomological network for the arts

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Marketing the arts  327

TWO INFLUENTIAL ELEMENTS Two other elements must be considered in any marketing analysis: time and the specificity of the firm. All companies must work within a changing environment. Market conditions evolve over time, as do consumer needs and tastes. The variables of the macroenvironment may be modified and the competition may adjust its strategies. An excellent marketing strategy may seem outdated after a few years or, even, a few months. Every organization has its own personality and acts as an individual entity. What may be an excellent marketing strategy for one firm may prove hopelessly inadequate for another. Neither their products nor their mission are necessarily the same. Their corporate images may also vary. It would therefore be risky to try to transplant a strategy from one firm to another.

THE COMPANY AND ITS MARKETING MANAGEMENT Decisions on marketing strategies must always conform to the company’s mission and objectives. These decisions must also take into account the organization’s human, financial and technical resources. Implementation of a marketing plan requires the skilful coordination of all parties involved. For example, the production, finance and personnel departments must be included to ensure that resources are available. A financial plan must be agreed before financial outlays are made. Personnel must be advised in case additional staff are needed. As soon as a strategy is set up, corporate executives must be kept up to date on the operation. Monitoring allows the company to compare results with objectives and, if need be, to adjust any discrepancies through corrective measures.

CONCLUSION Although the various elements of the marketing model have been presented individually, they are interdependent. They form a whole in which one or a majority may influence the others. Marketing managers should be well acquainted with the market and the variables likely to influence it. They must correctly determine consumers’ needs, measure the level and development of the demand for a particular good, and divide the larger market into submarkets or segments in order to take advantage of opportunities and gain a distinct advantage over the competition. They must also study the different variables within the macro environment. Competition in any form may affect product sales. Demographics, culture, economics, laws and regulations, and technology constantly change the rules of the game. As a result, marketing professionals must use their information system wisely and know how to juggle the variables of the marketing mix and how to offer a perfect customer service.

SEE ALSO: Chapter 24: Demand; Chapter 44: Participation; Chapter 49: Pricing the arts.

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REFERENCES Briggs, S. (2007), ‘Fresh eyes: attracting and sustaining young visitors to Tate’, Museum Management and Curatorship’, 22 (1), 5–9. Carpenter, G. and D. Blandy (eds) (2008), Arts and Cultural Programming: A Leisure Perspective, Champaign, IL: Human Kinetics. Carù, A. and B. Cova (2005), ‘The impact of service elements on the artistic experience: the case of classical music concerts’, International Journal of Arts Management, 7 (2), 39–54. Christin, A. (2012), ‘Gender and highbrow cultural participation in the United Sates’, Poetics, 40 (5), 423–43. Colbert, F. (2009), ‘Beyond branding: contemporary marketing challenges for arts organizations’, International Journal of Arts Management, 12 (1), 14–21. Colbert, F. (2017), ‘A brief history of arts marketing thought in North America’, Journal of Arts Management, Law and Society, 4 (3), 167–77. Colbert, F. and A. Courchesne (2012), ‘Critical issues in the marketing of cultural goods: the decisive influence of cultural transmission’, City, Culture and Society, 3 (4), 275–80. Colbert, F. and D. Dantas (2019), ‘Customer relationships for arts marketing: a review of some important dimensions in the delivery for artistic and cultural organisations’, International Journal of Arts Management, 21 (2), 4–14. Colbert, F. and Y. St-James (2014), ‘Research in arts marketing: evolution and future directions’, Psychology & Marketing, 3 (8), 566–76. Colbert, F., P. Ravanas, J. Brunet, M. Restuccia, D. Rich and Y. St-James (2018), Marketing Culture and the Arts, 5th Edition, Chair in Arts Management Carmelle and Rémi-Marcoux, HEC Montréal. Gainer, B. (1993), ‘The importance of gender to arts marketing’, Journal of Arts Management, Law and Society, 23 (3), 253–60. Gainer, B. (1997), ‘Marketing arts education: parental attitudes towards arts education for children’, Journal of Arts Management, Law and Society, 26 (4), 253–68. Garbarino, E. and M.S. Johnson (1999), ‘The different roles of satisfaction, trust, and commitment in customer relationships’, Journal of Marketing, 63 (2), 70–87. Hume, M. (2008), ‘Developing a conceptual model for repurchase intention in the performing arts: the roles of emotion, core service and service delivery’, International Journal of Arts Management, 10 (2), 40–55. Hume, M., G.S. Mort, P.W. Liesch and H. Winzar (2006), ‘Understanding service experience in nonprofit performing arts: implications for operations and service management’, Journal of Operations Management, 24 (4), 304–24. Obaidalahe, Z., F. Salerno and F. Colbert (2017), ‘Subscribers’ overall evaluation of a multi-experience cultural service, tolerance for disappointment and sustainable loyalty’, International Journal of Arts Management, 20 (1), 21–30. Ravanas, P. (2008), ‘Hitting the high note: the Chicago Symphony Orchestra reverses a decade of decline with new program, new services and new prices’, International Journal of Arts Management, 10 (2), 68–78.

FURTHER READING Recommended further reading: Briggs (2007) on participation; Carpenter and Blandy (2008) on programming; Colbert (2017), Colbert and St-James (2014) and Colbert and Dantas (2019) on arts marketing; Gabarino and Johnson (1999) on customer relations; and Hume et al. (2006) and Hume (2008) on service experience and delivery.

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37.  Media economics and regulation Gillian Doyle

Media economics is the subject area that concerns itself with the economics of making and supplying media content, and it covers activities such as film-making, news production, print and online publishing, video-on-demand streaming services, and television and radio broadcasting. The economics of mass media is a lively and diverse area of scholarship which over a number of years has developed almost independently from cultural economics, but several areas of shared interest exist between these two subfields, for example, concerning economics of creativity or questions around copyright protection. Throsby (2001, p. 4) has described cultural provision in terms of activities that involve ‘some form of creativity in their production’ and where symbolic meanings are important and outputs embody intellectual property. Understood in this way, most if not all suppliers of media are involved in cultural industries. However, the scope of culture and of cultural economics extends well beyond media and includes, for example, the arts – ­literature, drama, dance, visual arts, and so on – and heritage. In media economics, the focus is on applying economic theories and concepts to all aspects of media and on developing models and paradigms for the advancement of study of this particular subject area. This chapter gives a flavour of the concerns and issues which mark out media economics as a distinctive field and provides an introductory overview of the overlap between economics and media regulation.

WHAT IS SPECIAL ABOUT ECONOMICS OF MEDIA? In many respects the media industry is unique. Unlike other sectors, the business of producing and distributing media involves supplying messages and ideas, and this, inevitably, involves significant public welfare implications. So research that falls within the ambit of media economics stems not only from traditional economics, but also from the perspective of critical political economy. The justification for a broader and more normative approach, as opposed to focusing purely, say, on efficiency, is summarised well by Douglas Gomery (1993, p. 198) who observed that ‘studying the economics of mass communications as though one were trying to make toaster companies run leaner and meaner is far too narrow a perspective.’ Generally, the key concern underlying studies in media economics is how best to organise the resources available for media provision. Are firms producing the right types of goods and services and are they being produced efficiently? Answering these questions in the context of media sometimes involves challenges. One problem, as noted by Alan Peacock (1989) whose work on economics of broadcasting has been seminal, is that the welfare impacts associated with communicating with mass audiences are not easily incorporated within the framework of standard quantitative economic analysis. Other challenges stem from the unusual public-good aspects of media content, or from 329

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330  Handbook of cultural economics g­ rappling with the uncertainties and irrationalities that characterise production of creative output, or from the problem of trying to analyse an industry that is prone to constant technological upheaval and change. However, judging by the growth of work in this area, the distinctiveness of media economics is more of a draw than an impediment to scholarly interest. Media economics has advanced in popularity and has flourished internationally over the past three decades within departments of economics, business and media studies. Fuelling this trend has been a growing appetite to understand the effects of digitisation, convergence and globalisation in reshaping media businesses. Deregulation of national media is another key factor shifting the attention of media policy-makers and academics progressively more in the direction of economics. So, although media economics remains at a relatively early stage of development as a subject area with its own framework of theoretical concepts, its importance for industry, for policy-makers and for scholars is increasingly recognised. A number of characteristics distinguish media from other commodities. Media often operate in markets that are two-sided (Rochet and Tirole 2003; Anderson and Gabszewicz 2006) in that firms simultaneously generate different types of output which can be sold to separate and distinct user groups: first, media content (that is, programmes, news stories, and so on) which is consumed by media audiences and, second, audience attention which may be packaged and sold to advertisers. This, in itself, is unusual but in addition one of these outputs, media content, exhibits a number of interesting peculiarities which, over the years, economists have sought to elucidate. Early work in the field by Collins et al. (1988, p. 7) flagged up a similarity between broadcast output – for example, a programme broadcast on television – and other cultural goods in that ‘the essential quality from which their use-value derives is immaterial’. Many cultural goods share the common characteristic that their value for consumers is symbolic and tied up in the messages they convey, rather than with the material carrier of that information (that is, the radio spectrum, the digital file, and so on). The public-good characteristic of not being used up or not being destroyed in the act of consumption means that broadcast material and some other forms of media output exhibit the peculiarity that this same output can be supplied over and over again at no extra cost. In this respect, media content seems to transgress the most basic assumption upon which economics is based, scarcity. The various insights offered by Collins et al. (1988) regarding, for example, the non-rivalrous and non-excludable nature of broadcast output were an important early landmark in the development of thinking about how the economic characteristics of mass media differ from other industries. More recent work by Richard Caves (2000) again underlines the special characteristics of, in this case, creative activities – such as uncertainty of demand, incentives and motivations guiding artistic and creative talent – and how these shed light on the organisation and behaviour of firms in the creative industries (of which media are a part). A notable feature of the economics of media is the prevalence of economies of scale. Firms in this sector tend to enjoy increasing marginal returns as consumption of their output expands. This is owing to the public-good nature of media output and how it is consumed. The cost of producing a feature film, a music album or a television programme is not affected by the number of people who are going to watch or listen to it. First-copy

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Media economics and regulation  331 production costs are usually high but then marginal reproduction or distribution costs are low and, for some media suppliers, zero. Another long-standing feature that is highly characteristic of media industries is the prevalence of economies of scope. Economies of scope are generally defined as the savings available to firms from multi-product production or distribution. They are common, again owing to the public-good nature of media output and because a product created for one market can, at little or no extra cost, be reformatted and sold through another market. Since the value of media output is contained in ideas and messages that are intangible and therefore do not get used up or consumed in the traditional sense, the product is still available to the supplier after it has been sold to one set of consumers to then sell over and over again. For example, an interview with a celebrity can potentially be packaged into a documentary video, a news item, an audio transmission, a podcast, and so on. The reformatting or altering of the scope of a product intended for one audience into a product for a new audience, which extends consumption of the product, releases savings for the firm and therefore generates economies of scope.

KEY THEMES IN MEDIA ECONOMICS Although media economics spans a variety of issues from international trade and industrial organisation to innovation, a number of themes help to define this as a distinctive field. An enduring concern is the role of audiences and advertising in directing and supporting provision of media. Many media goods and services are funded at least partly through advertising, and so patterns of advertising activity tend to exert considerable influence over the fortunes of the industry as a whole. A good deal of work on economics of advertising was carried out in the 1970s and 1980s, much of which concerned itself with whether the role played by advertising is helpful in making the market system work more effectively (Schmalensee 1972; Chiplin and Sturgess 1981). A central concern was the extent to which advertising improves information flows and promotes competition, or whether expenditure on advertising may distort consumer decision-making and have a damaging impact on market access. Another theme in economics of advertising, whose practical relevance has been underlined in periods of economic recession, is that of the relationship between economic wealth (more specifically, growth rates for the economy) and cycles in advertising expenditure. In order to make more accurate predictions about future trends in advertising, many media agencies and organisations engage in collecting and analysing data about historic patterns of advertising activity and factors that have influenced these patterns. Historically, advertising has been ‘more volatile than GDP [gross domestic product], falling sharply during recessions and rising steeply in booms’ (Advertising Association 2009, p. 5). However, movements in GDP and in advertising expenditure also diverge on occasion (Van der Wurff et al. 2008), and have tended to do so increasingly in the digital era. Therefore, ongoing work in this area is concerned with understanding the exact nature, strength and consistency of the relationship between economic wealth and advertising activity. The numerous effects of the Internet on advertising has been a rich topic for research in media economics. A vast expansion in online advertising plus the capacity, in an online context, for greater efficiency in matching advertisers and consumers, has e­ ncouraged

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332  Handbook of cultural economics economists to examine the development and economic implications of targeting behavioural advertising (Athey and Gans 2010) and the effects on advertising markets of real-time bidding (RTB) and automated trade or programmatic advertising (Chen et al. 2014). The steady rise of social media networks and other online intermediaries as competitors for the advertising revenues which at one time were dominated by traditional media, and associated threats for news and magazine publishers, has been a major theme in media economics research, with significant amounts of work emerging on strategy (Küng 2017), innovation (Storsul and Krumsvik 2012) and processes of industry renewal (Doyle 2015). However, aside from the declining fortunes of the newspaper sector and the rise of fake news, other problems associated with the growing monopolisation of online advertising by technology giants such as Facebook and Google – including fraud and mismeasurement of advertising, and programmatic placement of advertisements on undesirable websites – have caused many advertisers to review the costs and benefits of investing their expenditure in new versus traditional media platforms (Barwise 2017). As Marc Bourreau and others note, the benefits for consumers of the digital advertising environment in respect of more effective targeting and lower prices for online services have to be weighed up against not only the nuisance of intrusive advertisements, but also the problem of loss of privacy (Evans 2009; Bourreau et al. 2017). A number of studies have examined the nature of audiences (and access to audience attention) as a commodity, audience ratings, how demand among advertisers for audience access is converted into revenue streams by media enterprises, and how markets for audience attention are evolving (Webster et al. 2000; Wildman 2003; Napoli 2012). Audience fragmentation, present as an issue in early work about television audiences (Barwise and Ehrenberg 1989), has remained an enduring concern over time (Webster and Ksiazek 2012; Lotz 2014). In addition, changes in audience behaviour, the greater empowerment of digital audiences and the issues around how to measure audience engagement in a multi-platform environment have been key themes in media economics research during recent years (Jenkins and Deuze 2008; Napoli 2012; Webster 2014), with much interest in questions concerning how big data is transforming audience research (Athique 2017). Turning from audiences to content, another important set of concerns in media economics is firms and how they produce and supply media content, the markets in which media organisations operate and levels of competition (Picard 2011). Media firms come in many different shapes and sizes. The notion spans a variety of different types of entities, from a small and specialist online publisher to a vast international conglomerate such as Comcast or WarnerMedia (originally Time Warner). Many media firms are commercial organisations but some are not and, consequently, standard economic theories about the behaviour of firms have their limits in this context. Nonetheless, the industrial organisation model (and associated structure–conduct–performance paradigm) which rests on the theory of firms has frequently provided a useful framework for work carried out by economists interested in media firms and industries (Hoskins et al. 2004). Another framework often deployed in economic analyses of media firms and markets is that of the value chain. Definitions of markets and sectors in media economics work are often implicitly or explicitly informed by this concept originally developed by Porter (1998). For media, the key stages in a vertical supply chain usually include: the production or creation of content (which usually, though not always, brings initial entitlement ownership of intellectual property); assembling that content into services and products

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Media economics and regulation  333 (for example, a newspaper or video-on-demand service or radio channel); and distribution or sale to customers. More participatory approaches to content production and the rise of prosumerism have demonstrated that, in a digital environment, value chains are not always straightforward and linear (Berman et al 2007; Kunz and Werning 2013). Even so, interdependence exists between all of the stages in the vertical supply chain and, as a great deal of research work in media economics has shown, this has important implications for the types of competitive and corporate strategies media firms will pursue. Two major forces which have brought enormous changes to market structures and boundaries and which have affected media firms, large and small, in recent decades are convergence and globalisation. Digital convergence has transformed irrevocably the landscape of media provision in recent years, blurring sectoral and geographic boundaries, changing audience consumption behaviours, altering conventional conceptions of the supply chain, opening up opportunities for innovation, and transforming levels of revenue and resourcing across the media industry (Doyle 2013). The economic and strategic implications of these changes have been a main focus for those interested in media economics (Chan-Olmsted 2006; Cunningham et al. 2015; Albarran 2016). A number of the business strategies and behaviours of media firms that economists have sought to shed light on reflect distinctive features and circumstances of this industry which are relatively long-standing. For example, strategies of risk-spreading are important in media owing to inherent uncertainties surrounding the success of any new product (Picard 2011). The hit-or-miss nature of the business of supplying a product such as a feature film or a television programme requires risk mitigation. Hoskins et al. (1997) explain how risks and uncertainties associated with generating high-cost audio-visual content can be offset through tactics such as using sequels. The use of sequels and series that build on successful formats and through the star system helps to build up brand loyalty among audiences and therefore to promote higher and more stable revenue streams. Many scholars working on economics of media have focused on the success of the Hollywood majors in counteracting risk and dominating international trade (De Vany 2004; Jin 2012). Control over distribution plus the ability to supply copious well-funded products are key to the risk reduction strategies of Hollywood. The ability of the majors to support and replenish a large portfolio of film output is dependent on being able to fully exploit new and old hits, but this is potentially under threat currently from growth of online distribution and, associated with this, illegal copying (Crisp 2015). This steers us back to media firms, for whom the need to understand, participate and capitalise effectively on technological advancements is a constant challenge. Media regulators also need to understand that media markets are constantly evolving owing to new technologies. Therefore, a great deal of work in media economics is fundamentally about exploring and uncovering the implications of recent technological changes. Currently, digitisation and growth of the Internet are the key forces for change. This is reflected in numerous studies that, in one way or another, shed light on how organisations have adapted their strategies to deal with these developments (for example, Küng et al. 2008; Aris and Bughin 2009; Achtenhagen et al. 2013; Dogruel 2015; Doyle 2015; Medina et al. 2015; Anderson et al. 2016; Küng 2017). However, in a climate of ongoing upheaval, the task of building a full understanding of the transformative impacts of convergence and of the development of digital distribution infrastructures is likely to remain a key challenge for economists for many years to come.

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ECONOMICS AND MEDIA REGULATION An important concern underlying a great deal of thought and research work related to economics of media is what role the state can or should play in media provision. What forms of state intervention in the media industry are desirable? There is an important political dimension to these questions, but economic considerations are often vital in guiding media policy decision-making. Media firms, similarly to those in all other sectors, are subject to the usual economic and industrial concerns (for example, growth and efficiency) and to the normal laws of the land (such as those on health and safety) wherever they are based. However, mass media organisations – and especially those in the broadcasting sector – are also frequently subject to a range of special rules and regulations that stem from their core business activity involving communication with audiences. In recognition of the socio-political and cultural importance of mass communications, interventions of one kind or another are generally seen as necessary or desirable and thus regulation is often at the forefront in determining the economic performance of media markets and firms. Whenever the state is confronted by an industry whose activity happens to have a strong impact on public well-being then, broadly speaking, two choices are available for how this can be dealt with. First, the state may take responsibility itself for being the provider of services in that industry and can organise provision through the public sector on a non-commercial funded by taxes, as is often done, for example, in defence, education and health care. In some countries, media provision is or has in the past been supplied and controlled mainly by the state, albeit this raises concerns in relation to freedom of speech and democracy. A second alternative is allow the forces of demand and supply to determine how resources should be allocated, that is, leave it to the free market and allow commercial firms to supply whatever consumers express a need for or want through their willingness to pay for it. The problem with taking the second approach is that there is no guarantee that the way in which resources are allocated and the type of media that is supplied under free-market conditions will match or be in accordance with the best interests of society. For example, there may be a tendency to over-supply the type of content that is mainstream and popular (perhaps even that is damaging, as long as there is demand for it) and to under-supply, say, the needs of non-affluent minority groups or groups within society which advertisers are not interested in reaching. Most countries adopt a mixed-economy approach with commercial firms supplying most media but supplemented by an element of non-market provision. In the UK, the BBC is the main provider of public-service content and its activities are funded by a compulsory licence fee imposed on all owners of television receiving equipment. This nonmarket approach of using public funds for broadcast and other media provision, while retaining considerable support in many countries, has become increasingly controversial as the technologies and avenues for distribution of media have advanced and multiplied. The broad ideological case in favour of relying on free markets to allocate resources is based on the idea that decentralised decision-taking, in which consumers exercise sovereignty, is usually better than decision-making carried out by the government. Even so, state intervention is sometimes called for to counteract problems or deficiencies arising from the free operation of markets. As far as media are concerned, generally, the most important

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Media economics and regulation  335 economic reasons why intervention may be required are to address market failures (such as those stemming from the non-excludable nature of broadcast output, discussed previously), to deal with the problem of externalities and to curb monopoly power. Note that governments also intervene in media markets for non-economic reasons (such as to protect minors or to achieve impartiality in news provision), but these are not the focus here. Provision of mass media is associated with both positive and negative externalities, that is, external effects imposed on third parties who did not choose to incur those costs or benefits. Broadcasting may have negative external affects when, for example, provision of violent content imposes a cost on society (through increasing fear of violence among viewers) that is not borne by the broadcaster. A market failure arises here in that broadcasters may well devote more resources to providing programmes with negative external effects than is socially optimal as long as those programmes are popular. Equally, some forms of media content are generally recognised as conferring positive externalities, for example, documentaries, and educational and cultural output but, again, since the benefits to society are out of step with the benefits to the firm, this meritorious output may well be under-supplied under free-market conditions. Externalities need to be corrected through some form of intervention, for example, content regulations that seek to restrict the supply of output that confers negative societal effects and/or other measures that encourage more production and supply of content seen as collectively desirable. Special support measures for meritorious content are very common and generally take two forms. Some interventions are protectionist and help domestic producers by restricting the permitted level of imports of competing non-domestic television or feature-film content. A great deal of work in media economics has focused on international trade in audio-visual and trade disputes, the dominance of US suppliers, and the efficacy of policy measures to counter this, for example, tariffs and quotas (Guerrieri et al. 2004; Hoskins et al. 2004). Aside from imposing trade barriers, the other main approach, adopted in many European states, is to provide grants and subsidies for content producers to boost indigenous production levels. The latter approach is sometimes seen as less tradedistorting than tariffs and quotas, and therefore preferable (Voon 2007; Burri 2011). Work in media economics has helped explain how production grants correct the failure of the market system to provide an adequate supply of certain forms of content, but also has highlighted dangers accompanying promotion of a culture of dependency and deviations from profit-maximising behaviour among local producers. Another main concern confronting media policy-makers is the way in which, on account of the prevalence of economies scale and scope in the sector, there is a natural gravitation towards oligopoly and monopolisation. Across the media and in related communications and technology sectors, mergers and acquisitions have taken place on a massive scale, encouraging the formation of numerous large transnational media conglomerates that wield significant amounts of market power. The coexistence of economies of scale and scope in the media means that joint production, that is, production within a single firm, of a set of media outputs will be more cost-effective than production by a number of different firms. In addition to supply-side economies of scale, the presence of network effects for many online media service providers and intermediaries such as search engines and social networking sites is another factor encouraging strategies of expansion and monopolisation (Srnicek 2016). Despite the arrival and growth of numerous new digital platforms and avenues for distribution of content in the ­twenty-first century, ­concentrations of

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336  Handbook of cultural economics ownership remain a widespread phenomenon in media (Noam 2016) and questions about how policy-makers should deal with these remain of enduring interest to those working in media economics. If media empires are a problem, how should they be tackled? What about monopolised control over specific access points and bottlenecks along the vertical supply chain for media? A further area of concern related to monopolisation in the media stems from the growing importance of data. The potential for big data to generate valuable insights, for example about what audiences like, and to become a source of competitive advantage has been amply demonstrated by a range of new digital content service providers such as Spotify and Netflix. Regulatory concerns about the potentially harmful implications of large-scale usage of return-path data have thus far focused primarily on consumer privacy. However, a growing body of work in the realm of media economics has drawn attention to the need for policy-making to pay more attention to the emergence and implications of asymmetries of power in relation to ownership and use of data, which now represents a key informational resource, particularly in the television industry (Schepp and Wambach 2016; Doyle 2018). Note that the main reason for public intervention to prevent media empire-building is usually not to do with economics but is about pluralism – the need, in the interests of democracy and social cohesion, to maintain a diverse and open system of media provision. However, regulation of ownership and of competition in the media industry also involves an important economic dimension. Corporate strategies of expansion and diversification, which are commonplace and especially characteristic of media, are typically associated with two key incentives related to profit-maximising behaviour: increased efficiency or increased market power. Efficiency gains imply an improved use of resources and are seen as beneficial to the economy as a whole but, by contrast, increased market power in the hands of individual firms poses a threat for consumers and rivals and is therefore seen as damaging for society and for the operation of markets. A problem for policy-makers is that proposed mergers and expansion strategies in the media and communications industries may often result in both these outcomes (Doyle 2013, pp. 188–9). Expansion makes possible greater efficiency but it facilitates market dominance and therefore poses risks for competition. Research work carried out by economists focusing on media concentrations is often aimed at shedding light on the natural monopoly problem, exacerbated in recent times by network effects, and on the challenges for policy-makers in finding suitable measures to accommodate the development of media firms, while enabling competition.

SEE ALSO: Chapter 8: Broadcasting; Chapter 20: Cultural diversity; Chapter 38: Motion-picture industry; Chapter 47: Platforms.

REFERENCES Achtenhagen, L., L. Melin and L. Naldi (2013), ‘Dynamics of business models— strategizing, critical capabilities and activities for sustained value creation’, Long Range Planning, 46 (6), 427–42.

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Media economics and regulation  337 Advertising Association (2009), The Advertising Statistics Yearbook, London: Ad Association/WARC. Albarran, A. (2016), The Media Economy, London: Taylor & Francis. Anderson, S. and J. Gabszewicz (2006), ‘The media and advertising: a tale of two-sided markets’, in V.  Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: Elsevier, pp. 567–614. Anderson, S., D. Strömberg and J. Waldfogel (eds) (2016), Handbook of Media Economics, Amsterdam: North-Holland. Aris, A. and J. Bughin (2009), Managing Media Companies, 2nd edn, Chichester: John Wiley & Sons. Athey, S. and J. Gans (2010), ‘The impact of targeting technology on advertising markets and media competition’, American Economic Review, 100 (2), 608–13. Athique, A. (2017), ‘The dynamics and potentials of big data for audience research’, Media, Culture & Society, 40 (1), 59–74. Barwise, P. (2017), ‘Disrupting the digital giants – advertisers and traditional media push back’, Media Policy Blog, 5 April, accessed 13 December 2019 at https://blogs.lse.ac.uk/medialse/2017/04/05/disrupting-the-digital-giants​ -advertisers-and-traditional-media-push-back/. Barwise, P. and A. Ehrenberg (1989), Television and Its Audience, London: Sage. Berman, S., S. Abraham, B. Battino, L. Shipnuck and A. Neus (2007), ‘New business models for the new media world’, Strategy & Leadership, 35 (4), 23–30. Bourreau, M., A. de Streel and I. Graef (2017), Big Data and Competition Policy: Market Power, Personalised Pricing and Advertising, Brussels: Centre on Regulation in Europe. Burri, M. (2011), ‘Reconciling trade and culture: a global law perspective’, Journal of Arts Management, Law and Society, 41 (2), 138–58. Caves, R. (2000), Creative Industries: Contracts between Art and Commerce, Cambridge, MA: Harvard University Press. Chan-Olmsted, S. (2006), ‘Issues in media management and technology’, in A. Albarran, S. Chan-Olmsted and M. Wirth (eds), Handbook of Media Management and Economics, Mahwah, NJ: Lawrence Erlbaum Associates, pp. 251–73. Chen, B. and S. Yuan and J. Wang (2014), ‘A dynamic pricing model for unifying programmatic guarantee and real-time bidding in display advertising’, Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, 24 August, New York: ADKDD, pp. 1–9. Chiplin, B. and B. Sturgess (1981), Economics of Advertising, London: Advertising Association. Collins, R., N. Garnham and G. Locksley (1988), The Economics of Television: The UK Case, London: Sage. Crisp, V. (2015), Film Distribution in the Digital Age: Pirates and Professionals, Basingstoke: BFI Palgrave Macmillan. Cunningham, S., T. Flew and A. Swift (2015), Media Economics, London: Palgrave Macmillan. De Vany, A. (2004), Hollywood Economics: How Extreme Uncertainty Shapes the Film Industry, London: Routledge. Dogruel, L. (2015), ‘Innovation research in media management and economics: an integrative framework’, Journal of Media Business Studies, 12 (3), 153–67, Doyle, G. (ed.) (2006), The Economics of Mass Media, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Doyle, G. (2013), Understanding Media Economics, 2nd edn, London: Sage. Doyle, G. (2015), ‘Multi-platform media and the miracle of the loaves and fishes’, Journal of Media Business Studies, 12 (1), 49–65. Doyle, G. (2018), ‘Television and the development of the data economy: data analysis, power and the public interest’, International Journal of Digital Television, 9 (1), 53–68. Evans, D. (2009), ‘The online advertising industry: economics, evolution, and privacy’, Journal of Economic Perspectives, 23 (3), 37–60. Gomery, D. (1993), ‘The centrality of media economics’, Journal of Communication, 43 (3), 190–98. Guerrieri, P., L. Iapadre and G. Koopman (2004), Cultural Diversity and International Economic Integration: The Global Governance of the Audiovisual Sector, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Hoskins, C., S. McFadyen and A. Finn (1997), Global Television and Film: An Introduction to the Economics of the Business, Oxford: Clarendon Press. Hoskins, C., S. McFadyen and A. Finn (2004), Media Economics: Applying Economics to New and Traditional Media, Thousand Oaks, CA: Sage. Jenkins, H. and M. Deuze (2008), ‘Editorial: convergence culture’, Convergence, 14 (1), 5–12. Jin, D. (2012), ‘Transforming the global film industries: horizontal integration and vertical concentration amid neoliberal globalization’, International Communication Gazette, 74 (5), 405–22. Küng, L. (2017), Strategic Management in the Media, 2nd edn, London: Sage. Küng, L., R. Picard and R. Towse (2008), The Internet and the Mass Media, London: Sage.

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338  Handbook of cultural economics Kunz, R. and S. Werning (2013), ‘Media management and social media business’, in M. Friedrichsen and W. Mühl-Benninghaus (eds), Handbook of Social Media Management, Berlin: Springer, pp. 253–68. Lotz, A. (2014), The Television Will Be Revolutionized, 2nd edn, New York: New York University Press. Medina, M., M. Herrero and E. Guerrero (2015), ‘Audience behaviour and multiplatform strategies: the path towards connected TV in Spain’, Austral Comunicación, 4 (1), 153–72. Napoli, P. (2012), ‘Audience evolution and the future of audience research’, International Journal on Media Management, 14 (2), 79–97. Noam, E. (ed.) (2016), Who Owns the World’s Media? Media Concentration and Ownership Around the World, New York: Oxford University Press. Owen, B. and S. Wildman (1992), Video Economics, Cambridge, MA: Harvard University Press. Peacock, A. (1989), ‘Introduction’, in G. Hughes and D. Vines (eds), Deregulation and the Future of Commercial Television, Aberdeen: Aberdeen University Press, pp. 1–8. Picard, R. (2011), The Economics and Financing of Media Companies, 2nd edn, New York: Fordham University Press. Porter, M. (1998), Competitive Strategy: Techniques for Analyzing Industries and Competitors, New York and London: Free Press. Rochet, J.-C. and J. Tirole (2003), ‘Platform competition in two-sided markets’, Journal of the European Economic Association, 1 (4), 990–1029. Schepp, N.-P. and A. Wambach (2016), ‘On big data and its relevance for market power assessment’, Journal of European Competition Law and Practice, 7 (2), 120–24. Schmalensee, R. (1972), The Economics of Advertising, Amsterdam: North-Holland. Srnicek, N. (2016), Platform Capitalism, Cambridge: Polity Press. Storsul, T. and A. Krumsvik (eds) (2012), Media Innovations, Gothenburg: Nordicom. Throsby, D. (2001), Economics and Culture, Cambridge: Cambridge University Press. Van der Wurff, R., P. Bakker and R. Picard (2008), ‘Economic growth and advertising expenditures in different media in different countries’, Journal of Media Economics, 21 (1), 28–52. Voon, T. (2007), ‘A new approach to audiovisual products in the WTO: rebalancing GATT and GATS’, UCLA Entertainment Law Review, 14 (1), 1–32. Webster, J. (2014), The Marketplace of Attention: How Audiences Take Shape in a Digital Age, Cambridge, MA: MIT Press. Webster, J. and T. Ksiazek (2012), ‘The dynamics of audience fragmentation: public attention in an age of digital media’, Journal of Communication, 62 (1), 39–56. Webster, J., P. Phelan and L. Lichty (2000), Ratings Analysis: The Theory and Practice of Audience Research, 2nd edn, Mahwah, NJ: LEA. Wildman, S. (2003), ‘Modeling the advertising revenue potential of media audiences: an underdeveloped side of media economics’, Journal of Media Economics and Culture, 1 (2), 7–37.

FURTHER READING Any of the following introductory textbooks and reference volumes will be helpful for those coming new to media economics: Doyle (2006, 2013); Hoskins et al. (1997, 2004); Owen and Wildman (1992); Picard (2011); Albarran (2016).

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38.  Motion-picture industry

Darlene C. Chisholm and Yu-Hsi Liu

In this chapter, we present an analysis of the economics of the motion-picture industry. We begin with a discussion of traditional film production, theatrical distribution and exhibition, describing each in the context of recent developments in the academic economics literature. We then analyze the significant impact that digitalization and technological innovation have had on the industry, including a fundamental change in the cost of producing and distributing films, the facilitation of movie piracy, the creation of new media distribution channels including video on demand, and the role of critical reviews and social networks in a film’s financial success. We conclude by discussing the promise of ‘big data’ analytics in predicting demand and financial performance of films.

TRADITIONAL FILM PRODUCTION We begin with a discussion of the development and production stages of a film, and start with the story. A screenwriter will pitch their story to a studio. The decision to purchase a screenplay is inherently risky for the studio, given the high degree of variability in the financial success of a film. Goetzmann et al. (2013) found that more complex screenplay pitches sell for lower prices, with short and simple pitches faring better. They also found this effect to be more pronounced for larger studios, as compared to smaller companies; larger studios are more likely to avoid complex pitches. The reputation of the seller also plays a prominent role in the sale of a movie idea. Luo (2014) found that buyers are less willing to consider movie ideas in their early stages when the seller is less experienced; movie ideas from more established sellers are purchased at earlier stages of development. This leads to a potential bias towards lower-quality film stories being developed, as less experienced sellers are required to invest more time in story development, and might abandon a project altogether; whereas a more experienced seller can secure a sale sooner, for a potentially under-developed story, based on their reputation alone. The development stage of a movie includes acquiring the story rights, followed by making the necessary arrangements with talent agents and the production studio, and arranging financing. The production stage includes a pre-production phase, the production of the film, collaboration between the producer and director, and post-production editing and creation of the final ‘negative’ or print. The marketing stage includes marketing the film, conducting market research, advertising, devising and implementing a foreign distribution strategy, and auditing and accounting for the revenues and costs associated with each stage of this process.1

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340  Handbook of cultural economics Casting the Film As a producer enters the first stage of film production, one of their first tasks is to line up the cast, particularly the actors who will play the leading roles in the film. Often, producers consult with talent agents, who act on behalf of actors and actresses to negotiate their contracts and who typically receive a percentage of the gross income received by their clients. An agent may approach the talent (the actor) with a firm offer for a film that has already received financing, or with an offer contingent on financing. If a producer seeks to engage a prominent actor or actress in their film, the offer will likely be a firm offer. According to Paul N. Lazarus III, past Director of the University of Miami’s School of Communication’s Motion Pictures Program, film producer and former agent, ‘if you are in hot pursuit of one of the handful of so-called “bankable” stars, the likelihood is that you will be competing with many projects with firm offers attached’ (Lazarus 1992, p. 28).2 Economists have examined the various contractual offers made to the talent involved in film production. The lead actors in a film, particularly among the bankable stars, are typically offered a fixed payment, a profit- or gross-sharing contract, or a combination of the two. Chisholm (1997) examined a data set of contracts for leading actors and actresses and found that an actor was most likely to receive a sharing contract in the cases in which the benefits from providing an incentive for the actor to work harder outweighed the transaction costs of writing and enforcing a share contract. The evidence provided weak support for the hypothesis that risk-sharing concerns influenced optimal contract design. Weinstein (1998) explored the historical evolution of producers’ contracting terms and concluded that the increase in the number of sharing arrangements for producers was best explained as a response to a more risky contracting environment. De Vany (2004) found that the complexity in directors’ contingent pay agreements reflects an attempt to contract in the face of highly uncertain revenue outcomes. Financing the Film A producer will seek financing from a variety of potential sources. He or she can choose to enter a ‘negative pickup’ deal with either a major or an independent studio.3 In such an arrangement, the studio agrees to distribute the film for the producer once the film is complete. The studio further pays an advance against the revenues received by the producer once the film is released and distributed. The producer can then take this agreement to a bank to try to secure funding for the production of the film. The bank and studio will require a completion guarantee, which historically involved a charge of 6 percent of the budget to compensate the bank and studio for financial services provided.4 If the producer incurs costs that are over the budget, the completion guarantee allows the financiers to complete the picture themselves. We next consider a negative pickup deal from an economic perspective.5 When a producer proposes a film project, standard investment theory would suggest that the distributor should formulate an expectation of revenues, R, and determine the expected variance, q 2, or degree of risk, associated with the project. In principle, the more uncertain the market prospects of the film, the greater the risk a studio faces in agreeing to distribute the film. However, de Vany and Walls (1996, 1999, 2004) argue that

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Motion-picture industry  341 revenue distributions have effectively infinitely large variances. De Vany (2006) proposes that this extreme uncertainty explains the pervasiveness of contingent contracting in the industry. Despite the highly uncertain environment, producers, studios, and bankers will still attempt to assess the risk associated with a film project. The studio will agree to distribute the film, without having observed the final product, if they expect the film to generate sufficient revenues to offset the cost of distributing the film, which will include the actual distribution and marketing costs, and the opportunity cost of not distributing an alternative film. Given the choice between two film projects, for a given estimated revenue, the distributor will be more likely to pick up the film with the smaller perceived risk. For a given degree of uncertainty, the distributor will be more likely to pick the film expected to generate larger revenues. The completion guarantee serves to limit some of the risk exposure to the distributor and to the bank or other lending institution. Further, once a distributor chooses to pick up a film, the bank will take the distributor’s choice as a signal about the anticipated risk involved with financing the film. Since it is in the interest of the distributor to make as accurate a measure as possible of the risk associated with a new film, the distributor’s and bank’s incentives are aligned. Thus, a profit-maximizing bank will be more likely to finance a film that has received a pickup guarantee from a distributor. A distributor may simply provide an advance to produce the film, in which case the financial terms will be stricter. Typically, the distributor will acquire all rights to the film in such an arrangement.6 Other sources of financing include: industry sources, such as talent agencies, and in-house production arrangements; lenders, such as financial institutions and distributors; and investors, including both public and private sources. Vogel presents an extensive and detailed discussion of financing and accounting practices in production and distribution deals (Vogel 2015, pp. 128–35, 194–265).

THEATRICAL DISTRIBUTION AND EXHIBITION Following production, a film is then distributed for exhibition. A film produced in the US is often first released in the domestic theatrical market, then in foreign theatrical markets, although simultaneous domestic and foreign release have become more common, particularly among higher-budget ‘event’ films. Further, with the expansion of subscription video-on-demand services, some films are released on streaming platforms on the same weekend as their theatrical release. Indeed, theatrical release may be bypassed altogether, particularly when films are produced by streaming services, such as Netflix and Amazon. We discuss these alternative release strategies of compressing, or even eliminating, the more traditional distribution windows, in the next main section, in the context of digitalization of the movie industry. However, we first examine common cinematic release strategies, as theatrical release remains a widespread practice, particularly for larger-budget films. Distribution in Historical Context In the early days of the industry, by 1930, the US motion-picture industry was dominated by five major studios, each characterized by full vertical integration, with studios

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342  Handbook of cultural economics c­ ontrolling film production, distribution and exhibition. This extensive vertical integration led to allegations of anticompetitive practices. In 1938, the Department of Justice initiated a series of actions against the major studios, together with three others, on behalf of non-studio movie exhibitors. In 1948, as a result of U.S. v. Paramount, the Supreme Court ordered the major studios to divest themselves of their theatres, to level the playing field for the smaller, non-studio exhibitors. The resulting separation of control of movie distribution from exhibition was formative in today’s distributor–exhibitor contractual relationships.7 We turn now to a discussion of contemporary distribution strategies and contracts. Distribution Strategies For a film’s initial domestic theatrical run, the distributor will choose between a wide national and a limited platform release. Films released widely are typically shown on thousands of screens on the opening weekend, whereas films in limited release may initially show in only a few cities, on a significantly smaller number of screens. A key economic characteristic of a film is that it is an ‘experience good’, that is, a consumer learns their valuation of the good only after consuming it. Strategically, a wide release can work in the distributor’s favor, given that the distributor has more information about the quality of the movie prior to its release. Since films often achieve their highest weekend attendance on the opening weekend, the distributor can generate a relatively high box-office take on that first weekend, even if the film is of relatively low quality; once consumers learn the true quality of the film, these consumers will share their assessments of the film with their social networks, resulting in a potentially precipitous decline in attendance in the weeks following the wide open for films experienced as ‘low quality’. A limited-release strategy might be chosen for films expected to appeal to a niche audience, such as arthouse films; this strategy can potentially benefit from a gradual build-up of positive word-of-mouth, resulting in an eventual expansion to wide release during the remainder of the film’s theatrical run. Chen et al. (2013) tested the efficacy of the wide-release strategy as compared to that of the platform release. They found that a platform release influences how consumers view the quality of a film in the early stages of the film’s run. However, once the platform film moves to wide release, attendance declines faster than for wide-release films after their release. In the context of international release strategies, Meloni et al. (2018) examined a sample of over 1400 American movies that were theatrically exhibited in 45 non-American countries, over a 12-year period. They used a hedonic model to estimate film revenues; this econometric approach facilitated the authors’ identifying specific factors that impacted movie attendance. They found evidence that cultural and geographical distance influence both the number of American films exhibited in a non-American country and the revenues generated by the films.8 Distribution Contracts In the US theatrical market, the contract between a distributor and an exhibitor for a given film typically involves an agreement on how to split the box-office receipts. The

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Motion-picture industry  343 distributor’s share of the net box-office receipts can be as high as 70 percent for the first two weeks of a major release’s run, declining to 60 percent and then stabilizing at a flat rate of 35 or 40 percent.9 De Vany and Walls (1996) examined revenue distribution patterns and found evidence of revenue streams having what amounts to infinite variance. However, once a film’s run has reached a critical number of weeks, the film is far more likely to sustain a relatively long run. Given the nature of the typical distributor–exhibitor contract, the exhibitor can benefit if a movie generates a steady audience over a relatively long run. In addition, the contract will include a rental escalation clause. If the film not only sustains a long run, but also generates significant revenue in a given week, the contract will revert to the exhibitor’s paying 90 percent of box-office receipts, less the house ‘nut’, which is an allowance for the theatre’s operating expenses. The exhibitor pays the distributor the higher of this amount compared to its flat rental fee against box-office receipts.10 Gil and Lafontaine (2012) examine revenue-sharing contracts for films distributed in Spain and find evidence that contracting terms reflect a preference for flexible pricing among distributors.11 An interesting question pertaining to theatrical distribution is, given the highly uncertain market in which distributors operate, how do they choose the specific theatrical release date for each of their films? A film’s genre, cast, director, plot and seasonal timeliness, among other attributes, play important roles in this decision. Further, the unique degree of product differentiation across all films potentially in release during the same time frame is significant in the determination of an optimal movie release strategy. According to Wyatt (1994, p. 97): ‘[T]he marketplace for films is divided not just by different demand functions (or preferences), but also by differences between the many films which appear simultaneously in the market.’12 Thus, a studio will strategically respond to the expected release patterns of the other studios.

DIGITALIZATION Digitalization has had a widespread impact on the motion-picture industry. Filming with digital cameras, rather than on film, created an opportunity to lower film production costs and to distribute film digitally, instead of the significantly more costly alternative of shipping movie prints to cinemas. According to the United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics (data.uis.unesco. org, accessed 11 December 2019), the percentage of indoor cinema screens in the US equipped for digital projection rose from 11.6 percent in 2007 to 99.3 percent in 2017. Similar patterns of digital-projection adoption characterize a wide range of international markets, many of which achieved 100 percent digital projection percentages by 2017. Exhibitors were initially reluctant to invest in the costly equipment required for digital projection; distributors participated in various arrangements to help, in effect, to share the cost of adoption with exhibitors. In a Journal of Economic Perspectives article, Joel Waldfogel (2017) examined the disruptive impact of digitization on media industries, including the movie industry, among others, such as the television and music industry, all characterized by copyrighted content. The technological capability of representing artistic content digitally

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344  Handbook of cultural economics immediately ­introduces the risk of illegal low-cost replication and distribution of that content. Waldfogel notes, however, that digitization also lowers the cost of distributing artistic content legally, resulting in a wider range of content choice for consumers, with potentially higher quality.13 Digital Film Piracy An extensive stream of literature has aimed empirically to assess the effect of illegal distribution of film content on the revenue generated from legal film exhibition and viewing. De Vany and Walls (2007) found that piracy on the Internet negatively impacted theatrical revenues for movies with wide releases; notably, they did not find evidence to support the hypothesis that illegal viewing had a complementary, demand-generating impact on cinematic viewing. McKenzie and Walls (2016) found a similar effect in Australia. Using data on torrent downloads, they found a statistically significant salesdisplacement effect on cinematic revenues, although they noted that the economic size of the effect was small. In response to the ease and pervasiveness of illegal downloading activity, anti-piracy laws and policies have been adopted. Orme (2014) studied these actions in the US and found them to be largely ineffective in helping the owners of film content recover revenue; they are particularly ineffective in the long term. McKenzie (2017) examined graduatedresponse policies in six countries and found that they did not have a positive impact on cinematic film revenue. Further, two studies examined the impact of the US government’s shutdown of Megaupload.com, a notable source of piracy, on studios’ film revenues. The results were mixed. Danaher and Smith (2014) found an increase in digital sales following the shutdown, suggesting consumers substitute legal content for illegal content. Peukert et al. (2017) found that only films with wide theatrical releases experienced a positive revenue impact, and that the average effect of the shutdown on film revenues was negative. These findings suggest that illegal downloading of film content may enhance demand for legal content via word-of-mouth mechanisms.14 Video on Demand Digital movie content has also anchored the rise of subscription video-on-demand (SVOD) streaming services, with which consumers can view films on a wide range of platforms, including televisions, laptop computers, tablets and smartphones. As streaming companies such as Netflix and Amazon invest in movie production, the essential nature of these firms moves closer to a vertically integrated structure, with production, distribution and in-home exhibition conducted all within one firm. Expansion of these companies will likely lead to further economies of scale and the potential for significant concentration in the industry, reminiscent of the dominance of the major studios during the early days of the industry.15 Critical Reviews and Social Networks Critics’ movie reviews are widely available on the Internet, in addition to aggregated professional reviews on sites such as Metacritic.com. User reviews also are widely accessible

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Motion-picture industry  345 online, including on Twitter.com and a range of other social-media platforms. Economists have studied the effects of professional reviews, peer reviews and more generally wordof-mouth on movie consumption choices. Hennig-Thurau et al. (2012) examined the ‘influencer’ and ‘predictor’ effects of reviews. They found a significant relationship between critical reviews and long-term theatrical revenues; namely, that highly rated films experience a stronger influence effect than films with lower ratings. Data on an extensive set of films released over a 19-year period, in Moretti (2011), show that social learning about film quality is an important factor in box-office revenues for films with positive surprises in quality, among other findings.16

CONCLUSION The economic analysis of the motion-picture industry is a growing and increasingly important strand in the economics literature. Economists have documented patterns of revenue distribution and contracting terms at all levels of the production–distribution– exhibition chain. Digitalization has disrupted the industry, leading to extensive piracy activity and innovation in both theatrical exhibition and movie viewing on a wide range of alternative platforms. A frontier research area in this field is in ‘big data’ analytics and machine learning.17 These tools hold significant potential for improving revenue forecasting, and modelling consumer-specific film-purchasing habits and preferences, with potentially significant welfare gains.

NOTES  1. See Vogel (2015), pp. 126–93.  2. According to Lazarus, ‘a bankable “star” is one around whom a picture can be financed – someone whom bankers would unhesitatingly finance in a feature film’ (Lazarus 1992, p. 28). See also De Vany (2006, pp. 649–50).  3. The ‘negative’ refers to the film produced, not a reversal of ownership.  4. Competitive pressures significantly lowered these rates in the 1990s. See both Donahue (1987) and Vogel (2015, p. 170).  5. Goettler and Leslie (2005) and Palia et al. (2008) explore competing hypotheses explaining the co-financing choice, including portfolio risk reduction, internal-capital market factors, and resource pooling.  6. See Donahue (1987, p. 49).  7. See Vogel (2015) and De Vany (2006) for detailed discussions of the Paramount Consent Decrees and their impact on the industry’s organization to the present. See also Chisholm (1993) for a related analysis of long-term versus short-term contracting between studios and actors prior to, and following, Paramount.  8. See also Zemaityte et al. (2018) on global cinema distribution.  9. See De Vany (2006, pp. 627–8) for a detailed discussion of exhibitor/distributor contracting terms. Also see Filson et al. (2005) for an empirical study of exhibition contracts, which examines the role of risk aversion and transaction costs in optimal contract design. 10. See De Vany (2006, pp. 627–8) for further details. 11. This finding is in contrast to risk-sharing and moral-hazard explanations, the latter of which emphasize the importance of using contracts as incentive mechanisms. Gil (2013) further compares formal and relational contracting in Spanish film distribution. 12. Einav (2007) finds empirical support for this proposition, particularly as it relates to seasonality. 13. See also Waldfogel (2016). 14. See also Koschmann and Bowman (2017). 15. See Aguiar and Waldfogel (2018) for further discussion of the impact of Netflix on competition among

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346  Handbook of cultural economics platforms as well as its vertical integration. See also Goldfarb and Tucker (2019) for further discussions of digital economics. 16. See Hsu and Jane (2016) for an analysis of the impact of word-of-mouth and critical reviews on box-office outcomes; see Brown et al. (2012) for a study on studios’ strategically preventing reviewers from viewing (and assessing) a film until after its theatrical release. 17. See Kim et al. (2015) and Lehrer and Xie (2018) for research on machine-learning algorithms, and on econometrics and analytics, respectively, applied to movie-industry data.

SEE ALSO: Chapter 14: Creative industries; Chapter 26: Digitization in the cultural industries.

REFERENCES Aguiar, L. and J. Waldfogel (2018), ‘Netflix: global hegemon or facilitator of frictionless digital trade?’, Journal of Cultural Economics, 42 (3), 419–45. Brown, A.L., C.F. Camerer and D. Lovallo (2012), ‘To review or not to review? Limited strategic thinking at the movie box office’, American Economic Journal: Microeconomics, 4 (2), 1–26. Caves, R.E. (2000), Creative Industries: Contracts Between Art and Commerce, Cambridge, MA: Harvard University Press. Chen, X., Y. Chen and C.B. Weinberg (2013), ‘Learning about movies: the impact of movie release types on the nationwide box office’, Journal of Cultural Economics, 37 (3), 359–86. Chisholm, D.C. (1993), ‘Asset specificity and long-term contracts: the case of the motion-pictures industry’, Eastern Economic Journal, 19 (2), 143–55. Chisholm, D.C. (1997), ‘Profit-sharing versus fixed-payment contracts: evidence from the motion pictures industry’, Journal of Law, Economics, & Organization, 13 (1), 169–201. Chisholm, D.C. and G. Norman (2006), ‘When to exit a product: evidence from the U.S. motion-picture exhibition market’, American Economic Review: Papers & Proceedings, 96 (2), 57–61. Chisholm, D.C., V. Fernández-Blanco, S.A. Ravid and W.D. Walls (2015), ‘Economics of motion pictures: the state of the art’, Journal of Cultural Economics, 39 (1), 1–13. Danaher, B. and M.D. Smith (2014), ‘Gone in 60 seconds: the impact of the Megaupload shutdown on movie sales’, International Journal of Industrial Organization, 33 (March), 1–8. De Vany, A. (2004), ‘Contracting with stars when nobody knows anything’, in A. De Vany, Hollywood Economics: How Extreme Uncertainty Shapes the Film Industry, London: Routledge, pp. 231–54. De Vany, A. (2006), ‘The movies’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 615–65. De Vany, A. and W.D. Walls (1996), ‘Bose-Einstein dynamics and adaptive contracting in the motion picture industry’, Economic Journal, 106 (439), 1493–514. De Vany, A. and W.D. Walls (1999), ‘Uncertainty in the movie industry: does star power reduce the terror of the box office?’, Journal of Cultural Economics, 23 (4), 285–318. De Vany, A.S. and W.D. Walls (2004), ‘Motion picture profit, the stable Paretian hypothesis, and the curse of the superstar’, Journal of Economic Dynamics and Control, 28 (6), 1035–57. De Vany, A.S. and W.D. Walls (2007), ‘Estimating the effects of movie piracy on box-office revenue’, Review of Industrial Organization, 30 (4), 291–301. Donahue, S.M. (1987), American Film Distribution: The Changing Marketplace, Ann Arbor, MI: University of Michigan (UMI) Press. Einav, L. (2007), ‘Seasonality in the U.S. motion picture industry’, RAND Journal of Economics, 38 (10), 127–45. Filson, D., D. Switzer and P. Besocke (2005), ‘At the movies: the economics of exhibition contracts’, Economic Inquiry, 43 (2), 354–69. Gil, R. (2013), ‘The interplay of formal and relational contracts: evidence from movies’, Journal of Law, Economics, & Organization, 29 (3), 681–710. Gil, R. and F. Lafontaine (2012), ‘Using revenue sharing to implement flexible prices: evidence from movie exhibition contracts’, Journal of Industrial Economics, 60 (2), 187–219. Goettler, R.L. and P. Leslie (2005), ‘Cofinancing to manage risk in the motion picture industry’, Journal of Economics and Management Strategy, 14 (2), 231–61.

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Motion-picture industry  347 Goetzmann, W.N., S.A. Ravid and R. Sverdlove (2013), ‘The pricing of soft and hard information: economic lessons from screenplay sales’, Journal of Cultural Economics, 37 (2), 271–307. Goldfarb, A. and C. Tucker (2019), ‘Digital economics’, Journal of Economic Literature, 57 (1), 3–43. Hennig-Thurau, T. and M.B. Houston (2019), Entertainment Science: Data Analytics and Practical Theory for Movies, Games, Books, and Music, Cham: Springer. Hennig-Thurau, T., A. Marchand and B. Hiller (2012), ‘The relationship between reviewer judgments and motion picture success: re-analysis and extension’, Journal of Cultural Economics, 36 (3), 249–83. Hsu, Y.-L. and W.-J. Jane (2016), ‘Bidirectional causality for word of mouth and the movie box office: an empirical investigation of panel data’, Journal of Media Economics, 29 (3), 139–52. Kim, T., J. Hong and P. Kang (2015), ‘Box office forecasting using machine learning algorithms based on SNS data’, International Journal of Forecasting, 31 (2), 364–90. Koschmann, A. and D. Bowman (2017), ‘Simultaneous estimation of legal and illegal supply and demand: the case of motion pictures’, International Economic Journal, 31 (4), 555–77. Lazarus, P.N. III (1992), The Film Producer: A Handbook for Producing, New York: St Martin’s Press. Lehrer, S.F. and T. Xie (2018), ‘The bigger picture: combining econometrics with analytics improve forecasts of movie success’, NBER Working Paper No. 24755, June, National Bureau of Economic Research, Cambridge, MA. Luo, H. (2014), ‘When to sell your idea: theory and evidence from the movie industry’, Management Science, 60 (12), 3067–86. McKenzie, J. (2017), ‘Graduated response policies to digital piracy: do they increase box office revenues of movies?’, Information Economics and Policy, 38 (March), 1–11. McKenzie, J. and W.D. Walls (2016), ‘File sharing and film revenues: estimates of sales displacement at the box office’, B.E. Journal of Economic Analysis and Policy, 16 (1), 25–7. Meloni, G., D. Paolini and J.D. Tena (2018), ‘American beauty: trade flows and export costs of US movies’, Journal of Cultural Economics, 42 (4), 701–16. Moretti, E. (2011), ‘Social learning and peer effects in consumption: evidence from movie sales’, Review of Economic Studies, 78 (1), 356–93. Moul, C.C. (ed.) (2005), A Concise Handbook of Movie Industry Economics, New York: Cambridge University Press. Nowell-Smith, G. (ed.) (1996), The Oxford History of World Cinema, Oxford: Oxford University Press. Orhun, A.Y., S. Venkataraman and P.K. Chintagunta (2016), ‘Impact of competition on product decisions: movie choices of exhibitors’, Marketing Science, 35 (1), 73–92. Orme, T. (2014), ‘The short- and long-term effectiveness of anti-piracy laws and enforcement actions’, Journal of Cultural Economics, 38 (4), 351–68. Palia, D., S.A. Ravid and N. Reisel (2008), ‘Choosing to cofinance: analysis of project-specific alliances in the movie industry’, Review of Financial Studies, 21 (2), 483–511. Peukert, C. (2019), ‘The next wave of digital technological change and the cultural industries’, Journal of Cultural Economics, 43 (2), 189–210. Peukert, C., J. Claussen and T. Kretschmer (2017), ‘Piracy and box office movie revenues: evidence from Megaupload’, International Journal of Industrial Organization, 52 (May), 188–215. Prag, J. and J. Casavant (1994), ‘An empirical study of the determinants of revenues and marketing expenditures in the motion picture industry’, Journal of Cultural Economics, 18 (3), 217–35. Ravid, S.A. (1999), ‘Information, blockbusters, and stars: a study of the film industry’, Journal of Business, 72 (4), 463–92. Sawhney, M.S. and J. Eliashberg (1996), ‘A parsimonious model for forecasting gross box-office revenues of motion pictures’, Marketing Science, 15 (2), 113–31. Squire, J.E. (ed.) (2017), The Movie Business Book, 4th edn, New York: Routledge. Vogel, H.L. (2015), Entertainment Industry Economics: A Guide for Financial Analysis, 9th edn, New York: Cambridge University Press. Waldfogel, J. (2016), ‘Cinematic explosion: new products, unpredictability and realized quality in the digital era’, Journal of Industrial Economics, 64 (4), 755–72. Waldfogel, J. (2017), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214. Waterman, D. (2005), Hollywood’s Road to Riches, Cambridge, MA: Harvard University Press. Weinstein, M. (1998), ‘Profit-sharing contracts in Hollywood: evolution and analysis’, Journal of Legal Studies, 27 (1), 67–112. Wyatt, J. (1994), High Concept: Movies and Marketing in Hollywood, Austin, TX: University of Texas Press. Zemaityte, V., B.S. Coate and D. Verhoeven (2018), ‘Media trade beyond country borders: five types of global cinema distribution’, SSRN working paper, accessed 11 December 2019 at https://ssrn.com/abstract=3228310.

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FURTHER READING Excellent references on business practices, and economic and historical analyses of the industry, include NowellSmith (1996), Caves (2000), De Vany (2004, 2006), Squire (2017), Moul (2005), Waterman (2005), Vogel (2015) and Hennig-Thurau and Houston (2019). Seminal empirical work on box-office revenue determinants includes Prag and Casavant (1994), Sawhney and Eliashberg (1996) and Ravid (1999). Research on film-programming choice in exhibition includes Chisholm and Norman (2006) and Orhun et al. (2016). Analyses of digital economics and technological change include Peukert (2019) and Goldfarb and Tucker (2019). For an analysis of recent research in motion-pictures economics see Chisholm et al. (2015).

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39.  Museums*

Víctor Fernández-Blanco and Juan Prieto-Rodríguez

THE MUSEUM: AN ECONOMIC DEFINITION Most people would agree that museums are cultural institutions par excellence. However, more questions arise when we want to establish a definition of the museum and explain its economic characteristics. There are many definitions regarding the museum as an institution devoted to the collection, storage, display and research of objects, artefacts or, even, intangibles. Along these lines, the Statutes of the International Council of Museums (ICOM 2017, p. 3) offers the following definition: ‘a museum is a non-profit, permanent institution in the service of society and its development, open to the public, which acquires, conserves, researches, communicates and exhibits the tangible and intangible heritage of humanity and its environment for the purposes of education, study and enjoyment’.1 We might categorize this as an institutional definition; note that it is not uncontroversial, since it leaves out for-profit organizations that collect or exhibit any kind of object. Alternatively, although they recognize the importance of the functions defined by the ICOM, Ginsburgh and Mairesse (1997) note that this definition risks neglecting other activities such as leisure, tourism or regional economic development. In the end, it offers a partial, conservative and, even, biased definition of the museum. Following an economic point of view together with the seminal perspectives of Montias (1973) and Peacock and Godfrey (1974 [1997]), we offer a definition that considers the museum as an economic agent. We posit it as an organization that follows a general path specified by economic behaviour, that is, the maximization of an objective function under a set of economic and institutional restrictions. From this perspective, we allow room for various objectives, including the maximization of attendance and the maximization of profits; thus our definition acknowledges that such goals require efficient management and that economics can help to achieve them.2 Considering the museum to be an economic agent, our analysis starts by defining its production function to describe technology rather than economic behaviour and shows the relationship between the quantities of production factors used and the maximum amount of product obtainable. The main inputs a museum deploys are labour and capital. Under the first category, we include not only specialized and administrative labour but also volunteers; capital includes financial resources, buildings, equipment and the museum’s collection itself. Any definition of museum must take into account that it has a multi-output production function, including conservation, exhibition, research, and so on. If we accept Becker’s (1965) procedure, all of these outputs can be considered to be market goods, which when combined with inputs and time, allow visitors to obtain desirable commodities such as knowledge, aesthetic experience and/or simply enjoyment. We can group museum outputs into three broad categories: 349

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350  Handbook of cultural economics 1. C  ollection – this includes the identification, documentation, expansion and preservation of museum contents. 2.  Exhibition – this makes funds available to citizens for use as purely aesthetic enjoyment and/or entertainment experiences as well as for education, training and research. 3.  Other services – the content of this category is much broader and more varied; for example, it includes catering and merchandising. These services emerge and evolve as museums are re-orientated towards better serving visitors, and thus, these services become increasingly important as a funding source. A transversal phenomenon that affects the provision of these services is the impact of new technologies and the digitization process. Museums (Navarrete and Borowiecki 2016) and other cultural heritage institutions, such as archives (Guccio et al. 2016), are using digital technologies to help them produce new services related to collection and exhibition. Museums are not simply digitizing their collections, but also using new technologies to get closer to their public, changing the traditional practices of conservation and exhibition of cultural heritage. Apart from their own outputs, museums may generate important externalities such as changes in the appeal and image of the cities, attracting tourists, but also developing economies of agglomeration attracting new companies. Owing to these externalities that make the cities that house them better places to live and work, in recent decades, museums have been seen as mechanisms or agents of economic development. A prerequisite of good installation decisions is to have a clear idea of the determinants of the spatial location of cultural institutions and of how a fixed allocation of cultural facilities may affect the economic behaviour of individuals.3 Owing to the high number of projects that did not meet their objectives, for instance, The Public in West Bromwich (UK) or the City of Arts and Sciences in Valencia (Spain), a critical perspective might interpret some projects in terms of a new kind of social lottery. These projects can be understood as a type of political betting game played by politicians who are not concerned about the crowding-out implications of the game (Buettner and Janeba 2016). In addition, we can add a new type of output, namely, the economic impact of the museum (Mairesse and Vanden Eeckaut 2002; Plaza 2010). Once we have adopted an economic approach, an analysis of the museum can be pursued by utilizing the main instruments of economics. This involves understanding the demand and supply sides of museums and then delineating the logic of their incentives, which may or may not be defined independently by the market if the museum follows a commercial strategy.

THE DEMAND SIDE OF MUSEUMS The demand side includes private and public components. Private demand can be considered the result of an individual utility maximization process, and therefore demand is particularly sensitive to an individual’s preferences, captured by his or her utility function, together with the constraints he or she must fulfil. These constraints may include not only budget constraints that are linked to traditional economic variables, such as prices

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Museums  351 or income, but also (and even more importantly) time constraints.4 The bulk of empirical research on private demand in the context of museums is mainly focused on onsite visitors’ characteristics and attendance rates. However, by using new technologies, the traditional definition of attendants is challenged. Onsite and online visitors may have a different profile (Evrard and Krebs 2018) but digitalized collections are now a standard way of exhibition, and visitors to the museum online collections should be considered to be a relevant part of the museum achievements. In general, onsite individual’s museum attendance increases with the level of income and education and age, at least until the median age and among women (Dickenson 1992 [1997]; Peterson et al. 2000). As regards ethnic origin, we find mixed results (Lewis and Seaman 2004). There are also studies that introduce qualitative determinants of museum demand, such as the positive impact of the quality of the collection (Luksetich and Partridge 1997) or repeated visits (Darnell and Johnson 2001). Although empirical research on online visitors or comparison of both types of attendants is becoming more common, it is still scarce. Evrard and Krebs (2018), using data from the Louvre museum, find that visits to the museum web page cannot substitute physical visits and that there is a strong complementarity effect between onsite and online visits. Mihelj et al. (2019), using data from the Taking Part Survey in the UK, find a similar effect, but fear that owing to this strong complementarity, online access, instead of democratizing cultural participation, can reproduce, or even increase, existing inequalities in assistance between socio-economic groups. Finally, there is another field of research that estimates museum demand functions and discusses price elasticity with the aim of understanding the impact of introducing or increasing admission fees. In general, these studies conclude that demand for museums is price inelastic (O’Hagan 1995; Luksetich and Partridge 1997). Since, in many cases, data on the entire population are not available, and only a sample of museum visitors is available, the results can be biased. Prieto-Rodríguez et al. (2005) have used a representative sample of the entire population to estimate a demand system in which museums are aggregated with other cultural products. They have found an elastic demand for cinema, theatre, concert, ballet and museum tickets when considered together. Regardless of price elasticity, we should bear in mind that visitors are a relatively select part of the entire population; consequently, policy should be orientated to attract people to those museums that are considered merit goods, among other legitimate targets. It is important that policy-makers recognize that foreign tourists, domestic tourists and local citizens give rise to completely different externalities, and therefore it could be difficult or even impossible to define policies that simultaneously fulfil the requirements of all three of these groups.5 Yet, these policies are the basis of public demand for museums, which incorporates components of externalities including values such us well-known existence, option, bequest, prestige and education values, with effects that can be considered as public goods. We should also highlight the museum as a local or regional development factor. The Guggenheim Museum in Bilbao can be considered the most representative museum in this context, and it has been joined by other franchise museums. For instance, we cite the new Louvre museums that have appeared in different areas, such as Abu Dhabi, a developing area, and Lens (France), an old mining and industrial region that was hardest hit by the industrial crisis. Public demand can be built-in through the social valuation of a museum. Some research has tried to measure the social valuation of a given museum, particularly using contingent valuation techniques (Martin 1994; Bedate et al. 2009). It is

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352  Handbook of cultural economics remarkable that, as Noonan (2003) has noted, willingness to pay is lower in the case of museums than in archaeological or historical sites.

THE SUPPLY SIDE OF THE MUSEUM When analysing museums as economic agents, we pay special attention to their production and cost functions as well as the nature of their ownership. We have already suggested that the most accurate approach to a museum is a multi-output production function with a cost structure similar to other cultural firms that have very large fixed costs, while variable costs account for a small percentage of the total costs. Moreover, marginal costs, that is, the change in total cost owing to an additional visitor, are close to zero. These two features (high fixed costs and negligible marginal costs) are common to other cultural sectors and, usually, are intensified owing to digitization of museums (Navarrete 2013b). Consequently, the presence of economies of scale can be verified, although in the largest museums (measured by the number of visitors) the situation can be reversed so that we see diseconomies of scale for onsite visits (Jackson 1988). Finally, there is empirical evidence of technical and scale inefficiency in museums (Mairesse and Vanden Eeckaut 2002 in Belgium; Basso and Funari 2004 in Italy; and Barrio et al. 2009 in Spain), although inefficiency is higher when the museum is focused on preservation than when orientated to visitors or external objectives (Mairesse and Vanden Eeckaut 2002). Alternatively, Bishop and Brand (2003) consider technical inefficiency to be directly related to public grants and volunteer activities. Museums are open to both public and private ownership. In Europe, since a great portion of museums include collections originally developed by the Church, royalty or the nobility, public ownership is more frequent, while in the US, the majority of museums are privately owned. In both cases, museums tend to be non-profit organizations. Public ownership provides stability to a museum as well as a lack of incentive to develop economically efficient management. Private ownership can improve economic efficiency, but it increases risk and uncertainty. Trying to exploit the advantages of both sides while simultaneously avoiding their disadvantages, the hybrid model incorporates a mix of public and private governing authorities, and provides more opportunities for the autonomous management of museums (Schuster 1998; Meier and Frey 2003).

FINANCING MUSEUMS Currently, museums combine several sources of income that are independent of the nature of the ownership: admission prices, the sale of items besides admission and public grants are undoubtedly the most important sources. Private donors are also very important in the US6 but less so in continental Europe, although European museums are slowly shifting from public to private funding, getting closer to the American model (Fabrikant 2016). As attention towards visitors and other potential customers has become more important, new sources of revenue have emerged, especially those linked to merchandising, restoration and selling of ancillary goods. These strategies are orientated towards people who do not necessarily visit the museum itself and towards people who are attracted to

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Museums  353 visit the collection only after they visit the museum café or its shop. There are also other means of finance, such as hiring facilities or lending out items from the collection, that are becoming quantitatively more important and fully accepted as an appropriate management practice, especially when financial difficulties arise. This was the case at the Musée National Picasso in Paris, which loaned part of its collection to the Centro de Arte Reina Sofía in Madrid in 2008, for a €3.5 million fee; ‘I have to pay for the expansion project and I need the money’, said Anne Baldassari, director of the Musée National Picasso in Paris at the time of this exposition (in Garcia 2008). However, revenues from ticket sales and public grants are still the main sources of income for museums. The presence of admission fees in museums has been the object of controversy. We find different types of arguments against charging fees. First, charging fees may reduce museum attendance, especially among lower socio-economic classes (Anderson 1998); however, empirical evidence does not support this hypothesis (Luksetich and Partridge 1997; Bailey and Falconer 1998). Second, charging for admission may not be an effective measure for raising revenues, since it could reduce public grants, private donations (Hughes and Luksetich 1999; Maddison 2004) or income from ancillary goods, such as sales in museum stores or cafés. Third, the Pareto-optimal pricing rule is to make price equal to marginal costs; owing to the typical cost structure of a museum with marginal costs close to zero, the efficient solution is not to charge. This solution is compatible with charging positive fees when congestion increases marginal costs (Maddison and Foster 2003)7 and reinforces the idea that in the presence of continuously decreasing average costs, the optimal welfare solution entails public finance.8 Fourth, museums generate well-known positive external benefits for the entire population, and the theory of market failure suggests that finance by public budgets is an efficient means of financing provision. However, considering that visitors benefit more than other people, the principle of benefit in taxation suggests that public finance should be complemented with fees. We conclude that both sources of income (that is, public grants and ticket prices) may coexist. We can also define an optimal financing schedule using a principal–agent framework under conditions of imperfect information (Prieto-Rodríguez and FernándezBlanco 2006). A museum, the public agency, which is risk-neutral, plays the role of the principal, and the manager of the museum, who is risk averse, plays the role of the agent. The principal designs a contract with the agent and sets down which payments correspond to each possible scenario under the contract. The agent chooses his or her action among a set of possible actions. The results of this action depend on the agent’s efforts, which may or may not be known, and on some uncontrollable environmental conditions, which are usually denominated as the state of nature, and impose uncertainty on the relationship. The results can be a measure of the number of museum visitors, where the probability of achieving a certain number of visitors depends positively on the agent’s effort. That is, the better is the manager’s policy, the higher is the probability of obtaining favourable results. The principal aims to maximize an objective function that depends positively on the number of visitors and the public agency’s valuation of such visitors and negatively on the amount of grants.9 The agent, the museum’s manager, can be considered a bureaucrat á la Niskanen (1968), and so his or her utility function depends positively on the museum budget (including both ticket and grants income) and negatively on his or her effort. Therefore, there is a conflict of interest between the principal and the agent. On the one hand, greater levels of effort help to assure a better result for the principal but reduce

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354  Handbook of cultural economics the agent’s utility. On the other hand, larger payments reduce the principal’s profit but increase the agent’s utility. The signed contract should make compatible the interests of both participants. Under these conditions, the principal should design a contract that tries to maximize the expected social benefit under the constraint that the agent agrees to sign the contract; that is, he or she obtains his or her reservation utility. The contract can be designed under conditions of symmetric or asymmetric information. In the case of symmetric information, the public sector (that is the principal) knows the effort put in by the museum manager (the agent), and the contract clauses should specify the optimal ticket price and grant level as well as the agent’s optimal effort. In the case of asymmetric information, the agent can hide his or her effort and, therefore, it cannot be included in the contract clauses. Then, the principal must design a payment schedule in the contract that gives the agent sufficient incentive to make the optimal level of effort. If the public sector knows the manager’s effort, the optimal grant policy implies a museum budget constant that is independent of the number of visitors. This means that the public agency must fully insure the manager’s museum budget, assigning him or her a subsidy that, given the optimal level of effort, allows the manager to obtain his or her reservation level of utility. Hence, the public sector must finance the museum budget deficit if it has not been completely covered by ticket sales. In this case, the public grant decreases with the number of visitors and box office income. The resultant ticket price is Pareto optimal since it equalizes expected marginal social benefit (that is expected marginal private revenue plus expected marginal social value) with marginal costs. Also, when there is a social benefit from visits, this optimal price is located at a point at which demand is inelastic, thereby providing a new justification for the inelastic pricing strategy. Finally, the manager’s optimal-effort level is Pareto optimal because, at equilibrium, the expected marginal revenue product of effort must be equal to the manager’s marginal rate of substitution between budget and effort. Under conditions of asymmetric information, the public agency faces great difficulty in controlling the manager’s effort, and it faces a moral hazard problem that leads the public sector to not use the grants to fully insure the manager. This is because he or she has incentives to be inefficient by reducing his or her effort and, for example, by making inefficient expenditures or not maximizing alternative sources of revenue. The best choice for the public agency is to use grants to provide adequate incentives to the manager in order to improve his or her effort level, thereby achieving more efficient museum management. The equilibrium is no longer a Pareto-optimal situation with respect to the budget and the grant. However, for prices, the solution is the same as that under symmetric information and therefore Pareto optimal. In summary, in the presence of asymmetric information, and even with a risk-averse manager and a risk-neutral public agency, grants and budgets depend on results, since higher budgets related to good results provide the main incentives to increase a manager’s level of effort. Hence, transferring ticket-pricing policy to the authority of the manager is not the best way to introduce adequate incentives under any circumstances. That is, the manager of a museum should not be left to decide the ticket price for admission into that museum. Instead, the public agency must regulate these prices in accordance with social valuation and use grants as an incentive mechanism to achieve optimal managerial effort.

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Museums  355

NOTES *

1. 2.

3. 4. 5. 6. 7.

8. 9.

This study received funding from the Government of Spain (ECO2016-76506-C4-1-R and ECO2017-86402C2-1-R) and the Regional Government of Asturias (FC-15-GRUPIN14-064). We are especially grateful to the editors for the trust that they have placed in us again to write this chapter about museums. The usual disclaimer applies. This definition was adopted by the 22nd General Assembly of ICOM in Vienna, on 24 August 2007, and incorporated without changes in the statutes approved by the Extraordinary General Assembly on 9th June 2017 (Paris, France). This economic view has its detractors. For instance, Cannon-Brookes (1996) thinks that this approach defines a museum as a delivery services firm and thereby obscures its traditional and historical mission. However, perhaps now the problem involves defining the objective function, instead of considering museums as economic agents in general terms. Discussions on the design of smart local and regional policies concerning, respectively, museums and cultural industries can be found in Suarez and Mayor (2017) and Plaza and Haarich (2017). The general ticket for El Prado used to be less expensive than a Big Mac meal in Spain. Now, the general ticket is €15, and is free every day during the last two opening hours. The use of tracking technologies for spatial management of cultural destinations (as described in Shoval and McKercher 2017) can help make some of these three groups’ requests compatible. Yermack (2017) studies the effects of restrictions placed upon donations to US art museums. This congestion problem arises, for instance, in special exhibitions, when a museum faces increasing marginal costs and a higher potential attendance that shifts up the demand curve. Hence, the optimal behaviour in this case is to charge a positive fee that eventually could generate profits for the museum. In any case, special exhibitions (for example, in superstar museums) are not put on frequently in the majority of museums. In addition, while special exhibitions increase the number of visitors, they can also disturb the display or attendance at permanent collections. Note that, when other sectors of the economy are charging prices above their marginal costs, museum ticket prices should be positive (above marginal cost) in order to achieve a Pareto-optimal allocation of resources (Bailey and Falconer 1998). The public agency’s valuation can be considered a constant, but if the public sector has different valuations for different visitors, it varies with visitor characteristics, allowing us to introduce the possibility of price discrimination.

SEE ALSO: Chapter 42: Non-profit organizations; Chapter 44: Participation; Chapter 45: Performance indicators.

REFERENCES Anderson, R.G.W. (1998), ‘Is charging economic?’, Journal of Cultural Economics, 22 (2–3), 179–87. Bailey, S. and P. Falconer (1998), ‘Charging for admission to museums and galleries’, Journal of Cultural Economics, 22 (2–3), 167–77. Barrio, M.J., Herrero, L.C. and J.A. Sanz (2009), ‘Measuring the efficiency of heritage institutions: a case study of a regional system of museums in Spain’, Journal of Cultural Heritage, 10 (2), 258–68. Basso, A. and S. Funari (2004), ‘A quantitative approach to evaluate the relative efficiency of museums’, Journal of Cultural Economics, 28 (3), 195–216. Becker, G.S. (1965), ‘A theory of allocation of time’, Economic Journal, 75 (299), 493–517. Bedate, A., L.C. Herrero and J.A. Sanz (2009), ‘Measuring the efficiency of heritage institutions: a case study of a regional system of museums in Spain’, Journal of Cultural Heritage, 10 (2), 258–68. Bertacchini, E. and F. Morando (2013), ‘The future of museums in the digital age: new models for access to and use of digital collections’, International Journal of Arts Management, 15 (2), 60–72. Bishop, P. and S. Brand (2003), ‘The efficiency of museums: a stochastic frontier production function approach’, Applied Economics, 35 (17), 1853–8. Borowiecki, K.J. and C. Castiglione (2014), ‘Cultural participation and tourism flows: an empirical investigation of Italian provinces’, Tourism Economics, 20 (2), 241–62.

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356  Handbook of cultural economics Buettner, T. and E. Janeba (2016), ‘City competition for the creative class’, Journal of Cultural Economics, 40 (4), 413–51. Cannon-Brookes, P. (1996), ‘Cultural-economic analyses of art museums: a British curator viewpoint’, in V. Ginsburgh and P.M. Menger (eds), Economics of Arts: Selected Essays, Amsterdam: North-Holland, pp. 255–74. Cellini, R. and T. Cuccia (2013), ‘Museum and monument attendance and tourism flow: a time series analysis approach’, Applied Economics, 45 (24), 3473–82. Cuccia, T., L. Monaco and I. Rizzo (2017), ‘Are less public funds bad? New strategies for art providers, in V.M. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer International, pp. 357–69. Darnell, A. and R. Johnson (2001), ‘Repeat visits to attractions: a preliminary economic analysis’, Tourism Management, 22 (2), 119–26. Dickenson, V. (1992), ‘Museum visitor survey: an overview, 1930­–1990’, repr. 1997 in R. Towse (ed.), Cultural Economics: The Arts, The Heritage and the Media Industries, vol. 1, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 272–81. Evrard, Y. and A. Krebs (2018), ‘The authenticity of the museum experience in the digital age: the case of the Louvre’, Journal of Cultural Economics, 42 (3), 353–63. Fabrikant, G. (2016), ‘European museums adapt to the American way of giving’, The New York Times, 15 March, accessed 10 December 2019 at www.nytimes.com/2016/03/17/arts/design/european-museums-are-shifting-toamerican-way-of-giving.html. Feldstein, M. (ed.) (1991), The Economics of Art Museums, Chicago, IL: University of Chicago Press. Frey, B.S. (2006), ‘The economics of museums’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1017–47. Frey, B.S. (2019a), ‘Cultural tourism’, in B.S. Frey, Economics of Art and Culture, Cham: Springer International, pp. 115–20. Frey, B.S. (2019b), ‘Museums’, in B.S. Frey, Economics of Art and Culture, Cham: Springer International, pp. 77–88. Garcia, A. (2008), ‘Entrevista a Anne Baldassari’, El País, accessed 10 December 2019 at elpais.com/diario/2008​ /02/02/babelia/1201910771_850215.html. Ginsburgh, V. and F. Mairesse (1997), ‘Defining a museum. Suggestions for an alternative approach’, Museum Management and Curatorship, 16 (1), 15–33. Guccio, C., D. Lisi, M. Martorana and A. Mignosa (2017), ‘On the role of cultural participation in tourism destination performance: an assessment using robust conditional efficiency approach’, Journal of Cultural Economics, 41 (2), 129–54. Guccio, C., M.F. Martorana, I. Mazza and I. Rizzo (2016), ‘Technology and public access to cultural heritage: the Italian experience on ICT for public historical archives’, in K.J. Borowiecki, N. Forbes and A. Fresa (eds), Cultural Heritage in a Changing World, Cham: Springer International, pp. 55–75. Hughes, P. and W. Luksetich (1999), ‘The relationship among funding sources for art and history museums’, Nonprofit Management and Leadership, 10 (1), 21–38. International Council of Museums (ICOM) (2017), ‘Statutes’, accessed 10 December 2019 at icom.museum/ wp-content/uploads/2018/07/2017_ICOM_Statutes_EN.pdf. Jackson, R. (1988), ‘A museum cost function’, Journal of Cultural Economics, 12 (1), 41–50. Johnson, P.S. (2003), ‘Museums’, in R. Towse (ed.), A Handbook of Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 315–20. Journal of Cultural Economics (1998), ‘Special Issue on the Economics of Museums’, 22 (2–3). Jung, Y. (2015), ‘Diversity Matters: theoretical understanding of and suggestions for the current fundraising practices of nonprofit art museums’, Journal of Arts Management, Law, and Society, 45 (4), 255–68. Lewis, G. and B.A. Seaman (2004), ‘Sexual orientation and demand for the arts’, Social Science Quarterly, 85 (3), 523–38. Luksetich, W.A. and M.D. Partridge (1997), ‘Demand functions for museum services’, Applied Economics, 29 (12), 1553–9. Maddison, D. (2004), ‘Causality and museum subsidies’, Journal of Cultural Economics, 28 (2), 89–108. Maddison, D. and T. Foster (2003), ‘Valuing congestion costs in the British Museum’, Oxford Economic Papers, 55 (1), 173–90. Mairesse, F. and P. Vanden Eeckaut (2002), ‘Museums assessment and FDH technology: towards a global approach’, Journal of Cultural Economics, 26 (4), 261–86. Martin, F. (1994), ‘Determining the size of museum subsidies’, Journal of Cultural Economics, 18 (4), 255–70. Meier, S. and B. Frey (2003), ‘Private faces in public places: the case of a private art museum in Europe’, Cultural Economics, 3 (3), 1–16. Mihelj, S., A. Leguina and J. Downey (2019), ‘Culture is digital: cultural participation, diversity and the digital divide’, New Media & Society, 21 (7), 1465–85.

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Museums  357 Montias, J.M. (1973), ‘Are museums betraying the public’s trust?’, Museum News, 51 (May–June), 25–31. Navarrete, T. (2013a), ‘Digital cultural heritage’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 251–71. Navarrete, T. (2013b), ‘Museums’, in R. Towse and C. Handke (eds), Handbook on the Digital Creative Economy, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 330–43. Navarrete, T. and K.J. Borowiecki (2016), ‘Changes in cultural consumption: ethnographic collections in Wikipedia’, Cultural Trends, 25 (4), 233–48. Niskanen, W.A. (1968), ‘The peculiar economics of bureaucracy’, American Economic Review, 58 (2), 293–305. Noonan, D. (2003), ‘Contingent valuation and cultural resources: a meta-analytic review of the literature’, Journal of Cultural Economics, 27 (3–4), 159–76. O’Hagan, J.W. (1995), ‘National museums: to charge or not to charge?’, Journal of Cultural Economics, 19 (1), 33–47. Peacock, A.T. and C. Godfrey (1974), ‘The economics of museums and galleries’, Lloyd Bank Review, 111, (January), 17–28, repr. 1997 in R. Towse (ed.), Cultural Economics: The Arts, the Heritage and the Media Industries, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 364–75. Peterson, R.A., P.C. Hull and R.M. Kern (2000), ‘Age and arts participation: 1982–1997’, Research Division Report No. 42, National Endowment for the Arts, Washington, DC. Plaza, B. (2010), ‘Valuing museums as economic engines: willingness to pay or discounting of cash-flows?’, Journal of Cultural Heritage, 11 (2), 155–62. Plaza, B. and S.N. Haarich (2017), ‘Arts, culture and creativity as drivers for territorial development, innovation and competitiveness’, in V.M. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer International, pp. 371–88. Prieto-Rodríguez, J. and V. Fernández-Blanco (2006), ‘Optimal pricing and grant policies for museums’, Journal of Cultural Economics, 30 (3), 169–81. Prieto-Rodríguez, J., D. Romero-Jordán and J.F. Sanz-Sanz (2005), ‘Is a tax cut on cultural goods consumption actually desirable? A microsimulation analysis applied to Spain’, Fiscal Studies, 26 (4), 549–75. Schuster, M. (1998), ‘Neither public nor private: the hybridization of museums’, Journal of Cultural Economics, 22 (2–3), 127–50. Shoval, N. and B. McKercher (2017), ‘Implementation of tracking technologies for temporal and spatial management of cultural destinations: Hong Kong as an example’, in V.M. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer International, pp. 281–94. Suarez, P. and M. Mayor (2017), ‘A geographical approach to “smart” location of museums’, in V.M. AtecaAmestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer International, pp. 191–8. Yermack, D. (2017), ‘Donor governance and financial management in prominent US art museums’, Journal of Cultural Economics, 41 (3), 215–35.

FURTHER READING A general introduction to the economics of museums is to be found in Peacock and Godfrey (1974 [1997]), Feldstein (1991), Johnson (2003), Frey (2006, 2019b) and the special issue on the economics of museums in the Journal of Cultural Economics (1998). For a more specialized treatment of the economic impact and the social valuation of museums see Martin (1994), Bedate et al. (2009) and Plaza (2010). Demand for museums is discussed in Luksetich and Partridge (1997), Dickenson (1992 [1997]) and O’Hagan (1995). For the link between tourism flows and museum demand see Cellini and Cuccia (2013), Borowiecki and Castiglione (2014), Guccio et al. (2017) and Frey (2019a). Production and cost functions are estimated in Jackson (1988), Bishop and Brand (2003) and Barrio et al. (2009). For a more specialized treatment of museums financing see Hughes and Luksetich (1999), Maddison and Foster (2003), Meier and Frey (2003), Prieto-Rodríguez and FernándezBlanco (2006), Jung (2015), Cuccia et al. (2017) and Yermack (2017). Different ways digitization can impact on museums are analysed in Navarrete (2013a) and Bertacchini and Morando (2013).

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40.  Music industry

Christian Handke

The music industry is one of the core cultural industries, which disseminate cultural products via sophisticated media infrastructures. Virtually all central topics of cultural economics have been discussed regarding music – from appropriate ways of financing creativity, success factors and determinants of demand, and complex processes in evaluating music, to the industrial organization of the music industry. Over recent years, economists have paid increasing attention to the music industry, and technological change has become a pervasive theme in the literature. In addition to discussing basic features of the music industry, a central motive in this chapter is thus the challenging subject of technological change.

BASIC CHARACTERISTICS This chapter focuses on the primary market for recorded music, where end-users acquire copies or access to copies. There are obvious links between the music industry in this narrow sense and other ways of marketing musical works – in live performances, by licensing to commercial users or by selling merchandise – but this chapter covers only the economic characteristics of the primary market. Cultural economics proposes a number of specific characteristics of cultural industries, such as the music industry. Music recordings have public goods attributes, so that their market value does not fully reflect their total social value. They also have experience good attributes (Nelson 1970), so that most users make choices with incomplete information. Preferences for specific genres of music are influenced by prior consumption of similar works and learning (often referred to as taste formation), as well as in complex social interactions, since users process signals of quality from other parties to inspire their own choices. Furthermore, creating musical work can entail non-pecuniary rewards or can be intrinsically motivated as an end in itself.1 Within the cultural sector, recorded music tends to be a simple creative work (Caves 2000), which as a rule is cheaper to create than films, television programs and many video games. Low costs of creation and intrinsic motivation to create help explain the extensive product differentiation in the music industry: there are literally tens of thousands of new songs and albums released per year. The variety of supply far exceeds the search or consumption capacities of even the most voracious and variety-seeking user. Furthermore, music pervades cultural boundaries more easily than many other cultural products, for example, those that are more language-based such as literature. The music industry has a long tradition as a glocal industry in which multinational firms sell virtually identical products in multiple territories but also invest in the creation of works that are of more local appeal (Dolfsma 2000). In addition, for recorded music, repeat consumption is the norm. In contrast to many films or literary works, individuals’ appreciation of specific musical works even tends to increase over several repetitions (Lacher and Mizerski 1994). 358

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Music industry  359 Also, users exhibit great taste for variety in music. Most users listen to many different musical works over any month or year. To summarize, markets for recorded music are complex, with many suppliers, relatively low barriers to entry for creators, extensive product differentiation, and many users picking and mixing many products in their consumption schedule. In the course of digitization, this holds more than ever. The costs of creating and disseminating music have fallen. There are many works available and users have few technical restrictions in their product searches and can often sample the product. In addition, the music industry has gone through substantial changes to its financial situation and its structure.

EBBS AND FLOWS The music industry has exhibited several extended periods of booms and recessions over the twentieth century. Technological change features prominently in any explanation of major ebbs and flows in this industry (see for example Peterson and Berger 1975; Tschmuck 2006; Handke 2010). According to the widely used statistics of the International Federation of the Phonographic Industry (an organization mostly representing larger record companies; IFPI 2017, 2019), the global market for sound recordings peaked in 1999 at almost US$24 billion (nominal trade value and excluding revenues from synchronization and performance rights) and fell to circa US$12 billion in 2014. Even including increasing revenues from synchronization and performance rights, this amounts to a halving of music industry revenues in inflation adjusted terms, and the pattern is consistent across most countries. The coincidence with the diffusion of unauthorized digital copying (for instance, the adoption of compact-disk burners and, in particular, file sharing) is striking. Nevertheless, in a sizable empirical literature on the subject, it is still contentious to what extent unauthorized digital copying explains the slump in sales of sound recordings; for literature reviews, see Handke (2011), Liebowitz (2013) or Watson et al. (2015). After 2014, the primary market for sound recordings expanded again – also adjusted for inflation – and stood at US$16 billion in 2018. This growth was driven almost entirely by income from music-streaming services such as YouTube, Spotify, Deezer or Tidal, which accounted for just under US$9 billion in 2018.2 An important issue is the extent to which authorized streaming services have converted pirates by offering better value than illegitimate sources (Danaher et al. 2010); another issue is to what extent streaming services complement or substitute other music sales (Aguiar and Martens 2016). In either case, payments to rights holders per stream or view are notoriously modest. This may be caused by the market power of dominant Internet platforms or because pricing is restricted by de facto competition from unauthorized sources of music online (Handke 2015). The ebbs and flows regarding the commercial value of sound recordings have received much attention, but they do not tell the whole story. Even as music industry revenues plummeted between 1999 and 2014, the quantity and quality of recorded music supplied seems to have expanded. Not only are older works more easily available online than in the past, but each year, there is also much more new music released than in the 1990s, when music industry revenues were much higher (Handke 2012; Waldfogel 2012). Nor does the quality of works released seem to have suffered. Where such data is available, the average

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360  Handbook of cultural economics listening time to recorded music has greatly expanded (Handke 2012). As far as user evaluations are concerned, new music seems to be at least as appealing as ever (Aguiar and Waldfogel 2016; Waldfogel 2017). It seems that digitization has made the music industry more productive. The costs of creating and disseminating recorded music have fallen with digitization. It is also feasible that super-normal profits in the music industry have melted off with greater competition.

FUNCTIONS AND ORGANIZATIONS There is much experimentation with novel ways of organizing the production and commercialization of recorded music.3 The traditional market for music on physical carriers (for instance, compact discs) has been overtaken recently in terms of revenues by the digital market for music, where end-users access content via the Internet. Within the digital market, the predominant mode of commercializing music online has also changed – from ringtones via downloads to streams and subscriptions. Many Internet-based firms dealing with music have come and, more often than not, gone. It remains to be seen whether and when the digital market will stabilize around a dominant technology. In this context, it becomes harder to describe any typical organization of the music industry. This section identifies general aspects that do remain and, in order to do this, is ordered by main functions in the music industry and describes various organizations that often conduct these functions. Figure 40.1 depicts the main aspects of the chain of production in the music industry, with the essential stages of production in black and optional aspects of the value chain in grey. Caves (2000) distinguishes between creative inputs, the suppliers of which are intrinsically motivated, at least in part, and suppliers of humdrum inputs, which get finished creations to consumers and are reasonably well understood as conventional maximizers of pecuniary rewards. Creative inputs tend to be organized in small and flexible teams. Humdrum inputs are often organized in relatively stable and large organizations. An important challenge in the music industry is to align the incentives of various contributors in a joint production process.

Creation Composers Lyricists Performers

Recording Recording studies

Selection, financing, and coordination of various inputs

Sound engineers

Mainly: Record company

(appointed by creators or record company)

Creative inputs

Also: Music publisher and artist management

Content aggregation

Retailing For physical copies in shops, stores or via mail order

Promotion Often conducted by: - record company - creators - specialist firm - retailers

For digital copies via download or streaming platforms online

Humdrum inputs

Figure 40.1  Main aspects of the music industry value chain

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Music industry  361 The first essential function of the music industry is the creation of new, valuable sound recordings. Many people try their luck at composing or as recording artists, but only a tiny minority ever achieves a substantial income from this activity. Ambitious recordings also require sound engineering.4 Currently, individual creators can, in principle, make musical works available to a wide public on the Internet without much effort. In practice, successful creators virtually always cooperate with specialized intermediaries such as a record label or online music retailing platforms. Creators usually sell most commercially relevant copyrights to publishers (which acquire rights to compositions) and record labels (which acquire rights to recordings). In return, publishers and record labels may help finance the costs of creation; they usually contribute to marketing of sound recordings and may take care of several humdrum functions inhouse. Record labels traditionally play an important role in coordinating various parties along the music industry value chain. The specifics of contracts between music creators and intermediaries are an area that requires much more attention (Towse 2013, 2017). In the traditional music industry, selling copies on physical carriers, some aspects of production are manufacturing processes: there are pressing plants, trucks and bricksand-mortar shops. Expertise is required to predict demand and interface with retailers, to get the right products to the right locations at the right time. In the digital market, the marginal costs of reproduction and dissemination are much lower and converge with retailing (this is why reproduction and distribution do not feature in Figure 40.1). If the trend towards Internet retailing continues, the entire music industry adheres to the logic of information services with negligible marginal costs of reproduction and dissemination. Publishers and record labels tend to have many creators under contract and can exploit economics of scale and scope. Still, even these intermediaries often deal with content aggregators, who bundle up huge repertoires and set standard terms to reduce transaction costs in complex markets. One example are the copyright collectives or copyright management organizations (CMO, such as Germany’s Gesellschaft für musikalische Aufführungs- und mechanische Vervielfältigungsrechte, GEMA, or the American Society of Composers, Authors, and Publishers, ASCAP), which often operate as national monopolies, for instance, for the licensing of compositions for recordings (Handke and Towse 2007; Handke 2014). Other content aggregators that operate across multiple territories are ICE Services or Merlin music, a rights agency representing many independent record labels. Online platforms such as Spotify or YouTube follow a similar logic of standardization, as they jointly market huge repertoires to end-users under a narrow range of terms and conditions for rights holders and music users. Furthermore, deliberate efforts to attract potential users’ attention are a central activity in the music industry. The resources for promoting attention are traditionally an important asset of record labels. Social media provide new opportunities to reach out to, and interact with, users at low costs. Whether record labels, new organizations, or creators themselves are best suited to exploit these opportunities is hard to tell. Furthermore, the recommendation systems on Internet music platforms are also effective means to influence users, and there are probably incentives for platforms to use that to their advantage, for instance, by selling recommendation ranks, similar to notorious payola-practices of radio stations in the past (Coase 1979; Bhattacharjee et al. 2006a). Finally, retailers operate an infrastructure to make music recordings available to endusers, including a payment system. At the moment, music is often made available free to

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362  Handbook of cultural economics end-users via advertising financed online platforms (YouTube or Spotify Free), or users purchase subscriptions with fewer advertisements and enhanced sound quality and other perks (for example, Spotify Premium, Deezer). Offline, retailing is relatively fragmented between many shops and other retail outlets run by various organizations. Online, platforms such as the iTunes store or streaming platforms are highly integrated horizontally among a handful of organizations, which exploit network effects and offer additional services such as recommendation systems, based on user data. There may also be tendency towards vertical integration, with online retailing platforms taking over functions from other intermediaries in the music industry.

TRENDS AND TOPICS IN THE ACADEMIC ECONOMIC LITERATURE Researchers in the academic disciplines of economics, management and business studies have paid increasing attention to the music industry. Figures 40.2 and 40.3 illustrate this based on data from the academic database Scopus, which covers a reasonably comprehensive set of prestigious academic publications. Figure 40.2 plots the total number of journal articles from the Scopus category of business and economics, which prominently feature any of the stemmed terms ‘music industr*’, ‘record* industr*’ or ‘phonogra* industr*’. Only article titles, abstracts and keywords were considered and there were 355 journal articles in total.5 To control for a general expansion of research output covered on databases over time, Figure 40.3 plots the share of these articles in all research articles that feature the definite article ‘the’. Both plots illustrate an upward trend. It is striking that the apparent interest in the music industry increased, as music industry revenues, and thus its contribution to conventional assessments of economic growth declined after 1999. The literature is dispersed over many journals and combinations of academic disciplines; see Table 40.1. For Scopus, the Journal of Cultural Economics is the journal with most articles on the music industry. An efficient method to identify main topics in the economic literature on the music industry is to check how many articles feature terms associated with specific topics. 40 30 20 10

19

17

20

15

20

13

20

11

20

09

20

20

07

05

20

03

20

01

20

99

20

19

97

95

19

93

19

91

19

89

19

19

87

85

19

83

19

19

19

81

0

Note:  Search query: TITLE-ABS-KEY (‘music industr*’ OR ‘record* industr*’ OR ‘phonogra*industr*’) AND DOCTYPE (ar) AND (LIMIT-TO (SUBJAREA, ‘BUSI’) OR LIMIT-TO (SUBJAREA, ‘ECON’)).

Figure 40.2  Number of journal articles on Scopus on the music industry

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Music industry  363 0.6 0.5 ‰

0.4 0.3 0.2 0.1

19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 20 09 20 11 20 13 20 15 20 17 20 19

0

Note:  Absolute numbers as plotted in Figure 40.2 divided by the total number of journal articles featuring the definite article ‘the’ as a proxy for the total number of articles; additional search query for divisors: TITLE-ABS-KEY (‘the’) AND DOCTYPE (ar) AND (LIMIT-TO (SUBJAREA, ‘BUSI’) OR LIMIT-TO (SUBJAREA, ‘ECON’)).

Figure 40.3  Share in per-mille of journal articles on the music industry in virtually all economics and business journal articles on Scopus Table 40.1  The number of articles on the music industry in the six most frequently occurring journals Journal title Journal of Cultural Economics Management Decision Information Economics and Policy Creative Industries Journal Journal of Media Business Studies Review of Industrial Organization

No. of articles

Share in total %

22 14 12 11  6  6

6.2 3.9 3.4 3.1 1.7 1.7

Table 40.2 presents this information for the corpus of works on Scopus as introduced previously. We selected five first-order topics, most of which feature several sub-topics. Covering digitization is a particular challenge, since digital information and communication technology (ICT) is a multi-purpose technology and virtually all related articles focus on specific aspects of it; we therefore also used five sub-topics of digitization: 5(a) to 5(e).6 Overall, these figures provide useful indications of the relative coverage of topics in academic journal articles on the music industry. However, it would be wrong to think of these topics as clearly separated. There is extensive overlap in the set of articles on these topics, and the most cited papers often span several topics. Diversity The music industry is organized in a handful of major intermediaries and a vast number of smaller firms, as well as in even more fragmented creative inputs.7 Diversity of p ­ roducers of music as well as of the music produced and consumed was a predominant topic in sociological research on the music industry in the 1980s up to the early 2000s, usually

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364  Handbook of cultural economics Table 40.2 Economics and business/management articles on the music industry ordered by major themes (on Scopus) Topics All 1 Diversity

Articles 355

Share % 100

First Average age of Search terms(2) article in all articles(1) 1970

9.5

49

13.8

1986

8.3

2 Business models and entrepreneurship   Business models   Entrepreneur(ship)

126

35.5

1991

6.9

71 84

20.0 23.7

2000 1991

5.9 7.2

3 Competition and industry structure   Competition

179

50.4

1982

8.3

146

41.1

1982

8.8

32

9.0

1994

9.3

40 40

11.3 11.3

1994 2008

9.2 4.8

4 Innovation and technological change   Innovation   Technological change

190

53.5

1986

7.6

179 47

50.4 13.2

1986 1990

7.6 7.3

5 Digitization in general   Internet   Digital   5(a)  Digital retailing      Streaming      e-retailing

253 214 201 100 42 77

71.3 60.3 56.6 28.2 11.8 21.7

1987 1998 1987 1999 2000 1999

7.6 7.7 7.3 6.7 4.8 7.2

  5(b)  Copyright and unauthorized copying      Unauthorized copying

214

60.3

1984

8.2

178

50.1

1990

7.8

     Copyright      DRM

147 55

41.4 15.5

1984 2000

8.6 7.2

46

13.0

2008

4.2

7 3

2.0 0.8

2014 2017

1.7 0.7

19

5.4

1970

15.2

   Industry structure or     market structure   Superstars   Long-tail(3)

  5(c)  Social media

  5(d)  Crowdfunding   5(e)  Blockchain None of the above

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divers*

‘business* model*’ entrepreneur*

competi*, contestab*, monopol*, ‘market power’, collu*, cartel* ‘industr* structure*’, ‘market* structure*’ superstar* ‘long-tail’, longtail, ‘long tail’

innovat* ‘technological change*’ Internet, online digit* stream* itunes, spotify, deezer, subscription*, eretailing, ‘e-retailing’, ecommerce, ‘e-commerce’, ‘digital sales’, ‘digital market’, ‘sales online’, ‘internet sales’ copying*, pira*, p2p, peer, fileshar*, ‘file-shar*’, ‘file shar*’ copyright* ‘*right* management’, DRM, ‘protection measures’, ‘copy* protect*’, TPM ‘social media’, facebook, twitter, youtube, Instagram, snapchat, soundcloud, bandcamp, vine, periscope, ‘musical.ly’, myspace, ‘last.fm’ crowdfund* blockchain* All additional search terms excluded

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Music industry  365 Table 40.2 (continued) Notes: Initial search query: TITLE-ABS-KEY (‘music industr*’ OR ‘record* industr*’ OR ‘phonogra* industr*’) AND DOCTYPE (ar) AND (LIMIT-TO (SUBJAREA, ‘BUSI’) OR LIMIT-TO (SUBJAREA, ‘ECON’)). (1) In years in 2019, up to 30 April 2019. (2) All connected with OR; first-order topics feature all search terms of sub-topics. (3) Also a sub-topic of digitization.

in conjunction with industry structure (for example, Rothenbuhler and Dimmick 1982; Lopes 1992; Peterson and Berger 1996). The issue is less central in the recent economics literature. However, diversity and quality of music produced is highly relevant in welfare economic assessments of technological change and copyright. Business Models and Entrepreneurship Business models and entrepreneurship are miscellaneous topics to do with strategic management, organizational innovation and adaptation to (changes in) business environments. They are generally covered in conjunction with one of the other topics. See, for instance, Oestreicher-Singer and Zalmanson (2013) on music industry business models, social media and online retailing, Mason and Spring (2011) on business models and technological change in general, or Wilson and Stokes (2005) on cultural entrepreneurship in the music industry. Competition and Industry Structure This topic is more focused on entire industries rather than individual firms, and closely associated with diversity. Papers on competition and music industry structure predominantly address effects of specific aspects of technological change. In the past, a number of articles proposed that digitization tends to upset incumbent large firms, facilitates entry and fosters competition (Alexander 2002; Bockstedt et al. 2006). On the level of creators, superstar effects are a classic topic in cultural economics and in studies on music creators’ success (Chung and Cox 1994; Hamlen 1994). Of late, many studies have tested the long-tail hypothesis that owing to lower storage and search costs online, the demand for creative works would become less concentrated on a few hits than offline (Gaffney and Rafferty 2009; Dewan and Ramaprasad 2012). Empirical investigations have yielded nuanced results (Bhattacharjee et al. 2007; Dewan and Ramaprasad 2014). At the time of writing, it is far from clear whether the music industry is becoming more or less concentrated in the course of digitization. Innovation and Technological Change It makes little sense to discuss this topic separately from digitization. In principle, innovation and technological change could have other meanings and these terms are associated with the innovation economics specialization. In practice, however, virtually all articles discuss digitization (for example, Handke 2006; Moreau 2013).

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366  Handbook of cultural economics Digitization in General Over 70 percent of all music industry articles feature either the terms ‘Internet’ or ‘digit*’.8 Digitization is central in the literature. The multi-purpose technology of digital ICT has many different aspects that are virtually never discussed as a whole. We thus also separately report on different aspects. Digital Retailing Perhaps surprisingly, authorized digital retailing of music yields many fewer articles than dissemination by unauthorized copying. This may in part be owing to the availability of useful search terms. It may also reflect the curious development of the digital market for recorded music, where for a while, unauthorized dissemination services such as the early Napster were much more technically efficient than anything the proper music industry offered its customers. Highly cited papers on digital retailing include a formal-theoretical paper by Thomes (2013) regarding industry structure and displacement of piracy, as well as an empirical paper by Wlömert and Papies (2016) concerning Spotify and music industry revenues. Current online retailers offer additional services, for instance, recommendation systems and means for users to interact with each other. They also gather and analyze extensive information on music users (big data), which is a valuable commodity and deserves more attention. Furthermore, there is an intense debate on the potential market power of Internet platforms. A novel theoretical framework in which to address online retailing platforms is the theory of two-sided/multi-sided platforms (Armstrong 2006; Rysman 2009; Thomes 2013). Unauthorized Copying, Copyright and Digital Rights Management A majority of articles prominently feature terms associated with this topic. The literature largely consists of efforts to establish and gauge causal effects of piracy online on record industry revenues; for literature reviews, see Towse et al. (2008) or Watson et al. (2015). A few studies discuss the consequences of copyright enforcement measures (Bhattacharjee et al. 2006b; Adermon and Liang 2014; Danaher and Smith 2014). So far, affordable authorized streaming services seem to be more effective in containing unauthorized copying (Aguiar and Waldfogel 2018) but raise low revenues to creators and rights holders. Less work has been dedicated to alternative solutions, an exception being Handke et al. (2016) on copying levies. From a welfare economics perspective that tries to inform public copyright policy, it is essential to also take the position of users into account (Rob and Waldfogel 2006) and to consider the effects on the supply on new valuable music (Handke 2012; Waldfogel 2017). Social Media Owing to the experience attributes of music, new modes of gathering information and communicating about music could substantially improve efficiency (Gaffney and Rafferty 2009; Dewan and Ramaprasad 2014; Saboo et al. 2016). Furthermore, from a cultural economics perspective, intrinsic motivation to engage with creative activities could help

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Music industry  367 better explain the role of social media in the evaluation of music, as well as the noncommercial supply of music (user-generated content). It is hard to find any economics literature on these issues and the music industry. Crowdfunding and Blockchain Finally, at the time of writing there are two up-and-coming issues with a couple of very recent articles. Crowdfunding is a means to raise upfront finance from a broader public (Galuszka and Bvstrov 2014; Gamble et al. 2017; see also Chapter 17 in this volume). Even more recently, articles on the application of blockchain technology have started to appear (O’Dair and Owen 2019). This technology might come to be used for all types of transactions in the music industry, for creating a registry of works, smart licensing and monitoring of use, conducting (micro-) payments and enforcing copyrights. It remains to be seen whether blockchain technology can shape the future of the music industry, perhaps even establish the frictionless and highly competitive market that was once expected in the earlier stages of digitization but has failed to transpire thus far.

SUMMARY AND OUTLOOK Paradoxically, the interest of economists in the music industry has increased as the industry experienced a decline in financial terms. The central theme in the literature is technological change in the course of digitization. In some respects, the literature has gone full circle. It went from visions of more competitive and efficient markets online to concerns about the market power of digital retailers, as well as hardship for creators and traditional parts of the industry, and now new hopes concerning blockchain technology. Empirical studies of the music industry have brought up some puzzling results. Even though music industry revenues are much lower than in the past, indications are that the variety and quality of new music supplied has not suffered. In spite of falling costs in the music industry and initial long-tail effects of digitization, the contemporary music industry seems as dominated by superstars and central intermediaries (online platforms in addition to the remaining major record labels) as ever. The most puzzling aspect of the music industry, however, is the variability and constant mutation of how it is organized. It is an exciting and challenging time for anyone involved in the music industry and there is much demand for useful new insights. Things are moving so quickly that it is hard for anyone to keep up – and that includes academic researchers. The boundaries between the professional music industry and intrinsically motivated, user-generated activities are more blurry than ever. The copyright system goes from one revision to another – for instance, to increase the liability of Internet platforms for unauthorized copying by their users in the European Union. Crowdfunding and blockchain technology are heralded as novel solutions to longstanding challenges. Big data and artificial intelligence may even come to question the pre-eminence of human labor in the process of creating music (Peukert 2018). The expertise of cultural economists with regard to the idiosyncrasies of cultural industries should be very valuable in this context, if they manage to stay up to date.

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368  Handbook of cultural economics

NOTES 1. Baumol’s cost disease is a less salient issue because of intrinsic motivation to create and because the production and dissemination of recorded music is not as labor-intensive as in the traditional performing or visual arts. 2. Regarding physical copies, only revenues from vinyl record sales have increased since 2006 but make up a tiny fraction of the total. 3. See Varian (2005) for a comprehensive list of options how to market music in spite of its characteristics as a public good. 4. Among creators, there is a trade distinction between composers (as well as lyricists) and performers/ recording artists, which is applied in accounting processes regardless of whether for a specific recording, composers and performers are the same individuals. 5. All data was collected between 15 April and 30 April 2019. We have to rely on the classification of articles into research areas by Scopus. Many articles are classified into more than one research areas. 6. We could quibble over the selection of Boolean search terms, and we cannot exclude that there are other topics frequently addressed in this literature. However, we also checked the word count for the corpus, using atlas.ti, and found no indication of major omissions. Furthermore, almost 95 percent of all articles feature one or several of the topical search terms covered in Table 40.2. 7. The identification of articles on independents and majors – conventional expressions for the firms of different sizes in the recorded music industry – did not work since the two words and any stemmed version of them had too many unrelated meanings frequently found in the articles. 8. In Boolean searches, the asterisk includes all extensions of a word: here, for instance, ‘digital’, ‘digitization’, ‘digitalization’, and so on.

SEE ALSO: Chapter 14: Creative industries; Chapter 26: Digitization in the cultural industries; Chapter 41: Music publishing.

REFERENCES Adermon, A. and C.-Y. Liang (2014), ‘Piracy and music sales: the effects of an anti-piracy law’, Journal of Economic Behavior and Organization, 105 (September), 90–106. Aguiar, L. and B. Martens (2016), ‘Digital music consumption on the internet: evidence from clickstream data’, Information Economics and Policy, 34 (March), 27–43. Aguiar, L. and J. Waldfogel (2016), ‘Even the losers get lucky sometimes: new products and the evolution of music quality since Napster’, Information Economics and Policy, 34 (March), 1–15. Aguiar, L. and J. Waldfogel (2018), ‘As streaming reaches flood stage, does it stimulate or depress music sales?’, International Journal of Industrial Organization, 57 (March), 278–307. Alexander, P.J. (2002), ‘Peer-to-peer file sharing: the case of the music recording industry’, Review of Industrial Organization, 20 (2), 151–61. Armstrong, M. (2006), ‘Competition in two-sided markets’, RAND Journal of Economics, 37 (3), 668–91. Bhattacharjee, S., R.D. Gopal, K. Lertwachara and J.R. Marsden (2006a), ‘Whatever happened to payola? An empirical analysis of online music sharing’, Decision Support Systems, 42 (1), 104–20. Bhattacharjee, S., R.D. Gopal, K. Lertwachara and J.R. Marsden (2006b), ‘Impact of legal threats on online music sharing activity: an analysis of music industry legal actions’, Journal of Law and Economics, 49 (1), 91–114. Bhattacharjee, S., R.D. Gopal, K. Lertwachara, J.R. Marsden and R. Telang (2007), ‘The effect of digital sharing technologies on music markets: a survival analysis of albums on ranking charts’, Management Science, 53 (9), 1359–74. Bockstedt, J.C., R.J. Kauffman and F.J. Riggins (2006), ‘The move to artist-led on-line music distribution: a theory-based assessment and prospects for structural changes in the digital music market’, International Journal of Electronic Commerce, 10 (3), 7–38. Caves, R.E. (2000), Creative Industries: Contracts Between Art and Commerce, Cambridge, MA: Harvard University Press.

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Music industry  369 Chung, K.H. and R.A.K. Cox (1994), ‘A stochastic model of superstardom: an application of the Yule distribution’, Review of Economics and Statistics, 76 (4), 771–5. Coase, R.H. (1979), ‘Payola in radio and television broadcasting’, Journal of Law and Economics, 22 (2), 269–328. Danaher, B. and M.D. Smith (2014), ‘Gone in 60 seconds: the impact of the Megaupload shutdown on movie sales’, International Journal of Industrial Organization, 33 (March), 1–8. Danaher, B., S. Dhanasobhon, M.D. Smith and R. Telang (2010), ‘Converting pirates without cannibalizing purchasers: the impact of digital distribution on physical sales and internet piracy’, Marketing Science, 29 (6), 1138–51. Dewan, S. and J. Ramaprasad (2012), ‘Music blogging, online sampling, and the long tail’, Information Systems Research, 23 (3), 1056–67. Dewan, S. and J. Ramaprasad (2014), ‘Social media, traditional media, and music sales’, MIS Quarterly, 38 (1), 101–21. Dolfsma, W. (2000), ‘How will the music industry weather the globalization storm?’, First Monday, 5 (5), doi:10.5210/fm.v5i5.745. Gaffney, M. and P. Rafferty (2009), ‘Making the long tail visible: social networking sites and independent music discovery’, Program, 43 (4), 375–91. Galuszka, P. and V. Bystrov (2014), ‘Crowdfunding: a case study of a new model of financing music production’, Journal of Internet Commerce, 13 (3–4), 233–52. Gamble, J.R., M. Brennan and R. McAdam (2017), ‘A rewarding experience? Exploring how crowdfunding is affecting music industry business models’, Journal of Business Research, 70 (January), 25–36. Hamlen, W.A. Jr (1994), ‘Variety and superstardom in popular music’, Economic Inquiry, 32 (3), 395–406. Handke, C. (2006), ‘Plain destruction or creative destruction? Copyright erosion and the evolution of the record industry’, Review of Economic Research on Copyright Issues, 3 (2), 29–51. Handke, C. (2010), ‘The creative destruction of copyright – innovation in the record industry and digital copying’, PhD dissertation, Erasmus University Rotterdam, accessed 6 July 2019 at http://ssrn.com/abstract=163034. Handke, C. (2011), ‘Economic effect of copyright: the empirical evidence so far’, report for the National Academies of the Sciences, Washington, DC. Handke, C. (2012), ‘Digital copying and the supply of sound recordings’, Information Economics and Policy, 24 (1), 15–29. Handke, C. (2014), ‘The economics of collective copyright management’, in R. Watt (ed.), Handbook of the Economics of Copyright, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 179–204. Handke, C. (2015), ‘Digitization and competition in copyright industries: one step forward and two steps back?’, Homo Oeconomicus, 32 (2), 209–36. Handke, C. and R. Towse (2007), ‘Economics of copyright collecting societies’, International Review of Intellectual Property and Competition Law, 38 (8), 937–57. Handke, C., B. Balazs and J.-J. Vallbé (2016), ‘Going means trouble and staying makes it double: the value of licensing recorded music online’, Journal of Cultural Economics, 40 (3), 227–59. Harrison, A. (2017), Music: The Business, London: Virgin. Herstand, A. (2016), How to Make It in the New Music Business: Practical Tips on Building a Loyal Following and Making a Living as a Musician, London: Liveright. International Federation of the Phonographic Industry (IFPI) (2017), ‘Global music report’, IFPI, London, accessed 10 July 2019 at https://www.ifpi.org/downloads/GMR2017.pdf. International Federation of the Phonographic Industry (IFPI) (2019), ‘Global music report’, IFPI, London, accessed 10 July 2019 at https://www.ifpi.org/downloads/GMR2019.pdf. Krueger, A. (2019), Rockonomics: What the Music Industry Can Teach Us about Economics (and Our Future), London: John Murray. Lacher, K.T. and R. Mizerski (1994), ‘An exploratory study of the responses and relationships involved in the evaluation of, and in the intention to purchase new rock music’, Journal of Consumer Research, 21 (2), 366–80. Liebowitz, S. (2013), ‘Internet piracy: the estimated impact on sales’, in R. Towse and C. Handke (eds), Handbook on the Digital Creative Economy, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, 262–73. Lopes, P.D. (1992), ‘Innovation and diversity in the popular music industry, 1969 to 1990’, American Sociological Review, 57 (1), 56–71. Mason, K. and M. Spring (2011), ‘The sites and practices of business models’, Industrial Marketing Management, 40 (6), 1032–41. Moreau, F. (2013), ‘The disruptive nature of digitization: the case of the recorded music industry’, International Journal of Arts Management, 15 (2), 18–31. Nelson, P. (1970), ‘Information and consumer behavior’, Journal of Political Economy, 78 (2), 311–29. O’Dair, M. and R. Owen (2019), ‘Monetizing new music ventures through blockchain: four possible futures?’, International Journal of Entrepreneurship and Innovation, 20 (4), 263–76.

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370  Handbook of cultural economics Oestreicher-Singer, G. and L. Zalmanson (2013), ‘Content or community? A digital business strategy for content providers in the social age’, MIS Quarterly, 37 (2), 591–616. Passman, D.S. (2015), All You Need to Know about the Music Business, New York: Simon and Schuster. Peterson, R.A. and D.G. Berger (1975), ‘Cycles in symbol production: the case of popular music’, American Sociological Review, 40 (2), 158–73. Peterson, R.A. and D.G. Berger (1996), ‘Measuring industry concentration, diversity, and innovation in popular music’, American Sociological Review, 61 (1), 175–8. Peukert, C. (2018), ‘The next wave of digital technological change and the cultural industries’, Journal of Cultural Economics, 43 (2), 189–210. Rob, R. and J. Waldfogel (2006), ‘Piracy on the high C’s: music downloading, sales displacement, and social welfare in a sample of college students’, Journal of Law and Economics, 49 (1), 29–62. Rothenbuhler, E.W. and J.W. Dimmick (1982), ‘Popular music: concentration and diversity in the industry, 1974–1980’, Journal of Communication, 32 (1), 143–9. Rysman, M. (2009), ‘The economics of two-sided markets’, Journal of Economic Perspectives, 23 (3), 125–43. Saboo, A.R., V. Kumar and G. Ramani (2016), ‘Evaluating the impact of social media activities on human brand sales’, International Journal of Research in Marketing, 33 (3), 524–41. Thomes, T.P. (2013), ‘An economic analysis of online streaming music services’, Information Economics and Policy, 25 (2), 81–91. Towse, R. (2013), ‘The economic effects of digitization on the administration of musical copyrights’, Review of Economic Research on Copyright Issues, 10 (2), 55–67. Towse, R. (2017), ‘Economics of music publishing: copyright and the market’, Journal of Cultural Economics, 41 (4), 403–20. Towse, R., C. Handke and P. Stepan (2008), ‘The economics of copyright law: a stocktake of the literature’, Review of Economic Research on Copyright Issues, 5 (1), 1–22. Tschmuck, P. (2006), Creativity and Innovation in the Music Industry, Amsterdam: Springer. Varian, H.R. (2005), ‘Copying and copyright’, Journal of Economic Perspectives, 19 (2), 121–38. Waldfogel, J. (2012), ‘Copyright protection, technological change, and the quality of new products: evidence from recorded music since Napster’, Journal of Law and Economics, 55 (4), 715–40. Waldfogel, J. (2017), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214. Waldfogel, J. (2018), Digital Renaissance: What Data and Economics Tell Us about the Future of Popular Culture, Princeton, NJ: Princeton University Press. Watson, S.J., D.J. Zizzo and P. Fleming (2015), ‘Determinants of unlawful file sharing: a scoping review’, PLoS One, 10 (6), e0127921. Wikström, P. (2013), The Music Industry: Music in the Cloud, Cambridge: Polity Press. Wilson, N.C. and D. Stokes (2005), ‘Managing creativity and innovation: the challenge for cultural entrepreneurs’, Journal of Small Business and Enterprise Development, 12 (3), 366–78. Wlömert, N. and D. Papies (2016), ‘On-demand streaming services and music industry revenues – insights from Spotify’s market entry’, International Journal of Research in Marketing, 33 (2), 314–27.

FURTHER READING The economic literature on the music industry is dispersed over a wide range of articles and many other academic disciplines have produced valuable insights. There are also a number of book publications featuring hands-on advice for practitioners. Anyone seeking a detailed understanding of current businesses practices in the music industry will find the latest editions of such books useful, for instance: Passman (2015), Herstand (2016) and Harrison (2017). An academic account of developments in the music industry through the second half of the twentieth century is Tschmuck (2006); Wikström (2013) covers later developments. Recent publications with a broad scope regarding the music industry by outstanding US economists are Waldfogel (2017, 2018) and Krueger (2019).

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41.  Music publishing* Ruth Towse

There has been little economic research on music publishing, although until the advent of sound recording it was the main component of what is now called the music industry. Together with fees from live performance, sales of printed music were the main source of income for composers, songwriters and publishers until the early years of the twentieth century. Sales now constitute a relatively small proportion of the total revenues of music publishing, having been eclipsed by the shift to the licensing of musical rights. Those rights required adaptation to the new technologies of sound recording and later radio which hugely expanded the public’s access to music and quickly displaced live performance. That adaptation involved changes both to copyright law and to the business models of music publishers. The process that took place over the early decades of the twentieth century, however, was difficult and required time for new institutional arrangements for obtaining income for publishers, composers and songwriters to be accepted and to work. The transition has been echoed to an extent in the twenty-first century as the sound-recording industry adapted to electronic distribution, especially by streaming. It is worth noting in this context that piracy of printed music in different genres – opera, popular song or instrumental – and now a feature of digital recording and distribution, was already rife throughout the eighteenth and nineteenth centuries, and was almost accepted as a way of life despite many attempts to curb it through changes to and enforcement of copyright law. Nevertheless, there has been research relating to music publishing, often historical, on income from musical composition (Peacock and Weir 1975; Baumol and Baumol 1994; Scherer 2004), on the development of collective licensing in the UK (Ehrlich 1989) and on composers’ relationship with their publishers (Montgomery and Threlfall 2007; Drysdale 2013) and the absence of academic research is partly compensated by increasing online publication of data and the discussion of the relative earnings in the music industry from music publishing and sound recording. This chapter is based on Towse (2017), which used these sources as well as original research.

SOURCES OF REVENUE Before the widespread adoption of the phonogram and sound recording, music p ­ ublishers’ revenues came almost entirely from the sale of printed music. Songs were by far the greater part of their trade and by the last half of the nineteenth century, ownership of pianos in the home had become widespread and music for home performance popular and profitable (Ehrlich 1976). An early form of advertising songs was to have itinerant salesmen of printed songs sing their wares on street corners, while a more sedentary means of advertising piano music was to have it performed in the music publisher’s shop. In the eighteenth century, opera provided a source of printed songs for popular use, although opera scores and music were not on sale; nowadays, they are usually rented by the opera 371

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372  Handbook of cultural economics company from the publisher. Musical societies offered occasional performances, mostly of new music, and by the mid-nineteenth century, music halls had become the places of popular entertainment with published songs being promoted by performers for a fee (known as a royalty) to encourage sales for home entertainment. A few music publishers promoted their own concerts, that is, concerts performing their published music, by way of advertisement. By the mid-nineteenth century the author’s right to control live public performance of his or her work in concerts and in music halls (and later in broadcasts) had become recognised in copyright law, requiring the development of collaborative rights management by copyright management organisations (CMOs), often known as collecting societies, to administer the rights (Peacock and Weir 1975; Ehrlich 1989). Copyright management organisations now operate in other areas of the creative industries too, but they originated with practice in musical performance in France that later spread throughout Europe (and now the world). In music publishing these institutions are membership societies of composers, songwriters and music publishers that collectively administer public performance rights and mechanical rights by licensing and collecting royalties for their works and enforcing them on behalf of their members. Although the performing right was on the statute books in the UK and had been for some time, there was no arrangement until 1914 for collecting royalties from performances in the UK other than via music publishers, although the Société des auteurs, compositeurs et éditeurs de musique (SACEM) did so in France throughout the nineteenth century and managed rights of the performance of French music in the UK from the 1850s. British music publishers, however, resisted exercising the right as they believed it would put off performers, who effectively advertised their published music through live performances in music halls, churches and other venues, as they would have to pay for the right to perform it. They were locked into a business model of revenue from sales and adapted it only when new streams of income in the form of public performance and mechanical rights from sound recording, broadcasting and film became available – very much the approach taken by the sound recording industry in the late twentieth century in the face of digital piracy, as it clung to its sales model in the face of new ways of accessing music. Sound recording was a profound threat to the music publishers’ business model.1 Instead of relying on live performance in concerts and music halls or in the home, which required purchasing printed music, music lovers could now entertain themselves by listening to professional performances on the gramophone. Once copyright law had been adapted to the new technologies with the introduction of the mechanical right, though, collecting societies were formed whose role was to license and collect royalties from soundrecording makers so that composers and music publishers were able to realise revenues from the use of their music in sound recordings. Radio broadcasts of recorded music followed suit: the story of the relationship between the music industry and broadcasters, such as the BBC in the UK, was complex (see Peacock and Weir 1975). Television then followed as a source of royalties for the use of live and recorded music. The invention of cinema also provided a new source of revenue to music publishers, initially from the live performance of music, both accompanying film and with entertainment on the Hammond organ during the interval between films (which continued long after the invention of the ‘talkies’), and later from the synchronisation of music with the motion picture. Currently, some music publishers specialise in production or library

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Music publishing  373 music for use in audio-visual works in film, video, television programmes and games, with revenues from the so-called synchronisation right (an adaptation of the mechanical right) as the source of income. Table 41.1 shows that music publishing contributed nearly half of the total sources of world revenues from music in 2017, for which the performing right was by far the main source. Revenue from the mechanical right has fallen as sales of sound recordings declined. Direct licensing includes sales of printed music and synchronisation and grand rights (the latter for live performances of musicals and opera). Table 41.2 shows the relative roles of the various sources of revenues to music publishers in the UK: in classical music, sales and hires of published scores constitute two-thirds of Table 41.1  Global value of music copyright 2017, US$ billion Sound recording (record labels) Song-writer CMOs Music publisher direct revenues Total

$16.55 $9.37 $2.20 $28.10

Split: publishers 41 per cent and labels 59 per cent

Percentage of song-writing and music publishing revenues by underlying right* Performing right Mechanical right Private copying Direct licensing

67% 15% 3% 15%

Note:  * My calculations from Page’s 2014 data. Sources:  www.musicbusinessworldwide.com/the-global-value-of-music-copyright-topped-28bn-in-2017/ (accessed 8 December 2019); Will Page at www.musicbusinessworldwide.com/25-billion-the-best-number-tohappen-to-the-music-business/ (accessed 8 December 2019).

Table 41.2  Percentage of UK music publishing revenues from various rights and sources by genre 2012 Genre Popular music Mechanical royalties Live performance and broadcasting Synchronisation fees Other (ring tones, online, sheet music) Classical music Sales of printed music Hire fees Mechanical royalties Live performance and broadcasting Synchronisation fees Other

Percentage 40 36 14 10 50 15 12  8  5  5

Source:  Music Publishers Association (unpublished).

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374  Handbook of cultural economics revenues while in popular music (by far the larger sector), mechanical and synchronisation royalties account for three-quarters of all revenues.

MUSIC PUBLISHERS AS INTERMEDIARIES Music publishers act as intermediaries in the various markets for musical works, exercising rights contracted to them by composers and songwriters. Creators of songs and of other forms of music have the copyright in their works: songs fall into two categories with lyrics as literary works and the tunes as musical works, but they are also treated as a single work of joint authorship if words and music were written together.2 Copyright protects composers and songwriters from copying by others without their consent, enabling them to control the use that is made of their works and to contract with music publishers and others for their dissemination. Not all music is published, though; music commissioned for use in audio-visual works may be contracted by the composer directly with the film or other such producer. The traditional business model of the publisher was to acquire the rights of a song or other musical work, have it printed by a specialist music printer and then sell or license the printed music. In the case of orchestral works and instrumental music for ensembles, the parts for each instrument require specialised printing according to the item in question as there are conventions about how the score is written (for example, in different clefs for different instruments); orchestral parts are printed for each individual instrument with a copy of the whole score for the conductor; choral and operatic works for singers with orchestra are printed with a piano score or even simply as the individual vocal line. Some of these are sold directly to amateur and professional performers, others are purchased by the performing group or hired from the publisher; major orchestral works with many parts are usually stored by the publisher and hired out for the performance. Before the advent of computers and software that currently deal with the technical requirements of putting a score together, composers produced their work in manuscript either with parts sketched out or with just a piano score, giving rise to work for copyists who prepared the musical score for printing. These days many composers and songwriters can produce a printed score themselves thus removing the role of organising the printing from that of publication. Accordingly, music publication is now mainly concerned with acquiring and managing rights and arranging deals with users of music. Sub-Publishing Copyright underlies the management of rights but as it is national law, arrangements have to be made to license uses and obtain royalties in different jurisdictions. In music publishing this is typically achieved through contracts with foreign sub-publishers, which often result in different splits of royalties for the respective parties. A composer may have a 50:50 deal with the first publisher who then makes a deal with a foreign publisher for 60:40 (the latter to the composer). These mandates, as they are named, cause complications for CMOs managing rights and for deals made along the chain of production, as well as making it difficult to track royalties due.

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Music publishing  375

CONTRACTS IN MUSIC PUBLISHING Throughout the nineteenth century and into the early twentieth century in the UK, the standard contract in music publishing was a buy-out of all rights for a single payment; this is still required for synchronisation, although the composer retains the performing right or his or her share of it. Even after royalty contracts had become the norm (circa the 1920s in the UK) publishers often required the assignment of all rights from the composer or songwriter for the life of the copyright, sharing performing right royalties registered with the CMO on a 50:50 basis. Now there are various types of music publishing contracts in use; a single-song contract requires the assignment of the copyright for one work; an exclusive contract deal links the composer or songwriter (known as the writer) and publisher in a long-term relationship in which the writer agrees to assign all his or her works (which might, for instance, include commissions) to the publisher; or a co-publishing deal with the writer as publisher (for details, see Harrison 2011). These contracts are royalty deals whereby the publisher shares revenues from the song with the writer(s) and may provide an advance on royalties. Other contracts do not necessitate assigning the rights to the publisher, who can act as agent with a licence, for example, as in an administration contract. Whichever type is adopted, the publishing contract sets out the rights being transferred from the composer or songwriter to the publisher, the royalty rate, the term of the contract (how many years it lasts), any advance on future royalties and so on, and the territory covered, which would usually be worldwide. There are also so-called 360 contracts, which cover all aspects of a composer’s, songwriter’s or band’s activities, including concerts, merchandise and so on. The royalty rate to the writer varies according to the deal made between the parties: in the US, the publisher’s share was traditionally 50 per cent of the revenue from sales; in the UK up to the 1920s it was one-third each to the lyricist, composer and music publisher, but that changed when the US model was adopted. Another change is that songs are now typically written by teams of writers rather than individuals so that the payments to songwriters have to be split in multiples, depending on the number of individuals and the deals made between them (Osborne 2015). With changes in the uses of music, these shares can be different in different markets and in sub-publishing deals. The performing right is the most valuable of musical rights and is usually assigned or licensed to a performing right CMO – the American Society of Composers, Authors, and Publishers (ASCAP, USA), Gesellschaft für musikalische Aufführungs- und mechanische Vervielfältigungsrechte (GEMA, Germany), Japanese Society for Rights of Authors, Composers and Publishers (JASRAC, Japan), Performing Right Society (PRS, UK), SACEM (France), STIM (Sweden), and so on, to which composers, songwriters and publishers belong. The CMO administers the right in its territory and has arrangements with foreign CMOs for mutual collection and sharing of revenues and enforcement of the right. Traditionally, CMOs adopted blanket licensing as their business model and this is still in use, for example, in the UK between the BBC (the largest user of music) and PRS. The licence from the CMO entitles users to perform any of the works in the repertoire it controls, the revenues from which it then distributes to the writer and the publisher on a 50:50 split basis in accordance with the use made of their works. Large-scale users are required to report lists of the works they performed, while smaller-scale use is estimated by the CMO. Blanket licensing was universally adopted as a means of reducing transaction

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376  Handbook of cultural economics costs for both rights owners and users by CMOs. Digital distribution of music has made individual rights management feasible, although streaming and publishing agreements still tend to utilise blanket licensing.

CHANGING ECONOMICS OF MUSIC PUBLISHING The impact of digital recording and distribution affected music publishers less than the record industry, but they experienced a steep decline in mechanical royalties which so far have not been compensated by streaming revenues (although that tide is turning). Music publishers hold a stock of long-term assets based on assignment of copyright by writers for 70 years after their death. Most works produce little revenue after initial publication, but a few superstar titles can have a very long shelf life and capacity to earn (Towse 2016, 2017). Structure of the Industry Music publishing has a history of ever-increasing concentration: in the nineteenth century there were hundreds of music publishing companies, although a few increasingly large ones began to dominate the market, but by the twenty-first century three major companies – SonyATV (claiming leadership with 3 million copyrights),3 Universal Music Publishing International Group, and Warner Chappell Music Group formed a worldwide oligopoly. These dominant conglomerates own many publishing houses operating under their own names, as well as many record labels, and control catalogues in classical, pop, rock, jazz, and so on, as well as production music. They have been subject to scrutiny by national competition authorities and the European Commission for both horizontal and vertical integration.4 Economies of scale and scope and network economies apparently drive the mergers and acquisitions that have taken place over the past few decades in music publishing, in which large bundles of copyright assets are transferred between owners. Nevertheless, there are new entries and smaller independent music publishers that are able to survive in the market by signing talented artists, offering better services to them and being in niche markets of less popular genres. A prominent example is Kobalt Music, which has adopted a business model of acting primarily as an administrative publishing company instead of owning the copyright, and there are many smaller independent publishers. The Internet has benefited music publishers by reducing the risk and uncertainty of investing in new writers whose track record of ratings provides prior information on the potential market. Digital publication, which has removed the costs of printing and storing printed copies, has enabled publishers to offer more favourable deals to writers.

CONCLUSION Music publishing was one of the major creative industries of the nineteenth century that was subject to the shock of the new technologies of sound recording and radio in the early decades of the twentieth century, resulting in the decline of sales of printed music.

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Music publishing  377 Adaptation of copyright law and the development of CMOs changed the business model from sales of printed music to management of musical rights. Music publishing was less vulnerable to the impact of digital distribution owing, in part, to its ownership of back catalogues and the longer copyright term, but mechanical royalties declined sharply with the fall in sales of sound recordings. Performing right revenues dominate sources of income for music publishers. There have been major changes in CMOs as they adapt to streaming and management of individual rights with the development of conglomerates of national CMOs. The industry experienced a dramatic trend to concentration during the twenty-first century, with music publishing becoming part of large international oligopolistic corporations in which it occupies only a relatively small part of their total business.

NOTES * 1. 2. 3. 4.

I gratefully acknowledge advice from Dr Richard Osborne of Middlesex University on the data and on other aspects in this chapter. An interim mechanical technology was the pianola which also disrupted the sales model. For an accessible account of rights in songs, see www.copyrightuser.org/create/creative-process/going-fora-song/ (accessed 6 December 2019). On works of joint authorship, see Osborne (2015). www.sonyatv.com/en (accessed 4 December 2019). For example, the SonyATV takeover of the EMI catalogue. See http://ec.europa.eu/competition/mergers/ cases/decisions/m8989_610_7.pdf (accessed 4 December 2019).

SEE ALSO: Chapter 11: Contract theory and information goods; Chapter 14: Creative industries; Chapter 40: Music industry; Chapter 43: Orchestras; Chapter 51: Publishing.

REFERENCES Baumol, W. and H. Baumol (1994), ‘On the economics of musical composition in Mozart’s Vienna’, Journal of Cultural Economics, 18 (3), 171–98. Cooke, C. (2018), Dissecting the Digital Dollar, 2nd edn, London: UK Music Managers Forum. Drysdale, J. (2013) Elgar’s Earnings, Woodbridge: Boydell Press. Ehrlich, C. (1976), The Piano: A History, Oxford: Clarendon. Ehrlich, C. (1989), Harmonious Alliance: A History of the Performing Right Society, Oxford: Oxford University Press. Harrison, A. (2011), Music: The Business, 5th edn, London: Virgin Books. Montgomery, R. and R. Threlfall (2007), Music and Copyright: The Case of Delius and His Publishers, Aldershot, UK and Burlington, VT: Ashgate. Osborne, R. (2015), ‘“That’s the joint”: the harmonisation of words and music in EU law’, accessed 5 December 2019 at https://www.academia.edu/people/search?utf8=%E2%9C%93&q=Osborne%2C+R.+%282015%29%2 C+%E2%80%98That%E2%80%99s+the+joint.+The+harmonisation+of+words+and+music+in+EU+Law% E2%80%99%2C+. Peacock, A. and R. Weir (1975), The Composer in the Marketplace, London: Faber. Scherer, F. (2004), Quarter Notes and Banknotes, Princeton, NJ: Princeton University Press. Towse, R. (2016), ‘Copyright auctions and the asset value of a copyright work’, Review of Economic Research on Copyright Issues, 13 (2), 83–99. Towse, R. (2017), ‘Economics of music publishing: copyright and the market’, Journal of Cultural Economics, 41 (4), 403–20.

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378  Handbook of cultural economics

FURTHER READING There is little recent academic writing on music publishing apart from the works cited in the text. There are, however, many popular manuals for practitioners which provide a good deal of information on music publishing, especially dealing with digitisation, of which Cooke (2018) is an excellent example. A very accessible source is ‘Going for a Song’ one of the copyright user series (www.copyrightuser.org/create/creative-process/ going-for-a-song/, accessed 6 December 2019), which explains the role of copyright in the process of writing and recording a song.

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42.  Non-profit organizations* Dick Netzer

In all rich countries, firms organized on a not-for-profit basis produce cultural goods and services, together with for-profit firms (including independent professional artists) and the state. This is also true in many poorer countries. Non-profit firms are defined as organizations that have a formal structure and governance, which differ greatly among countries but share the characteristics that (1) the managers of the organization do not own the enterprise or have an economic interest that can be sold to other firms or individuals, and (2) any surplus of revenue over expenditure may not be appropriated by the managers of the organization, but must be reinvested in ways that further the stated purposes of the organization. These organizations will not be formed and continue to exist unless the organizers and managers expect and realize some economic rewards, including monetary compensation for their own services and non-financial rewards such as consumption benefits (producing cultural goods and services that they want to enjoy but which will not be produced without their efforts) and personal status. The rules under which non-profit cultural firms are formed and function differ greatly among countries (Quarter and Mook 2018). In some, the rules are highly structured and sharply differentiate non-profit firms from other culture-producing entities, especially in countries such as the US, in which the favored tax treatment of non-profit firms is central to their success (Alm and Teles 2018). In other countries, there is much less formality. For example, in Ireland, non-profit organizations may exist and receive favorable tax treatment without any formal legal status, although the latter is usually acquired by registering as a company in order to limit the liability of members (Donoghue et al. 1999, pp. 4–6). The effects of favorable tax treatment can be complex, and Schmalbeck (2006) found negligible effects of tax-exempt status on non-profit health institutions and the market for healthcare in the US. The extent to which non-profit firms are truly separate from the state can differ considerably within and among countries. Sometimes, ostensibly non-profit firms are very closely connected with, and governed by, the state and differ little from entities that are formally part of the state, while in other cases state bodies pretend to be non-profit entities (the Corporation for Public Broadcasting in the USA misleadingly advertises itself as a private corporation but is simply the federal government agency that disburses government grants to local radio and television stations). Moreover, the degree of distinctiveness of the non-profit sector has been changing over time. This blurring of the boundaries has been especially prevalent given the increasing propensity of formally non-profit entities to also engage in commercial activities (Oster 2018), and direct competition between nonprofit and for-profit organizations is increasingly observed (Brown and Slivinski 2018). In some countries, state cultural organizations may have substantial autonomy and may raise funds from private sources, so that they function much like entities that are formally private, non-profit organizations. This has notably increased in Europe (Boorsma 1998, pp. 31–2; Creigh-Tyte 1998, pp. 185–90; Klaic 1998, pp. 171–2). Even in France, where the state remains the sole provider of the most expensive cultural goods and services, there 379

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380  Handbook of cultural economics are some state museums that have been managed by private firms or associations. The Réunion des Musées Nationaux, a state entity representing up to 34 national museums that financed acquisitions and exhibitions and managed museum commercial activities, was converted in 1990 to an industrial and commercial private establishment, meant to increase flexibility, for example, by employing professionals who do not enjoy lifetime job security. However, it appears not to have been successful financially (Benhamou 1998, pp. 101, 107). In 2011, it was merged with the Grand Palais to become the RMN-GP (the abbreviated name), which reports to the Minister for Culture and Communication. Schuster (1998) discusses the ‘hybridization’ of American museums in recent years, a process that reduces the distinction between state and private non-profit museums, an extension of Hutter (1997), who discusses the quasi-privatization of state cultural entities in Europe in recent years, which often adds a second set of flexibility-reducing rules to those inherent in state operation and ownership. While reductions in non-profit managerial flexibility can present problems, it can also have beneficial effects. Yermack (2017) finds that in the US, it is increasingly common for reductions in management flexibility to be imposed by art museum donors, in part as a reaction to high rates of museum financial distress and perceptions of weak board of trustee and managerial control, with the term donor governance referring to restrictions placed on donor gifts to limit managerial discretion. He finds evidence that such restrictions have stabilized non-profit art museums, in part by inducing them to reduce administrative expenses, increase resources committed to program services and retain relatively high portions of cash donations for museum endowments. A substantial portion of the activities of non-profit organizations in some rich countries is explicitly redistributive in purpose, which can be traced back to the major role of the Church, rather than the State, in helping the poor. However, redistribution does not play an important role for cultural non-profit organizations, either in declared intent or in actual effect (whatever the declared intent may be). So cultural (and many other) non-profits can be explained by the conventional externality argument: (1) the production of private (excludable and rival) goods and services also generates significant amounts of public goods; (2) profit-maximizing firms are likely to operate at levels of private-goods output that provide only small quantities of the public goods; (3) democratic governments making budgetary decisions on a median voter basis offer subsidies that generate significantly less public-goods output than many voters prefer and are willing to pay for; and (4) these voters can be identified and persuaded to make gifts of money to that end. Governments are often not trusted to use gifts for such purposes, but instead substitute gift money for funds that otherwise would be provided by ordinary government budgets. The less governments are trusted in this way, the larger the role of non-profits should be. In addition, givers are unlikely to make such gifts to profit maximizing enterprises, since the managers and owners of such enterprises can readily use the gift money to enhance profits rather than produce more public goods. This trust argument for the importance of the non-profit form in the arts is largely accepted without comment in the literature, in part because, as Hansmann (1980) asserted, the non-profit form is well suited to deal with situations in which consumers are incapable of evaluating the goods delivered or promised. Non-profit firms will have little incentive to take advantage of consumers, since there is no gain to managers from so doing. However, there is at least one forceful dissent.

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Non-profit organizations  381 West (1987, pp. 37–9) notes that this is a form of the principal–agent problem and markets have generated a variety of solutions, for example, the use of professional advisers; critics perform this role in the arts. Moreover, the conventional view conflicts with economists’ presumption that self-interested behavior by all parties leads to efficient solutions ordinarily. Next, West (1987, pp. 39–42) turns to the frequent claim (for example, in Throsby and Withers 1979) that non-profit firms are likely to produce at a lower price and higher output level than for-profit firms that are monopolies. If the social objective is to expand cultural experiences, then subsidies confined to non-profits seem the right course. West challenges this conclusion; he shows that this is true only for very simple monopoly situations, with a single price. With perfect price discrimination, only the for-profit firm will have the socially optimum output. Finally, West notes that virtually everything said to be wrong about subsidies to for-profit firms is just as true for non-profits. In a comment, Heilbrun (1988, pp. 87–9) notes that West’s argument rests on his assertion that unit costs are likely to be higher in the non-profit sector than in the profit-making sector, owing to what self-interested behavior in the latter case will do: keep costs down to ensure that there is more profit to appropriate. Part of that case is the assertion that managers will be paid more in non-profits. West’s rejoinder (1988) is that since m ­ anagers cannot appropriate profits, there is an incentive to inflate their salaries. Boards are likely to be amenable to this, instead of a protection against it. Moreover, subsidies from government and private donors surely reduce resistance to high unit costs. Most of these longstanding and vibrant positions are ultimately empirical arguments, but it is difficult to resolve them empirically. Without resolving the debate, the previously discussed evidence found by Yermack (2017) regarding non-profit art museums is at least consistent with West’s concerns, inasmuch as the donor imposed restrictions on museum managerial autonomy were found to reduce administrative expenses, improve programmatic spending, and otherwise correct problems that had not been adequately addressed by oversight boards or museum managements, who were viewed as enjoying considerable private benefits from museum control. In a more well-known article, Hansmann (1986), has added a more direct (and possibly much less altruistic) explanation for non-profit cultural organizations, relating to the cost structure of production in performing arts companies, museums and cultural broadcasting (but not production by independent individual artists). Fixed costs are very high relative to variable costs. Thus, it may be impossible to fully recoup costs from charges paid by direct users in most cases. It would be inefficient to charge would-be customers anything more than the low variable costs. The exceptional cases ordinarily are those in which the performance or exhibition can have a very long run, during which the fixed costs per performance are modest, and thus admission charges paid by very large numbers of customers can cover costs, as in the commercial theatre in London, New York and other places. Price discrimination can help, but will not solve the problem unless the demand curve has an odd shape. The conventional price discrimination on the basis of the location of seats is limited in effect (unless builders of theatres provide a very large number of badly placed seats). Moreover, price discrimination in conventionally designed theatres is restrained by the fact that tickets are transferable. More successful examples of this type of price discrimination have been examined in the for-profit concert industry (Courty and Pagliero 2012), and its potential for further application in the non-profit arts was modeled and exhibited by

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382  Handbook of cultural economics Baldin et al. 2018). The role of price discrimination in furthering distributional objectives for non-profit organizations was examined by Steinberg and Weisbrod 2005). Hansmann sees gifts by individuals as a form of voluntary price discrimination: it is the donors’ way of ensuring that the performance or exhibition or cultural broadcast takes place, by surrendering some of their consumer surplus to the producer of the cultural output they strongly prefer. Seaman (1985) examines this argument empirically for US non-profit performing arts organizations. He finds that ticket price discrimination operates as the standard model would predict and is reasonably effective, while the substitution of donor price discrimination for ticket price discrimination is only partly true. However, the data do show that very large percentages of individual donors are attenders (Frey and Pommerehne 1989, p. 65), so the possibility of the substitution is real. In the US, a very large fraction of private gifts to cultural organizations comes from individuals, instead of from companies or foundations (and many of these entities reflect, in their giving, the personal preferences of the individuals who created the foundations or run the companies). Other examinations of price discrimination via donor behavior include Kushner and King (1994), who treat the performing arts as a club good and find a positive interaction between charitable giving and attending (and buying tickets for) performing arts concerts, and Steinberg (2007), who addresses the challenges of voluntary price discrimination via membership fees for a wider variety of non-profit organizations beyond just the arts. For an expanded review of both dynamic as well as static pricing issues, including price discrimination, see Seaman (2018). In countries where the state plays a large role in the financing of these types of cultural production, the selfish motives of affluent attenders will be less significant and there will be less reason for the cultural enterprise to be a non-profit, instead of a state, enterprise. However, if the enterprise is a non-governmental one, the state is likely to insist that the producer be a non-profit enterprise. Few governments give significant amounts of subsidy to for-profit cultural enterprises. An exception is cases in which the subsidies have been offered to film exhibitors or producers, to encourage the production and showing of locally made films. Such generous and fungible tax credits have contributed to the US state of Georgia hosting more feature film productions in 2016 than any other location (including the UK and California), according to a study by Film L.A. (Hensley 2017), with Georgia continuing to rank at or near the top as a location for the film and television industry (pending any adverse industry reaction to recent controversial legislative social policies). However, the overall record of such subsidies and incentives remains mixed, with economists largely remaining skeptical about the wisdom of such policies. The lack of clear success of these cases suggests the difficulty of preventing for-profit enterprises (and their employees) from appropriating the proceeds as extra income, and the regional economic benefits relative to the fiscal cost of such subsidies have been widely questioned (for example, Luther 2010; Mathis 2012). Thus, as Throsby (2000, pp. 116–18) and others note, if the cultural enterprise requires grants and gifts in addition to income from sale of services in order to survive and generate the public goods that motivate the organizers, the not-for-profit form is the primary practicable corporate structure. However, even as the corporate structure is shaped by the goals of the organizers, the non-profit form itself can affect the choices that cultural entrepreneurs make among their multiple objectives. There is a substantial economic literature on the economic behavior of the managers of museums, starting with Peacock and Godfrey (1974). Grampp, perhaps the economist

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Non-profit organizations  383 who has been the most spirited critic of the economic behavior of museum keepers, denies that it is the non-profit status of nearly all museums that is the explanation: ‘Nonprofit does not in principle signify inefficiency even if it does in practice. A prudent use of resources . . . should be as important to an art museum as to a commercial gallery’ (Grampp 1996, p. 221). Instead, he attributes his catalogue of economic sins, notably the failure to utilize much of their capital in the form of the collection at all, by exhibiting little of it at any time, not preserving and protecting it adequately, minimizing opening hours, and so on, to rent seeking by those who run museums. However, rent seeking by managers can flourish only if their decisions are seldom if ever overruled by their principals – those who own the enterprise – and if their tenure in office is secure. Many museums, large and small, are state museums; in government, security of tenure and insulation of managerial decisions are legendary. In theory, this need not be the case for non-profit enterprises. As Grampp and others note, the proclivities and motivations of non-profit museum managers and their principals – boards of trustees – often are quite similar. Both gain satisfaction from non-economic management of museums, and have no reason to maximize either the utility of museum visitors or financial results: gifts and grants ensure that the latter is satisfactory. However, recent research has demonstrated that gifts and grants do not always provide a cushion that allows museum managers and their principals to avoid maximizing the utility of museum visitors and moving toward more financial sustainability. Efforts to sell works from a museum collection (deaccessioning) or to trade works with other museums to potentially provide a better visitor experience, can be met with hostility by donors (of both art works and money), which can prevent museum managements from taking steps that might optimize the collection that it is capable of exhibiting (for example, Di Gaetano and Mazza 2017). Nonetheless, the economist critics of museum behavior often see the non-profit form, instead of state auspices, as more conducive to economic management. Peacock (1998, p. 25) views non-profit auspices as an alternative to state auspices that can afford more flexibility in management decisions. The issue of deaccessioning that was addressed by Di Gaetano ad Mazza (2017) was also notably addressed by Frey (1994), who argues that economizing behavior by museums, such as selling works from the collection to raise money for purchasing other works, better conservation, improved climate control, longer hours and, most of all, exhibiting a larger percentage of the collection requires more independence from the state than is normally the case in Europe, but common in the US. All Frey’s examples of good behavior are American non-profit museums. However, he recognizes that ‘The question of legal ownership is not decisive, but what matters is that the persons responsible for public museums be given the necessary incentives and independence to employ the resources and possibilities at their disposition more freely’ (Frey 2000, p. 47, original emphases). One curator suggests that the problem the critics address may lie in the legal framework, rather than in the organizational form: he notes that, in civil law countries, museums’ collections are generally viewed as public property and ‘as such inalienable except in extremis. In common law countries, trustees are groups of persons to whom care of objects is entrusted for specific purposes, and therefore conceivably can be sold’ (Cannon-Brookes 1996, p. 260). Presumably, in civil law countries, even non-profit museums could not sell works from the collection, while, in common law countries, even state museums might be free to do so.

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384  Handbook of cultural economics Although trustees may govern state as well as non-profit museums, and other producers of cultural services and both non-profit and state entities may be subject to similar limits on their discretion under the laws of that country, it seems that non-profit status is likely to provide more opportunity for flexibility in these matters. Moreover, while non-profit auspices do provide scope for much uneconomic behavior by managers, that scope may be narrower than is the case for state auspices. Uneconomic behavior often is the very purpose of state provision of the service. A possibly important consideration in cultural policy is whether the private non-profit form affects the choice of strategies for intervention in art markets by state bodies, such as arts councils. In a 1985 paper, Throsby notes that intervention may occur in either or both of two markets, and on either side of those markets: (1) the market in which artists are the sellers and those who bring the work of artists to consumers (performing arts producers, art dealers and museums of contemporary art) are the buyers, and (2) the market in which those firms interact with final consumers. He concludes that the usual point of ­intervention – grants to firms instead of to artists or consumers – is likely to increase quality in the first market and quantity in the second, with some important exceptions. Conceivably, state cultural firms may be under political pressure to increase quantity, in either or both markets, while non-profit cultural firms that rely heavily on non-state sources of funds may feel more freedom to emphasize quality goals. Moreover, since the personal rewards of non-profit trustees and managers have a large non-monetary component, notably social status, it is to be expected that the non-profit form on balance will encourage emphasis on the quality goal. Frey and Pommerehne (1990) examine the economic consequences of the basic differences in institutional form in theatres, comparing the commercial theatre and the subsidized theatre, which includes both non-profit theatres and state theatres. While they explicitly deal with state subsidies, the analysis applies to private gifts as well. The predominant form of subsidy for theatre organizations that are non-profit entities and theatres that are not directly part of the public administration is lump-sum subsidy that is not closely related to output, input or prices, meant to ensure the existence of the organization. This type of subsidy eliminates incentives to earn any visible profits, which ‘is often accomplished by improving quality above the level desired by the audience, distributing rents to employees, concentrating on the “artistic side” and disregarding other possible sources of revenue’ (Frey and Pommerehne 1990, p. 180). Less common are ticket subsidies, which may be intended to increase audience size, but which can be diverted readily to quality improvements. State theatres, in contrast, especially in continental Europe, usually receive subsidies to cover prospective operating deficits. However, Achieving a surplus or reducing a deficit does not benefit the theatre; the implicit tax rate is 100 per cent. Moreover, future subsidies are reduced. Therefore, the directors of a public theatre have a strong incentive not to reduce the deficit, but rather to increase it above the projected level. The sanctions against doing so are low. (Frey and Pommerehne 1990, p. 182, original emphasis)

Why does the importance of non-profit organization of cultural production differ among rich democratic countries? Economists should be and are skeptical about explanations for any institutional differences in economic organization on the basis of ancient accidents of history. If culture is a normal good, we would not expect the demand

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Non-profit organizations  385 for cultural output to vary inversely with per capita income; instead, we would expect demand to be positively associated with per-capita income, probably with considerable variation from the trend line. Thus it is plausible that the aggregate demand (relative to gross domestic product, GDP) for the public goods that cultural activities generate is roughly similar among the rich countries. This may be true, but it is consistent with differential financing of cultural activities by the state in democratic countries, without the need to resort to the political history of the preindustrial age. A simple explanation is that the views of the median voter on the size and composition of the state budget may be very different from the views of the median among those voters who articulate their positions on the state budget for cultural goods and services. Also, given the differences among countries in the structure of decision making on the state budget (for example, between federal and unitary government countries), the median voter model might work in different ways in different countries, with differential results in respect of state financial support of culture. Then, if the demand for the public goods associated with cultural production is similar among countries, the outcome of the median voter model should be offset by differential funding of cultural activities by non-profit organizations financed by gifts. The extent to which this is true should be affected by different countries’ rules on the organization and functioning of non-profits and the tax treatment of gifts. Thus, in the US, it is easy to organize tax-favored non-profit entities, and the after-tax cost to the donor of most gifts (by dollar value) to non-profit cultural entities in the form of bequests is only about 20 percent of the value of the gift, and that of most gifts during the lifetime of the donor is only about 60 percent of the value of the gift (numerical examples that applied to the early twenty-first century, but are always subject to modification by changes in the tax code. Indeed, the 2017 changes in the US tax code are widely viewed as reducing the tax incentives for making such gifts). It should be no surprise that individual gifts to non-profit organizations of all kinds constitute a much higher percentage of personal income than in most other rich countries, and that the US (probably – comparative data on this are very limited) is at the extreme upper end of the distribution as regards the relative role of non-profit organizations in cultural production. The Urban Institute’s National Center for Charitable Statistics provides extensive data on key aspects of the non-profit sector in the US. Three of their many conclusions are worth quoting directly (McKeever 2018), including some findings from Giving USA Foundation (2018), and also providing estimates of the important contributions made by volunteer labor (see also Bania and Leete 2018):  ●  Of

the non-profit organizations registered with the IRS, 501(c)(3) public charities accounted for just over three-quarters of revenue and expenses for the non-profit sector as a whole ($1.98 trillion and $1.84 trillion, respectively) and just under two-thirds of the non-profit sector’s total assets ($3.67 trillion).  ● In 2017, total private giving from individuals, foundations, and businesses totalled $410.02 billion (Giving USA Foundation 2018), an increase of 3 percent from 2016 (after adjusting for inflation). According to Giving USA (2018) total charitable giving rose for the fourth consecutive year in 2017, making 2017 the largest single year for private charitable giving, even after adjusting for inflation.  ● An estimated 25.1 percent of US adults volunteered in 2017, contributing an estimated 8.8 billion hours. This is a 1.6 percent increase from 2016. The value of these hours is approximately $195.0 billion. (McKeever 2018, ‘Highlights’ section, p. 1)

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386  Handbook of cultural economics It is also useful to provide some recent historical perspectives, focused on a key component of the non-profit sector; museums. At the end of the twentieth century, non-profit museums in the US accounted for roughly 70 percent of the receipts of all museums, government museums (which include the very large and lavishly financed federal government museums in Washington) for about 25 percent and for-profit museums for about 5 percent. A very small part of the receipts (less than 10 percent) of the non-profit museums came from government grants, about 25 percent from earned income (largely admissions payments), and the rest from investment income and current gifts by private parties (American Association of Museums, now the American Alliance of Museums 2000). By 2014, and focusing on one of the more important types of museums among the diverse array represented by the American Alliance of Museums, a survey by the Association of Art Museum Directors (with responses from 220 of its 236 non-profit members in North America, 204 of which are in the US and 16 in Canada and Mexico), confirmed the ongoing importance of funding sources other than governmental, but also reflecting the accelerated efforts to diversify funding sources, especially in the wake of the 2008–09 economy-wide financial crisis that badly affected museums of all kinds (Association of Art Museum Directors 2014). Government support from all levels (federal, state, county and city) accounted for 18 percent of revenue and support (only 6 percent from the federal government), with total endowment support representing the largest single revenue category at 21 percent. That same percentage was received from all private sector donations and contributions, consisting of 10 percent from individuals, 7 percent from foundations and trusts and 4 percent from corporations. The related category of benefit events generated another 4 percent. Colleges and universities accounted for 3 percent of total financial support. Earned income from admissions was only 7 percent of all revenues (although an additional 7 percent was received from individual/ family memberships, and 1 percent from corporate memberships), but other sources of earned income are worth noting. Museum stores alone generated 8 percent of total revenues, with another 6 percent deriving from facility rentals, restaurants and catering, educational events and exhibition fees. Very few US performing arts companies are government entities. In 1997, non-profit entities accounted for nearly all the receipts of opera companies, symphony orchestras and chamber music organizations, and dance companies, and 37 percent of the receipts of theatre companies; for-profit theatre companies accounted for nearly all the remainder of theatre receipts. About one-fourth of the receipts of promoters of arts events (­usually, the owners or operators of performance venues not owned by specific performing ­companies; Lincoln Centre in New York is the largest of these) were in the non-profit sector. The National Endowment for the Arts (NEA 2012, relying also on data from the Urban Institute’s National Center for Charitable Statistics), identifies revenue sources for not-for profit performing arts and museums organizations between 2006 and 2010, with governments at all levels accounting for only 6.7 percent in contrast to the 38.2 percent derived from contributions from all sources (individuals dominating at 20.3 percent but also including foundations and corporations). Earned income for this more broadly defined non-profit arts sector is much more important than what was cited above for only art museums, being 40.7 percent, and supplemented by 14.4 percent from interest and

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Non-profit organizations  387 endowment earnings. These results are broadly consistent with earlier data, but with a few interesting variations. Non-profit organizations accounted for 20 percent of the receipts of the broadly defined performing arts sector, including mass culture music groups, performing arts companies’ promoters, agents and managers, and independent artists and performers (US Census Bureau 2000), but the important earned income component for those non-profit organizations was higher in that earlier period, at 62 percent compared with the combined 55.1 percent including interest and endowment earnings. By contrast, the 32 percent from private gifts, past and present was lower than the later 38.2 percent component. The relative unimportance of government grants remained the most stable result over those two periods, being 6 percent in the earlier data (US Census Bureau 2001) compared with 6.7 percent as cited by the NEA (2012). Non-commercial broadcasting in the US (known imprecisely as public broadcasting) is devoted to news and public affairs programming, children’s programming and cultural programming, the last accounting for as much as 40 percent of total costs (other than station and network operation). Most of the local stations are operated by state and local governments and their universities and colleges, but nearly all the primary (veryhigh-frequency) stations in major metropolitan markets are operated by non-profit corporations. Thus, most of the receipts and expenditure of the public broadcasting system are the province of non-profit enterprise. However, the role of government funding is much more important than in the case of museums and the performing arts, although funding from all governments, including the federal government, for the Corporation for Public Broadcasting (CPB) has been declining. All government sources provided nearly 40 percent of the receipts at the turn of the twenty-first century (CPB 2000), but by fiscal year 2017 overall government funding (federal, state and local) had fallen to 25.6 percent, although this increases to 32.1 percent if tax-based funding from state colleges and universities is added (CPB 2017, table 6). As viewers/listeners are always told, it is a myth to believe that the CPB is primarily funded by the US federal government. Such support in fiscal year 2017 was only 14.8 percent, with subscriber contributions being the largest component of funding at 31.3 percent, and businesses and foundations combining for an additional 23.5 percent (from CPB 2017, table 6). It is very difficult to piece together comparable data for other countries regarding the importance of non-profit entities in the production of cultural services. However, the Comparative Non-profit Sector Project of Johns Hopkins University has generated comparative data across countries on the economic importance of non-profit cultural production relative to national economic measures, and remains perhaps the most comprehensive effort to address this issue.1 As Tables 42.1 and 42.2 show, the economic importance of the non-profit cultural sector is relatively small in the USA, although much of the American cultural sector is organized on a non-profit basis. Presumably, it is the relative economic unimportance of the entire cultural sector – for-profit and non-profit – in the US that explains this result. It should be noted that the now-standard international classification scheme for non-profit organizations combines, in one subsector, culture, arts and recreation. The inclusion of recreation may explain what appear to be anomalous results: for example, the high figure for Australia in Table 42.2. Throsby (1996) makes it clear that the non-profit component of the culture sector in Australia is exceedingly small.

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388  Handbook of cultural economics Table 42.1  Non-profit culture and recreation operating expenditures, 1990 Country

Percentage of GDP

France Germany Hungary Italy Japan Sweden United Kingdom United States Average

0.59 0.26 0.67 0.22 0.04 1.03 0.98 0.20 0.64

Note:  GDP = gross domestic product. Source:  Salamon et al. (1999, app. B). Tables updated to 20 January 2000 from www.jhu.edu/~cnp/pdf (accessed 1 June 2019).

Table 42.2  Employment in non-profit culture and recreation organizations, 1995 Country or area

Percentage of total non-agricultural employment in the country or area

European Union Central Europe Japan Australia United States

0.70 0.39 0.11 1.15 0.55

Source:  Salamon et al. (1999, app. B). Tables updated to 20 January 2000 from www.jhu.edu/~cnp/pdf (accessed 1 June 2019).

NOTES *

This chapter was modified, expanded and updated by Bruce A. Seaman. The editors are most grateful to him for his generosity in undertaking this difficult and selfless task, which enables us to retain the bulk of the original chapter by the late Dick Netzer (1929–2008). See also his obituary (Seaman 2008). 1. There is a standard international classification scheme for non-profit economic activity. The sector referred to here is ‘culture and recreation’.

SEE ALSO: Chapter 39: Museums; Chapter 43: Orchestras; Chapter 50: Public support; Chapter 55: Tax concessions.

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Non-profit organizations  389

REFERENCES Alm, J. and D. Teles (2018), ‘State and federal tax policy toward non-profit organizations’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 370–85. American Association of Museums (AAM) (2000), ‘1999 AAM museum financial information, a report from the National Survey’, AAM, Washington, DC. Association of Art Museum Directors (2014), ‘Art museums by the numbers 2014’, Association of Art Museum Directors, New York. Baldin, A., T. Bille, A. Ellero and D. Favoretto (2018), ‘Revenue and attendance simultaneous optimization in performing arts organizations’, Journal of Cultural Economics, 42 (4), 677–700. Bania, N. and L. Leete (2018), ‘The valuation of volunteer labor’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 323–36. Benhamou, F. (1998), ‘The contradictions of désétatisation: museums in France’, in P.B. Boorsma, A. van Hemel and N. van der Wielen (eds), Privatization and Culture: Experiences in the Arts, Heritage and Cultural Industries in Europe, Dordrecht: Kluwer Academic, pp. 95–110. Boorsma, P.B. (1998), ‘Privatizing the muse – and all that jazz’, in P.B. Boorsma, A. van Hemel and N. van der Wielen (eds), Privatization and Culture: Experiences in the Arts, Heritage and Cultural Industries in Europe, Dordrecht: Kluwer Academic, pp. 23–45. Brown, E. and A. Slivinski (2018), ‘Markets with competition between for-profit and non-profit firms’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 132–45. Cannon-Brookes, P. (1996), ‘Cultural–economic analysis of art museums: a British curator’s viewpoint’, in V.A. Ginsburgh and P.-M. Menger (eds), Economics of the Arts: Selected Essays, Amsterdam: Elsevier, pp. 255–74. Corporation for Public Broadcasting (CPB) (2000), ‘Public broadcasting revenue, 1999’, annual report, CPB, Washington. Corporation for Public Broadcasting (CPB) (2017), ‘Public broadcasting revenue, fiscal year 2017’, annual report, CPB, Washington. Courty, P. and M. Pagliero (2012), ‘The impact of price discrimination on revenue: evidence from the concert industry’, Review of Economics and Statistics, 94 (1), 359–69. Creigh-Tyte, S. (1998), ‘Mixed economy and culture: Britain’s experience’, in P.B. Boorsma, A. van Hemel and N. van der Wielen (eds), Privatization and Culture: Experiences in the Arts, Heritage and Cultural Industries in Europe, Dordrecht: Kluwer Academic, pp. 183–97. Di Gaetano, L. and I. Mazza (2017), ‘“Better an egg today than a hen tomorrow” on the implications of deaccess policies for donations to museums’, Journal of Cultural Economics, 41 (3), 237–58. Donoghue, F., H.K. Anheier and L.M. Salamon (1999), Uncovering the Non-profit Sector in Ireland: Its Economic Value and Significance, Baltimore, MD: Johns Hopkins University and Dublin: National College of Ireland. Enjolras, B., L.M. Salamon, K.H. Sivesind and A. Zimmer (2018), The Third Sector as a Renewable Resource for Europe, Heidelberg: Springer. Frey, B.S. (1994), ‘Cultural economics and museum behaviour’, Scottish Journal of Political Economy, 41 (3), 325–55. Frey, B.S. (2000), Arts & Economics: Analysis & Cultural Policy, Berlin: Springer. Frey, B.S. and W.W. Pommerehne (1989), Muses and Markets: Explorations in the Economics of the Arts, Oxford: Basil Blackwell. Frey, B.S. and W.W. Pommerehne (1990), ‘A comparative institutional analysis in the arts: the theater’, in M. Hechter, J.-D. Opp and R. Wippler (eds), Social Institutions: Their Emergence, Maintenance and Effects, Berlin: Walter de Gruyter, pp. 171–86. Giving USA Foundation (2018), ‘Giving USA 2018: the annual report on philanthropy for the year 2017’, Giving USA Foundation, Bloomington, IN. Grampp, W. (1996), ‘A colloquy about art museums: economics engages museology’, in V.A. Ginsburgh and P.-M. Menger (eds), Economics of the Arts: Selected Essays, Amsterdam: Elsevier, pp. 221–54. Hansmann, H.B. (1980), ‘The role of non-profit enterprises’, Yale Law Journal, 89 (5), 835–901. Hansmann, H.B. (1986), ‘Non-profit enterprise in the performing Arts’, in P.J. DiMaggio (ed.), Non-profit Enterprise in the Arts: Studies in Mission & Constraint, New York and Oxford: Oxford University Press. Heilbrun, J. (1988), ‘Non-profit versus profit-making firms: a comment’, Journal of Cultural Economics, 12 (2), 87–92. Hensley, E. (2017), ‘Study: Georgia now no. 1 in feature film productions’, Atlanta Business Chronicle, 31 May. Hutter, M. (1997), ‘From public to private rights in the arts sector’, Boekmancahier, 32, 170–76.

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390  Handbook of cultural economics Klaic, D. (1998), ‘Unlike airlines and phone companies: performing arts in Europe’, in P.B. Boorsma, A. van Hemel and N. van der Wielen (eds), Privatization and Culture: Experiences in the Arts, Heritage and Cultural Industries in Europe, Dordrecht: Kluwer Academic, pp. 170–82. Kushner, R.J. and A.E. King (1994), ‘Performing arts as a club good: evidence from a non-profit organization’, Journal of Cultural Economics, 18 (1), 15–28. Luther, W.J. (2010), ‘Movie production incentives: blockbuster support for lackluster policy’, Special Report No. 173, Tax Foundation, Washington, DC, January. Mathis, T. (2012), ‘Louisiana film tax credits: costly giveaways to Hollywood’, Louisiana Budget Project report, Baton Rouge, LA, August. McKeever, B. (2018), ‘The non-profit sector in brief 2018: public charities, giving and volunteering’, Urban Institute, National Center for Charitable Statistics, Washington, DC, 13 December. National Endowment for the Arts (NEA) (2012), How the United States Funds the Arts, 3rd edn, Washington, DC: NEA. Netzer, D. (2006), ‘Cultural policy: an American view’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1224–51. Oster, S. (2018), ‘Product diversification and commercial ventures’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 269–84. Peacock, A. (1998), ‘The economist and heritage policy: a review of the issues’, in A. Peacock (ed.), Does the Past have a Future? The Political Economy of Heritage, London: Institute of Economics Affairs, pp. 1–26. Peacock, A. and C. Godfrey (1974), ‘The economics of museums and galleries’, Lloyds Bank Review, 111 (January), 17–28. Quarter, J. and L. Mook (2018), ‘The social economy: an international comparison’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 428–41. Salamon, L.M., H.K. Anheier, R. List, S. Toepler, S.W. Sokolowski and Associates (1999), Global Civil Society: Dimensions of the Profit Sector, Baltimore, MD: Johns Hopkins Center for Civil Society Studies. Schmalbeck, R.L. (2006), ‘The impact of tax-exempt status: the supply-side subsidies’, Law and Contemporary Problems, 69 (fall), 121–38. Schuster, J.M. (1998), ‘Neither public nor private: the hybridization of museums’, Journal of Cultural Economics, 22 (2–3), 127–50. Seaman, B.A. (1985), ‘Price discrimination in the arts’, in V.L. Owen and W.S. Hendon (eds), Managerial Economics for the Arts, Akron, OH: Association for Cultural Economics, pp. 47–60. Seaman, B.A. (2006), ‘Empirical studies of demand for the performing arts’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1224–51. Seaman, B.A. (2008), ‘Dick Netzer (1929–2008)’, Journal of Cultural Economics, 32 (3), 227–9. Seaman, B.A. (2018), ‘Static and dynamic pricing strategies: how unique for non-profits?’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 199–224. Seaman, B.A. and D.R. Young (eds) (2018), Handbook of Research on Non-profit Economics and Management, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Steinberg, R. (2007), ‘Membership income’, in D.R. Young (ed.), Financing Non-profits: Putting Theory into Practice, Lanham, MD and Plymouth: AltaMira Press, pp. 121–56. Steinberg, R. and B.A. Weisbrod (2005), ‘Non-profits with distributional objectives: price discrimination and corner solutions’, Journal of Public Economics, 89 (11–12), 2205–30. Throsby, D. (1985), ‘Intervention strategies in arts markets’, in C.R. Waits, W.S. Hendon and H. Horowitz (eds), Governments and Culture, Akron, OH: Association for Cultural Economics, pp. 16–28. Throsby, D. (1996), ‘Government support for the arts and culture: the Australian model’, paper presented at a forum on ‘Stimulating a Philanthropic Culture for Australia’s Creative Future’, Museum of Contemporary Art, Sydney, 2 October. Throsby, D. (2000), Economics and Culture, Cambridge: Cambridge University Press. Throsby, C.D. and G.A. Withers (1979), The Economics of the Performing Arts, London and Melbourne: Edward Arnold. US Census Bureau (2000), 1997 Economic Census, Arts, Recreation, and Entertainment, Geographic Area Series, United States, EC97S71A-US(RV), Washington: USCB. US Census Bureau (2001), 1997 Economic Census, Arts, Recreation, and Entertainment, Subject Series, Summary, EC97S715–0SM, Washington: USCB. West, E.G. (1987), ‘Non-profit versus profit firms in the performing arts’, Journal of Cultural Economics, 11 (2), 37–47. West, E.G. (1988), ‘Government Grants to non-profit firms: still searching for the rationale’, Journal of Cultural Economics, 12 (2), 93–5.

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Non-profit organizations  391 Yermack, D. (2017), ‘Donor governance and financial management in prominent US art museums’, Journal of Cultural Economics, 41 (3), 215–35.

FURTHER READING For further context regarding the unique characteristics of American cultural policy, see Netzer (2006). Seaman (2006) provides a review of the complex factors affecting the demand for the largely non-profit performing arts, while Enjolras et al. (2018) provide a comprehensive view of the more broadly defined ‘third sector’ in Europe. For a treatment of the diverse issues confronting non-profit organizations as addressed by many of the top scholars in the field, see Seaman and Young (2018).

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43.  Orchestras

Luis César Herrero-Prieto and Mafalda Gómez-Vega

Symphony orchestras are among the most classical of cultural institutions in the history of human artistic expression, since they merge the passion and excitement of those who enjoy the experience of live music, the talent of those who perform it and the work of those who compose it, which therefore embraces them in the realm of musical cultural heritage. Orchestras are also complex organisations which may be understood from a threefold perspective: as cultural institutions they preserve and promote the musical heritage of past, present and future composers; as music entities their raison d’être is to stage live performances, that is, to perform and play in front of an audience; and, as social corporations, orchestras are organisations that manage specific capital and labour resources to produce goods and services, a process which may be subject to evaluation and analysis from an economic standpoint. The production chain of a symphony orchestra may be summed up as the organisation and coordination of the talent of a group of professionals, musicians and maestros, orchestra conductors and guest soloists who use technically adapted infrastructure (concert hall and equipment) and other capital elements (the instruments themselves) to perform a musical repertoire that is both programmed and subject to specialisation. All this constitutes the endowment and creative cultural offer of the symphony orchestra as an organisation, which requires further resources related to management, technical production, documentation, and so on, and the importance of which depends on the relevance of the entity, to produce services (performances) that cater to public demand. Nevertheless, output is not confined solely to the number of concerts or spectators. Output may be measured also by applying criteria of quality and diversity of the musical repertoire. Other products emerge from recordings, tours, educational activities, and more intangible circumstances, such as the brand value associated with the orchestra’s prestige, and the concert hall as a building, which triggers other effects such as impacts of tourism. As part of the performing arts, symphony orchestras have been subject to analysis in the leading studies on cultural economics as a scientific discipline, owing to the cost disease problem which characterises them (Baumol and Bowen 1966). However, they are also affected by other key analytical issues, such as funding, cost structure and analysis of efficiency, typifying demand and the evaluation of symphony orchestra quality – issues we consider next.

COST DISEASE AND ORCHESTRA FUNDING The principal argument concerning the cost disease affecting symphony orchestras is that they are highly labour intensive, and there are scarcely any gains in productivity, given the reduced substitutability of capital; it is not possible to speed up production or reduce the amount of labour involved in a given piece of music. This means that labour costs per product unit continue to rise over time, leading to an inevitable gap with potential 392

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Orchestras  393 revenue and, therefore, to the possible financial collapse of orchestras. Whereas in other activities of the same production type in the economy this endemic disease is dealt with through price increases, in the performing arts, and particularly for orchestras, this would not appear to be a practical solution, given the policy of setting prices for long periods (seasons) coupled with the possible danger of losing spectators in the medium and long terms. This is why most of the initiatives in this field are ultimately geared towards nonprofit organisations and public entities as an institutional form, which depend to a greater or lesser degree on public and private subsidies. Most of the economic literature addressing symphony orchestras has focused on verifying to what extent this problem exists (Felton 1994; Throsby 1996; Dempster 2002), even though there is evidence that cost disease is not always a terminal problem and that orchestras find different ways to balance this deficit in the long term. It appears (Flanagan 2012) that the real pressure arising from costs is not so much caused by musicians’ salaries, the labour-intensive work, but other causes linked to musical programming (more complex repertoires, the cost of bringing in guest soloists and conductors, and so on) and the growth of operating costs (administration expenses, advertising, fundraising, and so on), which may ultimately be adjusted, provided that they are not seen to substantially affect the capacity to attract audiences. Finally, we also need to consider whether part of the financial pressure that orchestras face may not be directly related to the economic cycle, and this may lead them to suffer cutbacks in public and private support during a recession, so that they have to become more self-sufficient in the market or suffer artistic deficit. All this depends on the system of support and institutional organisation available to them (McGrath et al. 2017). The solution to this endemic problem stemming from the gap between expenditure and income lies in an understanding of the financing structure of symphony orchestras, where there are two major sources of income. On the one hand is performing income which comes from tickets sold, but which may also include payments for recordings (compact discs, videos, broadcasts, and so on), streaming reproductions and educational activities. On the other is non-performing income, which includes the sale of merchandising, renting out venues and, above all, from public subsidies and private sponsorship. This gives rise to two models of orchestra funding, which are distinguished by their greater or lesser dependence on their own income and, therefore, also on the proportion of public and private funding. The first model is that of a wide variety of institutions, including American orchestras, which depend on their own funding and private sponsorship, wherein advertising costs and fundraising become key factors. The second is the more widespread continental model, where orchestras tend to be public entities or foundations that are principally maintained through public authority contributions, whether at a national, regional or local scale. In the latter, there are interesting instances of principal– agent conflict, which affect the quality of the programming and how audiences are drawn (McGrath et al. 2017). Whichever institutional and financing model symphony orchestras adopt, controlling Baumol’s disease and ensuring orchestras’ long-term solvency depends on three complementary strategies (Flanagan 2012): (1) the growth of their own revenue, where we can expect more revenue from the use of price discrimination policies for different demand elasticities; (2) curbing growth in spending, exploring new ways of hiring performers, changing repertoires to reduce large-scale requirements and cutting any expenses that do not affect the long-term rise in audience numbers; and (3) fostering non-performance income by exploiting utilities derived from the orchestra’s activities, and

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394  Handbook of cultural economics from sponsorship and diversification of sources of private funding. Also, the long-term benefits of education and economic development can help to swell audience numbers and better maintain orchestras’ own income (Brooks 2006). An interesting and complementary issue in financing is the analysis of how external fundraising impacts the running and quality of symphony orchestras. Brooks (1999) examined whether public subsidies lead to a crowding-out effect on private donations or whether, in contrast, they bolster sponsorship, and found that the latter only occurs when orchestras accredit excellence. McGrath et al. (2017) evidence how Canadian orchestras, given their public-funding structure, tend to control fiscal deficit at the expense of greater artistic deficit, since they move towards safer and more standardised repertoires during periods of cutbacks as a means of justifying public subsidies through greater audience success, while American orchestras tend towards capturing private funding. For American orchestras, Luksetich and Hughes (2008) find that those heavily dependent on ticket sales may be forced to perform easy and popular programmes in order to have greater audience appeal, while state lump-sum grants give rise to more innovative repertoires, especially in medium and small orchestras. However, Pompe et al. (2011) establish that increased funding for ticket sales, endowments and local government increases the likelihood that an orchestra will perform a non-standard repertoire, while Tamburri et al. (2015) specify that greater funding from federal government encourages even more innovative programming compared with those who depend more on local administration funds.

COST STRUCTURE AND EFFICIENCY EVALUATION Orchestras should be viewed as multi-product, non-profit enterprises with a cost structure that is determined by the elevated fixed costs, often sunk costs (expenses related to the premises, musicians’ pay and the royalties arising from the music score and performance rights), so that the marginal cost of catering to one additional spectator is very low whatever the capacity and final audience in the concert hall. It is therefore a situation that is comparable to a natural monopoly where the optimum rule for determining prices through marginal costs never manages to cover the average costs. The entity is thus faced with either setting very high prices for a limited market, or lower prices geared towards greater spectator numbers, in the hope of finding subsidies or donations that will cover the funding deficit. Lange and Luksetich (1984, 1995) and Felton (1992) show that orchestras tend to set low prices, in the inelastic part of the demand curve, which indirectly provides another strategy, namely, the possibility of applying price discrimination policies and significantly increasing revenue through selective ticket sales at higher prices. This is common practice for entities in the performing arts sector that have high fixed costs, particularly symphony orchestras (Seaman 1987). For these entities there is always the possibility of finding demand segments and spectators who are willing to pay a higher price depending on, for example, visibility, the quality of the sound, the location of the seats in the concert hall, whether attending premieres, discounts for large purchases (season tickets), or other less frequently tried formulas, such as convincing people to join ‘friends of’-type associations or dynamic price discrimination strategies (last minute tickets). Concerning market behaviour, symphony orchestras, in their position as non-profit or public organisations, do not tend to pursue maximum benefit, but seek to optimise

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Orchestras  395 other objectives, such as production level, quality and prestige, or a combination of all three. Exploring these aspects proves interesting. First, orchestras are a multi-product entity whose performances are not confined to the number of concerts or spectators, but also fulfil other aims such as educational functions, conservation of musical heritage and social impact. Secondly, there tends to be a dichotomy between principal and agent (policy-makers and managers, respectively) when it comes to establishing objectives, and this often affects the design and quality of the musical programming (McGrath et al. 2017; Gómez-Vega and Herrero-Prieto 2019). Thirdly, it is becoming increasingly important to understand and justify how symphony orchestras obtain their resources. Efficiency evaluation studies of orchestras as a system are still uncommon, perhaps owing to the difficulty in gathering sufficient reliable data of a multi-output production function in which, given the rigidity of capital equipment, the focus should mainly fall on allocative efficiency studies. Nonetheless, examples of studies which should be cited include Luksetich and Hughes (1997) and Hong (2014), who seek to measure how efficient various networks of orchestras are when attempting to secure funds (fundraising function) with which to subsequently design and produce their musical programme.

PARTICIPATION AND TYPIFYING DEMAND The greatest problem that orchestras seem to face relating to demand and participation is declining interest over time on the part of audiences (Flanagan 2012; Pompe et al. 2018). However, the results may not be that discouraging and may depend on the unit of measurement used. For instance, in Spain the number of classical music spectators has fallen over the past 15 years, as did the number of concerts during the years of the economic recession, although the mean attendance per concert has increased. In addition, and even though the experience of listening to live music is hard to substitute, alternative closely related products, such as streaming to places other than the concert hall or the presence of increasingly high-quality sound recordings, have emerged, which have affected spectator numbers at live performances. It is therefore interesting to consider whether the new technologies are generating parallel demand for less expensive products and should therefore be deemed a factor which contributes to rather than undermines continued interest in classical music. These new technologies also afford orchestras fresh opportunities to reach a wider audience beyond the confines of the concert hall (Towse 2014). Festivals and orchestra tours which, given their exceptional nature or integration during moments of leisure and tourism, might also impact audience numbers, again in places other than traditional venues. Returning to aspects that typify demand, this is an area of analysis that has proved prolific (Seaman 2006), with most studies indicating that demand for symphony orchestra concerts is relatively inelastic vis-à-vis prices and become more elastic as the size of the orchestras reduces (Lange and Luksetich 1995). This result is indicative of an affinity and loyalty in consumer preferences, and has implications for revenue, since orchestras could increase income by raising prices. There is also some evidence that cross-elasticity regarding other cultural goods is positive, which might play a role in substitute consumption, such as cinema or opera, although this latter effect is qualitatively small and not always reliable (Flanagan 2012). The results are even more ambiguous for income elasticity.

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396  Handbook of cultural economics Zieba and O’Hagan (2013) estimate an income elasticity rate of 1 or thereabouts for German orchestras, and Felton (1992, 1994) also found results of 1 or slightly higher for total attendance at the largest orchestra groups in the USA, but less than 1 for s­ ubscribers’ databases. We might therefore suspect that symphony concerts could act as luxury goods, yet ultimately depend on individuals’ features mainly relating to their background, wealth and accumulated prior experiences. One question to ask is what other factors in the institutional environment of orchestras might affect concert attendance? Pompe et al (2018) demonstrate that subscription ticket buyers are more sensitive to price changes than total buyers, and that hiring a new musical director may increase subscription ticket sales. Flanagan (2012) states that higher marketing expenditure increases attendance at regular season concerts, but with diminishing returns, that is, successively smaller gains on attendance per concert. We could also question orchestras’ performance as regards programming a more qualified and richer musical supply. Does the presence of guest soloists or conductors, other than the orchestra’s own music staff, attract a sufficiently larger audience? What about inviting top performers and leading conductors who belong to the superstar category? Do these actions justify the expense vis-à-vis improving orchestras’ income? The answers to these questions might be justified based on the economy of welfare using the argument that the provision of cultural goods is merit goods, although the reasons tend to lose sway when the objective is the financial sustainability of orchestras.

EVALUATING THE QUALITY OF SYMPHONY ORCHESTRAS The issue of excellence in symphony orchestras emerges, since one implication of cost disease might be to adjust the budget, cutting back on the quality of the music programme and suffering artistic deficit. Yet, it may also respond to the problem of the choice of cultural policy, among the objectives of which is to ensure quality and innovation, or opt for less stringent scheduling formulas as a means of saving costs and securing audiences. Evaluation is a complex issue given the multi-dimensional nature of the artistic output of orchestras. It may be approached from the demand side, by analysing results regarding the number of spectators, concert-hall occupation rates or audience satisfaction, or from the supply side, by evaluating the characteristics of the musical repertoires. In this regard, there are studies that explore quality through the opinion of experts and critics (Tobias 2004), although, in recent years, studies appraising the musical programme through a range of quality indicators have come to the fore. First, is the contemporaneity index (Bertaux et al. 2015), which seeks to quantify the weight of programmes devoted to contemporary composers, deemed more complex in performance terms, and more intensive in the work involved, in the number of instruments and in the need for rehearsals. Consequently, these programmes are felt to be of higher quality in technical terms and tend to take greater risks with audience attendance and revenue compared with more standard preferences in classical musical consumption. Secondly, other works use an index of conventionality, or risk index as an inverse version (Pompe et al. 2011; Tamburri et al. 2015), which seeks to express how original and innovative an orchestra’s repertoire could be regarding composers already scheduled for performance by other orchestras. The more often their works are performed during a season, the more conventional the programme is felt to be, and vice versa. Finally, Ito

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Orchestras  397 and Domian (1987) use an indicator of the best-known composers, referring to the best internationally known musicians, whose quality is beyond question given their popularity and reputation. This index enables analysis of another facet of quality in symphony orchestra repertoire, namely, their prestige and recognition, although they may also be viewed as safer programmes, based on demand, since they involve little risk and usually ensure larger audiences. Gómez-Vega and Herrero-Prieto (2019) offer a summary, merging information from three indices by constructing a composite indicator using data envelopment analysis (DEA) as a mathematical optimisation technique, and assuming therefore that technical abilities, originality and tradition when programming are three complementary criteria of repertoire quality. They apply this approach to the Spanish symphony orchestra network. Results of their study indicate a satisfactory level of quality for the sample, and further indicate that the index of contemporaneity and the index of risk make the greatest contribution to achieving maximum quality for orchestras. The research also seeks to explore which external drivers impact the programming strategy, applying regression analysis between the index of aggregate quality and external variables related to the determinants inherent in orchestra management, together with various socio-economic aspects of the surrounding geographical area. A prominent result is the effect of variables that contribute to securing higher quality, such as a longer season, ticket prices or being located in the country’s capital. How old the orchestra is, a larger capacity concert hall and greater cultural consumption in the reference region were found to have a negative impact on symphony orchestra quality. The level of human capital in the area is also directly correlated to repertoires that are more contemporary and offer greater innovation, whereas the opposite effect is apparent with programmes based on the best-known composers. This latter type of repertoire is related to more densely populated areas and those that have a higher mean population age. These findings show that orchestras are partly the result of the features of their environment and that, to some degree, they must accept their location vis-à-vis the quality and sustainability of their performance. Only a handful of internationally renowned and accredited orchestras lie outside these determining factors, and their strategy, as with other instances in cultural economics, must be framed within an analysis of the superstar phenomenon.

SEE ALSO: Chapter 29: Festivals; Chapter 41: Music publishing; Chapter 42: Non-profit organizations; Chapter 46: Performing arts.

REFERENCES Baumol, W.J. and W.G. Bowen (1966), Performing Arts: The Economic Dilemma, New York: Twentieth Century Fund. Bertaux, N., K. Skeirik and D. Yi (2015), ‘Art music and the economy: the Modernity Index and the Cincinnati Symphony Orchestra, 1895 to 2013’, International Journal of Economics and Business Research, 9 (4), 376–92. Brooks, A. (1999), ‘Do public subsidies leverage private philanthropy for the arts? Empirical evidence on symphony orchestras’, Nonprofit and Voluntary Sector Quarterly, 28 (1), 32–45. Brooks, A. (2006), ‘Nonprofit firms in the performing arts’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: Elsevier North-Holland, pp. 473–506.

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398  Handbook of cultural economics Dempster, D.J. (2002), ‘The Wolf Report and Baumol’s curse: the economic health of American symphony orchestras in the 1990s and beyond’, Harmony, 15 (October), 1–23. Falck, O., M. Fritsch and S. Heblich (2011), ‘The phantom of the opera: cultural amenities, human capital, and regional economic growth’, Labour Economics, 18 (6), 755–66, doi:10.1016/j.labeco.2011.06.004. Falck, O., M. Fritsch, S. Heblich and A. Otto (2018), ‘Music in the air: estimating the social return to cultural amenities’, Journal of Cultural Economics, 42 (3), 365–91, doi:10.1007/s10824-017-9310-4. Felton, M.V. (1992), ‘On the assumed inelasticity of demand for the performing arts’, Journal of Cultural Economics, 16 (1), 1–12. Felton, M.V. (1994), ‘Evidence of the existence of the cost disease in the performing arts’, Journal of Cultural Economics, 18 (4), 301–12. Flanagan, R.J. (2012), The Perilous Life of Symphony Orchestras: Artistic Triumphs and Economic Challenges, New York: Yale University Press. Gómez-Vega, M. and L.C. Herrero-Prieto (2019), ‘Measuring emotion through quality: evaluating the musical repertoires of Spanish symphony orchestras’, Journal of Cultural Economics, 43 (2), 211–45. Hong, J. (2014), ‘Data envelopment analysis in the strategic management of youth orchestras’, Journal of Arts Management, Law, and Society, 44 (3), 181–201. Ito, T. and D. Domian (1987), ‘A musical note on the efficiency wage hypothesis: programmings, wages and budgets of American symphony orchestras’, Economics Letters, 25 (1), 95–9. Lange, M. and W. Luksetich (1984), ‘Demand elasticities for symphony orchestras’, Journal of Cultural Economics, 8 (1), 29–48. Lange, M. and W. Luksetich (1995), ‘A simultaneous model of symphony orchestra behaviour’, Journal of Cultural Economics, 19 (1), 49–68. Luksetich, W. and P. Hughes (1997), ‘Efficiency of fund-raising activities: an application of data envelopment analysis’, Nonprofit and Voluntary Sector Quarterly, 26 (1), 73–84. Luksetich, W. and P. Hughes (2008), ‘Effects of subsides on symphony orchestra repertoire’, Working Paper No. 4, Economic Faculty, St Cloud State University, St. Cloud, MN. McGrath, T., R. Legoux and S. Sénecal (2017), ‘Balancing the score: the financial impact of resource dependence on symphony orchestras’, Journal of Cultural Economics, 41 (4), 421–39. Pompe, J., L. Tamburri and J. Munn (2011), ‘Factors that influence programming decisions of US symphony orchestras’, Journal of Cultural Economics, 35 (3), 167–84. Pompe, J., L. Tamburri and J. Munn (2018), ‘Subscription ticket sales for symphony orchestras: are flexible subscription tickets sustainable?’, Managerial and Decision Economics, 39 (1), 71–8. Seaman, B. (1987), ‘Price discrimination in the arts’, in W. Hendon and V. Owens (eds), Managerial Economics for the Arts, Akron, OH: University of Akron Press, pp. 47–60. Seaman, B. (2006), ‘Empirical studies of demand for the performing arts’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: Elsevier North-Holland, pp. 415–72. Tamburri, L., J. Munn and J. Pompe (2015), ‘Repertoire conventionality in major US symphony orchestras: factors influencing management’s programming choices’, Managerial and Decision Economics, 36 (2), 97–108. Throsby, D. (1996), ‘Economic circumstances of the performing artist: Baumol and Bowen thirty years on’, Journal of Cultural Economics, 20 (3), 225–40. Tobias, S. (2004), ‘Quality in the performing arts: aggregating and rationalizing expert opinion’, Journal of Cultural Economics, 28 (2), 109–24. Towse, R. (2014), Advanced Introduction to Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Zieba, M. and J. O’Hagan (2013), ‘Demand for live orchestral music – the case of German Kulturorchester’, Journal of Economics and Statistics, 233 (2), 225–45.

FURTHER READING The most comprehensive and wide-ranging study on the economy of orchestras is the work by Flanagan (2012), although it focuses on the case of American symphony orchestras. Towse (2014), in the section on performing arts and orchestras, offers an extremely rich summary of what needs to be known about the issue, together with the main analytical challenges to emerge. A complementary, albeit less well-known, aspect to this line of work is the study of musical facilities as economic prosperity, for which we recommend the works of Falck et al. (2011, 2018).

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44.  Participation

Victoria Ateca-Amestoy

Cultural participation takes many more forms than attendance at highbrow artistic manifestations. Both the opening of cultural boundaries and digitization pose significant challenges to characterize and explain the ways and reasons for individuals getting engaged in cultural experiences. In this chapter, we discuss how Becker’s (1973) economic approach to human behaviour can be a suitable model to study differences in individual rates and intensity of participation, regardless of the ways in which participation takes place. Humans satisfy a need for cultural appreciation through access to cultural goods and services that need to be combined with personal resources such as time, money, specific human cultural capital and social relations.

INTRODUCTION People engage with cultural experiences in many ways; they are driven by different motivations and limited by diverse personal and social constraints. Cultural participation is defined in the United Nations Educational, Scientific and Cultural Organization’s (UNESCO’s) 2009 Framework of Cultural Statistics as ‘the activities of audiences and participants in consuming cultural products and taking part in cultural activities and experiences (book reading, dancing, participating in carnivals, listening to radio, visiting galleries)’ (UNESCO 2009, p. 20). This is the last stage of the cultural cycle, a process that always starts with some creative act and ends in participation (UNESCO 2009). For some cultural manifestations, this process is highly mediated and needs to go through intermediate phases of production, dissemination, and exhibition, reception or transmission, as in the case of printed media. However, for some other manifestations, as in amateur artistic practice, creation and participation take place at the same time and are conducted by the same agent. Participation needs to be a voluntary act of engagement with some cultural manifestation (UNESCO 2012). When individuals decide to participate, they combine access to an artistic or cultural good or service with personal resources in an attempt to enjoy a pleasant or meaningful experience. Participation is a much broader concept than consumption, as buying a cultural good (for example, a book) does not guarantee that it is read and enjoyed, and that buying a cultural good is by no means the only way in which we can enjoy the non-material content embodied in that physical good. A distinctive characteristic of cultural participation is its voluntary nature. However, cultural experiences can be defined in many ways, as they can be more passive or active, creative rather than receptive, or more social and communitarian than individualistic and introspective. Some classifications distinguish modes of participation by the degree of involvement and creative control (for an overview, see UNESCO 2012). Traditional representation of cultural participation has concentrated on attending performing arts and heritage institutions, but what is and should be measured to represent 399

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400  Handbook of cultural economics cultural participation is hard to determine because of the opening of cultural boundaries (no longer with an exclusive interest in highbrow and legitimate cultural manifestations) and the widening of the mediated experiences owing to digitization. This is why merely measuring physically attendance at canonized cultural institutions misses an increasing part of the picture (de Haan and van der Broek 2012). Apart from reflecting individual free choice, related to what is done in discretionary free time, cultural participation is also conceptualized as a citizen’s right in democratic societies (United Nations 2009), highlighting the human right to the enjoyment of culture and recognizing the cohesive power of shared cultural experiences. Participation is linked to citizen’s rights and, in Europe, is related to the promotion of inclusive and reflective societies (Ateca-Amestoy et al. 2017). This cultural right also requires positive action by member states in order to ensure provision and equal access, thus creating new arguments for the public funding of some artistic events. Exploring and explaining differences in overall participation rates, it is important to check if there is effective equality of access to culture. O’Hagan (2017) discusses different approaches to characterize the equality of cultural participation, and presents how differences in participation rates reveal the difficulties for cultural policy to ensure representation of society not only in highbrow and heavily publicly funded cultural activities, but also in participatory ways of engagement. For publicly subsidized cultural activities, many highlight the arbitrary transfers to the wealthiest members of the society, sometimes neglecting other considerations such as the troublesome conception of merit goods à la Musgrave (2018), or non-use dimensions such as existence and bequest values of those manifestations.

MICROECONOMIC FOUNDATIONS OF PARTICIPATION IN THE ARTS In the economic approach proposed by Becker (1973), households are seen as factories that produce and enjoy commodities, which are the basis of the individual’s utility function and are typically produced inside the household with a combination of market goods and personal resources, such as time and some skills. Those skills are represented by the consumption capital accumulated over time, increased by past investment in formal and informal education as well as previous consumption. What differentiates cultural appreciation (in general, leisure) from any other commodity is the first-person criterion. In contrast to the commodity food, that can be produced by someone else and enjoyed by the individual, cultural appreciation has to be produced and enjoyed at the same time by the same individual. This implies that it is a highly time-intensive commodity. The economic approach to cultural participation explains differences in observed participation by the variations in available personal resources, that is, personal and social time, money and material resources, and cognitive ability. Gray (2011) explains how individual decision models characterize the allocation of scarce resources (time and money), together with complementary factors (for example, individual cultural capital and social capital) and resource availability, to maximize utility defined by the cultural appreciation and as a composite commodity (related to demand; Lèvy-Garboua and Montmarquette 2011). Some means of participation are more time intensive, others are

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Participation  401 more money intensive, some are more social, yet others require higher levels of specific cultural human capital, and so on. The availability of resources explains differences in individual participation choices. We discuss how the model would explain differences in three traditional dimensions of cultural participation, namely, live attendance, media consumption and active practice. Attendance at a highbrow arts event, such as a chamber music concert, requires the audience to have the competence to understand and enjoy its meaning (typically acquired by formal education, specific artistic education and early exposure), as well as some synchronous time with like-minded others (it being a highly social activity) that has to coincide with the timing of the performance. Moreover, it requires a reasonable proximity to the place where the event takes place. Further, individuals might have to buy a ticket, pay transportation or childcare. Thus, in order to produce a pleasant cultural experience, different individuals would face different shadow prices. Enjoying that same concert at home could be achieved if the individual bought a record or watches a streamed performance. He or she would need to have the relevant equipment at home and synchronize his or her time in the case of the live-streaming or decide when to listen to the record. Also, the highly specialized cultural capital to enjoy the concert still would be required. Finally, this individual could decide to interpret the concert himself or herself with other amateur musicians, in which case the instruments would be needed but, more importantly, a very substantial endowment of cultural capital would be required in order to interpret skilfully and beneficially. Also, the individual would need to have access to specialized networks to find people to play with. Individual differences in choice can be therefore be rationalized within the Beckerian framework for any type of cultural engagement.

EMPIRICAL RESULTS ABOUT THE DETERMINANTS OF CULTURAL PARTICIPATION Individual decision-making models allow us to derive testable hypotheses about the effect of different variables on participation. These are further complemented with observations regularly reported in the literature. The time allocation model inside the household á la Becker presents an individual decision-making framework to analyse how different members of the household allocate their time and money to jointly produce and enjoy pleasant experiences that we model as the commodity of arts appreciation (Becker 1973). Individuals face constraints when trying to fulfil leisure needs owing to differences in the full price of those commodities, in their own resources and in the resources of other members of the household. This also implies that observed differences in behaviour should be attributed to differences in resources, and not to differences in tastes, which are assumed to be stable through time and not very different across individuals. Observed differences in participation would be also rationalized by differences in the productivity of some individuals to derive more pleasurable experiences out of one type of services or the other, which in turn, explain differences in the full price of leisure commodities. When using the Beckerian framework, education is the most important variable, a result that fits with the finding of having education as the single best predictor of cultural participation. Both specific artistic and formal education are key inputs in the production

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402  Handbook of cultural economics function that determine skills and the available stock of consumption capital for a given individual. The higher the level of education, the higher the understanding and fulfilment that individuals can derive from cultural engagement (O’Hagan 2017). This is the key determinant of one of the most important barriers to participation (lack of interest) and, more importantly, to explain participation in highbrow cultural practices as well as its intensity (Willekens and Lievens 2016; Suarez-Fernandez et al. 2019). The effect of education is found to be remarkably similar across countries; see Falk and Katz-Gerro (2016) for heritage visits across 24 countries in the European Union (EU). Education is also related to digital skills, so its effect on digital cultural engagement could be even greater (Ateca-Amestoy and Castiglione 2016). Informal education and early socialization are also found to have a positive effect on cultural participation (early exposure to the arts is sometimes directly reported and sometimes represented by parental educational level). Past consumption and early exposure to the arts are important for highbrow engagement. This is in line with learningby-consuming and rational-addiction models, first, because of the cumulative nature of personal cultural capital and, secondly because of the experience good nature of cultural goods (O’Hagan 2017). However, other processes of socialization, such as adult socialization, have been explored less (probably, owing to lack of suitable data), except for some research on spouses’ participation. The influences of other members of the household can operate between generations or across members of the same generation (spouses in Upright 2004; Lazzaro and Frateschi 2017). The results of participation for subsamples of men and women (Muñiz et al. 2014) differ from the results of participation for subsamples of men and women that are identified at the household level (Montgomery and Robinson 2010). Peer effects on participation are also found for audio-visual participation of teenagers, even if this can be an individualistic practice (Escardíbul et al. 2013). In general, social networks, that is, the number of people with whom someone usually spends leisure time, are found to have a positive effect on participation (Willekens and Lievens 2016). There might be other factors determining the specific cultural consumption capital of the individual, for instance, being a creative worker. Bille (2010) tests for the influence of creative-class belonging on engagement in leisure activities and finds significant effects on leisure and cultural habits. Income determines the available material sources to produce cultural appreciation. This variable has a positive effect on participation, but the possible luxury-good nature (income elasticity above 1) of different types of cultural goods and services is not a clear. Differences in discretionary time availability are also among the main drivers of differences in social participation in leisure activities. Unlike some other commodities, in order to produce leisure, the individual must both produce and consume that commodity in his or her own time. The full (shadow) price of leisure is a combination of the prices of market goods and the opportunity cost of time (forgone earnings of time not dedicating to paid work, opportunity cost of time dedicated to household chores, and so on). For social cultural participation, leisure time has to be synchronous with enjoyable company others, since one of the most important reasons for participation is spending time with friends and family. Differences in household composition, such as the presence of dependent members, would explain part of the observed differences in participation or the choice between alternative ways of engagement.

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Participation  403 Labour status also determines time availability. However, having a great deal of time not committed to paid work, for example, if unemployed, does not imply higher engagement in some cultural activities. As regards time availability and differences by gender, Willekens and Lievens (2016) found constraints related to childcare have a stronger negative effect for women, and working full-time increases the participation rates of women, but this is not the case for men. Gender is classified by Seaman (2005) among the mixed factors, together with sexual orientation, race, ethnic origin and others, that determine whether some individuals are more likely than others to participate in social activities. In addition to consideration of differences in the opportunity cost of time by gender, women are more likely to be socialized early in cultural and artistic activities, female adult participation is more likely than male participation and the intensity of participation for women tends to be higher. Cameron (2019) describes the influence of race and ethnicity as more problematic. Differences are found for the US that could be interpreted as early socialization idiosyncrasies for ethnic groups (NEA 2015). One of the worries of cultural administrators is the ageing of the audiences of the performing arts. The effect of age on participation is not clear and could partially capture cohort effects relating to, for instance, digital skills or health status. While older individuals have more time to invest on their specific cultural consumption capital, some cultural practices are more popular among younger individuals. The locational provision of cultural services is subject to economies of agglomeration, so both the ability to participate at all in live events (performing arts and visits) as well as the ability to participate more intensely depend on the availability of resources in the place of residence. It is surprising that bigger places of residence not only are associated with higher attendance rates, but also with higher rates of purchase of newspapers and periodicals or even more digital access to cultural content. Evans (2016) discusses the divide between cultural participation and provision of accessible cultural infrastructure and services. Individuals do not only engage with cultural expressions in their home towns. Cultural participation is a popular activity both for cultural travellers (or cultural tourists), and for people travelling for other reasons.

SOURCES OF INFORMATION AND EMPIRICAL METHODS While there are some international surveys on cultural participation (special modules of the EU Survey on Income and Living Conditions, and various releases of Eurobarometer, Latinobarometer, World Values Survey, European Social Survey, International Social Survey Programme and similar), researchers have identified problems in collecting and analysing those data (see O’Hagan 2017). A great deal of the evidence comes from national surveys and, as Ciccercia (2017) argues, the statistical representation of cultural participation in different countries is shaped by its distinctive values and customs. There are specific surveys on cultural participation conducted by official statistical agencies in most European countries, the US, Canada, China and Japan, and in most Latin American countries (UNESCO 2012). In 2009 and 2012 UNESCO proposed a general framework and guidelines to normalize what is measured. In an effort to overcome the challenges of digitization and

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404  Handbook of cultural economics e­xpanding boundaries of culture and cultural participation, the European Statistical System Network on Culture (ESS-net) reports for the EU decided to adopt the ICET ­information–communication/community–enjoyment and expression–transaction (ICET) model (an adaptation of a framework to address Internet usage). This model acknowledges four forms of cultural participation: information (seek, collect and spread information on culture); communication and community (to interact with others on cultural issues and to participate in cultural networks); enjoyment and expression (to enjoy exhibitions, art performances and other forms of cultural expression, to practise the arts for leisure, and to create content online); and transaction (to buy art and to buy or reserve tickets for shows). However, the ICET-framework implementation is still rarely found in national surveys on cultural participation. Alternative ways of measuring and characterizing cultural participation are found in the analysis of time use surveys (for example, the American Time Use Survey). Since time is a strategic complement resource in the production of cultural appreciation, the surveys can be a valuable source of information on cultural participation. A radical new approximation to study cultural participation is by means of usergenerated data. This includes information from digital transactions, as in ticketing, social network content or digital traffic. Currently, analysis shows no big divergences between the results from surveys from representative samples of the population and from online analysis (Hanquinet et al. 2019). What can be explained is dramatically determined by the data available on how participation is measured and on which explanatory variables are included. There are a number of empirical challenges when estimating participation models. We comment on two of them and present some of the econometric strategies. The first challenge is disengagement and how to deal with very low rates of participation for some arts practices. Some research distinguishes between interested non-attendees and the truly disengaged people (NEA 2015). This implies the existence of two different subpopulations. The first is formed by individuals who would be willing to participate if some of the restrictions they face on resources were alleviated (for example, if they had more money, if prices were lower, or if they had more leisure time), so that their observed choice is the result of a utility maximization process whereby they reach a corner solution. The second subpopulation is formed by individuals who choose zero and are true nonparticipants. This unobserved heterogeneity is frequently dealt with by estimating latent class models of some class (such as finite mixture models). There are regular findings that indicate that some variables determine taste, whereas others are related to the availability of resources and determine more or less frequency of engagement (Suarez-Fernandez et al. 2019). The second challenge is related to the possible complementarity or substitutability of different ways of participation, in particular for digital participation and traditional live participation. It remains hard to find supportive evidence for the competing hypotheses of cannibalization or of market creation between digital alternatives (Mihelj et al. 2019), or to identify the areas in which they can be different or more attractive to different groups of people, for instance, for younger members of audiences (Evrand and Krebs 2018).

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Participation  405

SOME TOPICS OF INTEREST AND A REVIEW OF ONGOING DEBATES There is an increasing interest in further understanding the drivers of and barriers to participation (NEA 2015), as well as better understanding the outcomes of cultural participation at the individual and aggregate levels. Bonet and Négrier (2018) examine different paradigms for cultural policy, and identify social, technological and political reasons to understand contemporary dimensions of participation and to explain aggregate differences. Only when we understand the barriers will policy-makers be able to design effective policies to increase and extend cultural participation. Commonly reported barriers are lack of interest linked to low educational attainment, but also difficulty of access. For the outcomes of participation, a great deal more research is needed to identify causal effects. Positive outcomes include the effects of cultural participation in health and well-being (Węziak-Białowolska 2016), and in cognitive abilities of children (Cabane et al. 2016), as well as social resilience, civic participation and engagement and inclusion of disadvantaged groups. For some people, this implies an instrumentalization of the arts and culture that are seen as a means by which to solve societal challenges. However, denying that powerful transformative role of participation would imply a misuse of collective resources and, at the individual level, it would imply not taking into consideration that many people who participate are driven by values beyond the intrinsic enjoyment of the arts, with socializing among friends and family members being the most common motivation for arts attendance (NEA 2015).

SEE ALSO: Chapter 20: Cultural diversity; Chapter 24: Demand; Chapter 52: Ratings, reviews and recommendations.

REFERENCES Ateca-Amestoy, V. and C. Castiglione (2016), ‘The consumption of cultural goods through the internet. How is it affected by the digital divide?’, ACEI Working Paper No. AWP-04-2016, Association for Cultural Economics International. Ateca-Amestoy, V., V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds) (2017), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer. Becker, G.S. (1973), The Economic Approach to Human Behaviour, Chicago, IL: University of Chicago Press. Bille, T. (2010), ‘Cool, funky and creative? The creative class and preferences for leisure and culture’, International Journal of Cultural Policy, 16 (4), 466–96. Bonet, L. and E. Négrier (2018), ‘The participatory turn in cultural policy: paradigms, models, contexts’, Poetics, 66 (February), 64–73. Cabane, C., A. Hille and M. Lechner (2016), ‘Mozart or Pelé? The effects of adolescents’ participation in music and sports’, Labour Economics, 41 (August), 90–103. Cameron, S. (2019), ‘Individual choice behaviour’, in S. Cameron (ed.), A Research Agenda for Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 41–62. Ciccercia, A. (2017), ‘Measuring cultural participation in Italy’, in V. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer. De Haan, J. and A. van der Broek (2012), ‘Nowadays cultural participation: an update of what to look for and

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406  Handbook of cultural economics where to look for it’, in ‘European Statistical System Network on Culture (ESS-net) final report’, Eurostat, Luxemburg, May, pp. 397–417. Escardíbul, J.O., T. Mora and A. Villarroya (2013), ‘Peer effects on youth screen media consumption in Catalonia (Spain)’, Journal of Cultural Economics, 37 (2), 185–201. European Statistical System Network on Culture (ESS-net) (2012), ‘European Statistical System Network on Culture (ESS-net) final report’, Eurostat, Luxemburg. Evans, G. (2016), ‘Participation and provision in arts & culture – bridging the divide’, Cultural Trends, 25 (1), 2–20. Evrand, Y. and A. Krebs. (2018), ‘The authenticity of the museum experience in the digital age: the case of the Louvre’, Journal of Cultural Economics, 42 (3), 353–63. Falk, M. and T. Katz-Gerro (2016), ‘Cultural participation in Europe: can we identify common determinants?’, Journal of Cultural Economics, 40 (2), 127–62. Gray, C.M. (2011), ‘Participation’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 326–31. Hanquinet, L., D. O’Brien and M. Taylor (2019), ‘The coming crisis of cultural engagement? Measurement, methods, and the nuances of niche activities’, Cultural Trends, 28 (2–3), 198–219. Lazzaro, E. and C. Frateschi (2017), ‘Couples’ arts participation: assessing individual and joint time use’, Journal of Cultural Economics, 41 (1), 47–69. Lévy-Garboua, L. and C. Montmarquette (2011), ‘Demand’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 177–89. Mihelj, S., A. Leguina and J. Downey (2019), ‘Culture is digital: cultural participation, diversity and the digital divide’, New Media & Society, 21 (7), 1465–85. Montgomery, S.S. and M.D. Robinson (2010), ‘Empirical evidence of the effects of marriage on male and female attendance at sports and arts’, Social Science Quarterly, 91 (1), 99–116. Muñiz, C., P. Rodríguez and M.J. Suárez (2014), ‘Sports and cultural habits by gender: an application using count data models’, Economic Modelling, 36 (January), 288–97. Musgrave, R.A. (2018), ‘Merit goods’, in Macmillan Publishers Ltd (ed.), The New Palgrave Dictionary of Economics, London: Palgrave Macmillan. National Endowment for the Arts (NEA) (2015), ‘When going gets tough: barriers and motivations affecting arts attendance’, NEA Research Report No. 59, National Endowment for the Arts, Washington. O’Hagan, J. (2017), ‘Attendance at/participation in the arts by educational level. evidence and issues’, in V. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Prieto-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer. Peuckert, C. (2019), ‘Flexible digital supply behavior’, in S. Cameron (ed.), A Research Agenda for Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 63–86. Seaman, B.A. (2005), ‘Attendance and public participation in the performing arts: a review of the empirical literature’, Research Paper No. 06-25, Andrew Young School of Policy Studies, Georgia State University, Atlanta, GA. Snowball, J. (2019), ‘Government policy’, in S. Cameron (ed.), A Research Agenda for Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 116–40. Suarez-Fernandez, S., M.J. Perez-Villadoniga and J. Prieto-Rodríguez (2019), ‘The changing role of education as we move from popular to highbrow culture’, Journal of Cultural Economics, doi: 10.1007/s10824-019-09355-2. United Nations (2009), ‘Right of everyone to take part in cultural life’ (art. 15, para. 1 (a), of the International Covenant on Economic, Social and Cultural Rights), General comment No. 21. Committee on Economic, Social and Cultural Rights, 43th session, United Nations. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2009), The 2009 UNESCO Framework for Cultural Statistics, Montreal: UNESCO Institute of Statistics. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2012), Measuring Cultural Participation, Montreal: UNESCO Institute of Statistics. Upright, C.B. (2004), ‘Social capital and cultural participation: spousal influences on attendance at arts events’, Poetics, 32 (2), 129–43. Węziak-Białowolska, D. (2016), ‘Attendance of cultural events and involvement with the arts – impact evaluation on health and well-being from a Swiss household panel survey’, Public Health, 139 (October), 161–9. Willekens, M. and J. Lievens (2016), ‘Who participates and how much? Explaining non-attendance and the frequency of attending arts and heritage activities’, Poetics, 56 (June), 50–63.

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Participation  407

FURTHER READING For a comprehensive view of cultural participation statistics, see ESS-net (2012) and UNESCO (2012). For a review of open questions and further research to better understand cultural participation, see Cameron (2019), Peukert (2019) and Snowball (2019). Microdata for participation in the US derived from different editions of the Survey of Public Participation in the Arts and can be accessed via the National Archive of Data on Arts and Culture (NADAC) at https://www.icpsr.umich.edu/icpsrweb/NADAC/ (accessed 10 December 2019). An overview of participation in European countries using different data sources can be found in the Compendium of Cultural Policies and Trends in Europe at https://www.culturalpolicies.net/themes/cultural-participation-andconsumption/ (accessed 10 December 2019).

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45.  Performance indicators

Trilce Navarrete Hernández

Performance indicators (PIs) are used in relation to concepts for which a direct measure is not always observable when monitoring development towards a desired goal. For this reason, they are devised as combined relevant quantifiable values that can be followed in time to give a partial metric of a given action. Performance indicators may be used to report effectiveness by measuring profitability within the commercial sector, for example. In contrast, arts and cultural organisations, as well as other non-profit sectors, have a specific legal and financial structure to support the organisational goals related to delivering intangible services (such as a cultural experience, education, health or sustainability) and to advance societal values (Forbes 1998). In addition, services provided may have public-good characteristics, may be a natural monopoly, may suffer from socially inefficient levels of consumption (or production) owing to information asymmetries, and may receive public subsidy or be publicly provided, requiring a different approach than a simple investor-management accountability system. As a result, PIs to measure effectiveness are not easy to define and, if developed, may not indicate whether the organisation is operating on its production frontier, that is, efficiently (Peacock 2003). Performance indicators are intended to support decision-making on the allocation of resources by evaluating opportunity costs and, in the cultural sector, have often responded to changes in cultural policy. Schuster (1997) notes three characteristic periods: in the 1960s, the concept of social indicators was developed to complement economic indicators; in the 1980s, attention moved towards making inventories of the size and activity of the sector; and in the 1990s, a focus on monitoring the management of the use of public funds for accountability drove the design and use of PIs. We can add two additional turning points in the development of PIs for the arts and culture sector. First, the recognition of intangible cultural heritage and, to a certain extent, digital heritage1 by UNESCO in 2003, which have raised the need for revised indicators. The publication of the latest UNESCO framework for cultural statistics in 2009 reflects this effort. Second, as we approach 2020, the increased availability of digital metrics has made quantitative measurement more amenable to arts and culture, particularly the creative industries, and exploration of new metrics and PIs is under way. Performance indicators can be grouped into three main types, depending on their function: for internal quality improvement (formative assessment PIs), for external accountability (summative assessment PIs) or simply for descriptive purposes (descriptive PIs) to understand the given area of inquiry. We describe each type and provide some examples.

FORMATIVE ASSESSMENT PIs Performance indicators of this type (1) are used for internal quality assessment, (2) respond to a specific internal policy decision process, (3) are meant to document internal 408

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Performance indicators  409 performance and (4) are change-orientated in order to improve the quality of the work being performed. These PIs are tailored to the specific goals, make-up and history of an organisation and may not always be compatible with those of other organisations. The type of PIs created for formative assessment can also be referred to as micro indicators (Madden 2005). Generally, organisations develop a set of critical PIs, selected and defined to support management in monitoring factors of particular interest regarding an activity, an organisational unit or a desired goal. These are referred to as key performance indicators (KPIs) and are aligned with the organisation’s strategy. For example, an institution such as a museum may want to produce large quantities of scanned material for online publication, where the goals are to increase access for research, to reduce the risk of damage or theft of the originals by users and to lower the price per scan. In this case, the quality of the process is defined by the ability to capture the relevant parts of the object in an image and by the correctness of the file name, audited mostly automatically across the production chain with some manual quality controls. Such an institution would develop a set of PIs that document the price per error-free scan and the number of requests of scans by consumers over time. In contrast, another institution may consider the number of objects manually photographed using the highest quality of standard (for example, regarding colour, sharpness, light, or background) and the file format, giving less attention to economies of scale and focusing instead on custom imaging. These examples demonstrate that while two institutions can have a similar goal (that of creating accessible quality digital images of the collection), they may nevertheless approach evaluation differently and use different PIs. Taking another example, from museums, quality of output can be reported as the number of donors and amount of funds in a year to make a certain number of acquisitions possible, while another museum may decide to stop acquisitions altogether and rather focus on repatriation or restitution of collections, reporting use of private funds to achieve this. Indicators measuring resources, their provision and costs, are the most widely used, followed by indicators of service provision. These indicators can respond to questions of internal efficiency in the allocation of resources to a given goal, such as the number of staff needed to deliver a service in a given time. Instead, measures of outcome are not simple to design, and pose methodological problems as they can be profoundly influenced by factors beyond the control of the arts and culture institution. Whereas an effective healthcare system, for example, is measured by the ability to attain improvements in health (say, to decrease the post-neonatal mortality rate), effectiveness in arts and cultural services is less easy to express. In addition, factors that profoundly influence the outcome will have to be considered, such as the local social and economic circumstances. Increasingly, arts and culture institutions are asked to articulate their value propositions or to demonstrate the impact of the services provided. Few institutions keep track of consumers (repeat visits), and most instead report general consumption, where the volume of ticket sales is used as an indirect indicator of artistic quality. Documenting change in composition or participants has proven challenging. A certain level of harmonisation in PIs can be achieved when comparison between institutions is desired, eventually making formative assessment PIs part of a set of summative assessment PIs. This is the case of library PIs which evolved from an internal work process and have been standardised internationally (see the ISO 11620 Information

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410  Handbook of cultural economics and documentation – Library performance indicators) (ISO 2014). Such an international standard aims at endorsing the ‘use of performance indicators regarding the quality of library services in libraries and to spread knowledge about how to conduct performance measurement’ (https://www.iso.org/standard/56755.html, accessed 13 December 2019). For museums, there is an international standard on the collection of statistics (ISO 18461 International museum statistics; ISO 2016), while an international standard on the formulation of PIs in under way (ISO 21246 Information and documentation – Key indicators for museums; ISO forthcoming).

SUMMATIVE ASSESSMENT PIs Performance indicators of this type are designed to verify performance, mostly for external accountability based on comparisons with a set benchmark or desired quality of service, or to verify compliance with a certain regulation. Performance indicators created for external accountability are designed by government bodies, such as cultural councils, and international organisations, such as UNESCO. These institutions make use of the available data to respond to their policy questions but can also develop tools to gather the desired data. These indicators are used to specifically capture performance in a particular type of cultural form, such as music, or institution type, such as museums (meso indicators), or for national or regional comparison across the entire sector (macro indicators). The UNESCO Culture for Development Indicators (CDIS) describe a set of 22 qualitative and quantitative indicators across seven policy dimensions to map the role of culture in development. Culture may have an impact on: (1) development processes in the economy, measured by contribution to gross domestic product, employment and household expenditure; (2) in education, measured by type of education and professional training; (3) in governance, measured by policies, infrastructures and civil society; (4) in society, measured by participation, identity-building and trust; (5) in gender, measured by equity; (6) in communication, measured by freedom of expression, Internet use and diversity of media content; and (7) in heritage, measured by heritage sustainability (UNESCO 2014). Performance indicators used for external accountability have encountered some issues. Schuster (1997) noted that PIs can be extremely powerful to dictate behaviour when attached to financial rewards, since cultural institutions may want to manipulate results to gain a greater benefit. This opportunistic strategic behaviour is further observed as managers choose to cite or ignore indicators when convenient. Another issue is the difficulty of generalising results across institutions, using the same method to report performance, as this may lead to skewed comparisons. This is because institutions may pursue different objectives (responding to their organisational mission), may have different needs (for instance, a video museum has different expenses than a historical museum when delivering a service), may have different costs (for instance, owing to organisation size or location), may benefit from different levels of managerial competence in the use of resources or there may simply be errors in the measurement (as organisations manipulate results for their own benefit).

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Performance indicators  411

DESCRIPTIVE PIs Descriptive PIs, used for monitoring activities, are not specific to an organisation or a programme but instead are meant to track changes across longer periods of time. For example, the measurement of the number of museums in a given region relative to the population in the same region can be used as indicator of the cultural infrastructure available or the equity in service delivery. Similarly, the share of the population that participates in a cultural activity can be used as indicator of cultural vitality or social engagement, and the number of volunteers per visitor can be used as indicator of economic impact or community engagement.

CHALLENGES There are three main challenges to the construction of indicators: the interpretative nature of definitions and concepts, the availability and quality of data, and ever-changing requirements. Definitions All indicators are constructed to provide an approximate numerical measure of a concept, which is generally actioned by means of a set of PIs. Performance indicators are therefore strongly susceptible to the definitions guiding them (Madden 2005). It may be inevitable that by selecting particular PIs, some aspects may become visible while others may be marginalised. Taking a museum example, using the number of visits as an indicator of the quality of an exhibition excludes the number of citations of a publication reporting the curatorial investigation behind the exhibition. Performance indicators are conceptual technologies that shape which issues are discussed and how. Performance indicators are meant to measure and monitor activities, to compare against a strategic vision or a regulation, but they are not able to explain why these results are obtained. This is the role of the analyst interpreting the data (methods generally include ratios, relations, cluster analysis, regression analysis, data envelopment analysis and creation of composite indicators). The selection of PIs is crucial, as is transparency of their analysis. This is particularly noticeable when devising metrics for abstract, heterogeneous concepts, where quantification is fuzzy, such as for quality of service. Proxies or surrogates often are devised, for example, to quantify quality based on the novelty of programming, or prestige and recognition of the artists (Gómez-Vega and Herrero-Prieto 2019). Since PIs are based on quantitative metrics, differences in the definitions of related terms may also prove a challenge. This is the case of the application of the definition of museum, which in some countries may include institutions open by appointment only, while in other countries only includes institutions open regularly throughout the year. All country definitions are interpretations of the official International Council of Museums (ICOM) definition of a museum. This makes the work of large statistical centres highly valuable to homogenise when possible, as in the case of Eurostat.

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412  Handbook of cultural economics Data Availability and Quality Performance indicators ‘lie at the nexus between the production of cultural data and the analysis of cultural phenomena’ (Madden 2005, p. 221). That is, data is gathered based on what is to be analysed and with an understanding of the services developed. However, owing to the cost of data collection, there is a tendency to focus on measures available (such as concert tickets or streaming sales), neglecting less easily quantifiable phenomena (such as participation in amateur choirs). One of the most difficult metrics is quality of service, making it almost impossible to truly assess efficiency. Quality of data is a further important issue, where results may reflect the collection and analysis process rather than the service being evaluated. Data availability may be affected by changes in policy priorities, which may expand, change or reduce data gathered across years, or changes in funds available to gather the data, making it difficult to analyse changes over time. In the Netherlands, the national statistical office (Centraal Bureau voor de Statistiek, CBS) has stopped collecting data about archives owing to a budget reduction; this had not been taken up by any other national institution at the time of writing. Museum data, however, has been streamlined and collected collaboratively with the National Museum Association (NVM). Increasingly, digital technology allows for automated logs of all transactions, yet these are generally privately owned and rarely available for public analysis or academic research. Data-gathering requires commitment, systematic work and long-term vision. These are not always available. An example can be found in the data available about museums in the European Group of Museum Statistics (EGMUS), which show varying activity across countries, years and data reported. In addition to the efforts of individuals employed in statistical offices (or other responsible institutions), quality data-gathering requires resources as well as a policy directive to guide the recurrent production and analysis of records and surveys. An increasingly digital lifestyle has enabled the documentation of a number of transactions that could feed a comprehensive analysis of arts and cultural activities and lead to eventual correlations. Statistical offices are partnering with telecommunication firms to purchase data-sets on the behaviour of tourist groups from a chosen region, for example. The challenge of the newly available big data lies in the rules and regulations protecting privacy, as well as in the cost of data acquisition and analysis, particularly when held by a private firm (for example, Google). Changing Requirements With the emerging need for evidence-based policy, new indicators require new data sources. Sustainable Development Goals (SDGs) conceived with UNESCO, for example, envision culture playing a key role in the development of economies, societies and individual capital. Furthermore, new forms of cultural production and consumption are emerging, which enable new insights in the arts and culture ecosystem. This requires policy-makers, as well as institutions, to devise new PIs to better respond to their needs. Performance indicators for education have a more robust collection system, for instance, to consider educational attainment (counting resits, dropout rates and progression) and employment and earning benefits. To date cultural indicators remain a snapshot

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Performance indicators  413 of cultural behaviour, even if they are tracked across time, because of the lack of analysis of a holistic cultural system. Currently available data on cultural participation does not allow for estimating the financial incentives to invest in arts and culture (measured by the private and public costs and benefits for an individual attaining a certain level of participation). This is an established measure in education (OECD 2018). The position may change as result of the SDGs and the increasing prominence of the creative industries within the economy.

POLICY IMPLICATIONS There is a complex relationship between the production of PIs and their interpretation, the former generally responding to the needs of policy analysis for the latter (Bonet 2004; Madden 2005). Performance indicators are a strong transformative tool owing to their capacity to reflect and explain determinants. The principal–agent relationship in the arts and culture sector is extremely complex. The government provides funding, as well as regulations, and requires PIs for accountability and future policy strategy decisions. The value of statistical information to support PIs is dependent on the relevance of the data collected, on its comparability and on its sustainability (homogeneous data series) (Bonet 2004). Development of PIs for the arts and culture sector could benefit from a policy practice of evaluating services across sectors and across time periods. Whereas education and health are understood as systems,2 provision of arts and culture remains ad hoc and is not treated holistically within regions or across time. Why are PIs for arts and culture programmes lagging behind other sectors such as health or education? Schuster (1997) proposed three main reasons: policy-makers rely on evaluations of the producers and allocate funds accordingly, evaluations are costly and resources scarce (paying for an evaluation will reduce available grants), and negative evaluations are not welcomed. It is important to remember that ‘there is no such thing as “the performance” of cultural institutions’, but that PIs provide a quantitative measure on the area to be evaluated and are never an exhaustive representation of an arts and culture organisation (Pignataro 2011, p. 336). Similarly, PIs should not be prescriptive in their interpretation; instead, they should serve as tools for further reflection on the quality of the service or the ability to reach a policy goal.

NOTES 1. Digital heritage was first recognised by UNESCO in 2003 with the Charter on the Preservation of Digital Heritage, in which digital production of, access to and preservation of information and creative expression was identified to be part of a new cultural legacy. In 2015, the UNESCO Guidelines for the Recommendation Concerning the Preservation of, and Access to, Documentary Heritage Including in Digital Form recognised cultural documentary information to be at the core of all archive, library and museum collections. These collections are increasingly digital, enabling the emergence of new services and forms of consumption. 2. The healthcare system is focused on the service providers (health prevention, promotion and protection), while the health system is conceptualised more broadly, to include non-healthcare factors, such as lifestyle, the socio-economic context of the consumer or human biology (Arah et al. 2006).

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414  Handbook of cultural economics

SEE ALSO: Chapter 42: Non-profit organizations; Chapter 48: Political economy; Chapter 50: Public support.

REFERENCES Arah, O., G. Westert, J. Hurst and N. Klazinga (2006), ‘A conceptual framework for the OECD Health Care Quality Indicators Project’, International Journal for Quality in Health Care, 18 (1), 5–13. Bonet, L. (2004), ‘Reflexiones a Propósito de Indicadores y Estadísticas Culturales’ (‘Reflections regarding indicators and cultural statistics’), in Boletín GC: Gestión Cultural No. 7: Indicadores y Estadísticas Culturales. Forbes, D. (1998) ‘Measuring the unmeasurable: empirical studies of nonprofit organisation effectiveness from 1977 to 1997’, Nonprofit and Voluntary Sector Quarterly, 27 (2), 183–202. Gómez-Vega, M. and L. Herrero-Prieto (2019) ‘Measuring emotions through quality: evaluating the musical repertoires of Spanish symphony orchestras’, Journal of Cultural Economics, 43 (2), 211–45. International Organization for Standardisation (ISO) (2014), ISO 11620:2014, 3rd edn, ISO/TC 46/ SC 8, Information Science, Quality Statistics and Performance Evaluation, ICS 01.140.20, Geneva: ISO. International Organization for Standardisation (ISO) (2016), ISO 18461:2016, ISO/TC 46/ SC 8, Information Science, Quality Statistics and Performance Evaluation, ICS 01.140.20, Geneva: ISO. International Organization for Standardisation (ISO) (forthcoming), ISO/DIS 21246. ISO/TC 46/SC 8, Information Science, Quality Statistics and Performance Evaluation, Geneva: ISO. Madden, C. (2005), ‘Indicators for arts and cultural policy: a global perspective’, Cultural Trends, 14 (3), 217–47. Organisation for Economic Co-operation and Development (OECD) (2018), Education at a Glance, OECD Indicators, Paris: OECD. Peacock, A. (2003), ‘Performance indicators and cultural policy’, Economia della cultura, magazine of the Associazione per l’Economia della Cultura/AEC, Bologna, accessed 13 December 2019 at http://www.econo​ miadellacultura.it/english.html. Pignataro, G. (2011), ‘Performance indicators’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 332–8. Sacco, L., G. Ferilli and G. Tavano (2018), ‘From Culture 1.0 to Culture 3.0: three socio-technical regimes of social and economic value creation through culture, and their impact on European cohesion policies’, Sustainability, 10 (11), 38–60. Schuster, M. (1997) ‘The performance of performance indicators in the arts’, Nonprofit Management and Leadership, 7 (3), 253–69. Srakar, A., V. Čopič and M. Verbič (2018), ‘European cultural statistics in a comparative perspective: index of economic and social condition of culture for the EU countries’, Journal of Cultural Economics, 42 (2), 163–99. United Nations Educational, Scientific and Cultural Organisation (UNESCO) (2014), Culture for Development Indicators: Methodology Manual, Paris: UNESCO.

FURTHER READING Literature on PIs for the health or education systems is much richer than literature on PIs for arts and culture. However, Madden (2005) provides a useful a global overview of IPs and related issues at the turn of the twentyfirst century. For a methodological discussion, Srakar et al. (2018) provide an example of the economists’ approach to constructing a cultural index as composed indicator for public financing and participation, education in culture, and private financing of culture. Sacco et al. (2018) propose the application of existing indicators towards eight areas of cultural participation impact: innovation, welfare and cultural welfare, sustainability, social cohesion, entrepreneurship, lifelong learning, soft power and local identity.

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46.  Performing arts Ruth Towse

The term performing arts is a broad grouping of live art forms, only some of which have been researched in cultural economics. While orchestras, opera, ballet and spoken theatre have all featured in the subject, circus, puppetry and mime, among other live performance, have not. Popular music has been dealt with under the heading of the music business and analysed as a mixture of live and recorded work, and popular musicals have had some mention but, largely, work on performed arts in cultural economics has concentrated on building-based, subsidised performance by arts organisations, including in the past few years the digital transmission of live events to cinemas and other means of access. In some cases, the organisation could be that of a festival which brings together many different performances or that concentrates on one art form, such as a theatre festival, or combines performing arts with other offerings, such as art exhibitions and talks; festivals have become increasingly popular with audiences and promoters. The performing arts have played a significant part in the development of cultural economics, owing to the work by Baumol and Bowen (1966) which set the theoretical and empirical framework for research in this subject, initially in relation to the performing arts but later spreading to a broader range of topics. Their focus on rising costs in the performing arts provided the inspiration for much of the subject matter of cultural economics in subsequent years. The essential features of their analysis are that productivity increases from technological progress in the economy are at best limited in the arts (the ‘stagnant’ sector) owing to the inherent requirements of the performed repertoire and, being also labour-intensive, are subject to cost pressures from the ‘dynamic’ other sectors of the economy in which workers are rewarded by higher wages. These combined effects push up costs in the live performed arts and, without some countervailing effect, such as subsidy or sponsorship, prices must rise in the arts, reducing demand and access by those who cannot afford to pay them; alternatively, quality might be compromised in cost-cutting exercises (the ‘artistic deficit’). Digital technologies have increased audiences for the performed arts but the cost of mounting the initial production is still likely to rise, the more so as digital distribution may call for higher-quality artists and sets and costumes. Live performance in all art forms shares some common features: production requires the input of highly skilled labour of a varied character that is delivered to an audience at a specific moment of time and in a specific place that has been advertised in advance. Once the curtain goes up, the audience is fixed in size and, before the advent of digital transmissions of live performances, nothing could be done to increase the revenue from the sale of tickets of that performance. For the art forms that have been studied, the venue for the performance is most often a theatre or concert hall that has been purpose built, often a historic building that has limited capacity for audience size, contributing to rising costs per attendee and per performance. The subsidised performing arts, traditionally, rarely adopted the sound and visual systems widely used for mass audiences in popular concerts often held in huge stadia. The development of digitisation of live performances 415

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416  Handbook of cultural economics has altered those features, with important consequences for the finance of the performing arts. This chapter therefore covers in broad terms the production and finance of the performing arts and aspects of technological change affecting their supply and demand.

PRODUCTION FUNCTION OF PERFORMANCE A production function relates the output of an activity to the quantity of inputs used to produce it; the greater the quantity of inputs, the greater the quantity of the output. The production function can therefore be used to formalise this relationship in any economic activity, including the performing arts. Every performance requires the input of capital in the form of the venue (theatre, concert hall, and so on), the facilities it offers for staging the production, such as the stage, back stage and front of house services and labour, which includes the performers and other expert staff; the location of the venue may also be important for some purposes. The state of technology in the venue is taken as given in the short run, though it may improve facilities and therefore the productivity of the inputs in the long run. Similarly, the human capital skills of the people working in the venue, including the performers, may also improve productivity over time, for example, by reducing the number of rehearsals needed to achieve a specific level of quality in the performance. Productivity is the measure of output per unit of input. Labour input is measured using the number of hours worked or the number of people employed, which can be broken down into different categories, such as artistic and non-artistic labour, performers and stage staff, and so on. Capital is usually measured by value, although it may be possible to identify specific items by quantity. Productivity usually focuses on the value of output per unit of labour. Capital and labour may be both complements and substitutes for each other; labour is deemed to be more productive when it works with an appropriate amount of capital, in which case they are complementary. They may also be substitutes, for example, digital technology enables lighting systems to be controlled by computer instead of manually, and pre-recorded music substitutes for live music by performers. These relationships are crucial to Baumol’s prognosis of the cost disease in the performing arts. Fixed Coefficients and Baumol’s Cost Disease Substitution implies that it is possible technically to choose different combinations of capital and labour to produce a given output, a choice that in economic terms is determined by relative input prices; if wage rates increase, labour gets more expensive and if capital could be substituted, that would avoid increasing costs of production. The theory underpinning Baumol’s cost disease is that this flexibility does not exist in the performing arts; instead, the combinations of capital and labour, and particularly of specific types of labour, are fixed by the nature of the works that are performed. The classic example is the string quartet: it takes four players (with their instruments, although that is not often mentioned) to play a particular work – say, a Haydn quartet – and the same amount of time to play it now as when it was first performed. Therefore, there are fixed coefficients in the production function of the performance, and the same would apply to a Shakespeare

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Performing arts  417 play and an opera by Mozart. Thus, according to these stipulations, productivity cannot be increased. That led Baumol (1967) to model the performing arts as the stagnant sector in an otherwise dynamic economy that is growing in productivity owing to the adoption of increasingly capital-intensive methods of production. Greater productivity drives up wages in the economy as a whole, including those of people working in the performing arts, assuming (as Baumol did) that labour markets are integrated. Even if performers’ pay did not rise at the same rate as that of others, eventually fewer performers could survive as the cost of living would rise and they would change occupations, while nonartistic workers, who can easily transfer to work in the productive sector, would leave the stagnant sector and therefore arts organisations must pay them the going wage in order to retain them. In order to preserve the quality and quantity of performing arts supply, costs must go up and would be passed on to audiences as price rises. The rate of increase of ticket prices for the performing arts would inevitably be higher than those of goods and services in general, for two reasons: first, the increase in wage rates without an accompanying increase in productivity and, second, the labour-intensive nature of the performing arts that causes the wage bill to be disproportionately greater than in the rest of the economy. Baumol argued that these inevitable forces would lead to an income gap in the finances of arts organisations and, without outside support, they would cause an artistic deficit. Therefore, subvention by public finance or private philanthropy was needed to ensure the survival of quantity and quality in the performing arts.

MEASUREMENT OF OUTPUT The question of quantity and quality immediately leads to the issue of how they are to be measured. As far as quality is concerned, Baumol saw it as having to do with sustaining the classic repertoire – performances of the great works for orchestra, string quartet, opera and ballet, the theatre, and so on. This raises the question whether smaller-cast plays or chamber orchestras performing a different repertoire (say of Baroque music) are offering a lower-quality supply. This is a subjective matter on which economists perhaps are not sufficiently expert. What is important, though, is to understand that this is what Baumol set as a standard in the theory of the cost disease. More amenable to objective analysis is the question of how to measure quantity. Should it be the number of performances of a given work, the number of works performed (even the number of new works performed) or the number and type of people attending the performances (new audiences, disadvantaged people, and so on)? This is a topic that comes up in relation to performance indicators used by public funding organisations wishing to monitor the achievement of their objectives in granting subsidy to arts organisations. Each measure of output would yield a different result for productivity. The cost of a specific production (meaning the presentation of a work) can be calculated per performance or per seat in the venue or per attendee, and each would be different (and funding bodies may also calculate the amount of subsidy per attendee). The choice is dictated by circumstances; however, that choice may determine the validity of the cost disease, as the discussion on technology, to which we now turn, demonstrates.

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INFLUENCE OF TECHNOLOGY The introduction and adoption of digital technologies have had an impact on the performing arts, for which the capacity of the venue had previously determined the size of the audience. More performances could be put on, up to a point, for example, by having two per day that would spread the fixed costs of the production (the set and costumes, rehearsal time, and so on), but for some art forms the same performers could not do both (opera and ballet being notable cases) so extra performers would have to be hired. All this changed with the advent of technologies that enable non-attenders to access the performance, whether by sound recording, television or film, or digital delivery online in real time. It is now possible to hear and/or see performances from around the world in our own homes or in the local cinema. That means that the number of consumers vastly exceeds the numbers attending live performances and, if that is taken as the measure of output, then productivity has certainly risen very considerably. Some critics raise the question of whether this dilutes quality, but what is incontrovertible is that this has significant implications for the finance of the performing arts, a topic that remains to be explored in detail in cultural economics.

DEMAND AND PARTICIPATION Before turning to finance, this section briefly discusses demand for, and participation in, the performing arts. From what has been written previously, it can be seen that the 1960s view of the cost disease, experienced in many countries during subsequent decades, predicted falling audiences as prices rose. Some of the effects of price would be tempered by strong, possibly addictive, tastes for the arts that made demand inelastic, and positive income elasticity that, with rising incomes, would also mitigate the results. Even so, audience data show a reduction in participation. Some performing arts have only ever attracted a small proportion of the population – opera and ballet being the lowest at well below 10 per cent of the adult population in many countries. These data, though, are mostly for ticket-buying audiences; those participating by buying the digital versatile disc (DVD) or listening to the radio have to be identified in other ways that do not get into data on live performance. Interestingly, new digital means of delivery also enable the arts organisation to charge, albeit indirectly; you can pay a significant sum to see the Metropolitan Opera’s live performance via satellite in a cinema near you.

FINANCE OF THE PERFORMING ARTS The cost disease predicted that in order to avoid the artistic deficit of falling quality and quantity of the performing arts, organisations’ income gaps would have to be filled by some form of subvention. For many European arts organisations, that simply meant that the state authority that owned and managed performance venues had to spend more of the public budget on them. In the USA, the UK and the other countries with a similar model, though, that meant more public subsidy or private funding to privately owned and managed non-profit performing arts organisations. That was unpalatable to some

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Performing arts  419 governments (and to some economists) who saw the performing arts as being enjoyed only by a relatively small elite of above average income-earners who could pay the higher prices. However, even with subsidy, prices could never be so low as to attract all-comers and, even if they were, seating capacity in typical venues would inevitably limit the number who could be accommodated; moreover, there was evidence that however low prices were, many people just would not go though the doors of those venues. Digitisation has now changed that and a generation of young people who have grown up with new technologies are willing to experience the performing arts in new ways that are not only different but also are available at a vastly lower cost or even free. Research on participation in the arts could show whether the size and composition of audiences has changed fundamentally. Rising costs can still be present on the supply side; the cost disease is not mitigated in relation to the fixed or sunk costs of creating a production, but its deleterious effects may be neutralised by increased demand as new technologies are utilised to reach vastly greater paying audiences, with the fixed costs of performances, as with mass media, being spread over vastly bigger and broader based audiences with much lower marginal costs and lower prices.

THE IMPACT OF DIGITAL TECHNOLOGIES In what has come to be known as event cinema, live performances are filmed and streamed to local cinemas in real time and may also be accessed on demand as recordings. With its programme ‘The Met Live’, New York’s Metropolitan Opera paved the way in 2006 with broadcasts of its performances in real time to cinemas, followed in quick succession by other leading international opera, ballet and theatre companies around the world. By 2012 the Met Live reported that over 3 million viewers had seen its productions worldwide. In a similar vein, orchestral concerts and other music events can be downloaded, for example, via the BBC iPlayer and the Berlin Philharmonic’s ‘Digital Concert Hall’, in which video streamed concerts can accessed by television, computer, tablet or smartphone. There have been few studies of the economic aspects of these events, however. A notable exception is Bakhshi and Throsby (2014), who analysed willingness to pay and measures of the elasticity of demand for visits to the UK’s National Theatre (NT) with its ‘NT Live’ programme. An important question for arts managers and policy-makers is that of cannibalisation; whether digital distribution encourages attendance at the theatre (or other venue) or audiences prefer the digital version, that is, is there complementarity or substitution at work here? Cinema live performance seems to cross a border between the in-theatre experience and the purely digital experience at home; audiences in live cinema applaud, even though it does not reach the players, showing that there is involvement in the liveness of the event. More research is needed in cultural economics to understand the economic and cultural implications of these developments for the supply and demand for performing arts.

SEE ALSO: Chapter 28: Event cinema; Chapter 43: Orchestras; Chapter 44: Participation; Chapter 56: Theatre.

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REFERENCES Bakhshi, H. and D. Throsby (2014), ‘Digital complements or substitutes? A quasi-field experiment from the Royal National Theatre’, Journal of Cultural Economics, 38 (1), 1–8. Baumol, W. (1967), ‘Macroeconomics of unbalanced growth: the anatomy of urban crisis’, American Economic Review, 50 (2), 415–26. Baumol, W. and W. Bowen (1966), Performing Arts: The Economic Dilemma, Hartford, CT: Twentieth Century Fund. Towse, R. (2019), A Textbook of Cultural Economics, 2nd edn, Cambridge: Cambridge University Press.

FURTHER READING All the topics touched on in this chapter are analysed in more depth in my Textbook of Cultural Economics (Towse 2019). Hadida’s Chapter 28, ‘Event cinema’, in this volume provides an in-depth study of that topic.

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47.  Platforms

Maya Bacache-Beauvallet and Marc Bourreau

A 13-year-old girl is writing a story. It is not her diary, and her sister won’t be her only reader, as she is writing a novel and posting it on FanFiction. A musician is playing his guitar in the subway, but he is not waiting for a producer to come across – he just managed to finance his first album on Kickstarter. An old man is leaving a concert, posting pictures of the show and recommendations to his friends and family on his Facebook account. Platforms are everywhere in our daily life, and they have disrupted the traditional value chain of cultural industries, such as music, movies, books, video games and performing arts. We first provide a definition of platforms and explain how the development of platforms has impacted the value chain in cultural industries. Second, we discuss the changes to price and non-price strategies in business models, brought by the increasing role of platforms.

WHAT ARE CULTURAL PLATFORMS? What is a Platform? FanFiction, Kickstarter and Facebook are examples of online platforms, more specifically of multi-sided platforms. Multi-sided platforms have become prominent in cultural industries, but also in many other industries, and they vary greatly in various aspects, such as the number of sides or the nature of their business models. For instance, payment card systems such as Visa or MasterCard are two-sided platforms that enable direct interactions between cardholders and merchants. Social networks such as Facebook can be viewed as one-sided platforms (the interactions revolving around the group of users) or multi-sided platforms (when interactions take place between users, but also with advertisers and third-party content providers). E-commerce marketplaces such as eBay are two-sided platforms that allow buyers and sellers to trade a wide variety of products. Newspapers are also two-sided platforms, selling different products to their two sides (that is, news to readers and advertising space to advertisers), whereas on a crowdfunding platform such as Kickstarter, project owners and supporters interact around a single product (that is, the funding of a project). Though the economic literature on multi-sided platforms is 15 years old,1 there is still a lack of consensus regarding the definition of a multi-sided platform. We propose the following definition, which is very similar to the definitions proposed by many authors (for example, Armstrong 2006; Evans 2008; Rysman 2009; Katz and Sallet 2018): Definition 1:  A multi-sided platform is an intermediary that facilitates direct interactions between distinct groups of users, and which exhibits network effects, across or within, those groups of users. 421

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422  Handbook of cultural economics A distinctive feature of a multi-sided platform, highlighted by this definition, is the presence of network effects. There are within-group or direct network effects when the value of joining and/or using the platform for a given agent depends on the number of other agents in his or her group joining and/or using the platform. Cross-group or indirect network effects arise when the value of joining and/or using the platform for a given agent depends on the number of agents in the other groups who join and/or use the platform. Network effects can be either positive or negative. For instance, advertising is typically perceived as a nuisance by consumers, and therefore on a multi-sided platform such as YouTube there are negative cross-group network effects from advertisers to consumers. By contrast, advertisers value positively the number of viewers (or eyeballs) on the platform, which implies positive cross-group network effects from viewers to advertisers. A limit case of this definition would be a one-sided platform, exhibiting (direct) network effects within its only group of users. An example of one-sided platform would be a social media such as Facebook, without advertising and third-party content providers. On this type of platform, which corresponds to Facebook in its early days, users would interact with each other, and value the participation of others owing to direct network effects. There are two main conditions for a multi-sided platform to be sustainable or for this type of business model to be profitable to adopt for a firm: 1.  The multi-sided platform must create value by reducing transaction costs between its different groups of users. A platform failing to reduce transaction costs would not be efficient, and would thus quickly disappear from the market, as users would find it more efficient to interact directly outside of the platform. 2.  The multi-sided platform should have some market power over its distinct groups of users. Market power refers to the ability of the platform to set different prices to those that would prevail under perfect competition. In particular, market power enables the platform to charge different prices to each side, in a way that attracts all sides. According to Rochet and Tirole (2006), the structure of prices, not only the level of prices, matters for a multi-sided platform and thus the platform should have the ability to skew prices to influence participation or usage. For instance, a platform such as YouTube offers free content in order to attract viewers, and charges a price above cost to advertisers. The same condition on market power applies to non-price strategies aimed at attracting users. Examples of platforms in cultural industries include content distribution platforms, such as YouTube (videos), Steam (video games), Amazon KDP (e-books) and Instagram Live Video (live streaming of performing arts), crowdfunding platforms, such as Kickstarter or Indiegogo, and video game consoles, such as the PlayStation or the Xbox. More specifically, gaming consoles are two-sided platforms, enabling interactions between consumers and game developers, and characterized by cross-group network effects. A higher number of games, but also higher-quality games, make a console more attractive to consumers.2 Conversely, a larger installed base of consumers encourages game developers to supply new games for a console. Video game platforms also exhibit within-group network effects: users can share advice, recommendations, and be available for a multi-player game, making a gaming platform with a higher number of users more attractive to consumers.

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Platforms  423 While many platforms in cultural industries are multi-sided in the sense of definition 1, some do not fit well with it. For example, Netflix buys rights for movies and ­television shows from content owners, typically for a fixed amount and a limited period, and then sells access to its movie-streaming service to end-consumers against a subscription fee. In this case, there is no direct interaction between the two sides, that is, the content producers and the consumers; producers do not even know the audience of their programmes on Netflix (and they sometimes complain about it). Following Hagiu and Wright (2015a), we thus also define a second type of platform – the reseller platform: Definition 2:  A reseller platform is an intermediary which buys products or services from independent suppliers and resells them to consumers (possibly with some re-design), and whose products or services sold to consumers exhibit network effects. Examples of reseller platforms include streaming platforms such as Netflix or Amazon Prime Video for movies and television shows, Apple Music or the paid version of Spotify for music, and content stores such as the iTunes Store. For instance, Apple Music buys rights for music titles from record companies, and then resells the music titles as a large bundle to consumers, against a subscription fee. The service exhibits network effects, because a higher number of users allows it to offer better recommendations to users, making the service more attractive to users. In the rest of the chapter, we refer to a platform as either a multi-sided or a reseller platform. As Hagiu and Wright (2015a) note, being a multi-sided or a reseller platform is very often more a choice of business model than an intrinsic characteristic of an industry or a firm. Moreover, platforms can implement both business models: for instance, Amazon offers both a reseller platform and a multi-sided platform (the marketplace). A final important feature of platforms that we have to highlight, and which has important implications when there is competition between platforms, is whether users single-home or multi-home, that is, whether they join and/or use only one platform (single-homing) or more than one (multi-homing) on a specific market. The decision for a user to single-home or multi-home is going to depend, first, on the specific costs incurred to join or use each platform (including switching costs) and, second, on the differentiation between platforms. For example, for content platforms (for music, books, movies, and so on), the incentive for a consumer to multi-home rather than single-home depends on the price of each platform, but also on the overlap between the content offered by each platform. The choice between single-homing and multi-homing can also be influenced by platforms’ strategies: a platform may encourage single-homing on a given side through, for example, reward programmes and reputation systems, or by striking exclusivity deals with participants on this side. On many advertiser-supported platforms, we observe multi-homing on both sides: many consumers read various newspapers or watch different television channels, and since advertisers follow the eyeballs, they tend to multi-home too. By contrast, consumers single-home on music streaming platforms such as Spotify, or on video game consoles,3 because there is a large overlap between the content offered by competing platforms in these markets.

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424  Handbook of cultural economics A High Degree of Heterogeneity All platforms fit the previous characterization and share these common features. Nonetheless, platforms also show a wide variety in their characteristics: they develop in many different industries; they have different business models; they also differ in the number of sides, the nature and the magnitude of network effects, and in the number of markets they operate in. Some authors have tried to categorize multi-sided platforms to highlight the common features between apparently different platforms. Filistrucchi et al. (2014) distinguish between non-transaction platforms (where there is no transaction between the different sides) and transaction platforms (where a transaction exists and is observable). For instance, FanFiction is a non-transaction platform, while video game consoles are transaction platforms. Schiff (2003) distinguishes between platforms offering matching services and others that just act as an intermediary without any added-value activity. Crowdfunding platforms are matching platforms, while Babelio, a French platform of book reviews, provides a specific service of ratings and literary critic. Evans and Schmalensee (2008) categorize platforms in four types: exchange platforms that facilitate the transaction of goods or services between buyers and sellers; advertiser-supported media that bring together advertisers, content producers and audiences; transaction systems, which correspond to payment systems; and, finally, software platforms, which provide services (such as software development kits) to developers and allow consumers to run the software applications on the platform. Most platforms in cultural industries are either advertiser-supported platforms (for example, YouTube) or exchange platforms (for example, Steam). Video game consoles are software platforms. The Impact of Platforms on the Value Chain in Cultural Industries Digitization and the platform revolution are disrupting the value chain of cultural industries (performing arts, books, music, movies, video games, and so on), from creation and production to distribution and consumption of cultural goods.4 Fanfiction platforms such as Quotev or FanFiction modify the creative process and foster content innovation. Online platforms such as BandLab (music) and Artella (animated films and video games) facilitate collaboration between artists at the creation stage. Crowdfunding platforms such as Kickstarter or Gofundme allow financing small cultural projects. Digital platforms have reduced dramatically distribution costs for artists. YouTube enables the distribution of videos on a very large scale. A music artist can make his or her music available on iTunes or Spotify at very low cost. An author can easily upload his or her manuscripts on Amazon Kindle Direct Publishing (KDP). Niche movies can be distributed on streaming platforms such as Netflix or Amazon Prime Video and reach a global audience. Finally, the system of recommendations and ratings on platforms for cultural goods5 generates direct network effects between platform users. The development of social media platforms calls for an overhaul of the system of promotion. Facebook currently plays a more decisive role than traditional critics in promoting cultural goods. That is, active audiences have replaced passive consumers.

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Platforms  425 As a consequence of all these trends, artists who previously failed to emerge can now be produced and previously unfunded projects can reach their audience, which explains the emergence of a long tail of products in the cultural sector.

PLATFORM BUSINESS MODELS IN CULTURAL INDUSTRIES Platforms in cultural industries compete with rival platforms – for example, YouTube competes with Dailymotion, Steam with Epic Games, Netflix with Amazon Prime Video, and Spotify with Apple Music and Deezer. Platforms thus have to implement various strategies to attract users and sustain their business model in a competitive environment. Strategic decisions concern the prices charged to the different sides of the platform, but also non-price strategies such as how much to invest in innovation or how many sides to attract. Pricing Strategies A first critical choice made by platforms is pricing. Prices can be of different types: some platforms charge subscription fees (for example, Netflix), others usage fees (for example, advertisers pay usage fees to YouTube). Designing the pricing strategy of a platform business can be challenging, owing to the presence of direct and indirect network effects among the different groups of agents participating on the platform. Contrary to traditional markets, platforms should not set prices based only on marginal costs and price elasticities; network effects also matter. As a consequence, very often we observe that multi-sided platforms set asymmetric or skewed prices on their different sides: on YouTube, consumers can join for free, whereas advertisers pay for advertising space; game console manufacturers sell their hardware to consumers at below-cost prices and charge game developers royalties on the sales of games; and Amazon KDP charges a 30 per cent royalty fee to self-published authors, but no additional fee to readers on top of the e-book price. In its pricing decision, a platform must take into account the cross-group (indirect) network effects. Indeed, the price established on one side of the platform influences not only the demand on this side, but also the demand on the other sides, through crossgroup network effects. For instance, setting a low price for a game console will generate a high demand from consumers for the console, but will also attract a large number of game developers anticipating potentially large sales for their games. As a general rule, a monopoly platform should set a lower price on the side that generates the largest network effects on the other sides (see, for example, Armstrong 2006). At the extreme, the platform can find it efficient to set a price below marginal cost or even to provide its product or service free on one side (the loss-leading side) in order to attract a large number of users on this side and monetize them on the other sides (the profit-making sides). Asymmetric pricing thus solves the which-comes-first problem, which states that users on one side (for example, game developers) will not participate without users on the other side (for example, consumers), and vice versa. By attracting the loss-leading side through very low prices, the platform makes its service valuable for the other (profit-making) sides and ensures their participation.

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426  Handbook of cultural economics Competition reduces the mark-ups platforms can charge, but it may also raise the skewness of prices. This is because, compared to a monopoly situation, platforms now compete to attract consumers: for a given platform, lowering prices on one side does not only attract new users on this side, but also attracts users from competing platforms, which makes the platform more attractive on the other sides as well, to the detriment of rivals. Whether users single-home or multi-home also influences platform competition. A specific situation, the competitive bottleneck (Armstrong 2006), arises when one group of users single-home (for example, buyers of video game consoles), while the other group of users multi-home (for example, game developers). Platforms can act as monopolists and set high prices on the multi-homing side, while competing aggressively on the other side to attract single-homing consumers. Multi-sided platforms can also use price discrimination to attract the users who generate the largest cross-group network effects on the other sides. For instance, in the video game industry, console manufacturers offer attractive royalty deals to the most popular game developers. Non-Price Strategies The platform must also make non-price decisions. An important decision for platforms in cultural industries is how much to invest in innovation. The quality and speed of innovation matter to attract users. For instance, in the video game industry, manufacturers invest to improve processing speed, graphic quality, gaming experience, and so on. Streaming platforms such as Netflix or Spotify invest in recommendation systems to offer a high quality of experience to their users and differentiate from their rivals. The returns from quality investments can be amplified by cross-group network effects: if the platform improves quality of service on one side, and thereby stimulates demand on this side, this also fosters demand on the other sides through cross-group network effects. A platform has other important decisions to make that define its business model. In particular, the platform must determine how many sides to attract, and it must decide on the platform design and how to regulate participation and interactions (Hagiu 2014). A critical decision concerns the number of sides to attract. For instance, Facebook was at first a one-sided platform where users could share information among friends, and it evolved into a multi-sided platform with advertisers and third-party content providers (for example, game developers). By contrast, video game consoles are usually not open to advertisers, and enable interactions between only two sides – consumers and game developers. The profit-maximizing number of sides depends on the nature of indirect network effects generated by the candidate new side; that is, there may be conflicts of interest between sides, and opening a new side may involve trade-offs for the platform. For instance, in the case of the video game consoles, consumers would be negatively affected by the presence of advertisements, and some may decide to exit (or stop using) the platform. Cultural platforms, similar to any other platform, must also decide on the functionalities and features to implement. In a similar spirit as asymmetric pricing, a platform can choose to introduce a given functionality on one side but not on the others. For instance, ratings are very often open to the audience but not to artists. A given functionality may also generate value on one side, while harming the other sides; in this case, the platform has to trade-off between the interests of its various sides. For instance, on a­ dvertiser-supported

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Platforms  427 platforms, functionalities which make advertisements more prominent will please advertisers but be perceived as a nuisance by consumers. The platform regulates participation within the platform as well as the interactions between the different sides. Regulating participation makes sense when entry of lowquality users on one side may reduce the value of the platform for the other sides (that is, create negative cross-group network effects). For example, in the video game console market, while the availability of high-quality games stimulates console sales, entry of low-quality games may damage the reputation of a console and hurt sales. Console manufacturers thus exert some quality control to avoid entry of low-quality games.6 Also, the platform may wish to regulate the interactions between sides. For instance, on a crowdfunding platform, owing to moral hazard issues, a consumer may pledge to finance a project, but upon discovering that others are financing the project, withdraw from the deal. On the other side, an artist may launch a project to test his audience, but eventually renounce the launch even if financed. In order to avoid such shirking behaviour, crowdfunding platforms design their price structure appropriately, with a fixed price and a variable share depending on the amount of the project.

CONCLUSION: COMPETITION AND PUBLIC POLICIES The prominent role of platforms in cultural industries raises many challenges for public policy. In particular, platforms may have an impact on cultural diversity. In Chapter 52 of this volume, Belleflamme and Peitz discuss how recommendations and ratings of cultural products by users of platforms may affect diversity. In addition, the increase in the number of cultural goods available implies that consumer attention is becoming a scarce economic resource. Platforms develop strategies to steer consumer attention towards specific content, for example via recommendations. On a streaming platform such as Spotify, it may increase the platform’s market power for content owners.7 It may also increase consumer usage of the platform and thus the value for the other side, that is, the advertisers competing for consumer attention.8 Streaming platforms (such as Spotify) increase the availability of cultural goods but can also divert consumers’ attention: on the one hand, they level the playing field between well-known artists and new artists, but on the other, by selecting which songs and artists to promote, they can give a decisive advantage to a few, possibly established, artists. Therefore, while platforms and digitization have lowered barriers to entry for new artists in cultural industries, the market power of platforms on recommendations may raise barriers to visibility or success for the same artists.

NOTES 1. The early contributions were Caillaud and Jullien (2003), Rochet and Tirole (2003, 2006) and Armstrong (2006), among others. 2. Corts and Lederman (2009) reveal that an additional hit game increases console sales seven times more than an average quality game. 3. Derdenger (2014) find that less than 5 per cent of gamers own two consoles (or more) of the same generation.

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428  Handbook of cultural economics 4. For a comprehensive analysis of the impact of digitization on media industries, see, for example, Waldfogel (2017). 5. See Chapter 52, ‘Ratings, reviews, recommendations’ by Paul Belleflamme and Martin Peitz, in this volume. 6. Atari lost its leading position in the 1980s, partly because it allowed entry of poor-quality games, which damaged its reputation as a good gaming platform. 7. Bourreau and Gaudin (2018) analyse when a streaming platform can use a personalized recommendation system to steer consumers from one content provider to another. They show that the use of a recommendation system strategically biased in favour of the cheaper content allows the platform to reduce its royalty payments to content providers. 8. Aguiar and Waldfogel (2018) find significant effects; for example, being added to ‘Today’s Top Hits’ on Spotify raises streams by 20 million and is worth in the region of $77 000.

SEE ALSO: Chapter 26: Digitization in the cultural industries; Chapter 52: Ratings, reviews and recommendations; Chapter 57: Video game industry.

REFERENCES Aguiar, L. and J. Waldfogel (2018), ‘Platforms, promotion, and product discovery: evidence from Spotify playlists’, NBER Working Paper No. 2471, National Bureau of Economic Research, Cambridge, MA. Anderson, S.P. and J.J. Gabzewicz (2006), ‘The media and advertising: a tale of two-sided markets’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: NorthHolland, pp. 567–614. Armstrong, M. (2006), ‘Competition in two-sided markets’, Rand Journal of Economics, 37 (3), 668–91. Bourreau, M. and G. Gaudin (2018), ‘Streaming platform and strategic recommendation bias’, CESifo Working Paper No. 7390, Centre for Economic Studies, IFO Institute for Economic Research, Munich. Caillaud, B. and B. Jullien (2003), ‘Chicken & egg: competition among intermediation service providers’, Rand Journal of Economics, 34 (2), 309–28. Corts, K.S. and M. Lederman (2009), ‘Software exclusivity and the scope of indirect network effects in the U.S. home video game market’, International Journal of Industrial Organization, 27 (2), 121–36. Derdenger, T. (2014), ‘Technological tying and the intensity of competition: an empirical analysis of the video game industry’, Quantitative Marketing and Economics, 12 (2), 127–65. Evans, D. (2008), ‘Competition and regulatory policy for multi-sided platforms with applications to the web economy’, mimeo, accessed 15 December 2019 at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1090368. Evans, D. and R. Schmalensee (2008), ‘Markets with two-sided platforms’, in W.D. Collins, J. Angland and the American Bar Association, Issues in Competition Law and Policy, vol. 1, Chicago, IL: ABA Section of Antitrust Law, pp. 667–94. Filistrucchi, L., D. Geradin, E. Van Damme and P. Affeldt (2014), ‘Market definition in two-sided markets: theory and practice’, Journal of Competition Law and Economics, 10 (2), 293–339. Hagiu, A. (2014), ‘Strategic decisions for multisided platforms’, MIT Sloan Management Review, 55 (2), 71–80. Hagiu, A. and J. Wright (2015a), ‘Marketplace or reseller?’, Management Science, 61 (1), 184–203. Hagiu, A. and J. Wright (2015b), ‘Multi-sided platforms’, International Journal of Industrial Organization, 43, 162–74. Katz, M. and J. Sallet (2018), ‘Multisided platforms and antitrust enforcement’, Yale Law Journal, 127 (7), 2142–75. Rochet, J.-C. and J. Tirole (2003), ‘Platform competition in two-sided markets’, Journal of the European Economic Association, 1 (4), 990–1029. Rochet, J.-C. and J. Tirole (2006), ‘Two-sided markets: a progress report’, Rand Journal of Economics, 35 (3), 645–67. Rysman, M. (2009), ‘The economics of two-sided markets’, Journal of Economic Perspectives, 23 (3), 125–43. Schiff, A. (2003), ‘Open and closed systems of two-sided networks’, Information Economics and Policy, 15 (4), 425–42. Waldfogel, J. (2017), ‘How digitization has created a golden age of music, movies, books, and television’, Journal of Economic Perspectives, 31 (3), 195–214.

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Platforms  429

FURTHER READING The Journal of Economics and Management Strategy has published a special issue (2019, vol. 28, issue 1) on the economics of platforms. Hagiu and Wright (2015b) provide a general analysis and definitions of platforms. Rochet and Tirole (2003) discuss competition issues in platform markets. On the effects of platforms in cultural industries, see Anderson and Gabzewicz (2006) and Waldfogel (2017).

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48.  Political economy Isidoro Mazza

Cultural policies can be analysed from different perspectives. The normative approach of welfare economics interprets public intervention as a solution to inefficiencies and/or inequity. Policies would then emerge as if they were devised and implemented by a planner maximising social welfare. This approach, largely relying upon the principle of Pareto optimality, does not intend to be realistic but provides a fundamental benchmark for the evaluation of the outcome of the public sector. It rules out, however, the process of collective decision-making and policy implementation which leads to that outcome. Analysing such a process is fundamental to replicate or improve a policy and, to do so, we have to examine the institutional system where intricate agency relationships involving a number of actors (such as voters, organized groups, politicians, parties or bureaucrats) shape policymaking. This is the realm of research of the burgeoning literature on political economy, whose relevance for the cultural sector is evident when we consider the prominent role of government for the existence and development of the sector. This chapter briefly illustrates how political economy analysis has contributed to the understanding and assessment of cultural policies, and how it can provide useful insights on issues little explored until now.1

WHAT IS POLITICAL ECONOMY? Political economy has different and, even, unfolding meanings. As a field of investigation, it links political science and economics. As a methodological approach, for which it also goes under the denomination of public choice, can be defined as the economic analysis of political, or non-market decision-making (Mueller 2003). A fundamental behavioural postulate of this approach is rational individualism. People are assumed to be self-­interested and maximizing their objective in the public sector no differently from the market. Thus, public agents are expected to fulfil private interests over public interests, unless they have an incentive, or are bound to do so by institutional constraints: the constitution, laws regulating elections and government formation, the separation of powers among political entities or the oversight of the judiciary system. However, this view of political economy is restrictive in light of the evolution of the field. In its early stage, the political economic approach arose as a new field in its quest to define optimal criteria to aggregate collective preferences. It developed starting from the pioneering works on majority rule by Black (1948a, 1948b), on axiomatic social choice function by Arrow (1951) and on constitution design by Buchanan and Tullock (1962). From this normative beginning, the analysis has increasingly embraced a positive approach. Among the numerous issues investigated, attention has been devoted to modelling political competition – investigating its impact especially on redistribution and fiscal stabilization – the influence of interest groups on policy-making, the role of bureaucrats in the supply of government output, and decision-making in committees. 430

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Political economy  431 A central aspect of the analysis is the presence of information asymmetries pervading all steps of the political decision-making process; from the roots of democracy residing in voting to electoral competition and from government policy-making to the implementation of policies. The public sector shows a composite system of overlapping principal– agent relationships, where agents enjoy rents from information that is unknown for the principal. Following this reasoning, the government can be considered as an agent of the public and, at the same time, the principal of bureaucratic agents. The picture is further complicated by the existence of different tiers of (local) governments and bureaucracies, vertically and horizontally connected, and by the occurrence of coalition governments. Furthermore, political economy has developed in numerous different directories of research, among which the behavioural and institutional ramifications are probably the most significant. Behavioural political economics admits that individuals may have non-standard preferences bridging political economy and psychology (Schnellenbach and Schubert 2015). This adjustment is far from marginal, as it relaxes two fundamental assumptions in orthodox economic analysis: rationality and stability of preferences.2 This recent strand of research has provided behavioural underpinnings to explain phenomena left unsolved by previous analysis. One insight concerns the motivations for voting. The well-known voter’s paradox maintains that a rational individual should not vote, if voting is purely instrumental. The reason is that a single vote has a negligible expected impact on the final voting outcome and therefore the expected benefits of that vote (namely, to elect the preferred candidate) is lower than its cost. This result is evidently contradicted by reality and undermines the foundations of the economic analysis of elections. If we do not know why people vote, then we cannot try to predict how they vote. A considerable literature (Feddersen 2004; Bendor et al. 2011) has explored different ways around this problem. A behavioural explanation is that voting may not be instrumental but expressive; people would vote for the symbolic meaning to express their preferences (Hillman 2010; Hamlin and Jennings 2011). Voting would be part of expressive behaviour, showing the view that people have of themselves, as well as their morals and identity. Behavioural political economy has also contributed to reconcile theory and real-life observations of cooperation. A common belief in economics is that individuals will free-ride in contributing to the provision of a public good. Olson (1965) in his analysis of collective action warned that, when benefits from an action are collective but costs are private, individuals will not organize and cooperate for the common good; they will freeride. This has since become a widespread tenet in political economy, essential to explain the disproportionate political power of interest groups. Similarly, non-cooperation is the dominant strategy in prisoners’ dilemma situations that we frequently face. Yet we observe more cooperation than the theory predicts. Recent behavioural studies indicate that people may endogenously generate social preferences through an affective-tie mechanism triggered by interactions (Bault et al. 2017). This mechanism, which has neurobiological and experimental support, provides a number of intriguing cooperative results in a political economic context where the traditional dichotomy government-market is replaced by a more encompassing and relational system that includes also the community. Another major and recent advancement concerns the analysis of institutions, which connects political economy to political sociology. Institutions have traditionally played an important function in political economy. A shared view is that they represent the system

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432  Handbook of cultural economics of norms avoiding that politics surrenders to the whims of politicians and bureaucrats. Since information about the outcome of different policies is a public good but the cost of acquiring it is private and high, owing to the intrinsic difficulty in evaluating the multiple public policies, we expect that free-riding will discourage people from being informed. Moreover, as we have seen, information on politics would be useless, if voting is instrumental. Thus, citizens are conjectured to be rationally ignorant about politics (Downs 1957). If citizens do not have information to monitor and evaluate the activity of politicians and bureaucrats, they cannot reward or punish incompetent or inefficient governments through voting. Institutions may then come to the rescue of democratic systems. The lack of direct control of the public can nevertheless be replaced by political institutions that constrain the autonomy of the agents in the public sector, such as the separation of powers between president and parliament, and checks and balances between different political bodies and judiciary oversight. The quality of institutions then guarantee, to different extents, the functioning of the public sector and, consequently, of the market. A growing and influential literature has highlighted the importance of institutions for the correct functioning of the market and non-market sectors. There is evidence that institutions are a main driving force of economic development (Acemoglu and Robinson 2005; Tabellini 2010). A limit of political economic analysis is that it generally considers institutions as exogenous. The next challenge is then to understand how they originate and reform. In conclusion, from the previous discussion, it is correct to say that political economy now includes several approaches and, in a more encompassing view, it can be defined as ‘the methodology of economics applied to the analysis of political behaviour and institutions’ (Weingast and Wittman 2006 p. 3).3 In cultural economics, we have observed a noticeable increase in the number of political economic studies since the previous edition of this handbook was published in 2011. Yet, this strand of research has dealt with relatively few issues, if we consider the potential reach of political economy. Hereafter, we review some of these issues and make some suggestions for future research.

THE AGGREGATION OF PREFERENCES: DIRECT DEMOCRACY Decision-Making in a Committee One of the most important contributions in political economy took place right at the dawn of the field: the median voter theorem. A simple majority is a decision-making rule widely used in committees, since it allows the minimum amount of votes to pass a proposal, avoiding that self-contradictory (minority) proposals pass as well. However, majority rule presents the problem of instable majorities (cycling) as shown by de Condorcet (1785).4 The intrinsic weakness of majority rule is that it does not reveal the intensity of voters’ preferences. Black (1948a) solves this problem by finding that majority rule will determine a unique outcome if preferences of all voters are single peaked (there is a single optimum) and ordered along one political dimension. The winning alternative will be that valued most highly by the median voter, namely, the voter whose preferred alternative has the median position in the distribution of all the alternatives

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Political economy  433 valued most highly by each voter. This result has had a tremendous impact on the literature because it offers a simple solution; that is, knowing the distribution of preferences, we can easily predict the outcome under majority rule. The success of the median voter theorem is also because, under some specific and restrictive assumptions and introducing spatial competition, it is used to determine the outcome of electoral competition in a representative democracy. If we relax either the assumption of single-peaked preferences for any voter or that of one-dimensional issue we can again obtain cycles. Leaving aside the first assumption (consistent with the assumption that individuals have convex indifference curves), the second assumption is highly restrictive as it presumes that committee members can vote on one issue only, indicating whether they prefer more or less of it. In general, choices are made over different issues, as in the hypothetical case when a state lottery fund has to decide how to allocate resources into different cultural programmes. This problem can be tackled by exploiting the vast array of procedures aggregating preferences (Holler and Mazza 2013), whose normative and positive properties are investigated by social choice analysis. It is unfortunate, however, to notice the absence of its application to improve our understanding of decision-making in the committees of private and public institutions financing culture. Future analysis could shed light on the consequences that the procedures they adopt may have on the allocation of funds. Referenda The use of referenda is often purported to be the best way to elicit the preferences of the public. By fostering inclusiveness, direct democracy reduces the information rents of politicians, public officials and powerful interest groups, and improves government accountability. Asatryan and De Witte (2015), using data on 2000 Bavarian municipalities, find that more direct democratic activity is associated with higher government efficiency. Frey and Pommerehne (1995 [2000]) show that the use of this instrument for cultural decisions, for example, regarding public acquisition of art, is adequate to guarantee the quality of the public decision, even though it involves a large number of people. Referenda may also represent a way to elicit collective preferences circumventing paternalistic regulatory constraints that elites of experts could impose on society. However, referenda are not common in most countries, possibly for their high cost. This could be partially reduced in a sufficiently decentralized federation. Nonetheless, for several reasons we should be cautious in accepting an alleged superiority of direct democracy and embracing the use of referenda. First, Schulze and Ursprung (2000), investigating a referendum on the public support for Zurich Opera House, find that the variables affecting the approval rate in the referendum are those that influence public support for the arts in representative democracies; preferences of the electorate are reflected by cultural policies in representative democracy systems as they are in direct democracy. Second, the structure of the question in a referendum could have an impact on the outcome. Third, direct democracy does not avoid the possibility that special interest groups or social networks influence the voting outcome as much as, or even more than, they can do in a representative democracy. Fourth, the result of referenda may be biased and over-represent the preferences of the public. By examining a referendum held in 2009 in the Swiss canton of St Gallen on the public financing of the local theatre, Hofer (2019)

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434  Handbook of cultural economics finds that that voters were on average wealthier, better educated and older than the average population – all characteristics that are positive drivers of support for the referendum. Fifth, the lack of political filters between the result of the referendum and its implementation may have dangerous consequences. In a representative democracy, the electoral victory of a party supporting a potentially catastrophic policy does not immediately determine this policy, for the presence of institutional constraints (formation of the government, checks and balances between government and parliament, bureaucratic drift, and so on). This may not be the case in a referendum, if its result is constitutionally binding. Furthermore, the indication from behavioural political economy that voters may systematically deviate from rational expectations and voluntarily decide to hold irrational beliefs (Caplan 2006), reinforces the belief that referenda are riskier instruments of decision-making than elections.

POLICIES IN A REPRESENTATIVE DEMOCRACY Electoral Competition The analysis of competition between parties in an election is considered to originate from the seminal work by Downs (1957). His model exploits the median voter theorem by Black (1948a), replicating the assumptions of single-peaked preferences and unidimensional political space, and adding further restrictive assumptions: (1) parties are only interested in winning the election (they have no ideology strings), (2) all people vote and (3) are perfectly informed about the parties’ policies, and (4) vote for the policy closest to their ideal (making vote fully deterministic). Using a spatial model where two candidates (or parties) compete for votes, Downs shows that both parties will converge in choosing the policy preferred by the median voter.5 Owing to its analytical simplicity and, more importantly, that it leads to a unique equilibrium policy, Downs’s model of electoral competition has experienced an enormous diffusion even recently, when sophisticated and influential models still build on similar analytical frameworks.6 Nonetheless, the assumptions of a single political dimension, that all people vote and that ideology is irrelevant, together with the result of full convergence of political platform, cast serious doubts on the empirical relevance of this model and its power to predict policies, and have led many scholars to generalize it or to search for alternative models (Ansolabehere 2006). There are numerous models of electoral competition. Depending on their different assumptions, we can derive different strategies that candidates can adopt to win elections. Important aspects of elections are uncertainty and ideology, both absent in Downs’s model. Voters may be uncertain about candidates’ abilities and/or platforms, and candidates may be uncertain about voters’ preferences. Probabilistic voting models study the latter issue (Duggan 2006). Suppose, for example, that an incumbent government tries to gain support by targeting public expenditure. In these models, candidate A proposing an expenditure policy that favours a group more than candidate B’s policy is not certain to receive the votes of that group. The reason is that candidate A is uncertain about the idiosyncratic (for example, partisan and/or ideological) preferences that voters in that group have for him or her. A probabilistic voting model would conjecture that, in this case, candidate A obtains just an increase in the probability of being voted by the members

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Political economy  435 of that group. It is then intuitive that candidates maximizing the probability of winning will target a group having homogenous preferences (for example, special interest groups) because their vote will be less uncertain than in other groups. Moreover, if ideology is important, each candidate will target groups with moderate partisan bias (the swing voters) because it will be too hard to try to have consensus among those voters with a strong bias against the candidate, and useless to try to attract those who are already in favour of the candidate. This hypothesis is puzzling as it goes against the common wisdom that candidates will chose to support their own. Several studies have tried to verify whether incumbent politicians target expenditure to loyal or swing voters. The empirical results are ambiguous, for they may be influenced by other institutional factors, such as party discipline and electoral rules. In majoritarian systems, where parties maximize the number of seats won, the government is expected to spend more on swing voters. In contrast, in proportional systems parties are likely to maximize votes and to assign more resource to loyal districts that can guarantee a relatively larger number of votes. Guccio and Mazza (2014) provide support for the latter hypothesis, examining how Sicily’s regional government (elected through a proportional system) allocated resources for cultural heritage conservation to the nine provinces of Sicily in the period 1992–2002. They find that the assignment of funds was influenced by the political characteristics of a province, such as loyalty to the main party, the number of regional political representatives elected in that province and that the regional secretary was elected in that province. Also Noonan (2007) finds that the political positioning of the receiving administration impacts the allocation of funds to state arts agencies in the US between 1969 and 2002. Party control of the state governance impacts positively the agencies’ appropriations. In electoral competition, the timing of expenditure is crucial. If voters do not elaborate rational expectations, they may reward an incumbent government when they see an economic improvement financed by public expenditure, without fully realizing that this will imply lower public expenditure and/or higher taxation in the future. Therefore, if public expenditure is used for political opportunism, we would expect a political business cycle; that is, higher expenditure (or tax reduction) when elections are approaching and lower expenditure (or tax increase) after the election. Benito et al. (2013) find evidence of a political budget cycle for cultural expenditure in the municipal elections in Murcia for the period 1995–2008. As additional corroboration that expenditure is politically motivated, they find that the cycle is larger when elections are expected to be closer. However, this result is not confirmed by other studies. Dalle Nogare and Galizzi (2011) use data on cultural expenditures of 106 Italian municipalities for the period 1998–2005 and find that cultural expenditure reduces in election years. Getzner (2002) examines public expenditure for culture in Austria from 1967 to 1998 and finds no evidence of electoral cycle for cultural expenditure. Moreover, cultural expenditure is not influenced by the incumbent’s ideology or used to acquire political consensus. In contrast, ideology is found to be relevant by Potrafke (2013). He finds that in two referenda in two different German cities, districts having a leftist orientation were against financing the building or enlargement of two concert halls. De Witte and Geys (2011) examining efficiency of 290 municipal libraries in Flanders in 2007, find that left-wing governments are more likely to care about maximizing library service potential. The strong ambiguity of these results is unsettling. Leaving aside the theoretical foundations of political business cycles, which

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436  Handbook of cultural economics are not tackled by the above literature, an explanation for the striking diversity of results could be that the above studies refer to countries having possibly different institutional, social and economic contexts. For example, municipal fiscal authority (the power to tax and to spend) could differ across those countries. Another, more general, shortcoming is that the political salience of cultural expenditure is difficult to ascertain. A municipal government that focuses on cultural expenditure to win elections expects that cultural services are relatively more appealing to voters than other services also provided by municipalities. Alternatively, it could be that cultural expenditure is complementary to (or a substitute for) other categories of expenditure, for example, education, in which case it does not necessarily represent the salient issue for voters. Special Interest Politics Public policy is a consequence of the composition of conflicting interests. However, we do not expect all interests to be equally represented at the political stage. We have discussed the reasons why people can be expected to be ignorant about politics. However, when policies can produce large selective benefits for narrow groups, characterized by a common interest, they have sufficient incentives to be informed and to overcome the transaction costs of organizing to influence policy-making (Olson 1965). These benefits, although considerable for a limited group, are hardly sufficient to cause an organized opposition from the taxpayers, individually paying for a tiny marginal fraction of the benefits received by the interest group. In contrast, large groups are supposed to have no incentive to organize for pressure activities for the presence of high organization and decision costs and the looming free-riding. The political economic literature shows contrasting views about the effects of lobbying on welfare. The Chicago school argues that institutions foster competition and transparency in the political system and that competition between lobbies will discipline policy-making and lead to an efficient outcome. Alternatively, the Virginia school emphasizes that private agents waste resources in rent-seeking activities and policy-makers choose inefficient forms of redistribution in order to disguise the transfers to powerful interest groups. In the past two decades a vast literature has investigated rent-seeking and the influence of organized groups on political outcome, relaxing the assumption of full ignorance of voters, but incorporating asymmetric information, and introducing different instruments of influence.7 Cultural goods have peculiarities that may favour the realization of special interest politics. Wealth transfers in the art sector can be disguised as something that is socially acceptable. In addition, the public may have limited specific knowledge to evaluate the cultural value deriving from public expenditure for the arts. Grampp (1989) provides empirical evidence that arts organizations do lobby government for subsidies in the US and the UK. However, we know very little about lobbying for the arts. An issue highly debated in the news, but lacking rigorous analysis, is government lobbying for a United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage listing. Although there is ample evidence of its existence, we need empirical research to understand the characteristics and extent of this phenomenon. This type of investigation could also interest the localization of touring cultural events (for example, the Cultural Capital of the Year or Manifesta).

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Political economy  437

THE SUPPLY OF GOVERNMENT OUTPUT The analysis of the policy-making process is complicated by the intricate governance system in the public sector. In evaluating a policy outcome, we should pay attention to the implementation of the policies where public officials (bureaucrats) may have substantial autonomy over decisions that affects the outcome of a policy. Delegation of authority to bureaucrats has comprehensible explanations8 but it may also cause a loss of political control on the outcome of public policies, owing to the information advantage of bureaucrats and to their power of initiating the policy-making process by submitting proposals to the legislator. Also, the risk of a bureaucratic drift may affect cultural policy. Compared with other areas of public intervention, cultural policy presents additional difficulties concerning the identification of the content and the range of intervention. For example, the definition of the types of visual and performing arts to be supported is barely codified. Consequently, the experts play the fundamental role of gatekeepers, both in the public sector and in the private sector. The absence of free entry makes the art market non-competitive. Rents may then be extracted by the experts because of their gatekeeping power.9 In a similar fashion, the criteria for identifying cultural heritage to be preserved and the typology of intervention are not uniquely defined. Peacock (1994) and Frey (2000) have warned against the risks of a dominant role of experts in the decision-making process, potentially generating elitist policies detached from the preference of the public or a bias towards conservation that disregards the costs caused to the private (see Grampp 1996; Fedeli and Santoni 2006).10 In order to reduce the gap between culture policy and people preferences, Peacock (1994) suggested improving public participation in policy-making, for example, allowing members of cultural organizations to elect their representatives in the public agencies implementing cultural policy. Following this suggestion, future research should be directed to investigate the agency relationships between government and public agencies in the cultural sector, which has not been sufficiently investigated.11

CONCLUDING REMARKS This chapter has tried to highlight how political economy can substantially contribute to the analysis of the cultural sector and its policies. The adoption of the political economic approach in cultural economics is growing, although the number of issues investigated remains limited. We then draw the attention to two issues that have been unduly overlooked. Increasing attention is being paid to the interpretation of culture as an instrument of soft power. This is a crucial issue for cultural industries and in the ongoing debate on restitution of cultural heritage. The political economic approach described here seems well equipped to shed important light on our understanding of the forms and efficacy of soft power. Another topic which has not been adequately studied is the political economy of the art sector. The activity of public museums is increasingly relying upon the support of private investors. These collaborations are likely to have an effect on the efficiency and activities of those institutions as well as spillovers to the market, which would be interesting to investigate.

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438  Handbook of cultural economics

NOTES  1. Early contributions to the development of a political economic analysis of the cultural sector are Peacock (1998) and Frey (2000). Insightful presentations of the political economy of arts and culture can be found in van der Ploeg (2006), Peacock and Rizzo (2008).  2. However, some behavioural models have embraced this revolution only partially, incorporating cognitive biases into otherwise standard utility functions used in neoclassical economics. Other models, instead, have tried ‘to actually explain (rather than just postulate) motivational and other psychologically informed extensions to the standard model’ (Schnellenbach and Schubert 2015, p. 396, original emphasis).  3. A fundamental survey of the field is in Mueller (2003). Weingast and Wittman (2006) provide an excellent review of the recent developments. Acemoglu and Robinson (2005) present the new institutional approach to political economy and its implication for development theory. Persson and Tabellini (2016) offer an encompassing examination of the theoretical models.  4. Suppose that we have to distribute a fixed sum, say €100, among a committee of three using simple majority rule. The agreement of two (for example splitting 50/50 between 1 and 2 respectively) can always be replaced by an alternative majority proposed by the excluded individual (55/45 between 1 and 3, then 50/50 between 2 and 3, and so on) in an endless cycling.  5. It is worth noting the closeness with the result shown by Hotelling (1929, p. 54) before even the development of modern political economy: The competition for votes between the Republican and Democratic parties does not lead to a clear drawing of issues, an adoption of two strongly contrasted positions between which the voter may choose. Instead, each party strives to make its platform as much like the others as possible. Any radical departure would lose many votes . . . Real differences, if they ever exist, fade gradually with time.  6. Withers (1979) is an early contribution adopting this model for the cultural sector.  7. Rent-seeking models and interest group models study similar issues but with different analytical frameworks. Rent-seeking models usually start from the existence of a contestable rent originating from regulation. The focus is then on the social cost of rent-seeking. Interest group models take into account the maximization problem of the legislator. Several studies have then investigated how interest groups’ activity influences the objective function of policy-makers. In this way, policies are endogenous in the model, depending on the institutional assumptions (see Persson and Tabellini 2016).  8. In addition to the legislators’ lack of time and/or expertise required to follow the implementation of a single policy, there can be strategic reasons such as the legislator’s wish to shift responsibility for a failure to the bureaucrat.  9. Experts may compete to be appointed institutional gatekeepers. Mossetto (1994) shows that quality certification by cultural institutions could contribute to the formation of economic rents and, consequently, rent-seeking activities. 10. On the other hand, this conservationist and academic bias could be helpful to counterweight a political economic bias that a local government may have for outstanding cultural heritage. Martorana et al. (2019) suggest that since the latter would attract tourism and external attention from the media more than would heritage with local relevance, a local government could choose a suboptimal allocation of resources in favour of the more prestigious cultural heritage. 11. An early study on this topic is Krebs and Pommerehne (1995).

SEE ALSO: Chapter 45: Performance indicators; Chapter 50: Public support; Chapter 53: Regulation of heritage.

REFERENCES Acemoglu, D. and J.A. Robinson (2005), Economic Origins of Dictatorship and Democracy, Cambridge: Cambridge University Press. Ansolabehere, S. (2006), ‘Voters, candidates, and parties’, in B.R. Weingast and D.A. Wittman (eds), The Oxford Handbook of Political Economy, New York: Oxford University Press, pp. 29–49. Arrow, K.J. (1951), Social Choice and Individual Values, New York: John Wiley and Sons.

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Political economy  439 Asatryan, Z. and K. De Witte (2015), ‘Direct democracy and local government efficiency’, European Journal of Political Economy, 39 (September), 58–66. Bault, N., J.J. Fahrenfort, B. Pelloux, K.R. Ridderinkhof and F. van Winden (2017), ‘An affective social tie mechanism: theory, evidence, and implications’, Journal of Economic Psychology, 61 (August), 152–75. Bendor, J., D. Diermeier and M. Ting (2011), A Behavioral Theory of Elections, Princeton, NJ: Princeton University Press. Benito, B., F. Bastida and C. Vicente (2013), ‘Municipal elections and cultural expenditure’, Journal of Cultural Economics, 37 (1), 3–32. Black, D. (1948a), ‘On the rationale of group decision making’, Journal of Political Economy, 56 (1), 23–34. Black, D. (1948b), ‘The decisions of a committee using a special majority’, Econometrica, 16 (July), 245–61. Buchanan, J.M. and G. Tullock (1962), The Calculus of Consent: Logical Foundations of Constitutional Democracy, Ann Arbor, MI: University of Michigan Press. Caplan, B. (2006), The Myth of the Rational Voter: Why Democracies Choose Bad Policies, Princeton, NJ: Princeton University Press. Dalle Nogare, C. and M. Galizzi (2011), ‘The political economy of cultural spending: evidence from Italian cities’, Journal of Cultural Economics, 35 (3), 203–31. De Condorcet, N. (1785), Essai sur l’application de l’analyse à la probabilité des décisions rendues à la pluralité des Voix, Paris: De L’imprimerie Royale. De Witte, K. and B. Geys (2011), ‘Evaluating efficient public good provision: theory and evidence from a generalised conditional efficiency model for public libraries’, Journal of urban economics, 69 (3), 319–27. Downs, A. (1957), An Economic Theory of Democracy, New York: Harper & Row. Duggan, J. (2006), ‘Candidate objectives and electoral equilibrium’, in B.R. Weingast and D.A. Wittman (eds), The Oxford Handbook of Political Economy, New York: Oxford University Press, pp. 64–83. Feddersen, T.J. (2004), ‘Rational choice theory and the paradox of not voting’, Journal of Economic perspectives, 18 (1), 99–112. Fedeli, S. and M. Santoni (2006), ‘The government’s choice of bureaucratic organisation: an application to Italian state museums’, Journal of Cultural Economics, 30 (1), 41–72. Frey, B. (2000), Arts & Economics. Analysis & Cultural Policy, Berlin: Springer-Verlag. Frey, B. and W.W. Pommerehne (1995), ‘Public support for the arts in a direct democracy’, repr. 2000 in B. Frey, Arts & Economics. Analysis & Cultural Policy, Berlin: Springer-Verlag, pp. 115–29. Getzner, M. (2002), ‘Determinants of public cultural expenditures: an explanatory time series analysis for Austria’, Journal of Cultural Economics, 26 (4), 287–306. Grampp, W.D. (1989), ‘Rent-seeking in arts policy’, Public Choice, 60 (2), 113–21. Grampp, W.D. (1996), ‘A colloquy about art museums: economics engages museology’, in V.A. Ginsburgh and P.-M. Menger (eds), Economics of the Arts: Selected Essays, Amsterdam: Elsevier, pp. 221–54. Guccio, C. and I. Mazza (2014), ‘On the political determinants of the allocation of funds to heritage authorities’, European Journal of Political Economy, 34 (C), 18–38. Hamlin, A. and C. Jennings (2011), ‘Expressive political behaviour: foundations, scope and implications’, British Journal of Political Science, 41 (3), 645–70. Hillman, A.L. (2010), ‘Expressive behavior in economics and politics’, European Journal of Political Economy, 26 (4), 403–18. Hofer, K.E. (2019), ‘Estimating preferences for the performing arts from referendum votes’, Journal of Cultural Economics, 43 (3), 397–419. Holler, M.J. and I. Mazza (2013), ‘Cultural heritage: public decision-making and implementation’, Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 17–36. Hotelling, H. (1929), ‘Stability in competition’, Economic Journal, 39 (153), 41–57. Krebs, S. and W.W. Pommerehne (1995), ‘Politico-economic interactions of German public performing arts institutions’, Journal of Cultural Economics, 19 (1), 17–32. Martorana, M., I. Mazza, A. Mignosa and I. Rizzo (2019), ‘The economics of heritage: some implications of devolution’, in M. Kunizaki, K. Nakamura, K. Sugahara and M. Yanagihara (eds), Advances in Local Public Economics, Singapore: Springer, pp. 249–60. Mossetto, G. (1994), ‘Cultural institutions and value formation on the art market: a rent-seeking approach’, Public Choice, 81 (1–2), 125–35. Mueller, D.C. (2003), Public Choice III, New York: Cambridge University Press. Noonan, D.S. (2007), ‘Fiscal pressures, institutional context, and constituents: a dynamic model of states’ arts agency appropriations’, Journal of Cultural Economics, 31 (4), 293–310. Olson, M. (1965), The Logic of Collective Action: Public Goods and the Theory of Groups, Cambridge, MA: Harvard University Press. Peacock, A. (1994), ‘The design and operation of public funding of the arts: an economist’s view’, in A. Peacock and I. Rizzo (eds), Cultural Economics and Cultural Policies, Dordrecht: Kluwer, pp. 167–84.

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440  Handbook of cultural economics Peacock, A. (ed.) (1998), Does the Past have a Future? The Political Economy of Heritage, London: Institute of Economic Affairs. Peacock, A. and I. Rizzo (2008), The Heritage Game, Oxford: Oxford University Press. Persson, T. and G. Tabellini (2016), Political Economics, Cambridge, MA: MIT Press. Potrafke, N. (2013), ‘Evidence on the political principal-agent problem from voting on public finance for concert halls’, Constitutional Political Economy, 24 (3), 215–38. Schnellenbach, J. and C. Schubert (2015), ‘Behavioral political economy: a survey’, European Journal of Political Economy, 40 (December), 395–417. Schulze, G.G. and H.W. Ursprung (2000), ‘La donna e mobile–or is she? Voter preferences and public support for the performing arts’, Public Choice, 102 (1–2), 129–47. Tabellini, G. (2010), ‘Culture and institutions: economic development in the regions of Europe’, Journal of the European Economic association, 8 (4), 677–716. Van der Ploeg, F. (2006), ‘The making of cultural policy: a European perspective’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1183–221. Weingast, B.R. and D.A. Wittman (eds) (2006), The Oxford Handbook of Political Economy, New York: Oxford University Press. Withers, G. (1979), ‘Private demand for public subsidies: an econometric study of cultural support in Australia’, Journal of Cultural Economics, 3 (1), 53–61.

FURTHER READING For a survey of political economy, see Persson and Tabellini (2016); for the implications for cultural policy, see van der Ploeg (2006). Peacock and Rizzo (2008) and Holler and Mazza (2013) apply the topic to heritage decision-making.

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49.  Pricing the arts Michael Rushton

This survey presents general rules for arts organizations setting menus of prices for live performances, museum exhibitions, festivals and similar. Pricing for unique works of visual art are considered elsewhere in this volume. The problem facing arts organizations is how to set prices to capture as much of the surplus generated by the events as possible. An arts presenter selling a single type of ticket – for example, general admission to a one-night-only performance – will maximize profits by setting the price where marginal revenue, defined as the increase in total revenues from reducing ticket prices just enough to increase demand by one ticket, equals marginal cost, which is the increase in the presenter’s costs resulting from admitting one more customer (in the arts marginal cost for a non-crowded event is near zero). However, most arts organizations have pricing policies that are more complex than this simple case, and that is the subject of this chapter. Specifically, arts presenters seek to exploit the variance in their customers’ willingness to pay for entry. Some potential customers are highly sensitive to price (I refer to these as marginal customers) while other potential customers have relatively inelastic demand and a higher willingness to pay (I refer to these as strong customers). In practice, arts presenters want to find a means of offering lower prices to marginal customers while still collecting a higher price from strong customers. These practices are commonly known as price discrimination. Firms selling goods in perfectly competitive markets must take prices as given, and so price discrimination cannot be used, but such situations are rare in the arts, as each performance, exhibition or festival has some unique characteristics.

DIRECT PRICE DISCRIMINATION Price discrimination can be achieved in two ways. One method is to charge different prices to different groups of customers, where it is easy for the arts organization to identify the group to which each customer belongs. This is known as direct price discrimination, or third-degree price discrimination. A common example is a performance or museum that gives a discount on the ticket price to students or to individuals above a certain age. This practice can be effective only where there is no arbitrage; students must not be able to purchase cheap tickets and resell them to those ineligible for the discount. Consider for example an arts organization selling tickets for general admission to an event, and that seeks to maximize profits (non-profit firms are dealt with below). Suppose the marginal cost to the firm of allowing an additional member of the audience is constant, and, for now, that there is no capacity constraint, that is, the venue is large enough to hold all potential audience members even at very low ticket prices; in this situation marginal cost is almost zero. There are two types of consumers; marginal consumers, with high sensitivity to price, and strong consumers, who particularly enjoy this type of 441

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442  Handbook of cultural economics event, and have relatively low sensitivity to price (all of the examples that follow can be expanded to more than two types of customers, but working with two types keeps the exposition simple). The first rule-of-thumb is that the organization will maximize profits by setting prices so that for each group, the marginal revenue from that group – defined as the change in revenue received from that group arising from a small decrease in price – is equal to the marginal cost. That is, it is as if the organization is selling two entirely separate products, following the usual profit-maximizing price-setting rule of finding the price and associated quantity sold where marginal revenue equals marginal cost. We need it to be the case that people cannot buy a ticket at the lower price and resell to those who would face a higher price. If the marginal consumers are students, we cannot have students purchasing tickets and reselling to non-students. Publishers can set different prices for the same title in different countries as long as the transportation costs of buying cheap in one country and selling dear in another are high enough that there is no profit in trying to do so. Now suppose there is a capacity constraint, as there are only so many seats in the venue, so setting prices according to the rule above would entail excess demand. The second rule of thumb is that prices should then be set in a way that the following two conditions are both met: (1) the marginal revenue for one group is equal to the marginal revenue for the other, and (2) the total demand for admission at those two prices is equal to the capacity of the venue. The intuition is that if we were satisfying condition (2), but marginal revenue for one group – for example, the marginal consumers – were higher than the marginal revenue from the other group – for example, the strong consumers – it would increase profits to lower the price for marginal consumers, sell them a few more tickets and raise the price for strong consumers, selling them fewer tickets, while keeping total demand the same (the capacity of the venue). What is gained in increased revenue from marginal consumers exceeds the loss in revenue from strong consumers, since the marginal revenue for the former is greater than the marginal revenue for the latter.

INDIRECT PRICE DISCRIMINATION The second method of price discrimination is called indirect or second degree, which involves offering to all potential customers a menu of prices for different packages of tickets and complementary goods, and allowing customers to effectively sort themselves according to the options they choose. An example is a museum that charges one price for general admission and an additional price for a special exhibit, which customers may or may not choose to see. There are a number of applications.

TWO-PART PRICING Suppose the organization can charge a general admission price T, and a price P for additional goods that are available once inside, where these additional goods are supplied with a constant marginal cost, MC (suppose there is zero marginal cost associated with general admission). There are many examples in the arts: a museum might have an additional fee for a special exhibit; there might be refreshments or souvenirs available for sale inside a

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Pricing the arts  443 museum or performing arts venue or film theatre; a company might sell hardware for reading digital books or listening to downloaded music recordings, as well as the actual texts or musical content; or, to use the example from the seminal paper on the subject (Oi 1971), an amusement park may charge an entry fee and in addition a price for each ride. To get started, imagine a simple case where consumers may differ in their willingness to pay for general admission, but there is no discernible way to classify consumers in terms of their demand for rides (continuing with the amusement park example). Then the profitmaximizing strategy is (1) set P, the price per ride, equal to the marginal cost per ride, and (2) set T such that, given the choice of P, the marginal revenue from the admission fee T is zero. The rationale is as follows. First, we know that the higher the setting of P, the lower will be the demand for general admission (what a customer is willing to pay as a cover charge is lower the more expensive are drinks once you get inside the nightclub; what a customer is willing to pay for an electronic book-reader is less the more expensive are individual downloads of books). If P is set above the marginal cost per ride, there is lost surplus; if rides are priced at $5 each but marginal cost per ride is only $2, then customers will leave the park when, given the number of rides they have already been on, and diminishing marginal utility, the reservation price for one more ride has fallen below $5. However, as long as that reservation price is still above $2, it would have been efficient to have allowed more rides; the customer would gain more in benefit from the last ride than it would have cost the firm to provide it. If the firm lowers the price per ride P to $2, it can recapture what might have been lost in revenues from rides in charging a higher entry fee T. It is best to create maximum surplus from rides, and capture that surplus through the general admission fee. So, to follow Oi’s example, Disneyland charges a high entry fee, but rides are free once inside. Museums charge for general admission, but do not have additional fees for each room in the general exhibition (special exhibitions are a different case). This model is amenable to direct price discrimination; the organization might want to set a lower T for students or seniors, following the rule of setting T as per the direct price discrimination rules described previously (in general, the different means of price discrimination discussed in this chapter are not mutually exclusive, and we observe arts firms pursuing many of them simultaneously). However, it would remain the case that all groups would be charged the same price P per ride. Now suppose a situation where consumer preferences for rides differ between ­customers, but we have no way of knowing, as we do with direct price discrimination, whether any specific individual is a great fan of rides or quickly tires of them. In this situation the firm would modify the two-part pricing rule in the following way: if experience has shown that our marginal customer has a strong (relative to others) preference for rides, then set P lower than we would have in the standard case, and capture the associated increase in consumer surplus by increasing T; and if the marginal customer has a low (relative to others) preference for rides, then set P slightly higher than in the standard case, which will necessitate a lower T. The intuition is as follows. Suppose the first case, where the price-sensitive visitors have a high preference for rides. Then offering subsidized rides is a way to bring them into the venue. The organization will not need to worry about losing too much of the custom of strong customers, since they value general admission highly but have a low demand for rides in any case. When we observe an amusement park offering a high general admission

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444  Handbook of cultural economics fee but free rides, even though the marginal cost per ride is positive, it is probably the case that marginal consumers have a high preference for lots of rides. Offering rides for free is not all that costly to the firm, since it is only the marginal consumers who will take advantage of the free rides from opening until closing. Now consider the opposite case, where the strong customer has a greater demand for rides than the marginal customer. Then the organization can entice the marginal customer into the venue with a low entry fee T, and capture the high surplus of the strong customer through charging them for the rides they so enjoy. This provides an explanation of the phenomenon so often remarked upon by laypersons: ‘Why is popcorn so expensive in movie theatres?’ It turns out that marginal, infrequent attendees of the cinema buy less popcorn per visit than those who attend more often and have relatively inelastic demand for going to the movies. It makes sense for the theatre owner to lower the price of admission into the theatre (to fill up seats that otherwise would be empty, with marginal, low willingness-to-pay audience) and earn high profits on popcorn sales from the strong customers (Gil and Hartmann 2009).

BUNDLING Suppose there is a good, X, not necessarily an arts-related good, for which there is some demand from price-sensitive, marginal consumers of the arts, but for which there is little interest from the average ticket-buyer for the arts. Then the arts organization might effectively price-discriminate by offering to all ticket-buyers a special discount on good X. This will help lure marginal consumers to the arts venue, but without having to provide any type of discount in price to the average price-inelastic attendees, who will not be interested in exercising their rights to buy X at a subsidized price. This practice is known as bundling. As an example, consider a theatre in London’s West End. It might charge high ticket prices, knowing that average theatre-attendees will pay the high price, and offer a bundle of a pair of theatre tickets, a pair of tickets on a sightseeing bus and dinner at a good, but not excellent, restaurant, where the price for the bundle is significantly less (although still above cost) than the price of buying all three goods separately. Here, the marginal customers are tourists, probably on a tight budget, and with many different things on offer in the city to compete for their limited time. They might not be willing to pay full price for theatre tickets, but will find the bundle an attractive option. Also, the theatre is able to attract their business without lowering the price for ordinary, unbundled tickets that would be purchased by London residents.

DIFFERENTIAL QUALITY Arts organizations can charge different prices for customer experiences of different characteristics and quality. For example, preferred seats, or preferred times of performances, can command a higher price than lower-quality seats or tickets for performances at lowdemand times of day or days of the week. Publishers offer different versions of books: hardcovers have the advantage of more durable binding and being immediately available, while paperbacks have the disadvantages of less durable binding and a delay (often a

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Pricing the arts  445 year) in release. Seats in the upper balcony, and paperback versions of novels, are priced to attract the marginal, price-sensitive consumers for those particular goods, while seats in the orchestra, and immediately available hardcover books, are priced higher, with the knowledge that some consumers will be willing to pay the higher price in order to obtain the highest quality. The challenge for the arts organization is to ensure that the quality difference is high enough relative to the price differential to avoid having too many consumers opt for the lower-quality/lower-priced alternative. Thus, while it makes sense to charge for the lower-quality version a price as close as possible to the marginal customer’s willingness to pay, in general the price of the high-quality version is something less than the maximum willingness to pay by high-demand customers, in order to avoid them switching to the lower-priced option. Cheung (1977) adds that high-quality seats might also be underpriced to prevent them from going unsold and, subsequently, occupied by those who bought lower-quality seats and then sneaked past the ushers into the vacant high-quality seats. An interesting empirical study concerns tickets for Broadway theatre, and the half-price day-of-show tickets that can be bought in person at selected outlets in New York. The dayof-show tickets are lower quality in that there is great uncertainty as to whether any will be available on the day of the show, and in the (deliberate) inconvenience in obtaining them – they cannot be purchased online or by telephone even though such purchases would be easy for theatres to accommodate, since regular tickets can be bought that way. Leslie (2004) used data on sales to find that the theatres were not engaged in profit-maximizing pricing, because the discount for day-of-show was too high – the high price differential combined with the relatively small difference in quality was inducing too much switching by strong customers into purchasing the discounted tickets. Leslie suggests a discount on day-of-show tickets of about 30 per cent would have been more profitable for the theatres. See also Courty (2003a, 2003b) on the timing of price discounts.

QUANTITY DISCOUNTS It is commonplace for museums to offer single-day tickets or memberships for families that cost less on a per-person basis than would be charged to a single individual, and this is recognition of the differential willingness to pay by a single individual and a set of two parents with children. In addition, discounts are given on the number of events attended: festivals offer menus of different numbers of performances to attend, where the cost per event is lower the more events are purchased; performing arts organizations offer season tickets; and museums offer memberships that lower the effective price per visit. For individuals, diminishing marginal benefits work on two levels here. Consider an opera season, where there are options for tickets to individual operas as well as season tickets. The more operas an individual sees in a season, the lower the marginal benefit for attending one more. However, that reasoning applies equally to the purchased of oranges or shirts. In addition, however, if an individual were to purchase tickets for the opera on an individual basis, he or she would first choose a ticket to their favourite opera of the season. If they were to buy tickets for a second opera during the season, the second ticket would be for an opera that is less preferred than the first one, and so the reservation price for that ticket would be less.

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446  Handbook of cultural economics In general, it is best for the arts organization to ensure that there is a variety of ticketpurchase options, to best capture the surplus from individuals with different willingness to pay not only for a single ticket, but who experience different rates of decline in marginal benefits. In particular, if the marginal cost to the arts presenter per extra visit is near zero, then it is efficient to offer as part of the menu a membership or subscription option with unlimited access at no additional charge. The rationale echoes the analysis of two-part pricing: for a member, a charge per additional visit will discourage at least some visits at the margin, visits that, at zero marginal cost, would have generated a surplus. By charging zero for additional access at the margin, the arts firm can capture the surplus from the marginal visits in the membership or subscription price. This model is commonplace across many genres: museum memberships with unlimited visits, streaming services such as Netflix or Spotify with unlimited and zero-priced streaming for subscribers, and online magazine and newspaper subscriptions.

PRICING WHEN PROFITS ARE NOT THE ONLY GOAL Suppose a museum or orchestra is run by the state or a non-profit. How would pricing depart from the profit-maximizing rules given above? It might be the case that prices do not change at all; the goals of outreach to underserved communities might best be reached by maximizing profits from museum admissions or concert tickets, and using the proceeds to fund educational programmes. Alternatively, suppose the goal is simply to increase attendance at the museum or concerts. First note that the means of price discrimination used by profit-maximizing firms already works to the benefit of those with a lower willingness to pay, who can get discounted admission on times and days of the week when demand is typically low, and who can get basic admission at a low rate without paying for special exhibits or prime-location orchestra seats. However, a state-owned or non-profit arts organization might discount the basic offering even further to achieve their goals of broad dissemination of the arts. Would the discount in prices ever extend to charging a basic admission price below marginal cost? We can imagine a few possibilities: the target customer of the deeply discounted price has a willingness to pay above marginal cost, but this is a means of transferring consumer surplus to that person; or, the target customer’s willingness to pay is below marginal cost, but (1) there are positive externalities associated with consumption, or (2) consumption now will alter preferences and willingness to pay in the future. If none of these factors is present, it is difficult to justify prices below marginal cost.

NEW DIRECTIONS IN PRICING Arts organizations continue to experiment with new methods of price-setting, owing to the possibilities created by technological change in online transactions and data management. For example, concert tickets can now be sold through online auctions (Halcoussis and Mathews 2007). Also, since sports franchises adopt methods of variable pricing through their seasons (Kemper and Breuer 2016), where prices adjust according

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Pricing the arts  447 to ­shifting demand for specific matches, we might begin to see the same for tickets for live performances in the arts (Labaronne and Slembick 2015; Seaman 2018). This practice, known as dynamic pricing, exploits information on ticket demand in the time period leading up to the performance to adjust prices upwards or downwards as a type of error-correction method. It has long been commonplace in pricing by airlines and hotels, which are similar to performing arts organizations in that an empty seat represents a lost opportunity for revenue that can never be regained; a seat on a specific flight, a hotel room on a particular night and a seat at the theatre on a specific date, are all similar to completely perishable goods, and cannot be held by the firm as inventory for later resale. The arts are different. If there is low demand for a flight or for a hotel on a specific night, cutting the price might attract a marginal customer but it will not signal to the customer anything about the quality of the flight or the hotel room. Even a sports team that cuts its prices midway through a disappointing season is not revealing anything about the quality of the team, since its performance on the field will have been well documented in the press, and any potential spectator will be at least partly aware of the fact. However, the arts are an experience good, and arts customers are sensitive to any advance information about the quality of the good – has the novel received good reviews, is a theatre production generating positive word of mouth? A cut in price in the face of lagging demand for tickets has the potential, at least, of signalling to potential buyers that the show is not particularly good, and so might have the opposite effect on demand, warning customers away, instead of attracting them.

SEE ALSO: Chapter 1: Application of welfare economics to the arts; Chapter 13: Cost of production; Chapter 24: Demand.

REFERENCES Adams, W.J. and J.L. Yellen (1976), ‘Commodity bundling and the burden of monopoly’, Quarterly Journal of Economics, 90 (3), 475–98. Ansari, A., S. Siddarth and C.B. Weinberg (1996), ‘Pricing a bundle of products or services: the case of nonprofits’, Journal of Marketing Research, 33 (1), 86–93. Cheung, S.N.S. (1977), ‘Why are better seats “underpriced”’, Economic Inquiry, 15 (4), 513–22. Clerides, S.K. (2002), ‘Book value: intertemporal pricing and quality discrimination in the US market for books’, International Journal of Industrial Organization, 20 (10), 1385–408. Connolly, M. and A.B. Kreuger (2006), ‘Rockonomics: the economics of popular music’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 667–719. Courty, P. (2000), ‘An economic guide to ticket pricing in the entertainment industry’, Recherches Économiques de Louvain, 66 (2), 167–92. Courty, P. (2003a), ‘Ticket pricing under demand uncertainty’, Journal of Law and Economics, 46 (2), 627–52. Courty, P. (2003b), ‘Some economics of ticket resale’, Journal of Economic Perspectives, 17 (2), 85–97. Courty, P. and M. Pagliero (2012), ‘The impact of price discrimination on revenue: evidence from the concert industry’, Review of Economics and Statistics, 94 (1), 359–69. Cowell, B. (2007), ‘Measuring the impact of free admission’, Cultural Trends, 16 (3), 203–24. Currim, I.S., C.B. Weinberg and D.R. Wittick (1981), ‘Design of subscription programs for a performing arts series’, Journal of Consumer Research, 8 (1), 67–75. Gil, R. and W.R. Hartmann (2009), ‘Empirical analysis of metering price discrimination: evidence from concession sales at movie theatres’, Marketing Science, 28 (6), 1046–62.

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448  Handbook of cultural economics Halcoussis, D. and T. Mathews (2007), ‘eBay auctions for Third Eye Blind concert tickets’, Journal of Cultural Economics, 31 (1), 65–78. Kemper, C. and C. Breuer (2016), ‘How efficient is dynamic pricing for sports teams? Designing a dynamic pricing model for Bayern Munich’, International Journal of Sport Finance, 11 (1), 4–25. Labaronne, L. and T. Slembeck (2015), ‘Dynamic pricing in subsidized performing arts’, International Journal of Nonprofit and Voluntary Sector Marketing, 20 (2), 122–36. Leslie, P. (2004), ‘Price discrimination in Broadway theater’, Rand Journal of Economics, 35 (3), 520–41. Leslie, P. and A. Sorenson (2014), ‘Resale and rent-seeking: an application to ticket markets’, Review of Economic Studies, 81 (1), 266–300. Maddison, D. and T. Foster (2003), ‘Valuing congestion costs in the British Museum’, Oxford Economic Papers, 55 (1), 173–90. Mortimer, J.H. (2007), ‘Price discrimination, copyright law, and technological innovation: evidence from the introduction of DVDs’, Quarterly Journal of Economics, 122 (3), 1307–50. Oi, W.Y. (1971), ‘A Disneyland dilemma: two-part tariffs for a Mickey Mouse monopoly’, Quarterly Journal of Economics, 85 (1), 77–96. Prieto-Rodríguez, J. and V. Fernández-Blanco (2006), ‘Optimal pricing and grant policies for museums’, Journal of Cultural Economics, 30 (3), 169–81. Ravanas, P. (2008), ‘Hitting a high note: the Chicago Symphony Orchestra reverses a decade of decline with new programs, new services, and new prices’, International Journal of Arts Management, 10 (2), 68–87. Rentschler, R., A.-M. Hede and T.R. White (2007), ‘Museum pricing: challenges to theory development and practice’, International Journal of Nonprofit and Voluntary Sector Marketing, 12 (2), 163–73. Rosen, S. and A.M. Rosenfield (1997), ‘Ticket pricing’, Journal of Law and Economics, 40 (2), 351–76. Rushton, M. (2015), Strategic Pricing for the Arts, London: Routledge. Rushton, M. (2016), ‘Touts out? The Waterson review on secondary ticketing’, Cultural Trends, 25 (4), 287–90. Rushton, M. (2017), ‘Should public and nonprofit museums have free admission? A defence of the membership model’, Museum Management and Curatorship, 32 (3), 200–209. Seaman, B. (2018), ‘Static and dynamic pricing strategies: how unique for nonprofits?’, in B.A. Seaman and D.R. Young (eds), Handbook of Research on Nonprofit Economics and Management, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 199–224. Shiller, B. and J. Waldfogel (2011), ‘Music for a song: an empirical look at uniform song pricing and its alternatives’, Journal of Industrial Economics, 59 (4), 630–60. Shy, O. (2008), How to Price, Cambridge: Cambridge University Press. Steinberg, R. and B.A. Weisbrod (1998), ‘Pricing and rationing by nonprofit organizations with distributional objectives’, in B. Weisbrod (ed.), To Profit or Not to Profit, Cambridge: Cambridge University Press, pp. 65–82. Steinberg, R. and B.A. Weisbrod (2005), ‘Nonprofits with distributional objectives: price discrimination and corner solutions’, Journal of Public Economics, 89 (11–12), 2205–30.

FURTHER READING Shy (2008) is a comprehensive, though technical, text on pricing; Rushton (2015) is a short text explicitly devoted to arts pricing, and much less technical. Courty (2000) provides a survey of ticket pricing. On different levels of quality and price discrimination see Rosen and Rosenfield (1997) on tickets, Clerides (2002) on books and Mortimer (2007) on evidence from video home system (VHS) and digital versatile disc (DVD) versions of movies. On bundling and subscriptions, see Adams and Yellen (1976), Ansari et al. (1996), Currim et al. (1981) and Ravanas (2008). Connolly and Kreuger (2006) and Courty and Pagliero (2012) consider when popular music performers will use price discrimination. On price discrimination for online music downloads, see Shiller and Waldfogel (2011). Leslie and Sorenson (2014) consider pricing strategies when there are secondary markets in tickets; also see Courty (2003a, 2003b) and Rushton (2016). On museum pricing see Cowell (2007), PrietoRodríguez and Fernández-Blanco (2006), Rentschler et al. (2007) and Rushton (2017). Maddison and Foster (2003) examine optimal museum pricing when customers are willing to pay to reduce crowding. On departures from profit-maximizing pricing when there are distributional objectives, see Steinberg and Weisbrod (1998, 2005).

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50.  Public support Bruno S. Frey

When cultural economists look at public support for the arts, they distinguish between two aspects: the positive issue where the extent of support by the government is analysed, and the normative issue of whether or not the arts should be publicly supported and, if so, to what extent. In the second case, the cultural economist desires to inform the public about an appropriate policy, a welfare-enhancing public policy towards the arts (O’Hagan 1998).

HOW DOES GOVERNMENT SUPPORT THE ARTS? Throughout history, governments have been heavily involved in the arts. Table 50.1 provides an overview of direct public spending on the arts in various countries in 2007 and 2017. Table 50.1 should be interpreted with great care because what counts as art expenditure, and what falls into the domain of government, varies considerably between the countries listed. Nevertheless, the table is able to show widely different amounts of direct public Table 50.1  Government spending for the arts per country as a percentage of overall government spending in 2007 and 2017 Country/region

2007

2017

European Union – 28 countries

1.1

1.0

Individual countries Belgium Germany Ireland Greece Spain France Italy Austria Finland Sweden United Kingdom

1.0 0.9 1.0 0.3 1.7 1.3 0.8 1.4 1.0 1.1 0.9

1.0 0.9 0.8 0.3 1.1 1.2 0.6 1.1 1.0 1.0 0.6

Norway Switzerland

1.1 1.2

1.3 1.2

Source:  Eurostat (2019), ‘General government expenditure by function’, accessed 24 March 2019 at https:// ec.europa.eu/eurostat/web/products-datasets/product?code=gov_10a_exp.

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450  Handbook of cultural economics expenditures for the arts. Greece spends much less, and Spain, France, Norway and Switzerland substantially more, than the other countries in Table 50.1. The source of public support also varies widely. Thus, for example, in Ireland in 2015 approximately 50 per cent of overall government spending on cultural services came from central government. In Norway, central government contributed 57 per cent of total cultural expenditures. In Germany it is less than 15 per cent; the bulk was coming from the Länder and municipalities (40 and 45 per cent in 2015, respectively). The extent of private sponsorship of the arts also varies widely between countries. It is important to realize that a substantial part of public support for the arts is given in an indirect way, by tax deductions. Individuals’ and firms’ gifts to the arts may be exempt from taxation. Hence, the higher the applicable (marginal) tax rate, the less costly it is to give to the arts. It has been observed that a reduction in tax rates led to lower donations to the arts. The extent of tax expenditure for the arts varies greatly between countries, and often depends on a large variety of conditions. It is therefore impossible to indicate its size, but most cultural economists assume that it is quite substantial, and often larger (for example, for the US) than direct expenditures. There is a basic difference between the two types of support. For direct expenditure, the decision about its size and the recipients is taken in the political sector, often by government bureaucrats. For tax expenditures, the support decision is delegated to individuals or firms. This may lead to a different size and type of art being supported. Many developed economies have constitutional provisions to support art. Of necessity, these rules have to be general. Their effect on the arts depends to a great extent on how the political actors and public officials apply them. There is considerable evidence that they prefer to support well-established cultural institutions providing generally accepted art, for instance, opera houses performing popular classical pieces by Verdi, Mozart, Puccini or Rossini. In contrast, more controversial and experimental art has difficulty in obtaining public support, because the public decision-makers who depend on public opinion and re-election try to avoid scandals, which are more likely to be provoked by this kind of art. Indirect aid via tax expenditure is less subject to these types of pressures and may bring about the support of a broader range of artistic activities.

SHOULD GOVERNMENT SUPPORT THE ARTS? Cultural economics has paid a great deal of attention to the question of what the rationale for the support of the arts could be. The analysis is based on welfare theory, which focuses on the question of whether the private market misallocates the resources in the domain of the arts, and in particular why too little art is provided for if it is left to the price system. It is useful to distinguish between the demand side and the supply side. Market Failures on the Demand Side According to welfare economics, too little art is supplied if the markets do not reflect all the preferences of individuals for enjoying art. The following types of demand are at best only partially reflected on markets:

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Public support  451 1.  External benefits in production and consumption. The provision of artistic activities may yield benefits, or positive external effects, to individuals and firms not involved in the production process. They reap a benefit for which they do not pay, and which the art producer in a market therefore does not take into account. Similarly, part of the benefits of artistic production may go to individuals and firms which do not pay for such consumption, and which therefore do not influence the production decisions on art markets. In both cases, production is too small compared to what is socially optimal. 2.  Non-market demand. People may value the option of visiting an artistic production though they never spend any money to attend themselves. People may even know beforehand that they will never themselves attend an artistic production but they value the existence of the activity. Some people may not themselves value art but consider it a bequest for future generations. In many cases, artistic production is closely identified with national identity, prestige and social cohesion. Examples are famous opera houses, theatres, orchestras and museums. Artistic production may also contribute to a liberal and broad education and lead to social improvements among the participants. The experimental nature of (some) artistic endeavours may foster innovation and risk-taking in quite different parts of society. In all these cases, the producers of art are not (fully) compensated in monetary terms for the benefits created. As a consequence, they are sometimes not able to provide the respective cultural activity at all, or only on a smaller scale than would be socially optimal. 3.  Art as a public good. Art may be of a collective nature, in that nobody (including those not paying) can be excluded from enjoying it, and that the consumption by one person does not reduce the consumption by other persons. This condition may apply to culture as a whole, or only parts of it (for example, the beauty of a cultural city may be enjoyed by many people without having to pay specifically for such a benefit). In contrast, the cultural consumption provided by, say, opera houses or museums, is not a public good, because people not paying may be excluded. Moreover, in these cases there is rivalry in consumption; those who fill a seat, or those who visit a museum, occupy space, which is then no longer available to others. But insofar as culture is a public good, the suppliers are incompletely compensated for their efforts, and supply is lower than socially optimal. Not all spillovers to other sectors induced by the arts constitute market failure. This holds in particular for the multiplier effects generated by expenditures for the arts. They increase the demand for other economic activities, such as hotels, restaurants or travel services, and thus work through the price system. No misallocation of resources is thereby created. The many studies of the impact effects of cultural activities (for example, musical festivals or special exhibitions), which measure the additional economic activity induced, can therefore not be taken as a rationale for government support of the arts. These studies, moreover, are often misplaced, as they focus on the additional turnover created instead of the added value. They also tend to disregard the alternatives available, that is, whether, say, a sports event, instead of the cultural activity considered, would generate even more economic activity.

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452  Handbook of cultural economics On the demand side, further arguments for government support of the arts relating to aspects beyond efficiency may be proposed. The following are particularly important: 1.  Merit goods. Some cultural activities should, from the viewpoint of society, be provided at larger quantities than the individual consumers would wish to purchase on a market. According to this view, consumer preferences should not be accepted; instead, the political decision-makers have to decide according to inherent worth. The idea of merit goods clashes with the basic idea in economics that the consumers know best what suits them. 2.  Lack of information. Consumers are often badly informed about the supply of art and this has often been used to support government intervention. While people are certainly not fully informed, it is necessary to face the question of whether consumers’ limited information is a rational consequence of their low interest in the arts. 3.  Irrationality. Individuals may be particularly subject to behavioural anomalies and paradoxes when they act in the area of culture, since the area eludes easy and clear definitions or categorizations. It may be argued that individuals therefore underrate the utility that culture provides them. The government should support the arts to make up for the lack of demand. 4.  Income distribution. The consumption of cultural goods should be open to all parts of society and not reserved just for the rich. Consequently, the government should support the arts in order to make its consumption available to individuals who are not able to pay much money for consuming them. Market Failure on the Supply Side The supply of art may deviate in four major respects from the ideals of a well-functioning market: 1.  Imperfect competition. The market for many cultural goods and services is characterized by monopolistic actors offering smaller quantities at higher prices than competitive suppliers would. The government might correct this market failure by supporting additional supply. However, this argument does not apply to all areas of the arts. Thus, auctions of art objects are an example of an almost perfectly competitive market. 2.  Declining cost. Art supply may be subject to increasing returns to scale. This means that additional quantities may be produced at lower average cost, and marginal cost is lower than average cost. The condition of efficient pricing, namely, that price equals marginal cost, produces a loss. If the government wants to impose marginal cost pricing, it must support the suppliers by covering the difference between marginal and average cost. 3.  Productivity lag. Suppliers in the live performing arts are subject to continuous cost pressure (Last and Wetzel 2011). They find it difficult, if not impossible, to increase labour productivity, but they have to pay wage increases similar to those in the rest of the economy. As a result, there is a tendency towards continually increasing deficits. In the long run, the performing arts can only persist if the government makes up for these deficits.

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Public support  453 4.  Low incomes. Artists tend to be, on average, poorer than other members of society. Egalitarian arguments may constitute a reason for governments to support individuals active in the cultural sector.

COUNTER-ARGUMENTS Some cultural economists committed to free market ideas remain unconvinced that the market failures discussed on the demand and supply sides really exist to any relevant extent. The external effects are claimed to be small, even non-existent, or at least not larger than those generated in many other areas of the economy. There is some truth in this argument. It is indeed possible to identify some market-external effects in most economic activities. However, most cultural economists, on the basis of both theoretical and empirical considerations, are convinced that cultural activities produce more extensive and important positive externalities than elsewhere. The undesired distributional aspects of cultural demand have also been put into question. It has been argued, and in some instances empirically shown, that government support of the arts often achieves the opposite of what is intended. High-income recipients are the principal consumers of cultural services, so they are also the main beneficiaries of government support. This has been illustrated by the example of highly subsidized European opera houses, which are mainly attended by individuals with above-average incomes, or younger persons (students) who will later in their lives enjoy above-average incomes (that is, people with above-average lifetime incomes). While this argument corresponds with the facts, its relevance should not be overestimated. The consumption of artistic goods and services is certainly not undertaken only by the rich, not least because a great deal of cultural consumption requires considerable time (for instance, an opera performance takes a whole evening) which, owing to the opportunity costs of time, is more expensive for high-income recipients. It is, in general, not the richest part of the population that benefits from publicly supported art but the (upper) middle class, which has sufficient time available for consumption. As to the undesired distributional effects on the cultural supply side, it has been argued that governmental support tends to favour the successful, and therefore richer, artists. This applies to some forms of government support. For example, in opera houses the high subsidies given by governments help to raise the already high incomes of the most successful singers and maestros. However, this observation should not be generalized. A great part of government support goes to artists with low, and sometimes very low, lifetime income, and thus works in the desired direction. As regards declining costs and the productivity lag of cultural supply, it has been claimed that they exist in many other areas of the economy and that they can be overcome by suitable measures. In particular, revenue can be raised by introducing prices, which capture the rents generated to the consumers by the cultural activity. Thus, price differentiation enables the setting of high prices for infra-marginal cultural consumers with a high consumer rent, while still setting prices equal to cost for marginal consumers. Cultural suppliers subject to the cost disease have various possibilities for productivity increases. Productivity can be raised, for example, by introducing more capital-intensive production, by seeking the substitution of actors by technological means, by choosing plays with a

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454  Handbook of cultural economics smaller number of actors or by having actors play several roles. The possibilities for a particular performing arts supplier to do this without lowering the quality of performance are severely limited because conservative people might not like this approach. In addition, the implementation of modern technological means might also influence the perception and acceptance by the traditional audience. This forces the director to be more careful about realizing such novel approaches (for example, modern operas such das schlaue Füchslein –The Cunning Little Vixen by Leoš Janáček). Productivity in the live performing arts may be on the increase owing to indirect influences. Thus, for example, owing to improved travelling conditions, an actor or a singer may perform at many more venues than previously, which increases his or her overall productivity. It should also be noted that the productivity lag only applies to live performing arts and much less, if at all, to other forms of the performing arts via television, radio, video or film. Indeed, these other forms constitute an enormous productivity increase in the arts, because a given live performance can be extended at very little, and sometimes even zero, cost to large audiences. Cultural producers, faced with high costs relative to revenue, have several means to avoid producing a loss. Revenue can be raised by collateral activities, such as running a shop (within the cultural venue and outside), a cafeteria and restaurant, renting out the premises for other activities and seeking support from private and corporate sponsors. Many art organizations have demonstrated that substantial income can be generated in this way. However, the possibilities are severely limited, for several reasons. The first is that many art institutions have little scope to engage successfully in this type of profit-making, mainly because they are not glamorous enough to attract sufficient visitors and sponsors. This applies to many local and regional suppliers, who nevertheless produce worthwhile art. Another reason is that such profit-orientated activities may threaten the content and quality of art. Cultural producers should not lose sight of what they stand for. They should not try to become entertainers, not least because they are likely to lose out against the established entertainment industry. This danger is real; some museums, for instance, have gone far in this direction by continually trying to feature blockbuster exhibitions of doubtful artistic quality. The profit-making potential is also limited because the cultural suppliers may thereby lose their non-profit status. This most obviously holds for the museum shops run outside their premises, say, in large shopping centres. If this status were lost, they would be subject to several additional taxes, and donations would no longer be exempt from tax. Both consequences would threaten the existence of many, if not most, cultural suppliers and would therefore have counterproductive effects. If the private opera houses and museums in the US were no longer classified as non-profit-making, donations would fall drastically, and they would hardly be able to survive.

COMPARATIVE VIEW Even if market failures have been theoretically and empirically identified for the arts, they constitute at best a prima facie argument for public support. It must be taken into account that government intervention is also subject to failure. The economics of politics (see Public Choice III, Mueller 2003) discusses many reasons why the decisions taken in the political process may systematically deviate from the preferences of the population. Most importantly, politicians are motivated by the need for re-election rather than by any

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Public support  455 direct incentive to provide welfare-maximizing cultural policies. As elections take place only every fourth or fifth year, politicians are insufficiently controlled by voters. They tend to develop into a political class of their own and to a considerable extent decide according to their own taste to what extent, and how, culture is to be supported. Political failures are also introduced by the behaviour of the public bureaucracy which, owing to its informational advantages, has large discretionary power to undertake a cultural policy of its liking. At the same time, both politicians and public officials are exposed to the influence of pressure groups. As a consequence, they tend to favour those cultural suppliers who are well organized, which in most cases comes down to concentrating the funds on a few large and well-established cultural suppliers (such as opera houses, national theatres and orchestras). In contrast, new, unorthodox and experimental art suppliers find it hard to obtain public aid, which tends to hamper creativity in the arts. To gain a balanced view, it is necessary to compare the extent of market and political failure in respect of cultural issues.

CONSTITUTIONAL ISSUES FOR AND AGAINST THE PUBLIC SUPPORT OF THE ARTS The arguments so far presented in favour of, or against, publicly supporting the arts are informed by the notion of market and political failure, respectively; but it can be argued that the world is imperfect. The idea of failure compared with an ideal situation is then of little relevance, because the whole economy and society is characterized by failures. According to this view, it does not make sense to identify the extent to which the cultural sector deviates from an ideal market, or from ideal political conditions, since all sectors in society deviate from an ideal situation to a significant extent. A more useful approach is to directly compare the sectors with each other. The question then becomes whether the cultural sector receives more or less public support than other sectors, and whether this support improves the conditions of the population. The first part of the question is easy to answer: the cultural sector does receive considerable support from the government but it is tiny compared with that of other sectors, such as agriculture, education, transport or defence. The second part of the question cannot be answered directly, at least while it is agreed that there is no such thing as a collective social welfare function, which would enable us to evaluate and compare the performance of the various sectors. Although this type of evaluation is not possible in an empirically relevant way, the issue can be successfully approached by moving to the constitutional level of analysis. The support of a sector by the public must be subject to a generally accepted decision process. In a democracy, this support must be approved by the citizens. In a representative democracy, the decisions taken by a duly elected parliament and government are taken as legitimate, even if they are not perfect. In a democracy with direct participation rights of the population via popular referenda (as in various states of the US, in Australia and Switzerland), the voting outcome to specific propositions, and the corresponding level of support for the arts, is taken as legitimate. Empirical research indicates that citizens are willing to support the arts with substantial funds if asked to decide in referenda. The fear sometimes raised that the population is not able to judge issues connected with culture, and will therefore reject the support of the arts by public means, finds no justification. In both types of democracy, by implication,

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456  Handbook of cultural economics whatever has been decided in the political process, in respect of the support of the arts and other sectors, must be assumed to fulfil the wishes of the population. In contrast, when the democratic process is violated, or when the decision process is taken in an authoritarian or dictatorial way, public support for the arts (or for any other sector) does not reflect the wishes of the population. In this instance, the arts supported conform to what the people in political power consider to be art. Only in relation to highly cultured rulers (for example, the Medici of the Renaissance, in Italy) will the publicly supported art be of lasting value. In the other instances, the activities of artists who produce for the benefit of authoritarian rulers (for example, is the socialist realism promoted by Stalin) are promoted. An important constitutional decision concerning public support of art is whether decision-making is centralized or takes place in a federal system of government. In the latter, art suppliers do not depend solely on one public authority but can try out their ideas on several public donors. This raises the possibility of, and incentives for, innovative art.

SEE ALSO: Chapter 1: Application of welfare economics to the arts; Chapter 55: Tax concessions; Chapter 58: Welfare economics.

REFERENCES Benhamou, F. (2004), L’Économie de la Culture, 5th edn, Paris: La Découverte. Cowen, T. (1998), In Praise of Commercial Culture, Cambridge, MA: Harvard University Press. Frey, B.S. (2003), Arts & Economics: Analysis & Cultural Policy, 2nd edn, Berlin and Heidelberg: Springer-Verlag. Frey, B.S. and W.W. Pommerehne (1990), Muses and Markets: Explorations in the Economics of the Arts, Oxford: Blackwell. Frey, B.S. and W.W. Pommerehne (1995), ‘Public expenditure on the arts and direct democracy: the use of referenda in Switzerland’, European Journal of Cultural Policy, 2 (1), 55–65. Grampp, W.D. (1989), Pricing the Priceless: Art, Artists and Economics, New York: Basic Books. Last, A.-K. and H. Wetzel (2011), ‘Baumol’s cost disease, efficiency, and productivity in the performing arts: an analysis of German public theaters’, Journal of Cultural Economics, 35 (3), 185–201. Mueller, D.C. (2003), Public Choice III, Cambridge: Cambridge University Press. O’Hagan, J.W. (1998), The State and the Arts: An Analysis of Key Economic Policy Issues in Europe and the United States, Cheltenham, UK and Lyme, NH, USA: Edward Elgar. Schulze, G.G. and H.W. Ursprung (2000), ‘La donna e mobile – or is she? Voter preferences and public support for the performing arts’, Public Choice, 102 (1–2), 129–47. Throsby, D. (2010), The Economics of Cultural Policy, Cambridge: Cambridge University Press. Towse, R. (2010), A Textbook of Cultural Economics, Cambridge: Cambridge University Press. Towse, R. (2014), Advanced Introduction to Cultural Economics, Cheltenham: Edward Elgar.

FURTHER READING This text is partly based on chapter 7 in Frey (2003). General discussions of the economics of cultural policy are provided in Towse (2010, 2014), Throsby (2010), Benhamou (2004) and Frey and Pommerehne (1990). Arguments against direct public support for the arts are advanced by Grampp (1989) and Cowen (1998). That citizens are prepared to support the arts, even if they do not personally engage in them, is shown in Frey and Pommerehne (1995) and Schulze and Ursprung (2000).

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51.  Publishing

Trilce Navarrete Hernández

Adoption of new technologies can disrupt market structures, leading to the demise of processes rendered obsolete (such as scribal labour) or eventually creating a new practice (such as the free publication of a crowdsourced encyclopedia). In the publishing industry, the current changes owing to the prevalent use of information and communication technology (ICT) and the Internet are reminiscent of the changes throughout the fifteenth through eighteenth centuries, when technological changes led to new market players, new products and services, and new consumption habits. Publishers have benefited from economies of scale and a significant reduction of costs, though not without a transformation in the sector. Further, while writers and readers appear to welcome digital libraries and printing on demand, believing it represents a liberation of tyrannical intermediaries, I argue that, as in the past, new intermediaries are emerging with adapted gatekeeper roles.

BRIEF HISTORY OF PUBLISHING Production of books has a millenary history. Starting randomly in Ireland during the eighth and ninth centuries, Irish monasteries were centres of manuscript book production followed by Spain, in the tenth century, who controlled 30 per cent of the European book market. While book production and consumption were determined by the capacity of the monasteries, Gutenberg’s printing press permitted an expansion of the book market during the Renaissance, with the adoption of movable type printing as the key technological innovation in Europe during the fifteenth century. Importantly, printers continued to evolve. Most publishers before the 1700s did their own printing, and the Dutchman Willem Blaeu improved the design of the wooden press in the seventeenth century, introducing larger presses to print maps. The firm had nine presses for type and six more for engravings in Amsterdam, as type required a different press to image printing. In the early 1800s, production was doubled with Stanhope’s iron hand-press and quadrupled with Koening’s steam press (Briggs and Burke 2009, p. 19). These technological changes required significant economic and human capital, for which clusters of production were not unusual. Venice was the centre for printed books in the fifteenth century, responsible for 27 per cent of the European market, with about 500 printers producing over 15 000 titles and 18 million copies. The Counter Reformation posed such restrictions on the multicultural market in Venice that production dispersed across Europe, eventually centralising around Basel and Geneva. Switzerland had the highest per capita book production in the sixteenth century, which was followed by Amsterdam in the seventeenth century, where over 270 booksellers and printers accounted for 8.5 per cent of book production – in addition to printing maps, art prints, and newspapers, an emerging genre. The French Enlightenment is most probably behind 457

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458  Handbook of cultural economics the fuelling of book production and consumption in the late eighteenth century in France. London followed to become the economic centre of book production in the eighteenth century, responsible for 23 per cent of the European book market, although Sweden implemented a strong literacy policy leading to the ‘explosion of the printing industry’ (Buringh and van Zanden 2009, p. 423; see also Briggs and Burke 2009). The growth in the sector required a restructuring of the organisation. While stationarii were associated with printing, publishing, selling and lending of books in the late medieval period (Mackenzie Owen 2007), the emergence of publishing houses enabled the separation of printing and selling. Publishers, in addition, hired authors to provide marketable content, for example, David Hume being paid for his historic writing and not for his philosophical work, or Caspar Barlaeus who was hired as the first academic editor by the Elzevir family for their publishing house. Since early on, a winner-takes-all approach was observed, where a few popular authors or editions would cross-subsidise lesser known publications. Images were as important as text, albeit posing additional technical challenges. Music publishing serves to illustrate this. In the fifteenth century, printed music was often limited to red staff lines on the page in most liturgical books, which were later filled by hand with the desired notes. The reason being that even though liturgical texts were fixed and thus shared across monasteries, musical traditions differed locally. Printers therefore omitted musical details in order to avoid limiting their market sales. Printing only the lines was also cheaper: printing a note superimposing a staff line required two impressions, doubling the costs. One early example from 1480 (Brevis grammatica) shows the opposite: only the notes and the clef were printed, so that the lines could be drawn by hand. Ottaviano Petrucci, a Venetian publisher, developed a three-stage printing process (first the notes, then the staves and, third, the text, the initial, signatures and page numbers) that stimulated the market for polyphonic music. In 1498 he obtained an exclusive right to print and sell music for voices, organ and lute across the Venetian Republic. Half a century later, Pierre Attaingnant, a Parisian printer, developed music printing from type in one impression. Both his printing technique as well as his musical repertoire were widely copied. Printing of music flourished with the publications by Tylman Susato in Antwerp, including 60 musical books between 1543 and 1561, later joined by Christoffel Plantijn. It appears that musical printing using movable type followed the same principles of text, as documented by the Plantin-Moretus printer in Antwerp (currently a museum and listed as World Heritage in 2005). As printers and musical notation developed in the later centuries, so did the complexity of preparing plates for printing with the usual breaking up of the individual elements for future re-use. This was a labour-intensive process (Boorman et al. 2001). An alternative was image printing. Musical theory books from the Middle Ages and the early Renaissance included diagrams linking music to arithmetical concepts, for which the use of woodblocks was most suitable. A woodcarver was hired to produce the images for the book run, which required the skill and often simplified the representation of a white note on a staff line. It has been estimated that over 300 works and 600 editions on music theory were printed by 225 printers in 75 towns in Europe in the sixteenth century, some of them running to 40 editions in 63 years. An early print on a metal plate survives from 1446. Music publishing using etching (where acid eats into a copper plate) was less common and lasted until the eighteenth century, while engraving (hand carved) became extensively used for printing music well

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Publishing  459 into the mid-1990s. Eventually, specialist engraving houses developed signature artistry on optimum legibility and layout design, such as the printing firms of Carl Gottlieb Röder from Leipzig illustrating musical publications from London, St Petersburg and Latin American publishers. His firm also used printed lithographs, increasing production from 30 to 300 sheets per minute (Boorman et al. 2001). Music publishing is not always dated, but estimates identify a significant growth of output after the eighteenth century owing to the rise of engraved music and the proliferation of song sheets. Considering a yearly music publishing of 80 titles in 1550, Boorman et al. (2001) estimate that music publication grew to 150 titles in 1700, 300 titles by 1750, 1000 titles by 1800, 10 000 titles by 1850, and reaching a peak of 50 000 titles by 1910. Other technologies to print music, as other iconographic material, include lithography (similar to etching but in stone); photographic transfer; stencils and dry transfer; and photography, while music printing using type eventually led to the invention of the musical typewriter (Boorman et al. 2001). Commercial sound recordings and the increasing prominence of digital recordings are behind the decrease in paper music publishing. The end of the twentieth century has seen an explosion of music publishing using music engraving software such as Sibelius and Finale (proprietary), MuseScore and LilyPond (open source), and the open initiatives MusicXML and MEI (Music Encoding Initiative). Music representation can also be audio based, which have seen a steady development in encoding formats such as MP3 (MPEG-1 or MPEG-2 Audio Layer III) (Orio 2006). Not surprisingly, music publishing is increasingly linked to multimedia display and data processing, as well as to distribution platforms and online storage. This brief history of printing highlights an important shift from the manual production of manuscripts used for knowledge transfer within monastic libraries, to the growth of a diverse and profitable mechanical (music) publishing industry, and more recently to an exploration of the possibilities of production, distribution and consumption of content using digital technology. The following sections discuss the publishing industry in general, from the production and consumption perspectives.

PRODUCTION Publishing has been associated with books, generally divided into trade and educational or professional books, and a variety of other print material such as journals, newspapers, magazines, and educational publications. More recently, social media has given rise to new forms of publication, such as websites and blogs. A significant share of publishing revenue comes from digital publication, including e-books, tablet applications or special social media content (Wikström and Johansson 2013). Book production broadly includes: content creation and acquisition; content selection and processing; transformation of content; distribution; and marketing and promotion (Picard 2011). The traditional quality signals of prizes, author reputation, book reviews and word of mouth, all increasingly also having a digital variant, making the sector relatively transparent (Canoy et al. 2006). Book production across the world continues to increase, with differences per country related to economic prosperity, the education level of the population or the population density. Canoy et al. (2006) analyse annual book title production by country between

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460  Handbook of cultural economics 1975 and 1999 based on production by gross domestic product (GDP) per capita, and find that greater incomes lead to greater sales, but the positive relationship found in lower per-capita income countries is not as strong in higher per-capita income countries (the US has a similar level of production to Greece). Countries with fewer years of schooling among the population have a clearly lower book production, while more years of education do not show a strong correlation with book production (Australia, Canada, France, Japan and the US have low book production), and population density does not bear any relation to size of book output. The main characteristics of the publishing industry include: having an uncertain demand, half of which consist of spontaneous purchases; high production costs and small marginal costs, with a short period of profitability; and enjoying an infinite variety of titles (or horizontal differentiation) and range of quality (or vertical differentiation) (Canoy et al. 2006). The free entry to the sector has led to a large number of competitors in each part of the production chain, who seek a profit in the continuous growth of production. Nevertheless, the sector is dominated by a few large publishing houses. The mergers in the publishing industry in the past decade can be largely attributed to new digital production processes with business models that strongly rely on advertisement fees, are increasingly personalised and provide content at distribution cost (close to zero) (Wikström and Johansson 2013). Similar to music, film and game publishing, over 35 per cent of book-publishing revenue comes from older publications, while 70 per cent of titles will not earn the author’s fee. For a general trade book, costs of printing can be divided into manufacturing (10 per cent), distribution (8 per cent), marketing (7.5 per cent), publisher’s overhead (8 per cent), author’s share (10 per cent), retail store discount (47 per cent), cost of returns (3.5 per cent) and publisher’s profit (6 per cent) (Vogel 2007). Authors’ earnings vary by genre, where television receives by far the higher earnings, followed by theatre or film, the Internet, and academic or educational content, while translations receive the lowest earnings (Towse 2019). Authors wanting to keep a larger share of the sale of a book will consider self-publishing. Self-publishing has further lowered the entry barriers to new writers, promising greater diversity in content and in quality as well as the reach to wider and richer markets (Wikström and Johansson 2013). Self-published independent authors capture between 30 and 40 per cent of the e-book market (Towse 2019). It has been estimated that 235 000 electronic and printed books were self-published in the US in 2011, with the example of the very successful Fifty Shades of Grey, first published in 2010, released as an e-book in 2011, and which was sold over 65 million times by 2012 (Wikström and Johansson 2013). However, while authors and publishers may avoid the multinational publishing houses, they may still rely on multinational online distribution platforms, such as Amazon or Apple Books, in order to reach consumers. Consumers, in turn, may be locked-in to a platform’s hardware, for example, Amazon’s Kindle, and a collection of books previously purchased. Since the appearance of the first e-readers in the mid-2000s, technological competition has led to a series of innovations to improve the quality of display, battery life, and general look and feel of the devices. However, smartphone technology has also evolved to compete in the market for portable screen devices, resulting in the convergence of the various e-readers on the market (Benghozi and Salvador 2015). The complexity of the market is evidenced by the role of

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Publishing  461 technological suppliers, digital platforms and book publishers involved in the technological innovations of e-readers. Elite writers in the sixteenth and seventeenth centuries chose to distribute their writings through manuscript copies, owing to the prejudice that mechanical printing led to the popularisation of books as well as to avoid religious, moral and political censorship (Briggs and Burke 2009). Similarly, writers in the twenty-first century may choose to distribute their work through established publishing houses in order to gain reputation as well as to reduce the risk of illegal copying. Illegal copying is not new to digital technology. Copyright was first proposed to protect writers in eighteenth-century London, but the ease with which digital copies are made and distributed online has led to new concerns. Evidence shows that consumer selections of titles accessed through shadow libraries respond to poor market distribution. Countries with higher use of peer-produced online libraries have a lower diversity of content in their local market (Bodo and Lakatos 2012; Bodo 2018). Online libraries (and online archives) evidence the challenges of translating a legal framework made for paper publication into the digital realm, where publication may be linked to other online functions such as searching, indexing and hosting. Educational and professional publishing is a specific market, as consumption is predictable based on the size of the school population, and is often repackaged in digital form available under a product bundle license (Vogel 2007). In the Netherlands, all 13 universities, the national library and the Dutch Research Council have signed the National Plan for Open Science aiming to provide full access to research results funded publicly by 2020. Agreements have been reached with Springer, Sage, Elsevier, Wiley, American Chemical Society, Taylor & Francis and Oxford University Press (VSNU 2018). In some disciplines, such as information science, most journals are only published digitally. The European Book Publishing Statistics report a slight decrease of revenue from academic book sales, down from 19.5 per cent in 2013 to 18.5 per cent in 2017. Revenue from the sale of educational books, however, increased from 18.8 per cent in 2013 to 21.2 per cent in 2016. Still, nearly half of the revenue from sales originates from consumer trade books, which account for over €10 million (FEP 2018). Eurostat (2016) reported an increase in the value added from book publishing from 9.837 in 2011 to 9.690 in 2013. As Canoy et al. (2006, p. 734) note, ‘the book market seems to flourish in one dimension (production) but not in the other (reading)’.

CONSUMPTION Reading enables lifelong learning and increases the chances of active participation in social and economic life. Reading is associated with educational attainment; in particular, higher educational attainment has a noticeable relationship to reading habits. Luxembourg has the lowest disparity between educational attainment groups (Eurostat 2016). The United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics reported 86 per cent of the adult (aged 15 years and older) global population have basic literacy skills, higher for those aged 15 through 24 (91.4 per cent) and lower for women (83 per cent) (UNESCO 2017).

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462  Handbook of cultural economics Literacy has recently been redefined by UNESCO as the ‘ability to identify, understand, interpret, create, communicate and compute, using printed and written materials associated with varying contexts’ (Montoya 2018). Increasingly, literacy skills have to be complemented by ICT skills to enable consumers to function as digital literates, for instance, to be able to use software programs, to copy, paste, move or download files, and eventually to write computer programs. Currently, UNESCO’s Sustainable Development Goal 4 aims to ensure literacy and numeracy by all youths and by a substantial proportion of all adults, by 2030. In spite of the goals, statistics report a declining trend in reading. Finland, for instance, reported a decrease in the population who read at least one book in the past 12 months, from 79.3 per cent in 2007 to 72.7 per cent in 2011. Similarly, Austria, Bulgaria, and Spain reported a decrease from 74.8 to 73 per cent, 52.1 to 48.2 percent and 60.8 to 58 per cent, respectively, during the same period. Only Germany reported an increase, from 72.8 to 75.3 per cent (Eurostat 2016). The apparent decrease in reading may be linked to the increased use of the Internet to access information, replacing the use of books and encyclopedias as reference sources, as well as to alternative sources of literature beyond the classical paper book format (including e-books). Population surveys of time spent in cultural activities are yet to adjust to the changing cultural consumption patterns. In the Netherlands, the number of books bought has decreased from 47.6 million in 2005 to 39 million in 2015 (including e-books, from 2010), while the sale points have increased from 1462 to 1525 during the same period. Similarly, the books lent from libraries decreased by 41 per cent, from 132.5 million books lent in 2005 to 79.7 in 2015. A popular library app (VakantieBieb) has stimulated e-book loans, which have doubled, reaching 4.7 million loans in 2016 (Schrijen 2019). Book consumption is price elastic, except in the case of bestsellers, owing to the large variety of books available for substitution. Book consumption is also income elastic, so purchases grow as reflection of greater income. The average price of an e-book in the Netherlands was €8.95 in 2018, a decrease by 68 per cent compared with the price of a printed book (or p-book), priced at €13.10 in 2018 (Leesmonitor 2019). However, not all books bought or lent are read. Dutch consumers reported reading 72 per cent bought books and 64 per cent of lent books, while the Kobo online bookshop reported 60 per cent of e-books bought are never opened (Leesmonitor 2019). Governments can devise a fixed book price agreement, where the publisher fixes a retail book price ‘intended to raise or maintain prices above the competitive level in order to provide an incentive to publishers and bookshops to increase the range of titles they supply. It emphasises non-price (access, greater choice) over price competition’ (Towse 2019, pp. 611–12). By setting a retail price, the publisher has the incentive to produce a greater number of titles, where the more popular serve to cross-subsidise the less popular, increasing the overall diversity of the market offerings. Bookshops, in turn, benefit from a certain equity of distribution by providing equal prices to consumers independently of the size of the bookshop, thereby increasing the diversity of firms in the market. Despite the arguments, empirical evidence has failed to link a fixed book price policy to a greater diversity of the market. This may be owing to the relative transparency of the market. Argentina, Austria, Germany, Greece, Israel, Italy, Japan, Lebanon, Mexico, the Netherlands, Norway, Portugal, Slovenia, South Korea and Spain have a fixed book price agreement, while Finland, Sweden, Ireland and the UK have freed book prices. Online

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Publishing  463 consumers may notice the same book to be priced differently on amazon.nl, for instance, and amazon.uk. The global market has further highlighted discrepancies in value added tax (VAT) across countries, influencing online consumer choice. Reduction of VAT for cultural services, for example, is one indirect form of government subsidy to stimulate consumption. The amount of the subsidy depends on the consumer: the greater the purchase, the greater the subsidy. Thus, a reduced VAT rate represents a decrease in government revenue that could otherwise be allocated as direct subsidy to a desired cultural good, such as: educational materials, since all books receive the same VAT rate; a cultural service, such as a public library or public provider; or consumer, such as youth or women readers. Evidence from a cross-country comparison shows that publishers do not transfer the reduced cost to the consumer in the form of a reduced price. However, the retail price for books does influence consumption (Borowiecki and Navarrete 2018). Governments stimulate reading and access to books through the provision of libraries. According to a report by the Online Computer Library Centre (OCLC 2003), there are about 1 million libraries worldwide holding over 16 billion books (4.5 million in public libraries, 3.7 million in school libraries, 3.5 million in academic libraries, 3.2 million in special libraries and 0.9 million in national libraries). According to Salaün (2013), libraries have two important contributions. First, the common collections benefit from network effects in that the larger the pool of contributors, the larger the benefit to the contributors’ consumers. It is more efficient to go to one large repository to find ‘all the content of the world’ than to have to travel to various libraries to find the desired book. Libraries have pooled resources to share the costs of collecting, organising, cataloguing, indexing and cross-referencing collections, facilitating the inter-library loan system. Similarly, online services (such as Google) share the functionalities of organising and providing access by consumers to vast quantities of information content that libraries have performed. A second contribution of libraries, key in characterising them from other Internet information services, is the provision of a sustainable repository. Libraries collect, organise and make accessible their holdings, but also protect their collections so future generations will also have access to the past investment.

CLOSING REMARKS The arrival of Gutenberg’s printing press led to a decrease in book price and explosion in the book market, which continues to expand book-title output through the digital publishing variant. Contemporary readers can sympathise with a Venetian writer from 1550 in his frustration that there were ‘so many books that we do not even have time to read the titles’ (Briggs and Burke 2009, p. 15). The increased availability of published texts resulted in an increase in population literacy as an indirect and long-term effect (Buringh and van Zanden 2009). Digital technology and the use of the Internet to distribute content may further eliminate illiteracy, though not necessarily in book form and perhaps not in text form. Video is positioning itself as a preferred online format for knowledge transfer, while video games and virtual reality are increasingly used as educational aids. Digital literacy skills are imminent.

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464  Handbook of cultural economics The publishing industry is part of the creative industries, which produce private goods (a book for purchase) and public goods (non-rival and non-excludable information which can be transferred). Publishing is also an important contributor to GDP and books have proven to be profitable luxury goods. Books are also carriers of core creative art forms, namely literature and music. The role of governments therefore lies in balancing intervention to correct eventual market failures related to the suboptimal production (or consumption) of cultural goods while stimulating literacy in the population, within a healthy and profitable market.

SEE ALSO: Chapter 13: Cost of production; Chapter 24: Demand; Chapter 41: Music publishing; Chapter 47: Platforms.

REFERENCES Benghozi P.-J. and E. Salvador (2015), ‘Technological competition: a path towards commoditization or differentiation? Some evidence from a comparison of e-book readers’, Systèmes d’Information et Management (SIM), 20 (3), 97–135. Bodo, B. (2018), ‘Library genesis in numbers: mapping the underground flow of knowledge’, in J. Karaganis (ed.), Shadow Libraries: Access to Knowledge in Global Higher Education, Cambridge, MA: MIT Press, pp. 53–78. Bodo, B. and Z. Lakatos (2012), ‘Theatrical distribution and P2P movies piracy: a survey of P2P networks in Hungary using transactional data’, International Journal of Communication, 6 (1), 413–45. Boorman, S., E. Selfridge-Field and D. Krummel (2001), ‘Printing and publishing of music’, in S. Sadie (ed.), The New Grove Dictionary of Music and Musicians, Oxford: Oxford University Press. Borowiecki, K. and T. Navarrete (2018), ‘Fiscal and economic aspects of book consumption in the European Union’, Journal of Cultural Economics, 42 (2), 309–39. Briggs, A. and P. Burke (2009), A Social History of the Media: From Gutenberg to the Internet, 3rd edn, Cambridge: Polity Press. Buringh, E. and J. van Zanden (2009), ‘Charting the “rise of the West”: manuscripts and printed books in Europe, a long-term perspective from the sixth through eighteenth centuries’, Journal of Economic History, 69 (2), 409–45. Canoy, M., J. van Ours and F. van der Ploeg (2006), ‘The economics of books’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 721–61. Eurostat (2016), Cultural Statistics, Brussels: Eurostat. Federation of European Publishers (FEP) (2018), European Book Publishing Statistics, Brussels: FEP. Leesmonitor (2019), ‘Leesmonitor’, Boekenvak, accessed 13 December 2019 at https://www.leesmonitor.nu/nl/ boekenvak#prijs-e-boek-daalt. Mackenzie Owen, J. (2007), The Scientific Article in the Age of Digitisation, Dordrecht: Springer. Montoya, S. (2018), ‘Meet the SDG 4 data: measuring youth and adult literacy and numeracy’, Data for Sustainable Development Blog, UNESCO, 29 August 2018, accessed 13 December 2019 at http://uis.unesco. org/en/blog/meet-sdg-4-data-measuring-youth-and-adult-literacy-and-numeracy. Online Computer Library Center (OCLC) (2003), ‘Libraries how they stack up’, Online Computer Library Center, accessed 13 December 2019 at https://www.oclc.org/content/dam/oclc/reports/librariesstackup.pdf. Orio, N. (2006), ‘Music retrieval: a tutorial review’, Foundations and Trends in Information Retrieval, 1 (1), 1–90. Picard, R. (2011), The Economics and Financing of Media Companies, New York: Fordham University Press. Salaün, J.-M. (2013), ‘The immeasurable economics of libraries’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 290–305. Schrijen, B. (2019), ‘Letteren’, in Boekmanstichting cultuurindex blog, Boekmanstichting, 12 December 2019, accessed 13 December 2019 at https://www.boekman.nl/cultuurindex/sectoren/letteren. Towse, R. (2019), A Textbook of Cultural Economics, Cambridge: Cambridge University Press. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2017), ‘Literacy rates continue

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Publishing  465 to rise from one generation to the next’, Fact Sheet No. 45, FS/2017/LIT/45, UNESCO Institute for Statistics, Montreal. Vereniging van Universiteiten (VSNU) (2018), Roadmap Open Access 2018–2020, The Hague: VSNU. Vogel, H. (2007), Entertainment Industry Economics: A Guide for Financial Analysis, Cambridge: Cambridge University Press. Wikström, P. and A. Johansson (2013), ‘Publishing’, in R. Towse and C. Handke (eds), Handbook on the Digital Creative Economy, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 344–52.

FURTHER READING For a thorough discussion on the publishing industry see Canoy et al. (2006).

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52.  Ratings, reviews and recommendations Paul Belleflamme and Martin Peitz

Before reading this chapter, you cannot know whether you will find it interesting, instructive or entertaining (even if you are familiar with the authors’ previous work). This chapter is what economists call an experience good, a good whose quality cannot be ascertained before it is consumed. Owing to this uncertainty, you may decide not to read this chapter and use your time differently. Anticipating this risk, the editors of this book and their publisher have put in place a number of strategies to not lose your custom. First, they have encouraged previous readers to rate and review the contents of the book, hoping that a high average rating and positive reviews will lead you to infer that this chapter is of high quality or is a good fit for your interests. Also, it may not be by chance that you came across this chapter in the first place; you may have been brought to it by a recommender system, using an algorithm that inferred that you would probably like it (on the basis of your past searches on various websites, of the behaviour of readers sharing your interests or characteristics, and of the popularity of the book). In general, potential consumers of cultural goods appreciate ratings, reviews and recommendations because they incur an opportunity cost in evaluating how cultural goods fare for quality and how they fit their tastes. It has been observed for as long as cultural goods have existed that consumers rely on what other consumers did in the past to make better informed decisions. Yet, digital technologies and the Internet have dramatically altered the role that ratings, reviews and recommendations systems (hereafter, 3R systems) play for cultural goods. They have done so in three major ways, which we explore in this chapter. First, digital platforms have developed 3R systems to an unprecedented scale and have thereby become the main intermediaries guiding consumption of cultural goods. Second, 3R systems have been turned into strategic instruments for competing platforms. Third, the increasing influence of 3R systems on consumers’ choices has affected cultural diversity.

DIGITAL PLATFORMS AND 3R SYSTEMS We define platforms as undertakings whose core mission is to enable and to generate value from interactions between users (see, for example, Belleflamme and Peitz 2018a). Since the Internet and digital technologies greatly contribute to reducing transaction costs, most platforms now operate online and are named digital platforms. Prominent digital platforms for the provision and distribution of cultural goods include Netflix, Hulu, Amazon Prime Video (movies, television shows), Spotify, YouTube, Apple Music, Pandora, Deezer, Tidal (music), Steam, Epic Games (games), Amazon KDP, Apple iBook (e-books), Facebook, Periscope and Instagram Live Video (live streaming of performing arts). Digital platforms also exist for the promotion and diffusion of other cultural 466

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Ratings, reviews and recommendations  467 goods, such as paintings, sculptures or crafts (for example, artwizard.eu organizes digital ­exhibitions); yet, as the consumption of these goods is much less scalable, these platforms are less prominent. As digital platforms have gradually become the main vector for the consumption of cultural goods, they are now often more prominent than traditional cultural intermediaries (such as labels, critics or specialist media) in dealing with the asymmetric information and matching problems raised by cultural goods. Platforms can integrate services by traditional cultural intermediaries (for example, products on Amazon are shown with quotes from professional critics) or use in-house experts (for example, Spotify creates very popular curated lists). In line with traditional practice (for example, the Billboard Hot 100 Chart), platforms also aggregate past consumption decisions to provide unconditional recommendations (for example, Spotify highlights the most popular songs through the algorithmic playlist Top50).1 However, on many digital platforms, consumers can obtain valuable, more granular information from reviews and ratings by other consumers. Platforms, then, play the following two roles: they invite consumers to evaluate various goods that have proved successful or popular with others, and they organize the exchange of the information across consumers. As information is provided and accessed by consumers, ratings and reviews are part of platforms’ information-pull strategy. In parallel, most platforms also pursue an information-push strategy by making recommendations to specific buyers; recommendations may then be based on the consumers’ characteristics and observed behaviour, as well as on the goods’ popularity and features. Importantly, digital platforms exploit the interdependence between information-pull and information-push strategies by using ratings and reviews as inputs for their recommendation algorithms. As a consequence, the efficiency of their 3R systems increases with the volume, variety and velocity of the data that they can collect about their users and the transactions they conduct.2 This huge quantity and diversity of data also gives digital platforms another advantage over traditional recommenders: they are able to personalize recommendations and ratings, and therefore cater better to their diverse audience.3 However, 3R systems can only help consumers if they contain relevant information. As far as ratings and reviews are concerned, their informativeness may be limited owing to the decisions made by their providers, that is, the consumers of cultural goods. First, consumers may leave noisy ratings and reviews (they fail to understand what they are asked and base their evaluation on irrelevant experiences, or they have idiosyncratic tastes). Second, some imposter consumers may have strategic motives to distort their evaluation and publish fake reviews; in particular, authors, publishers or vendors may manipulate reviews to promote the sales of their goods (and/or slow down the sales of rival goods).4 Third, consumers may be more prone to leave positive than negative feedback, owing to asymmetric herding behaviour; for instance, Muchnik et al. (2013) show that early positive ratings increase the likelihood of later positive ratings by 32 per cent.5 Finally, consumers’ ability to learn from ratings and reviews may be hampered by another behavioural bias, which leads consumers to treat correlated information as if it was coming from independent sources; owing to this correlation-neglect, consumers may fail to acknowledge that the ratings they observe depend themselves on information retrieved from earlier ratings, thereby putting too great a weight on earlier ratings.6 It is not known a priori what attitude digital platforms should have regarding how informative ratings and reviews are. On the one hand, more informative rankings

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468  Handbook of cultural economics and reviews tend to make the platform more attractive; platforms may then want, for instance, to counteract errors and manipulations. On the other, for-profit platforms may increase their revenues by sacrificing informativeness (for example, by affecting the aggregate rankings of goods, or by varying the ordering and display of individual reviews). Similarly, digital platforms may find it profitable to distort their recommender system or make it less informative. For instance, as Bourreau and Gaudin (2018) suggest, a digital platform that pays royalties to producers of cultural goods may prefer to bias its recommendations in order to enhance the consumption of goods that come with lower royalties.7

THE STRATEGIC USE OF 3R SYSTEMS Even if the main function of 3R systems is to solve the inherent asymmetric information and matching problems of cultural goods, digital platforms also deploy these systems for strategic reasons. By exploiting their 3R systems to leverage network effects and customize the cultural goods that they produce, digital platforms may find effective ways to retain their consumers, and even gain market shares, in cultural markets that are increasingly competitive. Let us examine how. Recall that platforms’ core mission is to facilitate the interaction between users and to generate value from this interaction. The main vector of value creation is the active management of the network effects that platform users exert on one another. Positive network effects arise because the more users interact on the platform, the more valuable the interaction is for every user. The point we make here is that 3R systems contribute to produce positive network effects. More precisely, 3R systems generate the following self-reinforcing mechanism: when a platform attracts more users, it collects more ratings and reviews and monitors more transactions; as a consequence, the platform can analyse bigger and richer data-sets, which enables it to make reviews and ratings more informative, and recommendations more personalized and precise; the platform then becomes more attractive and the user base grows. In summary, more users attract more users. However, a condition for this positive feedback loop to be turned into a competitive advantage is that network effects have to be specific to the platform; that is, only the users of the platform should benefit from the enhanced quality of the 3R systems (otherwise, the platform would not be able to appropriate the value it created by improving its 3R systems). This certainly applies to recommender systems, as recommendations are largely based on a consumer’s own behaviour; for instance, the more tracks you listen to on a streaming platform, the better the matches that the platform’s recommender system will suggest to you, as its algorithm will have a more accurate representation of your tastes. As for ratings and reviews, even if consumers of cultural goods often have access to them whether or not they purchase on a particular platform, studies show that consumers tend to take note of ratings and reviews only on platforms on which they complete their purchase.8 This suggests that the network effects stemming from rating and review systems tend also to be platform specific. Another, complementary, way by which digital platforms can use their 3R systems to gain a competitive advantage is to capitalize on the vast amount of data that these systems

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Ratings, reviews and recommendations  469 generate to produce their own content and serve it to the most appropriate audience. As Smith and Telang (2018) explain, ‘the wealth of data maintained by digital entertainment platforms can foster more creative freedom, not less. Instead of focusing solely on offerings with sure-fire mass appeal, these platforms can take a chance on unique content because they can deliver that content directly to the best audience’. Together, platform-specific network effects and content customization create switching costs for consumers of cultural goods: once they have subscribed with a particular digital platform, they tend to stay on that platform, as switching would mean losing a series of benefits (customized content, useful recommendations, informative ratings and reviews, curated playlists, social interactions with like-minded users, and so on). In the current context, in which consumers face difficulties in porting their data across digital platforms, switching costs allow platforms to enhance consumer loyalty and to compete better for their attention, which is the ultimate scarce resource in cultural markets.

3R SYSTEMS AND THE DIVERSITY OF CULTURAL GOODS Most cultural goods markets exhibit a distribution of sales that is highly skewed in that a limited number of goods (often a few hundred) account for the bulk of sales, while the vast majority of goods (which constitute the tail of the distribution) sell very few units. As Brynjolfsson et al. (2006) argue, online markets have a longer tail in the sales distribution than traditional offline markets. One driving force on the supply side stems from the lower inventory and distribution costs that allow online vendors, with virtual shelf space, to give access to a broader variety of goods than brick-and-mortar stores. There are further effects that contribute to increase the variety produced: online markets enhance the (re)production of niche products (for example, on-demand printing of books), as well as the production of user-generated content. On the demand side, 3R systems (together with search and sampling tools) have the potential to make consumers aware of and, pay attention to, this increased supply. Yet, awareness and attention are a necessary but not a sufficient condition for consumption. The question of interest is thus whether 3R systems also lead to the consumption of this increased supply, thereby making the long tail thicker (as the sales of niche goods would increase). Note first that, independently of 3R systems, there are several reasons why consumers might not take advantage of the increase in the variety supplied:9 information overload (more variety intensifies the consumers’ cognitive burden, which prevents them from making optimal decisions), incomplete information (more variety and an asymmetry of visibility make incomplete information problems more acute), herding (confronted with more experience goods, consumers may abandon their private information in favour of inferences based on the popularity of goods) and conformity (consumers caring about their social status may conform to the choices of other consumers instead of following their own tastes). How do 3R systems change the picture? It is plausible that the customization of recommendations (and possibly of ratings and reviews) alleviates the problems caused by information overload or incompleteness; we have argued previously that as digital platforms accumulate a larger volume and variety of data about their consumers, they can improve their algorithms and, thereby, expose consumers to a limited set

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470  Handbook of cultural economics of information that is directly relevant to them. One example is Spotify’s ‘Discover Weekly’ playlist, which makes a set of personalized recommendations to each user. The interplay between 3R systems and consumers’ imitation behaviour (owing to herding and/or conformity) is, however, harder to evaluate. On the one hand, 3R systems reporting popularity measures may lead to more concentrated sales, with best-sellers or blockbusters becoming even more popular. On the other, the directed search, which is inherent in recommender systems, may reduce consumers’ search costs to the extent that they feel more encouraged to search outside the set of cultural goods that they already know and like. Importantly, the relative weight of these two forces varies according to the way 3R systems are designed. As Peukert (2019) explains, recommender systems using collaborative filtering base their recommendations on consumers’ ratings and past consumption behaviour; as a consequence, these systems cannot recommend cultural goods that were never consumed or rated, which tends to make sales more concentrated. To counteract this tendency, hybrid systems also take other sources of information into account and artificially inflate the importance given to newly created goods. Moreover, the last generation of 3R systems personalize not only recommendations but also their appearance.10 Theoretical studies suggest that if the consumer population is characterized by taste heterogeneity, 3R systems that provide personalized recommendations may lead to a thicker tail in the aggregate, meaning that less-popular products receive a larger share of sales after the introduction of a recommender system (see Tucker and Zhang 2011). Two recent empirical analyses support this conjecture.11 Hosanagar et al. (2014) show that personalized recommendations induce consumers to widen their interests. Kretschmer and Peukert (2018) study how recommendations coming from YouTube affect the variety of music that consumers demand through other channels; they show that these recommendations trigger more sales of songs by new artists compared to established artists. A likely outcome, then, is that more niche products will be put on the market and that product variety in the market will increase. We close this discussion by mentioning two other factors that might affect the variety of consumed cultural products and that are linked indirectly to 3R systems. First, in addition to developing 3R systems, digital platforms have also introduced new pricing schemes that may influence consumers’ behaviour. In particular, users of streaming platforms usually pay a flat rate against an unlimited access to a huge library of content. Compared with a pay-per-view scheme, a subscription mechanism substantially lowers the cost of experimentation for consumers.12 Therefore, we expect the switch to streaming to increase the discovery of new cultural goods. Datta et al. (2018) confirm this conjecture empirically: they show that the adoption of streaming substantially raises the quantity and diversity of music consumption. Second, as the volume and variety of data generated by consumers’ behaviour on digital platforms (what they consume, how they consume, how they react to recommendations, the ratings and reviews they produce, and so on) enable platforms to produce cultural goods with features that are more appealing to specific groups of consumers, the question remains as to whether this mass customization reduces or enhances variety. Smith and Telang (2018) suggest the latter; they report estimates according to which the hit shows produced by Netflix attract fewer viewers than corresponding shows produced by traditional television networks. They interpret this not as a sign that Netflix fails to reach

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Ratings, reviews and recommendations  471 its consumers, but as evidence that Netflix’s strategy is precisely to meet its viewers’ needs by expanding their choice set and offering them a collection of movies and shows that caters to various tastes.

CONCLUSION Ratings, reviews and recommendations systems have always played a crucial role in alleviating the asymmetric information and matching problems raised by cultural goods. We have explained in this chapter how digital platforms profoundly alter this role; by developing 3R systems to an unprecedented scale and turning them into strategic instruments, digital platforms significantly affect cultural diversity.

NOTES  1. As Aguiar and Waldfogel (2018) show, being placed on a curated or non-curated playlist by Spotify has a strong impact on the number of times that a song is streamed.  2. As an illustration, it is estimated that Netflix subscribers (130 million worldwide as of July 2018) give about 4 million ratings and make about 3 million searches per day. Netflix also tracks its users’ behaviour: what they watch, when (day and time of the day), where (zip code), how (on which device), completion rate, viewing pattern (pause, rewind or fast forward), browsing and scrolling behaviour. Combining this data with a micro-classification of content (by genre, time period, mood, plot conclusiveness, and so on), Netflix is able to make recommendations that influence about three-quarters of its users’ activity (see Jenkins 2016; Bulygo 2018).  3. Greg Peters (Netflix’s Chief Product Officer) said in 2018: ‘Essentially, we create 300 million different versions of Netflix’ (where 300 million is the total number of profiles that Netflix’s subscribers have created; see Roettgers 2018).  4. Anecdotal evidence of manipulations of that type came from the accidental revelation of the true identities of book reviewers on Amazon.ca. It appeared that a large number of these reviews was written by people with an interest in the sales of the books, that is, the publishers, the authors themselves or their relatives and friends (see Harmon 2004). Mayzlin (2006) also explains how professional marketers are hired in the music industry to post positive reviews of new albums on fan sites and online chat rooms.  5. See Belleflamme and Peitz (2018b) for a detailed discussion of the previous three points.  6. See, for example, Enke and Zimmermann (2019), who provide evidence for the existence of correlation neglect in an experimental setting.  7. Bourreau and Gaudin (2018) give the example of Pandora, an online radio platform, which recognized that it manipulated its recommendation algorithm to affect the frequency at which a music title is played according to the ownership of this title; they also indicate that movie streaming platforms are suspected of biasing personalized recommendations towards their own productions. Sisario (2017) reports that Spotify tends to feed its popular playlists with tracks that the platform commissions from a set of artists and for which it pays lower royalty rates.  8. See, for example, Chevalier and Mayzlin (2006), who analyse the effects of book reviews on the sales patterns of Amazon and Barnes & Noble (the two leading online booksellers in the US at that point in time).  9. See Bourreau et al. (2015) for a detailed explanation. 10. As an illustration, Peukert (2019) reports the following quote by Netflix engineers: ‘Someone who has watched many romantic movies may be interested in Good Will Hunting if we show the artwork containing Matt Damon and Minnie Driver, whereas, a member who has watched many comedies might be drawn to the movie if we use the artwork containing Robin Williams, a well-known comedian.’ 11. For a review of the earlier empirical literature (from 2008 to 2012), see Bourreau et al. (2015). 12. 3R systems in combination with flat rates are possibly more effective in combatting piracy than pay-perview schemes, as they lead to a low sampling cost. On sampling in the context of piracy, see Peitz and Waelbroeck (2006).

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472  Handbook of cultural economics

SEE ALSO: Chapter 20: Cultural diversity; Chapter 24: Demand; Chapter 30: Google Trends data; Chapter 47: Platforms.

REFERENCES Aguiar, L. and J. Waldfogel (2018), ‘Platforms, promotion, and product discovery: evidence from Spotify playlists’, NBER Working Paper No. 24713, National Bureau of Economic Research, Cambridge, MA. Belleflamme, P. and M. Peitz (2018a), ‘Platforms and network effects’, in L. Corchon and M. Marini (eds), Handbook of Game Theory and Industrial Organization, vol. 2, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 286–317. Belleflamme, P. and M. Peitz (2018b), ‘Inside the engine room of digital platforms: reviews, ratings and recommendations’, in J.J. Ganuza and G. Llobet (eds), Economic Analysis of the Digital Revolution, Madrid: Funcas, pp. 75–114. Bourreau, M. and G. Gaudin (2018), ‘Streaming platform and strategic recommendation bias’. accessed 9 December 2019 at https://ssrn.com/abstract=3290617. Bourreau, M., S. Maillard and F. Moreau (2015), ‘Une analyse économique du phénomène de la longue traîne dans les industries culturelles’ (‘An economic analysis of the long tail phenomenon in cultural industries’), Revue française d’économie, 30 (2), 179–216. Brynjolfsson, E., Y. Hu and M.D. Smith (2006), ‘From niches to riches: the anatomy of the long tail’, MIT Sloan Management Review, 47 (4), 67–71. Bulygo, Z. (2018), ‘How Netflix uses analytics to select movies, create content, and make multimillion dollar decisions’, Neil Patel Blog, accessed 9 December 2019 at https://neilpatel.com/blog/how-netflix-uses-analytics/. Chevalier, J.A. and D. Mayzlin (2006), ‘The effect of word of mouth on sales: online book reviews’, Journal of Marketing Research, 43 (August), 345–54. Datta, H., G. Knox and B.J. Bronnenberg (2018), ‘Changing their tune: how consumers’ adoption of online streaming affects music consumption and discovery’, Marketing Science, 37 (1), 5–21. Enke, B. and F. Zimmermann (2019), ‘Correlation neglect in belief formation’, Review of Economic Studies, 86 (1), 313–32. Harmon, A. (2004), ‘Amazon glitch unmasks war of reviewers’, New York Times, 14 February, accessed 9 December 2019 at https://www.nytimes.com/2004/02/14/us/amazon-glitch-unmasks-war-of-reviewers.html. Hosanagar, K., D.M. Fleder, D. Lee and A. Buja (2014), ‘Will the global village fracture into tribes? Recommender systems and their effects on consumer fragmentation’, Management Science, 60 (4), 805–23. Jenkins, T. (2016), ‘Netflix’s geek-chic: how one company leveraged its big data to change the entertainment industry’, Jump Cut: A Review of Contemporary Media, no. 57, accessed 9 December 2019 at https://www. ejumpcut.org/archive/jc57.2016/-JenkinsNetflix/text.html. Kretschmer, T. and C. Peukert (2018), ‘Video killed the radio star? Online music videos and recorded music sales’, CEP Discussion Paper No. 1265, Centre for Economic Performance, London, accessed at https://ssrn. com/abstract=2425386. Mayzlin, D. (2006), ‘Promotional chat on the Internet’, Marketing Science, 25 (2), 155–63. Muchnik, L., A. Sinan and S.J. Taylor (2013), ‘Social influence bias: a randomized experiment’, Science, 341 (6146), 647–51. Peitz, M. and P. Waelbroeck (2006), ‘Why the music industry may gain from free downloading – the role of sampling’, International Journal of Industrial Organization, 24 (5), 907–13. Peukert, C. (2019), ‘The next wave of digital technological change and the cultural industries’, Journal of Cultural Economics, 43 (2), 189–210. Roettgers, J. (2018), ‘Netflix’s drama “Dark” may be from Germany, but 90% of its viewers are not’, Variety, 6 March, accessed 9 December 2019 at https://variety.com/2018/digital/news/netflix-dark-international-audience​ -1202719270/. Sisario, B. (2017), ‘While some cry “fake,” Spotify sees no need to apologize’, New York Times, 14 July, accessed 9 December 2019 at https://www.nytimes.com/2017/07/14/business/media/while-some-cry-fake-spotify-sees-noneed-to-apologize.html. Smith, M.D. and R. Telang (2018), ‘Data can enhance creative projects – just look at Netflix’, Harvard Business Review, 23 January, accessed 9 December 2019 at https://hbr.org/2018/01/data-can-enhance-creative-projects​ -just-look-at-netflix. Tadelis, S. (2016), ‘Reputation and feedback systems in online platform markets’, Annual Review of Economics, 8 (1), 321–40.

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Ratings, reviews and recommendations  473 Tucker, C. and J. Zhang (2011), ‘How does popularity information affect choices? A field experiment’, Management Science, 57 (5), 828–42.

FURTHER READING Tadelis (2016) covers rating systems and Belleflamme and Peitz (2018b) survey the economics of 3R systems with a focus on the platforms’ design decisions. Aguiar and Waldfogel (2018) and Datta et al. (2018) obtain valuable insights into consumer behaviour in the context of music streaming.

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53.  Regulation of heritage Ilde Rizzo

In very general terms, regulation can be defined as non-monetary government intervention usually aimed at restricting or modifying the activities of economic agents in line with government policy objectives. However, it is an area where too little or too much can be similarly harmful. When too limited, poorly conceived, redundant or incoherent, these rules can make it difficult to start up a new business, trade abroad or comply with basic administrative procedures . . . Unbalanced or disproportionate regulations can lead to losses in organisational performance, too much administrative discretionary power to make decisions or enforce rules and even to corrupt behaviour. (OECD 2018, p. 20)

The above statement well describes the lights and shadows characterizing regulation in all policy areas, and the cultural sector does not seem to be an exception as far as regulation design and implementation are concerned. This chapter explores these issues in relation to the cultural sector. Since the range of activities in the cultural field raises so many different economic questions, not all of them can be dealt with in the space available. Therefore, the analysis focuses mainly on issues connected with built heritage, an area in which regulation plays an even greater role than in other cultural fields. The economic rationale for government intervention relies on market failure arguments. The transmission to future generations, the improvement of education, strengthening of the sense of community and identity, the promotion of national prestige and the positive impact on local development through tourism are just some examples of the benefits, which cannot be provided through the market and call for public action, to avoid their under-provision. Also, reasons of equity require government intervention to increase heritage accessibility, by reducing social and economic barriers (Pignataro and Rizzo 2020). The existence of market failure in the heritage field is widely agreed, while the extent and the modes of government action are controversial and a matter of an ongoing debate. Government intervention is also subject to failure and does not necessarily ensure efficiency (Towse 2010; see also Chapter 50 in this volume). Government intervention follows different patterns, with a diversity of regulation, direct and indirect expenditure, depending on the prevailing economic and institutional setting. Benhamou (2013) provides a typology of possible alternative modes of intervention in the heritage field – subsidies versus regulations, incentives versus compulsory rules, direct versus indirect support, local versus national versus global intervention – and suggests that tensions may derive from conflicting interests. This chapter investigates the regulation of built heritage, paying special attention to the positive analysis of heritage regulation,1 to the features of the collective decision-making and to the economic and policy implications. 474

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Regulation of heritage  475

REGULATORY TOOLS In the heritage field, government policy aims to conserve and enhance heritage. In line with these policy objectives, regulation is used, on the one hand, to control the stock of heritage, both from the quantitative and qualitative point of view, in order to conserve those buildings or areas with a social value higher than the private one and, on the other hand, to promote the contribution of heritage to sustainable local development, ensuring that only compatible uses are put in practice. The trade-off between these objectives is almost inevitable and has to be addressed through the public decisionmaking process.2 A particular feature of heritage is that its deterioration or destruction cannot be compensated by the creation of new cultural capital as is the case with contemporary artistic items; therefore, conservation is needed to meet current needs without compromising the satisfaction of future needs (Rizzo and Throsby 2006). In this latter perspective, at a macro-level, regulation can be a useful tool for sustainable tourism policies for the protection of heritage against the congestion related to mass tourism. Many popular cultural sites already have management and monitoring systems, for example, timed ticketing or differential pricing, to cope with visitor pressure. This is especially challenging for emerging destinations, where tourism is rapidly growing without well-defined regulation (World Tourism Organization 2018).3 Regulation of heritage consists of different types of action: the identification of the buildings, sites or areas of historical importance, the assignment of a grade of significance, the imposition of limitations on the use of land affecting heritage and the definition, sometimes by both central and local governments, of rules to discipline the various methods of conservation (Peacock and Rizzo 2008). Regulation may also cover the requirements for professionals, at various levels, to operate in the field of heritage preservation. Listing is a main regulatory tool in the heritage field.4 Listing implies that information is collected, organized and communicated to identify and certify heritage and, therefore, it can be an important source of information on the social value of cultural heritage. In practice, lists are also connected with other policy actions. The owners of designated buildings are usually subject to various restrictions and prescriptions: on the transfer or the demolition of the buildings, on the use of land affecting the buildings, on the way maintenance or restoration is carried out, on the use of buildings as well as on access by the public. Regulation, therefore, constrains the exercise of property rights; owners are obliged to comply with prescriptions and penalties are involved for non-compliance. However, the designation may also bring about eligibility for various forms of government support, such as subsidies or tax incentives, to compensate owners for restrictions and preservation efforts, their extent varying across countries. A perverse effect of this complementarity is that it may create an incentive to apply for excessive preservation to obtain government support (see Chapter 31 in this volume). From the operational point of view, in the heritage field, regulation has advantages compared with other government tools. Its adoption or removal takes less time than is required for other forms of public intervention and, therefore, it allows for a greater timeliness of public action. Flexibility can be extremely useful in heritage to cope with the necessity of quick decisions, such as preventing the demolition of a building.

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476  Handbook of cultural economics The traditional command-and-control regulatory approach, can be questioned on the grounds of behavioural economics, suggesting a broad application of psychological insights to public policy aimed at changing people’s behaviour through nudging, that is, without mandate or bans but, instead, altering the choice architecture (Thaler and Sunstein 2008).5 For instance, psychological studies suggest that social comparisons can drive behaviour and that individuals may behave in relation to the behaviour of others, and they may be sensitive about how others view their actions, inducing pro-environmental behaviours (Congdon et al. 2011).6 In many instances, nudges work in concert with other tools, which makes it easier for individuals to take advantage of beneficial programmes that are already in place (Benartzi et al. 2017). Some insights might be interesting for the case of heritage regulation. For instance, sharing cultural heritage consciousness as well as social norms and habits about cultural heritage uses, might turn out to be effective means to foster proheritage behaviour in the management of restoration plans. Improving owners’ knowledge about their neighbours’ behaviour regarding the quality of the restoration implemented (for instance, sending a periodical newsletter, promoting meetings to allow communication among the interested parties or giving publicity about best practices) are likely to stimulate private good practices in cultural heritage restoration and use. This effect might be favoured by owners of old buildings located in historic districts, that is, a place rich in identity, who might feel part of a group because they belong to the same historic district.7

DECISION-MAKING PROCESS Cultural heritage policies are the outcome of a decision-making process, involving several actors. Political representatives, heritage agencies or state bureaucracies operate on the supply side, while the general public, pressure groups and professional associations are active on the demand side (Holler and Mazza 2013). The process is characterized by information asymmetries, in accordance with the principal–agent paradigm (Mazza 2011).8 In the heritage field, information asymmetry is more severe than in other policy fields owing to the high level of specific knowledge involved in heritage conservation decisions. The size of regulated sector is not well defined ex ante since the identification of what is heritage is not straightforward, especially when minor heritage is involved, being based to a large extent on the discretional evaluation of experts hired by the government. Thus, the type of expert (archaeologist, art historian, architect, urban planner, and so on) involved in this type of decision is important in determining the size and the composition of the stock of cultural heritage. Contrasting views may arise on the order of priorities concerning the extent and the type of intervention as well as the type of conservation that can take place (Peacock 1994).9 Moreover, the expertise of the regulator also affects the choices regarding the preservation of cultural heritage as it is versus innovative forms of re-use and, in a wider perspective, the balance between the conservation of the past versus the promotion of contemporary architecture. Biased heritage policies in favour of the past versus the future rely on the widely accepted assumption that future generations’ preferences are similar to current preferences, as well as on the training of experts.10 The adoption of technical standards of conservation is usually contested by practitioners because it is claimed that each item of heritage is unique and, therefore, conservation should be carried out case by case. Conservation itself is a wide concept,

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Regulation of heritage  477 which ‘­encompasses all aspects of protecting a site or remains so as to retain its cultural significance. It includes maintenance and may, depending on the importance of the cultural artefact and related circumstances, involve, preservation, restoration, reconstruction or adaptation or any combination of these’ (World Bank 1994, p. 2). The designation of a building or of an area can also be the result of rent-seeking behaviours of individuals and communities, to the extent that listing brings about not only negative effects, such as constraints and prescriptions, but also benefits, such as subsidies, tax incentives or other forms of government support (Noonan and Krupka 2010). On the grounds of the above considerations, the range and intensity of regulation appear to be more the endogenous product of the public decision-making process than just a policy instrument in the heritage field. From that perspective, it is not without significance that in many countries the discretionary power enjoyed by regulators is coupled with the tendency to extend the concept of heritage: heritage lists are large and keep growing worldwide, while de-listing rarely occurs. The above considerations assume that the main drivers of regulators or experts decisions are connected with auto-referentiality, prestige and reputation among the peer group, or any other aspect related to professional expertise. Decision-making, however, might produce opposite results, which have not received attention thus far in cultural economics. For instance, the action of influential pressure groups on urban planning might lead to the lack of designation of an area or the assignment of a low degree of significance, or the permission of transforming a historic settlement, not only with economic and social implications but also as far as the integrity of public action is concerned (Chiodelli 2018). Awareness of the importance of regulation and of the shortcomings related to the functioning of the decision-making process calls for strengthening the efforts for measuring and evaluating heritage regulatory activities to reduce the asymmetrical information enjoyed by the regulators, in order to increase their accountability and to improve the quality of regulation.11 Measurement problems usually arising in the cultural field (van der Ploeg 2006) are enhanced in the heritage regulation case. The concept of regulation is elusive when one wants to measure it since it is a non-monetary form of intervention and therefore is not accounted for in the public budget. Moreover, data are less reliable and comparable since they are affected by the institutional context. Notwithstanding the great attention devoted in the literature to the definition and measurement of the output of cultural heritage institutions and to the evaluation of their performance,12 this subject has been rarely investigated in the case of heritage regulatory activities. Finocchiaro et al. (2011) show that in Sicily the Regional Heritage Offices, which are run by experts and are responsible for heritage preservation, achieve, on average, low efficiency levels that seem to be positively affected mainly by the stimulus exerted by heritage owners and by political variables, while no significant effect is exerted by managerial variables such as the seniority of the Head of the Regional Heritage Office.13 The improvement of accountability and monitoring has been indicated recently as a profitable area of research to overcome the information problems, which are endemic to cultural policies (Cameron 2019). At international level, attention paid to the improvement of the accountability of regulators and the quality of regulation is mainly concentrated on economic sectors with great economic importance, such as public utilities or financial markets (OECD 2018). Ex ante regulatory impact assessment (RIA), stakeholder engagement when developing

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478  Handbook of cultural economics regulations and ex post evaluation are the widely agreed traditional pillars on which to build quality regulation. Useful hints can be derived for the assessment of regulatory activities for cultural heritage, however, without overlooking the specific features of this field, deriving from the coexistence of cultural and economic values. For instance, for the RIA, it is recommended to include cost and benefit analyses when considering the welfare impacts of regulation, taking into account economic, social and environmental impacts including distributional effects over time (OECD 2017). However, in cultural economics, the adequacy of costs and benefit analysis is controversial since cultural values are to be separated from economic values and cannot be assessed only in monetary terms, and the definition of a rigorous method to assess the multidimensional value of heritage is still in its infancy (Throsby 2013). Stakeholder engagement in developing regulation can be helpful to make regulation more demand orientated and to ensure that citizens and businesses feel included in the policy-making process and accept regulatory decisions. Simple digital tools such as digital public consultation or virtual meetings can be useful for the purpose. However, digital technology may have a wider potential beneficial impact in reducing information asymmetries and enhancing transparency of the decision-making process. There is growing attention being paid in the economic literature to the role of transparency in government performance, accountability and integrity, as well as to the promotion of trust in public institutions, and empirical analysis shows that these connections are mostly, though not always, positive and dependent on the particular context.14 There is no specific evidence for heritage regulation, but it is an interesting matter for investigation what information should be produced, how and by whom, to reduce the asymmetries of information and improve the accountability of heritage regulation policies. Accountability requires a clear statement of objectives and reliable and updated data, and their availability is likely to vary in relation to the institutional setting and the features of government internal organization. The effectiveness of web information, however, cannot be taken for granted and it very much depends on the format used to present information and its degree of complexity, since attention is a limited resource.15

ECONOMIC EFFECTS Heritage regulation cannot be considered to be only a technical matter, since it affects property rights and the possibility of using cultural heritage for private and collective purposes. The empirical evidence on the effects of listing on the values of designated buildings as well as of the surrounding properties provides mixed results, depending on the strength of constraints as well as on the available financial benefits such as subsidies or various forms of tax reductions (Benhamou 2013). At a more general level, the perception of the function of cultural heritage has changed through time: the acknowledgement of the importance of its intrinsic values (cultural heritage per se) is coupled with the increasing attention being paid to the enhancement of its instrumental role for economic and social development, urban regeneration and tourism usually being advocated as the most important factors.

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Regulation of heritage  479 The economic impact of cultural heritage is affected by the strength of regulation, that is, by extending the concept of heritage to artefacts of minor importance and by the range of compatible uses allowed for archaeological sites or historical buildings. The stance adopted by the regulator affects the costs regulation imposed on the regulated as well as on society as a whole. Costs include the administrative and bureaucratic costs related to the issue of regulatory acts (permissions, authorizations, demolition orders, standards, and so on) and the monitoring of their effective implementation, as well as the compliance costs imposed on all the regulated subjects (regardless whether private or public). Some of these costs can be foreseen because they are closely connected to conservation itself; for example, the requirement to use special materials, qualified operators, and similar, to ensure quality. Others are subject to a high degree of uncertainty as a consequence of the discretional decisions of the regulator; for instance, an adaptation (involving interior modifications for compatible uses) allowed by urban planning might not be permitted by the heritage regulator, with the consequence that a substantial amount of the potential benefits is lost and the public–private mix is likely to be adversely affected. The size of the overall costs involved in heritage regulation raises some doubts about the sustainability of the related conservation programmes: a conservationist stance on regulation may crowd out private investments, causing a deterioration of heritage and a considerable pressure on public expenditure. Thus, the objective of conserving heritage may not be fulfilled. Similar results might occur owing to the reaction of heritage owners to regulation. The threat of restrictions and of the related costs might induce owners to speed redevelopment, with negative effects on the heritage stock (Turnbull 2002). Alternatively, owners might decide not to comply with rules if they are too costly, provided that the risk of being detected is low; this is likely to happen in the presence of extensive regulation requiring considerable resources to be allocated to monitoring activities. Nudging might offer useful insights to address this type of issue. As a consequence, the objective of the regulatory policy, that is, conservation of heritage, can actually be endangered by the excessive expansion of the regulation itself. The need to introduce the opportunity-cost concept to drive the decision-making process is, therefore, called for.

SOME POLICY IMPLICATIONS On the grounds of the previously mentioned considerations, it is useful to sketch very briefly some possible institutional mechanisms available to society to restrain the discretionary scope of regulators and to improve public participation in the political decision-making process. The issue is both crucial and controversial; while it is widely agreed that taxpayers have a legitimate claim to influence public decisions about heritage as with other policies, it is also true that specific knowledge and expertise is involved so that these decisions cannot be left entirely to taxpayers’ choices. The problem we face – the need for a governance structure to restrain the discretionary scope of the regulator – is common to regulation in general and no unique solution can be provided since the choice is constrained by a country’s institutional endowment (Levy

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480  Handbook of cultural economics and Spiller 1996). Institutions also matter in the heritage field and various means can be envisaged to restrain the discretionary scope of the regulator. Devolution is usually indicated as a means of improving political participation and increasing government accountability; in the heritage field its positive effects would seem even stronger owing to the close links between regional or local communities and heritage (Rizzo and Throsby 2006). However, devolution is not enough if no adequate incentives are introduced in the regulatory decision-making process (Rizzo and Towse 2002). Different incentives are generated by different institutional features. In state-driven systems, such as that in Italy, where policy decisions are implemented by bureaucracies, the decision-making process is less demand orientated than in arm’s-length systems, such as in the UK, where independent agencies operate (Holler and Mazza 2013). As a consequence, participation of citizens and voluntary associations is likely to be enhanced, and the public scrutiny of the regulators’ decisions can be improved. Holler and Mazza (2013) outline, however, that the arm’s-length principle might not perform in the same way in all countries, since cultures impact on institutions and the behaviour of public actors. Finally, it might be useful at the local level to adopt codes of practice or guidelines agreed between the regulator and those involved in conservation activities (architects, building firms, engineers, and so on) in order to make prior commitments and reduce the uncertainty related to investment in conservation. There might be also a need for enlarging the scope of professional training for heritage regulators to meet the challenges of the trade-off between the preservation of the past and the promotion of contemporary heritage.

THE INTERNATIONAL DIMENSION Heritage regulation is also widespread at international level and, mutatis mutandis, raises issues which are similar to those arising within a national context. Regulation of built heritage at this level mainly consists of non-enforceable directives (charters, codes of practice, guidelines, and so on) implemented by agreement and not involving penalties, as well as of listing, such as the UNESCO World Heritage List (WHL).16 As Peacock and Rizzo (2008) show, heritage experts are considerably involved and the list of conventions, charters, recommendations, mostly issued on the same topics, has grown considerably over time; each organization seems mainly interested in pursuing its own objectives without paying much attention to the coordination of the various actions. The WHL also keeps expanding; however, this enlargement does not ensure that the aim of preserving cultural heritage, considered as a global public good, is fulfilled. Inclusion in the list is more representative of national than of global interests and is based on questionable selection criteria (Frey and Steiner 2013). Sustainability issues may also arise in poor countries owing to the high opportunity costs of preserving global heritage, which are not compensated by any significant financial support from UNESCO. Whether the WHL is effective in promoting tourism and, therefore, economic local development, is an open and controversial question (Noonan and Rizzo 2017). By focusing attention on designated buildings or areas, the WHL is likely to generate a displacement effect, to the disadvantage of other heritage, especially in respect of devolution, making local

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Regulation of heritage  481 governments very interested in the economic benefits deriving from tourism (Martorana et al. 2019). Regulation is also adopted to restrict the international circulation of works of art, with the aim of preserving national identity and prestige and to protect future generations’ interests. However, the effectiveness of such a policy tool is an open question (Giardina and Rizzo 1994). If the scope of the restrictions preventing the exports of the works of arts was very wide, collectors and/or dealers might be induced to leave the official economy and to undertake their exchanges in an illicit way with a very low risk of being detected and punished, since effective monitoring would be too costly. As a consequence, restrictions tend to be ineffective and are likely to have negative economic effects on the art market.

CONCLUDING REMARKS A general argument stems from this analysis: the range and intensity of heritage regulation cannot be justified in all cases on normative grounds since they often appear to be the endogenous product of a public decision-making process. The identification of what is cultural heritage and deserves protection varies through time and, crucially, depends on experts, who enjoy an informational advantage, because of their knowledge and professional training. If heritage regulators adopt a conservationist stance, that is, the list of buildings or areas claiming historical importance is enlarged and preservation orders prevent modifications for compatible uses, the conservation of heritage could be endangered. Extensive regulation would discourage private investment in heritage and would impose an unsustainable pressure on public funds. The need to introduce the opportunity-cost concept to drive the decision-making process is strongly called for. Also, it might be advisable to enlarge the scope of the professional training of regulators to reduce the tendency towards biased heritage policies in favour of the past versus the future. There is no unique solution to meet the need for a governance structure to restrain the discretionary scope of the heritage regulator, with the solution being constrained by the specific institutional framework in which regulation takes place: forms of greater public participation in decision-making and the improvement of information – through consultation and review procedures as well as regulatory assessment – are some of the means suggested here. Digital technologies, if carefully implemented, may have a broad, potentially beneficial impact in reducing information asymmetries and enhancing transparency of the decision-making process. Arm’s-length systems seem to be more effective in making regulation more demand orientated and accountable.

NOTES  1. Positive analysis criticizes the normative theory of regulation based on the welfare economics approach to market failure; a classical reference is Noll (1989).  2. Technology may provide a solution to such a trade-off; for instance, visits to heritage sites with problems of decay and deterioration can be substituted by virtual visits.  3. A survey conducted on 69 countries revealed that regulation was not considered important for cultural tourism policy (World Tourism Organization 2018).

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482  Handbook of cultural economics  4. Listing has a very broad meaning, referring to several forms of designation – for example, schedules, inventories, lists, classifications, surveys, registers, records, inscriptions and others – varying across national and local contexts (Schuster 2003).  5. Chetty (2015) outlines that behavioural economics makes three contributions to public policy: new policy tools, better predictions of effects of existing policies and new welfare implications. At policy level, behavioural insights teams have been created in some countries – for instance, in the UK, the US, Australia, Germany, the Netherlands and Singapore – to formulate more effective government policies using findings from psychology and behavioural economics.  6. Field experiments on residential energy consumption find that providing information to individuals about how their energy consumption compares with that of their neighbours can reduce consumption, and that individuals are more likely to respond to appeals to conserve energy when their response is made public (Allcott and Mullainathan 2010).  7. There is evidence to suggest that people tend to cooperate more with their in-group than with individuals not part of their in-group (Meier 2006).  8. A political decision-maker is the agent of society and, in turn, the principal of the bureaucracy. Being public agents assumed to be self-utility maximisers, the fulfilment of public interest crucially depends on the incentives and constraints imposed on them.  9. Peacock (2013) uses Panmure House, the former house of Adam Smith in Edinburgh, as an example to show how influential experts’ opinions generate conflicts between the objectives and the priorities of different public offices. 10. The evidence in psychology suggests that there are systematic biases in decision-making, for example: projection bias, that is, they expect their future preferences to be too close to current preferences; preference for the familiar, that is, the choice of a familiar option to simplify complex decisions; and choice avoidance, that is, avoiding the choice altogether, possibly in favour of the default action (Della Vigna 2009). 11. The notion of regulatory quality covers processes and outcome. The former refers to the way regulations are developed and enforced, according to the principles of consultation, transparency, accountability and evidence. The latter relates to outcomes, that is, whether regulations are effective, efficient, coherent and simple (OECD 2018). 12. Fernández et al. (2013) provide an extensive review of the methodologies for measuring the performance of cultural heritage institutions and of the empirical studies on this subject. 13. From a different perspective, Guccio et al. (2014) show that in Italy, the professional characterization of the decision-making process negatively affects the efficiency of public procurement for conservation: heritage authorities, are, on average, less efficient than the less specialized authorities, especially at controlling the final cost. 14. An extensive review is provided by Cucciniello et al. (2017). 15. Psychological studies indicate that format is important, leading to inattention to complex information (Della Vigna 2009). 16. This form of regulation is defined by Throsby (1997) as soft regulation as distinguished from hard regulation.

SEE ALSO: Chapter 31: Heritage; Chapter 45: Performance indicators; Chapter 48: Political economy.

REFERENCES Allcott, H. and S. Mullainathan (2010), ‘Behavior and energy policy’, Science, 327 (5970), 1204–5. Benartzi, S., J. Beshears, K.L. Milkman, C. Sunstein, R. Thaler, M. Shankar, et al. (2017), ‘Should governments invest more in nudging?’ Psychological Science, 28 (8), 1041–55. Benhamou, F. (2013), ‘Public intervention for cultural heritage: normative issues and tools’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 3–16. Cameron, S. (2019), ‘Contemporary challenges to cultural economics’, in S. Cameron (ed.), A Research Agenda for Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 21–40.

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Regulation of heritage  483 Chetty, R. (2015), ‘Behavioral economics and public policy: a pragmatic perspective’, American Economic Review, 105 (5), 1–33. Chiodelli, F. (2018), ‘The illicit side of urban development: corruption and organised crime in the field of urban planning’, Urban Studies, 56 (8), 1611–27. Congdon, W.J., J.R. Kling and S. Mullainathan (2011), Policy and Choice: Public Finance Through the Lens of Behavioral Economics, Washington, DC: Brookings Institution Press. Cucciniello, M., G. Porumbescu and S. Grimmelikhuijsen (2017), ‘25 years of transparency research: evidence and future directions’, Public Administration Review, 77 (1), 32–44. Della Vigna, S. (2009), ‘Psychology and economics: evidence from the field’, Journal of Economic Literature, 47 (2), 315–72. Fernández-Blanco, V., L.C. Herrero and J. Prieto-Rodríguez (2013), ‘Performance of cultural heritage institutions’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 470–88. Finocchiaro Castro, M., C. Guccio and I. Rizzo (2011), ‘Public intervention on heritage conservation and determinants of heritage authorities’ performance: a semi-parametric analysis’, International Tax and Public Finance, 18 (1), 1–16. Frey, B. and L. Steiner (2013), ‘World Heritage List’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp.  171–86. Giardina, E. and I. Rizzo (1994), ‘Regulation in the cultural sector’, in A. Peacock and I. Rizzo (eds), Cultural Economics and Cultural Policies, Dordrecht: Kluwer, pp. 125–42. Guccio, C., G. Pignataro and I. Rizzo (2014), ‘Evaluating the efficiency of public procurement contracts for cultural heritage conservation works in Italy’, Journal of Cultural Economics, 38 (1), 43–70. Holler, M. and I. Mazza (2013), ‘Cultural heritage: public decision-making and implementation’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 17–36. Levy, B. and P.T. Spiller (eds) (1996) Regulations, Institutions and Commitment, Cambridge: Cambridge University Press. Lichfield, N. (1988), Economics in Urban Conservation, Cambridge: Cambridge University Press. Martorana, M., I. Mazza, A. Mignosa and I. Rizzo (2019), ‘The economics of heritage: some implications of devolution’, in M. Kunizaki, K. Nakamura, K. Sugahara and M. Yanagihara (eds), Advances in Local Public Economics –Theoretical and Empirical Studies, Singapore: Springer International, pp. 249–60. Mazza, I. (2011), ‘Public choice’, in R. Towse (ed.), A Handbook of Cultural Economics, 2nd edn, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 362–9. Meier, S. (2006), ‘A survey of economic theories and field evidence on pro-social behaviour’, FRB of Boston Working Paper 06–6, Federal Reserve Bank of Boston, Boston, MA. Noll, R.G. (1989), ‘Economic perspectives on the politics of regulation’, in R. Schmalensee and R.D. Willig (eds), Handbook of Industrial Organization, vol. 2, Amsterdam: Elsevier, pp. 1254–87. Noonan, D. and D.J. Krupka (2010), ‘Determinants of historic and cultural landmark designation: why we preserve what we preserve’, Journal of Cultural Economics, 34 (1), 1–26. Noonan, D. and I. Rizzo (2017), ‘Economics of cultural tourism: issues and perspectives’, Journal of Cultural Economics, 41 (2), 95–107. Organisation for Economic Co-operation and Development (OECD) (2017), Government at a Glance, Paris: OECD. Organisation for Economic Co-operation and Development (OECD) (2018), Regulatory Policy Outlook, Paris: OECD. Peacock, A. (1994), A Future for the Past: The Political Economy of Heritage, Edinburgh: David Hume Institute. Peacock, A. (2013), ‘Adam Smith has returned to live in Edinburgh: a case study’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 491–8. Peacock, A. and I. Rizzo (2008), The Heritage Game: Economics, Policy and Practice, Oxford: Oxford University Press. Pignataro, G. and I. Rizzo (2020), ‘Conservation of historical buildings: the rehabilitation of the Benedettini Monastery in Catania’, in T. Bille, A. Mignosa and R. Towse (eds), Teaching Cultural Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 275–81. Rizzo, I. and D. Throsby (2006), ‘Cultural heritage: economic analysis and public policy’, in V.A. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 983–1016. Rizzo, I. and R. Towse (eds) (2002), The Economics of the Heritage: A Study in the Political Economy of Culture in Sicily, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Schuster, M.J. (2003), ‘Making a list and checking it twice: the list as a tool of historic preservation’, Working Paper No. 0303, Harris School of Public Policy Studies, University of Chicago.

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484  Handbook of cultural economics Thaler, R.H. and C.R. Sunstein (2008), Nudge: Improving Decisions about Health, Wealth, and Happiness, New Haven, CT and London: Yale University Press. Throsby, D. (1997), ‘Seven questions in the economics of cultural heritage’, in M. Hutter and I. Rizzo (eds), Economic Perspectives of Cultural Heritage, London: Macmillan, pp. 13–30. Throsby, D. (2013), ‘Assessment of value in heritage regulation’, in I. Rizzo and A. Mignosa (eds), Handbook on the Economics of Cultural Heritage, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. 456–69. Towse, R. (2010), A Textbook of Cultural Economics, Cambridge: Cambridge University Press. Turnbull, G.K. (2002), ‘Land development under the threat of taking’, Southern Economic Journal, 69 (2), 290–308. Van der Ploeg, R. (2006), ‘The making of cultural policy: a European perspective’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, Amsterdam: North-Holland, pp. 1183–224. World Bank (1994), ‘Cultural heritage in environmental assessment’, EA Sourcebook Update No. 8, September, accessed 10 March 2019 at http://siteresources.worldbank.org/INTSAFEPOL/1142947-1116497775013/​20​50​74​ 10/Update8CulturalHeritageInEASeptember1994.pdf. World Tourism Organization (2018), Tourism and Culture Synergies, Madrid: UNWTO, doi:10.18111/9789​ 284418978.

FURTHER READING Heritage regulation raises interdisciplinary issues because of the technical, artistic and architectural aspects of conservation. A classical reference to explore the meaning as well as the economic and technical implications of the different types of conservation is Lichfield (1988). The European Union (EU)-funded project Cultural Heritage Counts for Europe (CHCfE) (blogs.encatc.org/culturalheritagecountsforeurope/outcomes/, accessed 20 February 2019), launched in 2013 and completed in 2015, offers a multidisciplinary overview of evidence-based research and case studies on the economic, social, cultural and environmental impacts of heritage conservation practices and policies in the EU. A comparative view of national legislation and policies in the cultural field in the EU is provided by Compendium (www.culturalpolicies.net/web/index.php, accessed 2 April 2019). From a more operational perspective, at the international level, guidelines on impact assessments are provided by the Icomos report ‘Guidance on heritage impact assessments for cultural world heritage properties’ (https://www. icomos.org/world_heritage/HIA_20110201.pdf, accessed 2 April 2019). At the national level, there is evidence of the application of regulatory impact assessment to the heritage field, for instance, in the UK by the Department of Culture, Media and Sport’s, ‘Heritage protection for the 21st century: regulatory impact assessment’ (http:// www.culture.gov.uk/images/consultations/hrp_ria.pdf, accessed 10 March 2019).   The issues of the design and implementation of heritage conservation are well represented in the reports of English Heritage (Historic England since 1 April 2015). ‘Conservation principles, policies and guidance’ (in 2008) (www.historicengland, accessed 10 November 2019) offers an example of soft regulation, developed through extensive debate and consultation, to provide support for conservation decisions and for the sustainable management of the historic environment; ‘Heritage counts 2018’ provides data and indicators on conservation of historic environment as well as qualitative information and detailed evidence on the links between heritage, economy and society (https://historicengland.org.uk/research/heritage-counts, accessed 10 March 2019).

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54.  Superstars

Günther G. Schulze

What makes a star a star? Why are Madonna, Jay-Z or Tom Cruise so immensely rich? The competitive model in its simple version tells us that people are remunerated according to their (marginal) productivity. This would imply that, given the enormous differences in income between the average writer or actor and, say, Stephen King or Sean Connery, there would have to be a huge gap between the talent of the stars and of those that come next but do not enjoy a star status. If you agree with me that Britney Spears’s talent is not hugely different from that of your local music club’s singer, there must be more to the superstar phenomenon than the simple competitive model would be able to portray. This is what we investigate in three steps. The next section presents theoretical arguments for the existence of superstars, the third section discusses the empirical evidence for the arts, and the final section discusses how the superstar phenomenon has changed with increasing digitalization. Although the superstar phenomenon is not limited to the cultural sector – there are superstar law firms, doctors, managers, professors and athletes – the focus here is on superstars in the arts.

THEORETICAL CONCEPTS In his seminal paper on ‘The economics of superstars’, Sherwin Rosen (1981) explains how small differences in talent translate into large differences in earnings. The underlying reason for that is the concurrence of imperfect substitutability of different qualities (of the otherwise same service) on the demand side and a production technology that makes possible joint consumption. Rosen starts by acknowledging that different qualities of a narrowly defined service (for example, the performance of a particular Beethoven concert) are imperfect substitutes in consumption: people rationally favor fewer highquality services than more of the same service at mediocre levels.1 That might be true for a number of services (such as medical services) and this higher willingness to pay alone would lead to a difference in pay. It already explains the convexity of the function that translates quality into income.2 The enormous income differentials between superstars and their colleagues of lesser talent, however, are only explained if the consumption technology is taken into consideration. Public performances of, say, a classical concert exhibit the characteristics of a club good – unit costs decrease with rising audience size. At some point, congestion costs will occur as a classical live concert is more enjoyable in a medium-sized concert hall than in a football stadium. These congestion costs put a limit on the optimal size of audiences and therefore lead to non-degenerate market equilibria (more than one supplier). Still, artists of higher quality command higher prices and a greater audience and thus a larger income. Congestion is absent for canned performances such as compact disc (CD) productions, television performances, books, digital versatile discs (DVDs), videos on demand or movies. In Rosen’s set-up, this leads to a single artist 485

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486  Handbook of cultural economics (or single group of ­artists), the best, to serve the whole market. Potential market entry limits the market power of the artist, but since he or she is perceptibly better than the next best person, he or she enjoys an economic rent which leads to a higher price than his or her closest competitor would need to charge to enter the market. This quality difference can be small, although it needs to be perceptible; it is leveraged through the scale economies in production and can make total rent very large. Rosen has put forward a powerful idea in a simple model; given the simplicity of his arguments, he has left many important aspects for others to explore. He deliberately disregarded product differentiation as he defined his competitive market very narrowly and did not adopt a monopolistic competition model à la Lancaster or Dixit–Stiglitz.3 There are far more than only two or three movie superstars of each gender or a handful of superstar rock ’n’ roll bands, as his model would predict: heterogeneous tastes or a love of variety become an important limitation to star power, in addition to the threat of entry of close competitors. Moreover, Rosen did not explain why people prefer a single superstar performance to a series of performances of lesser quality, but instead assumed it. Finally, he did not explain the emergence of superstars, but assumed a given and observable distribution in quality among artists. Adler (1985) and MacDonald (1988) filled some of the gaps. MacDonald (1988) provides a dynamic version of Rosen’s model. In a two-period stochastic model, performers decide whether to perform and, if they do, the quality of their performance (good or bad) is observable to all who are interested. Since outcomes are serially correlated for each artist, first-period reviews have predictive power for the second period’s performance. This accumulation of knowledge leads to a separation of market segments in the steady state: those with bad first-period reviews leave the business for an exogenous alternative occupation, while those with a good first-period performance command a larger crowd and a higher price than the newcomers, since consumers face a much smaller risk as regards the performance quality and are willing to pay for this. These artists experience a vast income growth compared with their first-period income – they rise to become stars. In his article, ‘Stardom and talent’, Moshe Adler (2006) describes a learning process as the key to understanding the superstar phenomenon. Learning about art is very important because art consumption is positively addictive in that marginal utility from art consumption increases with the ability to appreciate art, which is a function of past art consumption (Stigler and Becker 1977): the more you know, the more you appreciate it. In the course of consuming art, consumption capital is accumulated and thus marginal utility from art consumption rises over time.4 This learning process does not refer to art in general but to specific art forms and, even, artists. Artist-specific consumption capital is built up by consuming the art service provided by the artist in question and by discussing it with others who are similarly knowledgeable about this artist. The latter effect creates positive network externalities as it is costly to search for someone with whom to interact about a specific artist.5 This explains the existence of stars: stars may be born because initially (slightly) more people happen to know one artist than any other artists of possibly equal (or even higher) talent and communicate about him or her more with others. Artist-specific consumption capital is built up more rapidly, and this artist will snowball into a star.6 Thus, in contrast to Rosen, Adler posits that initial popularity, not talent is decisive for the creation of superstars.7

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Superstars  487 The two concepts differ also in their implications for efficiency. In Rosen’s model, markets with superstars are efficient as equally or higher talented artists can enter the market and establish themselves as stars. In Adler’s model artists of higher talent may not attract consumers away from the incumbents as they enjoy higher popularity which serves as a barrier to entry to superstardom (Adler 2006). Borghans and Groot (1998) argue that superstars earn more than their marginal contribution to welfare because they have monopolistic power owing to their position as the best, at the expense of the other artists. Inefficiency may result also from rent-seeking activities of potential superstars trying to capture the superstar rent, resulting in rent dissipation. Frank and Cook (1995) argue that superstar salaries trigger stardom-seeking behavior by artists, who disregard alternative education and occupations, and end up underpaid compared with alternative occupations. Adler (2006) notes that artists also receive psychic income from being an artist, which makes solely monetary comparisons between being an artist and alternative occupations incomplete. Richter and Schneider (1999) argue that inefficiencies may arise since superstars enjoy an externality in consumption, popularity, which has an economic value (for example, in the form of commercials contracts) and that organization of performances has features of a natural monopoly.

EMPIRICAL EVIDENCE Hamlen (1991, 1994) tries to single out a superstar effect in the American record industry using a sample of 115 singers for the years 1955–87. Since the superstar phenomenon in the Rosen (1981, p. 846) sense requires that ‘small differences in talent become magnified in large earnings differences, with greater magnification of the earnings–talent gradient increasing sharply near the top of the scale’, an empirical analysis requires a quantifiable concept of talent. Hamlen uses data on the harmonic content of voice, a concept taken from the technical literature on voice, which measures depth and richness (for details, see Hamlen 1991, p. 731). He runs the total record sales (Hamlen 1991) and number of hit singles and hit albums (Hamlen 1994) on the measure of quality and other singers’ attributes (gender, race, year in which the singer first released a single or album, movie appearances, recognized band, writer of their own songs, and so on). In his second paper, Hamlen (1994) incorporates that the success in the low-end singles market may serve as a signaling device for quality that feeds into consumers’ choices in the top-end albums market.8 Although talent, measured by voice quality, increases sales, Hamlen (1991, 1994) fails to find a magnification effect. Rewards for talent are far less than proportional to differences in talent. Hence he cannot identify a superstar phenomenon in the Rosen sense. Furthermore, the low-end singles market functions as a quality filter for the albums market, which is in line with MacDonald’s idea of a multi-period information accumulation process. While voice quality is important in the singles market, it is less so in the albums market, in which success in the singles market serves as a quality indicator. Other singers’ attributes apart from voice quality, such as sex, race, appearances in movies and a good band, influence success as well. This already indicates that there is more to success than just talent. Chung and Cox (1994) show that the distribution of gold records in the period 1958–89 follows the specific Yule distribution f(i) 5 1/i(i 1 1), Σf(i) 5 1 where f(i) is the share of

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488  Handbook of cultural economics performers which have earned i gold records (i 5 1,. . ., ∞). Yule distributions in general have been shown to describe a variety of sociological, biological and economic phenomena, such as the distribution of incomes by size, of cities by population, of scientists by the number of paper, and so on. The underlying probability process can be described as a sequential buying process: one consumer after the other buys one record first, then in the second round each consumer buys a different record, and so on. The choice of records in each round follows two assumptions: (1) the probability that consumer k 1 1 buys a record that has been chosen by exactly i of the k previous consumers is proportional to i; and (2) there is a constant small probability that consumer k 1 1 chooses a record that has not been chosen previously. These assumptions represent a snowball effect, as described by Adler (1985). The observed distribution of gold records coinciding with a pattern as the consequence of a stochastic process which incorporates such a snowball effect, leads Chung and Cox (1994) to conclude that the superstardom phenomenon is merely the result of a probability mechanism which predicts that ‘artistic outputs will be concentrated among a few lucky individuals’ (Chung and Cox 1994, p. 771, emphasis in original). In their interpretation, difference in talent is not necessary for superstars to emerge; instead, luck initially increases the user base and reinforces itself. This supports Adler’s idea of the emergence of superstars. Giles (2006) measures the distribution of the lifetime of number one hits in the US charts and the number of number one hits per artists for the period 1955–2003. Contrary to Chung and Cox, he fails to find that his two measures of success are distributed according to the Yule–Simon distribution. Spierdijk and Voorneveld (2009) argue that both aforementioned contributions test only a specific Yule distribution (with ρ 5 1), which is economically implausible, and that the test they use (χ2 goodness-of-fit) is inappropriate for the superstar phenomenon. Using the three data-sets of Chung and Cox and of Giles, and applying parametric bootstrap, better estimation techniques and more powerful tests,9 they find that the Yule distribution approximates the empirical distribution well only for the lower quantiles; overall they reject the Yule distribution as its upper tail is too heavy. A generalized Yule distribution results in a much better fit. Filimon et al. (2011) indirectly test the two superstar theories. They analyze the introduction of local linguistic policies in Basque country and Catalonia that aimed to increase the local artistic (and language) content in the local media. According to Rosen, this should not have any influence on CD sales as the distribution of talent is unaltered; according to Adler, it should increase sales since popularity of local artists is increased through this measure while the popularity of the top artists remains unchanged. Utility of consumption of top artists’ music remains the same, while local music provides higher utility than previously. Filimon et al. (2011) find that, in Catalonia, overall music sales increased and they interpret this as support for Adler’s theory. The empirical analyses fail to provide conclusive evidence for the superstar phenomenon. In the Hamlen approach it is by no means clear that the harmonic content of voice is the relevant measure for artistic quality for singers of non-classical music (rock, folk, and so on). Charm, sex appeal, the contents of the lyrics and the stage performance are also very important factors for their success,10 but they are very difficult to measure. Thus Hamlen’s approach suffers from an omitted variable bias. Chung and Cox’s coincidence result does not tell us anything about the underlying reason for the selection of consumers; that the outcome is consistent with a pure reinforcing

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Superstars  489 probability mechanism does not prove it is at work. The observed outcome could also be explained by a preference for what consumers regard as the highest quality coupled with a preference for variety and with heterogeneous tastes.11 Filimon et al.’s (2011) analysis provides indirect evidence at best for superstar theories; their finding would be observationally equivalent to a model with differentiated goods and high search costs (without user-based popularity effects); a reduction in average search costs would increase overall consumption. The main difficulty in testing Rosen’s theory is correctly measuring artistic quality. However, superstars are not limited to the arts, but play an important role in sports and other areas. In sports these empirical problems are not as serious, since quality is easier to measure. Soft skills, such as charm, looks or lyrics, play a lesser role; performance is measurable in inches, milliseconds or goals and comprehensive statistics are readily available. Therefore, empirical analyses of the superstar phenomenon in sports are more promising (for example, Lucifora and Simmons 2003). In their analysis of salaries in the German soccer league Lehmann and Schulze (2008) test Rosen’s theory by including a host of performance parameters, as well as the Adler–MacDonald theory by including variables for that part of players’ media presence that is not explained by their performance on the field. Adler’s idea of the importance of individuals’ interaction for the acquisition of artist-specific consumption capital, and MacDonald’s idea of an information accumulation process, indicate an important role of the mass media for the acquisition of information and thus consumption capital. Media presence should therefore be included in empirical analyses of superstars. The authors emphasize the quantile regression approach as convexity of the talent-earning gradient and the role of media presence is particularly important for the upper tail of the income distribution; but they fail to find evidence that differences in performance or in media presence translate into more than proportional differences in the earnings of soccer stars.

SUPERSTARS IN THE DIGITAL AGE Ticket Prices versus Record Sales Krueger (2005) analyses the reasons behind soaring ticket prices for rock concerts.12 Inter alia, he tests whether the returns to superstar status have increased as consumer electronics and the Internet have become ubiquitous, thereby increasing the effective audience size. Krueger (2005) also measures superstar power by the space devoted to the artist or band in The Rolling Stone Encyclopedia of Rock & Roll. He finds that superstar effects are large and increasing, but that they cannot explain the surge in ticket prices. Instead, the increased illegal downloads of music decouple concert attendance from record sales and, thus, it no longer makes sense to keep ticket prices low in order to increase attendance and therefore record sales. Superstar versus Long-Tail Phenomenon How has digitalization of artistic products (CDs, MP3s, e-books) and increased online sales of art products changed the superstar phenomenon? This is subject to ­considerable

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490  Handbook of cultural economics debate. Proponents of the superstar theory argue that the winner-takes-all effect has intensified as markets have become more efficient, search costs have declined and transparency increased, which has made it easier to identify and acquire the highest-quality product (Frank and Cook 1995). In contrast, proponents of the long-tail theory (Anderson 2004, 2006) posit that demand shifts away from the most popular products (the head) to niche products (the tail) for three reasons. The decline in production costs leads to a higher product variety, the constraints of physical storage capacity disappear for digital products and are much lower for physical products traded online (compared to brick-andmortar shops), which makes niche products economically sustainable. Finally, new digital information channels have emerged (social media channels such as Facebook groups or YouTube channels, blogs, online forums and so on) that cater to specific niche interests, which makes it easier for consumers to find their ideal variety (Peltier et al. 2016). Weeds (2012) shows that superstar and long-tail phenomena can coexist. Empirical evidence has been inconclusive.13 Brynjolfsson et al. (2003, 2010) find that concentration of book sales in the US decreased during the 2000s. Bounie et al. (2010) show that online book sales in France are less concentrated than offline sales; Benghozi and Benhamou (2010) find no significant effect of a long tail for music, while Peltier and Moreau (2012) show that book sales in France shifted from bestseller to medium-selling books. Bourreau et al. (2013) finds that French record companies that have expanded their catalogue in response to digitalization are now selling fewer records of more titles, thereby not increasing their overall sales. Crain and Tollisson (2002) show, for the US music industry, that the superstar effect has increased since the 1970s. Bhattacharjee et al. (2007) find that the average survival time of albums in the US charts has declined in the period after the surge in peer-to-peer (P2P) file sharing, but that survival time of superstar albums has not. Thus digitalization has not eroded superstar power. Ordanini and Nunes (2016) consider the three major technological changes: the shift from analogue to digital recording (CDs), the shift from static to mobile audio files (MP3) and the shift from illegal file sharing to legitimate online music sales with digital rights management (DRM; such as iTunes). They analyze the US Billboard Hot 100 single charts and inquire whether concentration has occurred at the level of individual songs and of individual artists for the time periods studied. They create a nuanced view on the effect of technological changes on the superstar and long-tail phenomena, which depends on the time period (that is, the technological change) and the superstar definition (top 100 versus top 10). Overall they find a transition from fewer ­blockbusters (high-performing songs) by more superstars (artists) to more blockbusters by fewer superstars. Taken together, the emerging picture is still very mixed; results depend on country, art form (books, music), time span and product (for example, albums versus singles, comics versus fiction).

INTERNET SUPERSTARS: THE KYLIE JENNER PHENOMENON Digitalization has not only changed the business model for existing stars; it has created stars that would not exist without the Internet – Internet superstars. A prominent example is YouTube influencers, who have a very skewed income distribution, with most influencers making very little money and some becoming excessively rich (Bärtel 2018; Eror 2018).

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Superstars  491 Building a fan audience is essential for success – requiring attractive content of some sort – which is rewarded directly by YouTube or through paid-for product endorsements.14 This audience can be created by offline celebrity status (for example, as a singer or an athlete), but also exclusively online. The influencer engages in a parasocial interaction with his or her followers that regard the influencer as a role model and adviser (Horton and Wohl 1956; Lueck 2015; Rasmussen 2018). The queen of the social media influencer is Kylie Jenner who, void of any discernible exceptional talent, has become a billionaire at the age of 21. Capitalizing on the popularity of the show Keeping up with the Kardashians, Kylie Jenner has used her social media presence to create an illusion of intimacy and friendship but also of a role model attractive to a large impressionable audience. This enabled her to sell her own brands but also endorse other brands most effectively. She has quickly snowballed into a social media superstar.15 Kylie Jenner is not the superstar Sherwin Rosen had in mind.

NOTES  1. As a convenient modelling trick, he assumes that utility derived from this particular service y is the product of quantity n and quality per unit of output z, y 5 nz, thereby adopting a smooth quantity–quality substitution technology (comparable to the concept of labour in efficiency units). This allows him to use a competitive framework for the single market for y instead of modelling monopolistic competition in products of different quality. Imperfect substitutability is introduced through a fixed cost of consumption per unit of quantity, which gives rise to a preference of cost-minimizing consumers for fewer services of high quality (instead of more services of less quality) as this reduces the fixed costs. See Hamlen (1994) for a Dixit–Stiglitz model of artistic variety.  2. Rosen (1981, p. 846) writes: ‘Hearing a succession of mediocre singers does not add up to a single outstanding performance. If a surgeon is 10 percent more successful in saving lives than his fellows, most people would be willing to pay more than 10 percent premium for his services.’ Champarnaud (2014) argues that the matching of artists of different talent with consumers with different levels of connoisseurship may under certain circumstances lead to a concave rather than convex price-to-talent relationship.  3. See Rosen (1981 fn. 1, 1983) on this.  4. The idea goes back to Alfred Marshall, who wrote, ‘It is therefore no exception to the law [of diminishing marginal utility] that the more good music a man hears, the stronger is his taste for it likely to become’ (Marshall 1891 [1962], p. 94). There is substantial empirical evidence for such an addictive effect; see, for example, Smith (1998).  5. The mechanism is very similar to positive network externalities for the usage of word processors and other computer programs, which are more valuable the larger the user base, as exchange of files, troubleshooting and so on become easier. Similarly, the utility of social media networks and dating applications (apps) increases with the user base as the number of potential (conversational) partners increases.  6. Terviö (2009) shows that if it is costly to reveal talent, firms will refrain from searching for talent settling for, mediocre, talent of incumbents who are paid excessive salaries. Superstars are created by the talent revelation process rather than by the underlying scarcity of talent.  7. Superstars may be culture specific, which raises the question of how star power is affected by globalization (Adler 2006, p. 905).  8. Publication of singles typically precedes publication in the album market (although established stars sometimes go back to the singles market).  9. They use the discrete Anderson–Darling and discrete Kolmogorov–Smirnov tests with maximum likelihood (ML) and method-of-moment (MM) estimates. 10. The success of Bob Dylan, who is not renowned for his harmonic voice, or that of Britney Spears, the Spice Girls or AC/DC, and many others are evidence that there is more to a singer’s success than just a beautiful voice. 11. Crain and Tollison (2002) argue that switching consumption from a non-star to a star is more likely if the acquired consumption capital (for the non-star) is lower and the time horizon is longer, as individuals can enjoy easier communication with their peers about stars than non-stars, that is, if the consumers are younger. Switching is less likely if time preference rates are higher. They show that star concentration is

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12. 13. 14. 15.

higher for a younger population, but the proxies for time preference result in mixed evidence. They show determinants for the skewedness of the earnings distribution, but do not test the superstar theory (which they claim to be untestable owing to the difficulties to measure artistic quality). Between 1996 and 2003, ticket prices have risen by 82 percent while the Consumer Price Index (CPI) has increased by 17 percent. For a survey of contributions in the cultural context, see Peltier et al. (2016). https://influencermarketinghub.com/how-much-do-youtubers-make/ and https://www.mic.com/articles​ /192799/how-much-money-do-influencers-actually-make (both accessed 12 June 2019). https://www.youtube.com/watch?v=IwUStSSx3gU, https://www.youtube.com/watch?v=_L4JNftstL0, https://www.youtube.com/watch?v=1MszqmROsEA (all accessed 12 June 2019).

SEE ALSO: Chapter 16: Criticism; Chapter 35: International trade; Chapter 40: Music industry.

REFERENCES Adler, M. (1985), ‘Stardom and talent’, American Economic Review, 75 (1), 208–12. Adler, M. (2006), ‘Stardom and talent’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 895–906. Anderson, C. (2004), ‘The long tail’, Wired Magazine, 12 (10), 170–77. Anderson, C. (2006), The Long Tail, New York: Hyperion Press. Bärtel, M. (2018), ‘YouTube channels uploads and views: a statistical analysis of the past 10 years’, Convergence: The International Journal of Research into New Media Technologies, 24 (1), 16–32. Benghozi, P.-J. and F. Benhamou (2010), ‘The long tail: myth or reality?’, International Journal of Art Management, 12 (3), 43–53. Bhattacharjee, S., R. Gopal, K. Lertwachara, J. Marsden and R. Telang (2007), ‘The effect of digital sharing technologies on music markets: a survival analysis of albums on ranking charts’, Management Science, 53 (9), 1359–74. Borghans, L. and L. Groot (1998), ‘Superstardom and monopolistic power: why media stars earn more than their marginal contribution to welfare’, Journal of Institutional and Theoretical Economics/Zeitschrift für die gesamte Staatswissenschaft, 154 (3), 546–71. Bounie, D., B. Eang and P. Waelbroeck (2010), ‘Marché Internet et réseaux physiques: comparaison des ventes de livres en France’ (‘Internet market and physical networks: a comparison of book sales in France’), Revue d’Economie Politique, 120 (1), 141–62. Bourreau, M., M. Gensollen, F. Moreau and P. Waelbroeck (2013), ‘“Selling less of more?” The impact of digitization on record companies’, Journal of Cultural Economics, 37 (3), 327–46. Brynjolfsson, E., Y. Hu and M. Smith (2003) ‘Consumer surplus in the digital economy: estimating the value of increased product variety at online booksellers’, Management Science, 49 (11), 1580–96. Brynjolfsson, E., Y. Hu and M. Smith (2010), ‘The longer tail: the changing shape of Amazon’s sales distribution curve’, working paper, accessed 12 June 2019 at http://ssrn.com/abstract=1679991. Champarnaud, L. (2014), ‘Prices for superstars can flatten out’, Journal of Cultural Economics, 38, (4), 369–84. Chung, K. and R. Cox (1994), ‘A stochastic model of superstardom: an application of the Yule distribution’, Review of Economics and Statistics, 76 (4), 771–5. Crain, M. and R. Tollison (2002), ‘Consumer choice and the popular music industry: a test of the superstar theory’, Empirica, 29 (1), 1–9. Eror, A. (2018), ‘Just how much money do “influencers” make?’, Highsnobiety, 18 June, accessed 12 June 2019 at www.highsnobiety.com/p/how-much-do-influencers-make/. Filimon, N., J. López-Sintas and C. Padrós-Reig (2011), ‘A test of Rosen’s and Adler’s theories of superstars’, Journal of Cultural Economics, 35 (2), 137–61. Frank, R. and P. Cook (1995) The Winner-Take-All Society, New York: Free Press. Giles, D. (2006), ‘Superstardom in the US popular music industry revisited’, Economics Letters, 92 (1), 68–74. Hamlen, W. (1991), ‘Superstardom in popular music: empirical evidence’, Review of Economics and Statistics, 73 (4), 729–33. Hamlen, W. (1994), ‘Variety and superstardom in popular music’, Economic Inquiry, 32 (3), 395–406.

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Superstars  493 Horton, D. and R. Wohl (1956), ‘Mass communication and para-social interaction: observations on intimacy at a distance’, Psychiatry, 19 (3), 215–29, doi:10.1080/00332747.1956.11023049. Krueger, A. (2005), ‘The economics of real superstars: the market for rock concerts in the material world’, Journal of Labor Economics, 23 (1), 1–30. Lehmann, E. and G. Schulze (2008), ‘What does it take to be a star? The role of performance and the media for German soccer players’, Applied Economics Quarterly, 54 (1), 59–70. Lucifora, C. and R. Simmons (2003), ‘Superstar effects in sports: evidence from Italian soccer’, Journal of Sports Economics, 4, 35–55. Lueck, J. (2015), ‘Friend-zone with benefits: the parasocial advertising of Kim Kardashian’, Journal of Marketing Communications, 21 (2), 91–109. MacDonald, G. (1988), ‘The economics of rising stars’, American Economic Review, 78, 155–66. Marshall, A. (1891), Principles of Economics, repr. 1962, London: Macmillan. Ordanini, A. and J. Nunes (2016), ‘From fewer blockbusters by more superstars to more blockbusters by fewer superstars: how technological innovation has impacted convergence on the music chart’, International Journal of Research in Marketing, 33 (2), 297–313. Peltier, S. and F. Moreau (2012), ‘Internet and the “long tail versus superstar effect” debate: evidence from the French book market’, Applied Economics Letters, 19 (8), 711–15. Peltier, S., F. Benhamou and M. Toure (2016), ‘Does the long tail really favor small publishers?’, Journal of Cultural Economics, 40 (4), 393–412. Rasmussen, L. (2018), ‘Parasocial interaction in the Digital Age: an examination of relationship building and the effectiveness of YouTube celebrities’, Journal of Social Media in Society, 7 (1), 280–94. Richter, W. and K. Schneider (1999), ‘Competition for stars and audiences: an analysis of alternative institutional settings’, European Journal of Political Economy, 15 (1), 101–21. Rosen, S. (1981), ‘The economics of superstars’, American Economic Review, 71 (5), 845–58. Rosen, S. (1983), ‘The economics of superstars: reply’, American Economic Review, 73 (3), 460–62. Smith, T. (1998), ‘The addiction to culture’, paper presented at the biannual meeting of the Association for Cultural Economics International, Barcelona, 14–17 June. Spierdijk, L. and M. Voorneveld (2009), ‘Superstars without talent? The Yule distribution controversy’, Review of Economics and Statistics, 91 (3), 648–52. Stigler, G. and G. Becker (1977), ‘De gustibus non est disputandum’, American Economic Review, 67 (2), 76–90. Terviö, M. (2009), ‘Superstars and mediocrities: market failure in the discovery of talent’, Review of Economic Studies, 76 (2), 829–50. Weeds, H. (2012), ‘Superstars and the long tail: the impact of technology on market structure in media industries’, Information Economics and Policy, 24 (1), 60–68.

FURTHER READING Rosen (1981) and Adler (1985) are recommended as further reading.

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55.  Tax concessions John W. O’Hagan

Like most sins, tax breaks are easier to condemn than to resist . . . Tax expenditures now look likely to play a central role in this year’s [United States] elections. (Economist 2012) I am wealthy. I am also generous. After a lifetime fleecing the clients of a US investment bank I have become a patron of the arts. My accountant approves. A well-timed donation can help push down my tax rate towards single figures. Now, here’s the deal. You – and, by you, I mean other taxpayers rich and poor – must provide unlimited subsidies to match my largesse. (Stephens 2012)

The above quotes capture some of the heat of the debates raging both in the United Kingdom and the United States on the issue of tax expenditures in 2012.1 The reason is that, at that time, changes had been proposed to the taxation measures aiding the donation of gifts/bequests, including those to the arts, in both countries. Some of these measures have formed the cornerstone of government policy towards the arts in the United States since the beginning of the twentieth century and they are defended vehemently to this day. While such measures exist in some countries in Europe, albeit on a smaller scale, they, as in the United States, generate considerable debate from time to time. Many still call strongly for more of a United States-type tax policy in Europe. However, there have been trenchant criticisms of the United States’ tax-policy measures in relation to charitable contributions as they apply to the arts, the most authoritative and comprehensive of these still being that of Feld et al. (1983). Few currently involved in the arts or policy-making in the United States, though, appear to question the charitable contribution deduction as a means of channelling public money to the arts. Weil (1991) particularly, in a very elegantly argued piece, defends this tax policy over direct government grants and bemoans the diminution of the scale of the tax incentive resulting from tax changes in the United States. Simon (1987) also defended tax concessions over government grants in a comprehensive review of the tax treatment of non-profit organisations in the United States. There are other tax expenditures on the arts in Europe, which while much less in size than those for charitable contributions in the United States, and more elusive, are fiercely defended by the arts communities there and do matter greatly. Several European countries have tax deductions for charitable contributions and other tax breaks for the arts. The main policies, though, appear to relate to concessions regarding value added tax (VAT), changes in which are subjected to considerable public debate. Also, the important property tax exemption applying to non-profit organisations is prevalent in both Europe and the United States. What precisely are these tax measures? What is the cost of these measures to the taxpayer? What are the advantages and disadvantages of tax measures relative to direct subsidies? These are the questions that are addressed briefly in this chapter. 494

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Tax concessions  495 The next section outlines the extent and nature of a few of the main tax concessions to the arts in this regard in Europe and the United States. The intention of this section is not to document the detail of these concessions, but to establish that large-scale tax concessions do exist and that funding to the arts in the United States dwarf direct subsidies. They are sizeable also in Europe. Tax concessions are examined in relation to three different situations: charitable (cash) contributions, VAT and the taxation of artists’ income.2 These account by far for the main tax foregone arising from such concessions, and all raise interesting economic issues. The third section discusses the issue of why tax expenditures, such as direct grants and subsidies, are often not seen as a cost to the taxpayer. The penultimate section discusses the advantages and disadvantages of tax expenditures versus direct grants to the arts, based on two criteria: state interference, and value for money from the expenditure. The final section concludes the chapter.

EXTENT AND NATURE OF MAIN TAX CONCESSIONS Charitable Contribution Deductions A tax deduction changes the price to the donor of a charitable gift to the arts. Specifically, the deduction reduces the net cost to the donor of channelling a fixed sum to an arts institution and, thereby, could induce donors to provide even more than they would in the absence of the tax concession. Thus, for example, if a donor wanted to give €500 to a museum before the tax concession and the marginal tax rate of this donor was 50 per cent, then the effect of the tax concession would, first, be to reduce the after-tax cost to the donor to €250 and, second, to induce some response to this by the donor, in particular to increase the initial gift. If the donor increased the gift to €1000, the net cost would be €500, the same as the individual was prepared to donate before the tax concession. The magnitude of this induced giving is the price elasticity for charitable giving to the arts. It depends on the donor knowing the marginal tax rate, which in turn depends on his or her total income. There are several other features of any charitable contribution deduction which are important to note. First, the tax expenditure usually depends on the marginal tax rate of the donor, ranging from nothing for those who are not liable for income tax to the top rate times the value of the gift for those in the highest income bracket (for illustrative purposes assume that the top rate is 50 per cent). Thus the higher a person’s marginal tax rate, the more the gift will be subsidised by the state: therefore, a gift of €500 from those on the zero rate will cost the state nothing, and the donor the full €500, whereas a gift from a donor on a marginal rate of 50 per cent will cost the donor only €250, the state paying the rest of the bill of €250. Second, the legal constraints on the deduction can vary. The institution must have a favoured institution classification and how this is defined has a huge impact on the extent of the tax incentive. Third, the extent of tax deductibility is also critical, varying in principle from 0 to 100 per cent of the donation. Thus, the decision as to which institutions can benefit from this type of scheme and the extent of the tax deductibility of the contribution are critical features of any scheme. Fourth, the concession may only apply when the contribution is made to an institution, permanent or temporary, and not to an individual.

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496  Handbook of cultural economics The federal income tax code in the United States accounts for three significant income tax expenditures for the arts: individual charitable income tax deductions, corporate income tax deductions and capital gains tax foregone on gifts of property. The charitable contribution deduction accounts for the vast bulk of the tax expenditure under this heading and is the cornerstone of indirect federal aid to the arts in the United States. Only this tax expenditure is discussed in this chapter (see O’Hagan 2012 for a discussion of the other two).3 It also accounts for the bulk of overall funding to the arts in the United States. For example, it accounts for 10–15 times the amount of direct federal support through the National Endowment for the arts, the main channel for federal subsidies to the arts in the United States. Moreover, the relative importance of this tax expenditure appears to have increased significantly (Feld 2008).4 In Europe the situation is very different. Tax expenditures associated with charitable contribution deductions appear to be minimal, judging from the evidence that is available (see Schuster 1986; Economist 2012), the main reason being that, independent of tax concessions, Europeans may see charitable contributions as the function of their much higher general tax rates and not as something that they are expected to pay in addition to their taxes. Whatever the differences in the systems in operation in the major European countries and the United States, they are unlikely to explain the much greater take-up, and therefore tax expenditure, that arises in the latter. ‘The difference in practice surely must be more the result of the relative importance of the public sector in [the European] countries and of the relative lack of private initiative and support for the arts in the presence of such heavy public support’ (Schuster 1986, p. 325). This is certainly a plausible argument. Value Added Tax (VAT) The major effective tax concession in Europe is the preferential VAT treatment of the consumption of the output of the arts sector, but few estimates appear to have been made of the cost of this tax concession. This is a tax concession that would favour particularly the performing arts, as it usually applies to the output of all performing arts organisations, not just the publicly funded institutions, which also receive large levels of direct public assistance. Practice varies considerably between the countries of the European Union (EU), both regarding the standard rate and the rates that apply to the outputs of the arts sector. The level of the standard rate is important, as it is in relation to this that the tax expenditure associated with the lower rates would be calculated. The tax foregone associated with the concession is likely to be very sizeable, as it would amount to 15 to 20 per cent of boxoffice income of all performing arts companies, not just the non-profit institutions. This assumes, though, that attendance would not drop significantly if VAT was imposed on the performing arts sector. Reduced VAT rates apply to all arts institutions, which make this tax concession an unfocused funding device for the government. One further and crucial question is who benefits from VAT concessions? Is it the consumer or producer of the service, or is the benefit shared between the two? It is normally assumed that VAT is passed on fully to the consumer in the form of higher prices, and that the consumer pays the cost and therefore benefits from concessions in relation to it. This

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Tax concessions  497 needs qualification. If the consumer is charged in full for the VAT, then the consequent increase in price facing the consumer may lead to a fall-off in demand for the service and, subsequently, a loss for the producers. Also, if VAT rates fall, there is no guarantee that the price will fall, as the institution may decide to increase its margin and not pass on the benefit to consumers. Indeed, in the case of non-profit institutions, the reduction of VAT lessens the incentive for them to be more efficient by lowering costs of production to stay competitive with producers of other consumer goods and services that are subject to VAT. Taxation of Artists’ Income Several issues arise under this heading. First is the question of whether the income of artists should, for income tax and social security tax purposes, be treated differently to that of other taxpayers or not. Second is the issue of whether there should or should not be different treatment of business expenses in relation to artists. Finally, is the issue of the tax treatment of gifts/bequests by artists to arts institutions. We look at the first of these only (for a discussion of the other issues, see O’Hagan 2012). One European country, namely, Ireland, went so far as to exempt totally the income of creative artists from income tax. This measure was introduced in 1969 and it was estimated that the annual cost to the state of the scheme was equivalent to around 13 per cent of the total budget of the Arts Council, and that it came to twice as much as the total given to individual artists from direct funds.5 This tax provision was subjected to considerable criticism (see Schuster 1986) and has in recent years been greatly modified.

TAX BREAKS DO COST MONEY6 It appears odd that so many people still do not associate a cost (that is, a tax expenditure) with a tax break in relation to the arts, and that so many governments still have so little data relating to the precise cost of various tax concessions to the arts. Why is this? The first reason is that tax expenditure analysis in general, especially its inclusion in the budget process, is of recent origin and still is not formally included in budget accounts for many countries and therefore is not subjected to scrutiny as are other tax measures. Part of this has to do with the many different tax expenditures being extremely difficult to estimate, both for data reasons and because the estimation depends on what behavioural assumptions about the key players are made by the analyst.7 Nonetheless, in relation to tax expenditures in general there is now more awareness of the cost to the taxpayer, and many proposals for limiting their extent and cost are being examined (see, for example, Baneman et al. 2011; Barrios et al. 2016). Second, in relation to the arts, some have argued that the main tax break, the charitable contribution deduction, does not involve a tax expenditure at all, on the grounds that income devoted to a charitable cause (which is how a contribution to the arts is classified) is not available to the person for his or her own consumption, but for the consumption of all, and should not be taxed to him or her. There are very few in the economics or legal profession who appear to support this argument. Third, tax expenditures are rarely designed specifically for the arts, but are established in relation to some much wider target group, such as charities in the United States, of

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498  Handbook of cultural economics which the arts are only a tiny component. Even if estimates of the tax expenditure for the sector were available, it is unlikely that they would be available for every small subcomponent and hence could not be subject to public scrutiny. Fourth, it may be that the very obscurity of a tax expenditure removes the pressure to quantify it. The state’s contribution to a local wealthy individual’s gift to his or her local museum is never identified by the individual or the museum. It is this very obscurity that provided the driving force for the Feld et al. (1983) treatise; they see it as the principal defect of the tax-break system to the arts, preventing it from looming in the consciousness of arts administrators, scholars and the public alike. This is the case that Stephens (2012) also eloquently argues in the opening quotation. Whatever the controversy may be over the tax expenditure associated with taxation policy, it is clear that these tax breaks are highly valued by the arts community (judging at least from the reaction when there is a proposal to abolish them) as each and every one of them bestows favours on the arts sector, even though it may be very difficult to quantify the exact magnitude of the implicit subsidy involved. A related point is that even if the implicit subsidy could be accurately calculated, proposals to replace them with a direct and explicit subsidy are mostly rejected by the arts community, on the understandable grounds that there is no guarantee, that once the tax concession is abolished, governments will not subsequently renege on their promise to replace it fully with a direct subsidy.

WHICH FORM OF ASSISTANCE: GRANTS OR TAX EXPENDITURES? The one issue that divides policy and practice in relation to the arts sector in Europe and the United States is the relative merits of direct grants versus tax expenditures. This debate has been conducted largely in terms of state interference and efficiency8 (see, for example, Netzer 1978; Schuster 1986; O’Hagan 2012). State Interference It has always been feared that direct public funding of any significance would only come at the cost of extensive political interference in decisions relating to artistic and professional aspects of the arts sector. As one commentator put it in relation to the United States: ‘There was apprehension about philistine legislators and elected officials, straight out of H.L. Mencken’s gallery, who would seek to censor avant-garde program choices, witchhunt for obscenity and subversion, and generally favor the bland and mediocre over the exciting and distinguished’ (Netzer 1978, p. 36). Some government interference is unavoidable when public monies are being dispensed. Governments must choose between claimants for funds, as demand for funds will always exceed resources. Also, no government should give away money without laying down some minimum financial reporting requirements. Moreover, it may be desirable for the funding agency to lay down certain conditions relating to type and/or location of the arts being subsidised. For example, it may be stipulated that a specific percentage of funding should portray the work of, say, experimental playwrights, artists or theatre groups, or relate to minority ethnic interests. It may be stipulated that a symphony orchestra put on

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Tax concessions  499 some free concerts for schools or in public areas as part of its funding responsibilities. This may make perfect sense if the rationale for the grant in the first place is related to these objectives. Thus, although it may be anathema to some people in the arts to say so, some government influence over decision-making may be necessary if objectives deriving from the original rationale for the funding are to be achieved. How does this impinge on the issue of grants versus tax breaks? Advocates of tax breaks and expenditures believe that this funding ensures less government influence than do direct grants. The latter, it is argued, allows the cultural development of a nation or region to be influenced by a relatively small number of public or semi-public officials, whereas providing tax incentives to encourage private individuals to contribute more to the arts allows for a much more widely based and democratic choice as to which art form will be promoted and by how much. That is, tax expenditure decisions are made by donors who are many and varied, whereas there is only one arts council or government ministry reflecting, perhaps, only one set of views. The reality, however, is a little more complex than the above implies. First, arts councils and arts ministers are subjected to intensive lobbying and public scrutiny, and it is simply misleading to suggest that decisions are made without reference to the views of a broad spectrum of people. Second, private corporations and individuals who make choices about which art form to subsidise may be considerably less qualified to decide on which institutions merit public support than officials and expert advisers in arts councils and ministries. Experience in the United States has demonstrated that private donors often interfere more, and are arguably more philistine in their views, than state agencies (see Netzer 1978; Economist 2012). The most serious criticism made of tax expenditures in this regard, though, is that the people who make the decisions come predominantly from the upper-income groups of society and that it is they who determine what is produced. Finally, a government often provides grants for a specific purpose, for example, to bring about more performances of works by young French composers, and, for this, direct subsidy, not tax expenditure, is likely to be more appropriate. Tax legislation can be framed in such a way as to allow a government to pursue specific objectives, but, for administrative reasons, the scope is limited (see Schuster 1986). In summary, it is difficult to be categorical on the issue of which form of state assistance leads to the least undesirable interference in the arts sector. Efficiency There are several strands to this argument. First, there is the assertion that tax expenditures eliminate much needless administrative expense, for example, wages for arts council employees. Thus, government labour and other direct outlays may be kept to a minimum if tax expenditures are used instead of grants. However, overall operating costs may be increased by a switch to tax expenditures, as the latter provide incentives for people to hire lawyers and investment consultants to exploit the tax-reducing possibilities they offer. Also, the tax claims must be processed by government officials, and staff in arts institutions can spend considerable time courting wealthy potential donors, at very considerable cost to the institutions involved. It remains to be proven that a tax-expenditure system can transfer an equivalent amount of funds to arts organisations at a lower cost than government grant agencies.

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500  Handbook of cultural economics A second efficiency argument is that funding by direct grant could lead to rigidities in the structure of the arts industry subsidised in this way, thereby discouraging innovation and, through the continued directing of funds to established companies, deterring the entry of new firms. There is a great deal to this argument, and the problem arises when there is almost permanent commitment of large sums of public money to a largely fixed list of institutions, as is often the case with revenue grants and direct state provision. This type of a situation can lead recipient institutions to incur wasteful expenditures and it reduces their incentive to maximise alternative sources of revenue (for example, box-office receipts could, perhaps, be increased by better advertising and/or by experimenting with different prices). The difficulty is that recipient institutions often come to expect not only that the arts council/ministry grants will continue, but that they will increase year by year, and they plan their finances and activities on this basis. Consequently, the funding agencies are often in ‘the position of supporting numerous organisations involuntarily for fear that withdrawal of public support might precipitate insolvency. [Thus they] are as much locked into many of their existing grantees as the grantees are locked into the grantors’ (Netzer 1978, p. 175). Given a fixed or slowly increasing budget, the above clearly implies that funding agencies will have only limited capacity to support new applicants and/or to finance new initiatives. Therefore, the innovative role of the funding agency could be reduced: in the process it could lose much of its ethos and, eventually, its raison d’être for existence could be challenged. Tax expenditures probably would involve less rigidity and inefficiency. Private donors are more likely than government bureaucrats to insist on cost minimisation, and they are likely to be less reluctant to switch funds in response to changing tastes, and so on. However, there are problems with this as well. First, the government has very limited control over how private donors spend their money, even though the government shoulders a sizeable share of the cost of the donations. Thus, the money may be used efficiently by the recipient institutions, but the wrong institutions are receiving the public money; wrong in that these institutions are not priorities for public aid – even if the right institutions are receiving the funding, they may be using it, in response to the tax incentive, to purchase or produce the wrong inputs and/or outputs. It is almost irrelevant that they are converting inputs into outputs efficiently if the specification of inputs and outputs is incorrect. Second, it is possible that large corporations and wealthy individuals may also become locked into their grantees, as many of them may fear the adverse publicity that could surround a sudden withdrawal of funds.

CONCLUDING COMMENTS A few issues emerge from the above discussion. First, it is evident that tax concessions are a major part of policy in relation to the arts, not only in the United States, but also in Europe.9 Second, the individual charitable contribution deduction is the most important part of tax policy that affects the arts in the United States, and this does not necessarily result from significantly more favourable tax laws in this regard but because more people avail themselves of the tax concession. The reason for this is that, in Europe, people see it as the role of the state (and their higher tax levels) to fund the type of activities that are left to voluntary private charitable contributions in the United States.

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Tax concessions  501 Third, the tax concession in relation to VAT is probably the most important in Europe, at least in terms of tax foregone. This concession is much more broadly based, as almost everyone goes to events that have preferential tax rates, and therefore all gain. However, all lose as well, as the tax foregone must be recouped from other taxes, such as higher VAT rates on other goods and services or increased income taxes. For the providers of the services receiving favourable VAT treatment, though, it appears to be a particularly valued concession, and usually they, and not consumers, lobby against any clawing back of these concessions. Fourth, debate concerning the merits of grants versus tax expenditures focuses mainly on a discussion of government interference and efficiency. The main point to make here is that the debate is far from conclusive, with advantages and disadvantages attached to both the American and the European models of funding. For example, tax-based state expenditure on the arts might lead to a more diversified decision-making process and have the benefit of requiring a matching grant from the donor, but this expenditure might be totally inefficient in that it could go to arts institutions which least merit it.

NOTES 1. This chapter draws heavily on O’Hagan (2012). 2. Charitable contributions in kind and property tax exemptions are other important concessions but are not examined here (see O’Hagan 2012). 3. It is difficult to obtain data on giving to the arts, as the arts, culture and the humanities are all put in one category. In relation to total charitable contributions, circa 76 per cent comes from individuals, 12 per cent from foundations, 8 per cent from bequests through estates and 4 per cent from corporations (Schuster 1986). Thus, the overall picture is evident, individual contributions dominate. 4. For a discussion in general on tax expenditures, see Barrios et al. (2016). 5. See O’Hagan and Duffy (1988). 6. See also, Barrios et al. (2016). 7. For example, if the tax concession of a zero VAT rate on theatre admissions was abolished, what assumption would be made about the level of attendance as a consequence of the higher price? If, say, it dropped by 50 per cent, is the tax forgone calculated on attendance after or before the tax is imposed? 8. Also, in terms of security of funding, but space does not permit a discussion of this here. 9. An interesting extension to this research would be to examine tax policy in relation to the arts in other major blocs, such as China, India and Latin America.

SEE ALSO: Chapter 42: Non-profit organizations; Chapter 50: Public support; Chapter 58: Welfare economics.

REFERENCES Baneman, D., J. Rosenberg, E. Toder and R. Williams (2012), Curbing Tax Expenditures, Washington, DC: Urban Institute and Brookings Institution. Barrios S., F. Figari, L. Gandullia and S. Riscado (2016), The Fiscal and Equity Impact of Tax Expenditures in the European Union, Brussels: European Commission. Economist (2012), ‘Charities, tax and politics: one hand giveth’, The Economist, 21 April, accessed 6 December 2019 at https://www.economist.com/britain/2012/04/21/one-hand-giveth. Feld, A. (2008), ‘Revisiting tax subsidies for cultural institutions’, Journal of Cultural Economics, 32 (4), 275–9.

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502  Handbook of cultural economics Feld, A., M. O’Hare and M. Schuster (1983), Patrons Despite Themselves: Taxpayers and Tax Policy, New York: New York University Press. Hemels, S. and K. Goto (2017), Tax Incentives for the Creative Industries, Berlin: Springer. Netzer, D. (1978), The Subsidized Muse: Public Support for the Arts in the United States, Cambridge: Cambridge University Press. O’Hagan, J. (2012), ‘Tax expenditures: pervasive, “hidden” and undesirable subsidies to the arts?’, Homo Oeconomicus: Journal of Behavioral and Institutional Economics, 29 (2), 95–118. O’Hagan, J. and C. Duffy (1988), ‘The arts and Section 32 of the 1984 Finance Act’, Economic and Social Review, 19 (2), 147–51. Schuster, M. (1986), ‘Tax incentives as arts policy in Western Europe’, in P. DiMaggio (ed.), Nonprofit Enterprise in the Arts: Studies in Mission and Constraint, New York: Oxford University Press, pp. 320–60. Simon, J. (1987), ‘The tax treatment of nonprofit organizations: a review of federal and state policies’, in W. Powell (ed.), The Nonprofit Sector, New Haven, CT: Yale University Press, pp. 67–98. Stephens, P. (2012), ‘Philanthropy is no alternative to paying tax’, Financial Times, 16 April, accessed 6 December 2019 at https://www.ft.com/content/cf471bb0-87b2-11e1-ade2-00144feab49a. Weil, S. (1991), ‘Tax policy and private giving’, in S. Benedict (ed.), Public Money and the Muse: Essays on Government Funding for the Arts, New York: Norton, pp. 153–81.

FURTHER READING The key general readings on this topic are Feld et al. (1983), O’Hagan (2012), Schuster (1986) and Simon (1987). A general reference on tax breaks for heritage and the cultural industries is found in Hemels and Goto (2017).

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56.  Theatre

Marta Zieba

The definition of theatre as a live art form will differ regionally. Whereas in Englishspeaking countries, such as the UK or the USA, theatre usually refers to drama performances, in many countries of continental Europe, theatre is defined by different types of performances, such as drama, opera, classical music performance, ballet, musical and operetta, theatre for children, and others. Second, we also understand theatre to be an institution that produces live performances for the different art genres just mentioned. Many theatres in Europe and worldwide have also been heavily subsidised by governments or are run as public or state companies, as is the case, for example, in Germany, Austria, Italy or France. Numerous smaller and larger private theatre companies are not subsidised, or they are granted only a very small amounts by public or private donors. Private or for-profit theatres usually specialise in staging one or two productions which run for a long period or during the whole theatre season. These theatres also tend to produce more popular genre forms, such as musicals or comedies, in contrast to drama or opera. A prominent example of private theatre is the Broadway theatre in the US, discussed in Moore (1966) and Maddison (2005), but we can find similar private theatre structures in other countries. In contrast, the public or subsidised theatres are multi-branch theatres, as they produce many types of performances. They are also repertory theatres, which offer performances of various productions listed in the repertoire, spread over the entire theatre season. Public theatres are likely to have more formal legal structures and usually have a director or theatre management that will report to the appropriate licence holder. Although there is already established empirical evidence for the standard determinants of demand for theatre, such as admission price, income or education, more research is required to explore the impact of other influential factors. Furthermore, not many studies explicitly examined the supply side of theatre, and that analysis gained the most attention for non-profit or public theatres only. This is mainly owing to the lack of appropriate data, the complicated nature of artistic output produced and diffused institutional settings of theatrical institutions. Moreover, conventional supply analysis is not very useful in the context of theatre owing to information asymmetry and the merit-good characteristics of the supplied theatre output being difficult to observe. Therefore, previous research regularly focused on analysis of production or cost for theatrical firms. In this chapter, we first review the empirical evidence on the determinants of demand for theatre, using, to the best of our knowledge, the most important findings in the literature. Secondly, we discuss the production, cost and productive efficiency of theatres. We briefly discuss theatre management behaviour of publicly funded or subsidised theatres. We also emphasise the relationship between theatre management objectives, subsidies and productive efficiency of theatres.

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504  Handbook of cultural economics

THEATRE DEMAND The demand for theatre is usually measured by theatre attendance, which is the number of theatre visitors. Theatre attendance has been examined at a largely aggregated level, such as a country, region or city, or at a more disaggregated level, such as a firm or a single performance or production. The aggregate studies on theatre demand mostly examine the impact of standard demand factors, such as ticket price, income and price of other goods (substitutes or complements). The first of these studies were conducted by Throsby (1994), Withers (1980) and Gapinski (1984, 1986, 1988). The studies also include, to varying degrees, other variables, such as the price of leisure time, the past and future attendance, and the quality or output characteristics of theatre. Recently, more studies increasingly applied individual-level data and they examined the decision to attend, and/or frequency of attending, a theatre performance (Borgonovi 2004). These empirical papers usually obtained estimates on the effects of audience characteristics, including not only income but also education level, gender, age, marital status and other individual factors of theatregoers. Ateca-Amestoy (2008) examined the differences in these characteristics between those individuals who never attend a theatre performance and those who may go a positive number of times. In contrast to examining consumer choices using the revealed preferences, Grisolía and Willis (2011, 2012) and Willis and Snowball (2009) used the stated preferences approach by applying discrete choice experiments to assess people’s utility and willingness to pay (WTP) for the different attributes of theatrical productions. Theatre Ticket Price Most of the recent demand studies for theatre that applied richer panel data on the firm level in different countries confirmed that ticket price elasticity for theatre is negative and lower than one in absolute value. Zieba (2009) using data on 178 German theatres over 40 years found the own price elasticity in the range –0.26 to –0.43. O’Hagan and Zieba (2010) focused on examination of the quality for theatre demand by splitting the sample into West German and East German public theatres, and they found very similar results in respect of the admission price. They also applied the dynamic generalised methods of moments (GMM) panel data estimator to correct for the potential endogeneity bias in the price variable, but the price elasticity did not change. This result was in line with the assumptions of earlier studies that theatre ticket price is exogenously determined as supply does not respond to demand (Gapinski 1980; Moore 1966). Furthermore, Zieba (2011a) also found the own price elasticity to be circa –0.5 for Austrian non-profit theatres, while for Swiss non-profit theatres the elasticity differed between the Frenchspeaking theatres (–0.477) and the German-speaking theatres (–0.126). For Flemish subsidised theatres, Werck and Heyndels (2007) found the mean point estimate of price elasticity ranging between –0.16 and –0.14, indicating a very inelastic demand. Inelastic demand would indicate that theatres could charge higher admission prices and will not necessarily decrease the revenue from their tickets sales. Castiglione and Infante (2016), using panel data on Italian theatres over 34 years, estimated the rational addiction model including both the past and future attendance. Their results indicate that a 1 per cent increase in the ticket price in Italian theatres will

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Theatre  505 decrease theatre attendance by 0.7 percent. Moreover, the authors also estimated a longrun price elasticity which was equal to –0.2. They also found that the past and future price of tickets have a positive effect on theatre demand, providing the justification for the rational addiction theory. Castiglione and Infante (2017), as the only study, examined simultaneously the demand and supply of theatre, and found that while the ticket price was not relevant in the supply equation, it had a negative effect on demand, but again the theatre demand was not sensitive to the ticket price. Other factors can also determine the ticket price effect, as noted by Throsby (1994) and evidenced in later studies. Abbé-Decarroux (1994), using data on single productions, estimated that demand is price elastic for the reduced seat price at the Geneva Theatre for the period 1982–89. Corning and Levy (2002) also found price-elastic theatre demand, using data on single performances, and argued that this result is due to the correlation of the ticket price with other performance-related variables (that is, day of the week, or evening or matinee show). Akdede and King (2006) found that price elasticity of demand for Turkish theatres is largely elastic in the least developed cities (–3.19) compared with developed cities (–0.3). Moreover, Baldin et al. (2018) examined demand using the booking data from the sale system of the Royal Danish theatre for the period 2010–11 to 2014–15. They found that young customers are the most price-sensitive audience group, with the price elasticity of –1.84 whereas standard ticket buyers are less price sensitive: a 1 per cent increase in ticket price results in approximately 0.49 per cent decline in quantity demanded. Cross-Price Effects The data on other cultural goods that would be relevant substitutes or complements for theatre, are also difficult to obtain. Gapinski’s (1986) findings indicate that substitutes also come from other performing arts genres. Zieba (2009) found that the average ticket price for symphony concerts of German public orchestras located in the close proximity to theatre, had a positive effect on demand for German public theatres. However, Castiglione and Infante (2017) found that cinema is more of a complementary good than a substitute for theatre. Werck and Heyndels (2007) used both the average ticket price of other theatre companies and of cinemas in the relevant market but the two price coefficients were not significant. O’Hagan and Zieba (2010) similarly used the price of other theatres in their local proximity but their results were also ambiguous. The findings confirm the difficulty of identifying what substitute activities for theatre are (for example, sports, cinema, television, leisure and other live performing arts). It is also not clear how the digital supply affects the attendance at theatre. In the quasi-field experiment, Bakhshi and Throsby (2014) showed that live broadcasts of the Royal National Theatre to cinemas in the UK can generate greater audiences at the theatre. This implies that broadcasting would be a complementary good for theatre. Subjective and Objective Quality Throsby (1990) was the first serious attempt to address the issue of quality in relation to demand for the theatre. This study considered the repertoire classification and the standard of source material and production, and of acting and design. To measure these,

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506  Handbook of cultural economics the condensation of press reviews were used on a cardinal 1–5 scale. Corning and Levy (2002) also measured quality using critical reviews as the ordinal variable and found that they positively affect attendance at the theatrical performances in California. AbbéDecarroux (1994) used variables to measure quality similar to those applied by Throsby (1990), and the analysis covered 64 productions spread over seven years for one theatre company. A novel aspect of Throsby’s paper was the division of quality factors into those which can be observed in advance and others which are hard to evaluate before seeing the performance. Urrutiaguer (2002) addressed the issue of quality judgements and their measurement using data on theatre relating to France. As the author argued, the data were restricted in deriving proper findings and conclusions, but he did look at some interesting new indicators of quality, such as type of theatre director and level of public subsidy. Werck and Heyndels (2007), in addition to the repertoire classification, introduced a concept of objective output characteristics in the context of the Lancastrian consumer theory, which states that characteristics, not goods themselves, are relevant to consumers. They found that larger productions (measured by the cast size) and Dutch plays had a positive effect, but the innovation index, as a proportion of new productions in the programme, had a negative effect on attendance at Flemish theatres. Zieba (2009), and in particular O’Hagan and Zieba (2010), using an extensive data-set for East and West German theatres, found that the expenses for decor and costumes, and the artistic wages are important indicators of objective quality, and that reputation as measured by guest performances or guest attendance, had a strong positive effect. O’Hagan and Zieba (2010) in addition to the previously mentioned variables, found that the cast size also had a positive impact, while the innovation index had a negative effect on theatre attendance. These studies were comprehensive enough as they addressed simultaneously the issues of price, income and quality, and applied robust panel data models. Moreover, Grisolía and Willis (2011, 2012), using individual survey data for the theatre in Newcastle in England, applied discrete choice experiments and the latent class demand models, respectively. They proved that expert reviews and word-of-mouth opinions positively affect demand for regional theatre in England, and that the utility of attending the particular type of play (drama, comedy or musical) will depend on the consumer’s characteristics. Willis and Snowball (2009) further confirmed that both professional actors and shows directed by famous directors increase the WTP of National Arts Festival-goers in the South Africa. Income and Time Allocation Numerous studies confirmed a positive association between the level of income and demand for theatre, confirming that visiting theatre is not an inferior good. We also would expect the income elasticity of demand to exceed 1, but the results for the exact magnitude of the income effect are mixed. This might be because the income effect is correlated with the education level, but also because the participation in cultural attractions usually requires a sizeable amount of leisure time (Moore 1966; Throsby 1994). Withers (1980), using aggregate time-series data for US performing arts firms, and Zieba (2009), using panel data for German public theatres, confirmed that the income effect could be a net effect of two factors: a positive, large, full-income effect and a negative, leisure-price substitution effect.

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Theatre  507 Education Another reason why income elasticity was found to be inelastic, or even not significant, in the numerous previous studies is that, among other socio-economic factors, education was found to be the most important determinant of theatre demand or attendance (Borgonovi 2004; Ateca-Amestoy 2008; Willis et al. 2012). Education is also closely linked to the concept of cultural capital which is the ability to experience and admire the arts, having the capacity to inspire or to be inspired. Furthermore, cultural capital can also be defined as acquired taste that enables the possessor to appreciate the arts. Ateca-Amestoy (2008), in relation to theatre, confirms that cultural capital is determined by the following factors: the individual’s own general education, education transmitted by parents, early exposure to the arts and specific artistic training. Habit Formation and Rational Addiction According to Lévy-Garboua and Montmarquette (1996), the theory of habit formation is a deterministic approach to consumer behaviour, since any type of habit formation or the creation of consumption capital is an inevitable reality of the human condition. A few studies incorporated the role of habit formation by simply including past theatre ­attendance in the inter-temporal dynamic demand model (see, for example, Withers 1980; Krebs and  Pommerehne 1995; Urrutiaguer 2002; O’Hagan and Zieba 2010). Lévy-Garboua and Montmarquette (1996) studied the individual demand for theatre in France and noted that attending a cultural event involves an element of uncertainty or surprise. They estimated a learning-by-consumption demand model assuming that consumers alter their taste and behaviour through unsystematic experiences of cultural consumption, which might have a positive or a negative random impact. In a more recent study, Castiglione and Infante (2016) concluded that not only future and past attendance and the level of income influence theatre attendance, but also the level of past and future prices influence the probability of Italian theatregoers becoming addicted. The results suggest that Italian theatregoers are not myopic, that is, addicted in a pejorative sense as with cigarettes, drug or alcohol, but fully rational. Other Consumers’ Characteristics The findings about the socio-demographic determinants such as age and gender of theatregoers are still very fragmented. In general, females are more likely to attend but men will be more frequent visitors to the theatre (Ateca-Amestoy 2008). Werck and Heyndels (2007) included age in their panel data model, but it was not significant. Borgonovi (2004) and Willis and Snowball (2009) found that the impact of age will depend on the genre of shows being offered, and that older visitors are less likely to choose comedy or drama (in contrast to musicals) than those in the younger age group. Willis at al. (2012) also found that the higher proportion of young (25 years old or under) and 45 to 59-year-old age groups, the greater the number of trips to the theatre. According to Borgonovi (2004), this result is linked to the effects of the life cycle: family responsibilities that arise during middle age might reduce individuals’ cultural participation. Other gender-related variables (the number of adults in the household, marital status and the

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508  Handbook of cultural economics number of children under 13 years old) decrease both the likelihood and frequency of attendance. Moreover, Willis et al. (2012) found that those who are economically inactive or in professional occupations will be more likely to travel to the theatre. Finally, Grisolía and Willis (2012) identified that different pricing strategies should be applied to different consumer classes. The popular class embraces the youngest attendees, is interested more in comedies and has lower WTP. The affluent class enjoys all types of plays. The cultural class, whose members belong to the older age group and have high WTP, love all aspects of theatre, particularly drama performances. Overall, these results confirm that audiences vary in tastes for different theatrical productions (types of play). Capacity Constraint and Theatre Market The capacity of the theatrical venue is not only important for supply considerations but plays an important role for theatre demand. The capacity constraints have been adjusted either by using an appropriate model, such as Tobit regression (for example, Akdede and King 2006), and/or by directly including the capacity (as measured by the number of seats on offer) in the demand equation (for example, Corning and Levy 2002; Werck and Heyndels 2007; O’Hagan and Zieba 2010). In all cases, the capacity had a positive effect on theatre demand, as expected. Furthermore, Werck and Heyndels (2007) applied the concept of the spatial weight matrix approach to adjust for size of market for the Flemish theatres, as measured by the population. A similar method was used for German theatres by Zieba (2009, 2016) and O’Hagan and Zieba (2010). All these studies found very small differences in the results in respect of the market specification, or the population variable was insignificant. Willis et al. (2012) applied the travel-cost method to examine theatre demand at regional theatres in England and similarly found that distance does not affect people’s decision to visit the theatre, relative to other factors included in the demand model. This also can hold for theatres in many countries. For example, the public theatre scene in Germany is rooted in structures that developed historically, characterised by the existence of several centres with many provincial and urban theatres. Even small cities in Germany, for example, Meiningen, Coburg or Cottbus, have theatres and their attendance is not impacted by the population size. This is in line with Baumol’s (1971) argument that although, currently, the artistic activity is centred in the biggest cities, drama can, under certain circumstances, prosper in smaller cities; ancient Athens has more than once been cited as an example. Moreover, the literature also suggests that an important factor for theatre demand can be tourism that enlarges the theatre market. Tourists may have different preferences and more time at their disposal than the frequent theatregoers (Gapinski 1988). Zieba (2016) found that foreign tourists, in contrast with domestic visitors, had a positive and significant effect on total attendance at large theatres in Austria. The tourist intensity rate, which measures the number of foreign tourist arrivals per resident, had a significant effect on attendance at the opera performances, but it had no effect on attendance at the drama performances.

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Theatre  509

PRODUCTION AND COST OF THEATRE According to Baumol and Bowen (1966), the theatre sector is absent from the technological change that may be represented by an upward shift in the production frontier. Taking as an example, the output per man-hour of an actor playing Hamlet is fixed. As noted also by Marco-Serrano (2006), this particular type of production technology involves high fixed costs, since the organisation, directing, rehearsing, scenery and costume costs are independent of audience size and hence the average total costs will also be higher. This lack of technological progress, together with the increasing wage costs, enlarges the productivity gap from the rest of the economy. Throsby (1977) was the pioneering work in estimating the production technology of the theatre sector. He used theatre attendance as a measure of artistic output and estimated both the short-run and long-run Cobb–Douglas production functions for non-profit performing arts organisations in Australia. Gapinski (1980, 1984) estimated a transcendental production function and defined artistic output in terms of cultural experiences, which was the number of paid attendances for theatrical companies in both the US and the UK. His findings indicate that performing arts firms produce in the economic region with positive and diminishing marginal product for the primary inputs (artists and capital), and with positive but increasing marginal product for the secondary inputs (ancillary staff). Furthermore, this study found decreasing returns to scale over the whole range of inputs. Other empirical studies have relied on the estimation of cost functions for theatres, and their main emphasis has been on finding evidence for scale economies. Taalas (1997) estimated cost function for Finnish theatres and used theatre attendance as artistic output. Her findings suggest that in managing Finnish theatre, inputs are not combined in optimal proportions in light of prevailing market prices. The relative shares of inputs utilisation also vary when output expands and there are scale economies in the production of theatrical performances. In addition, Fazioli and Filippini (1997) estimated the translog cost function of 28 public theatres in Italy. They used the number of performances as artistic output and confirmed the evidence of economies of scale, to reveal that the majority of the Italian theatre companies operate at an inappropriately low-scale level. The more recent econometric techniques and improved data availability enabled researchers to examine the Baumol and Bowen’s productivity gap in greater detail by estimating the technical efficiency (TE) of theatres or by directly estimating the total factor productivity (TFP). Technical efficiency is one of the components of TFP, and for theatres it has been defined as the ability to obtain the maximum output from the given input vector (Marco-Serrano 2006; Zieba 2011b; Zieba and Newman 2013; Castiglione et al. 2018) or as the ability to use minimum inputs for the same level of output (Last and Wetzel 2010; Fernández-Blanco et al. 2019). The relevant studies focus on the estimation of TE instead of cost efficiency. Last and Wetzel (2010) used data on German public theatres and empirically proved that the assumption of cost-minimising behaviour cannot be maintained for public theatres. Subsequently, Last and Wetzel (2011) applied the Malmquist total factor productivity index. They observed, in line with the cost-disease hypothesis, a decrease in productivity caused by a combination of increasing labour costs and no (or very limited) opportunities to benefit from technological improvements. Except for Marco-Serrano (2006), who used a non-parametric linear programming data envelopment analysis (DEA), all other mentioned studies applied the parametric panel

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510  Handbook of cultural economics data stochastic frontier approach (SFA), which recognised not only the technical inefficiency component (deviations below the optimal output level or above the minimum input level), but also the random shocks that are beyond producers’ control, and an unobserved heterogeneity of theatres. The estimated average TE scores from previous research were all below 1 indicating that theatres are technically inefficient. Castiglione et al. (2018) found the TE score of circa 0.66, indicating that Italian performing arts firms (including theatres) could improve artistic output by 34 per cent by using the same level of inputs. Zieba (2011b) found TE scores of 0.87 for Austrian and 0.73 for Swiss theatres, respectively. The scores were higher in Zieba and Newman (2013) for German public theatres, which were about 0.85 on average for the period 1972–2004. The studies that used an input-orientated model provided higher average TE scores, whereby German public theatres were found to be 96 per cent efficient in Last and Wetzel (2010) for the period 1991–2005. Fernández‑Blanco et al. (2019) found that Polish public municipality theatres in Warsaw were 93 per cent efficient, indicating that inputs could be still decreased by 7 per cent. The lowest scores, however, were found by Marco-Serrano (2006) and they ranged between 24 and 54 per cent, but these results were obtained using a non-parametric DEA and therefore they are not directly comparable with other findings. The differences in the obtained TE scores may not only be due to the different methods applied but also to the differences in defining and measuring artistic output. The evidence confirms that if output is measured as the number of visitors (Zieba 2011b; Zieba and Newman 2013) or as the revenue from tickets sales (Castiglione et al. 2018) in the output-oriented TE model, the efficiency scores are lower, as expected, owing to the possible demand effects. Consequently, the TE scores are higher when the output is measured as the number of supplied tickets (Last and Wetzel 2010), or both as the number of productions and the number of performances (Fernández-Blanco et al. 2019) in the input-orientated TE specifications.

THEATRE MANAGEMENT Another important issue to consider is the role or objectives of theatre management. According to Krebs and Pommerehne (1995), institutional setting may be an important component in understanding managerial behaviour and outcomes of theatrical institutions. For public theatres, we can distinguish between the politicians and cultural bureaucrats (those involved in theatre’s administration or management). Whereas the bureaucrats might strive for non-pecuniary goals, such as power and prestige, and control over a large budget, the decision on the level of subsidisation is taken by the politicians. For example, non-culturally interested politicians will impose certain conditions such as minimum capacity utilisation of theatre or minimum revenue from ticket sales. The culturally interested politicians will emphasise the quality or artistic production. As a result, theatre management or director’s objectives will face a trade-off between budget, attendance and quality, while the latter will be influenced in the form of repertoire (that is, highbrow versus lowbrow productions). Subsidies Understanding how theatre repertoire, quality and efficiency are influenced by the level of funding is particularly important where substantial public resources are devoted to

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Theatre  511 providing services that, arguably, could be provided by the private sector (Castiglione et al. 2018). Werck et al. (2008) found that theatres’ budgets have an impact not only on the number of plays they perform but also on their nature, providing the first systematic empirical evidence that theatres will make qualitative changes to output owing to cost pressures. In a study on English theatres, O’Hagan and Neligan (2005) found a negative relationship between subsidy as a proportion of total income and the conventionality of theatre programmes. Neligan (2006) provides similar evidence for German public theatres, confirming that financial factors (public subsidy and subscription income) do play an important role for repertoire decisions. Thus far, there were only a few studies in this field that confirmed the hypothesis that subsidies increase not only the quality but also the efficiency of theatres. The more recent findings of Zieba (2011b) for Austrian and Swiss non-profit theatres, and of Fernández-Blanco et al. (2019) for Polish municipal theatres in Warsaw, indicate that public funding increases the TE of the examined theatrical firms. Hence, public subsidies not only affect the repertoire conventionality but they also result in theatre managers being more efficient. Organisational Form The legal or organisational form of a theatre which defines the way in which a theatre company is organised, financed and controlled, will affect the economic performance of theatres. While Castiglione et al. (2018) found that the legal form has no effect on efficiency of Italian theatres, Zieba and Newman (2013) examined the effect of institutional setting on efficiency of German public theatres. Theatre managers or directors, who often have been appointed by the city council or another licence holder, run the German public theatres. The rights and duties of the theatre management will change depending on the legal form of theatre. In Germany, we can generally distinguish between public theatres, regulated under public law, and public theatres, governed under private law. Using the natural experiment of the reunification of East and West Germany in 1990, Zieba and Newman’s (2013) results provide evidence to support the hypothesis that theatres organised in public legal forms, where theatre management is subject to strict monitoring and reporting requirements, are more technically efficient than those organised in private legal forms where monitoring and reporting is less stringent. Furthermore, Zieba and Newman’s study found that the decreased subsidies as a consequence of the reunification led to a further decrease in the efficiency of German public theatres organised in private legal forms. However, the reunification competition shock had a positive effect on the efficiency of privately organised public theatres located at the border, while the effect on those theatres organised in public legal forms was insignificant or negative. The empirical findings suggest that whereas public legal forms are better instruments to control the theatre managers, the private legal forms allow the theatre managers more flexibility, which may prove very useful, particularly when the market for artistic performances becomes increasingly competitive.

SEE ALSO: Chapter 24: Demand; Chapter 46: Performing arts.

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REFERENCES Abbé-Decarroux, F. (1994), ‘The perception of quality and the demand for services: empirical application to the performing arts’, Journal of Economic Behavior and Organization, 23 (1), 99–107. Akdede, S.H. and J.T. King (2006), ‘Demand for and productivity analysis of Turkish public theater’, Journal of Cultural Economics, 30 (3), 219–321. Ateca-Amestoy, V. (2008), ‘Determining heterogeneous behavior for theater attendance’, Journal of Cultural Economics, 32 (2), 127–51. Bakhshi, H. and D. Throsby (2014), ‘Digital complements or substitutes? A quasi-field experiment from the Royal National Theatre’, Journal of Cultural Economics, 38 (1), 1–8. Baldin, A., T. Bille, A. Ellero and D. Favaretto (2018), ‘Revenue and attendance simultaneous optimization in performing arts organizations’, Journal of Cultural Economics, 42 (2), 677–700. Baumol, W. (1971), ‘Economics of Athenian drama – its relevance for the arts in a small city today’, Quarterly Journal of Economics, 85 (3), 365–76. Baumol, W.J. and W.G. Bowen (1966), Performing Arts: The Economic Dilemma, New York: Twentieth Century Fund. Borgonovi, F. (2004), ‘Performing arts attendance: an economic approach’, Applied Economics, 36 (17), 1871–85. Castiglione, C. and D. Infante (2016), ‘Rational addiction and cultural goods: the case of the Italian theatergoer’, Journal of Cultural Economics, 40 (2), 163–90. Castiglione, C. and D. Infante (2017), ‘The evolution of theatre attendance in Italy: patrons and companies’, in V.M. Ateca-Amestoy, V. Ginsburgh, I. Mazza, J. O’Hagan and J. Pietro-Rodríguez (eds), Enhancing Participation in the Arts in the EU: Challenges and Methods, Cham: Springer, pp. 155–69. Castiglione, C., D. Infante and M. Zieba (2018), ‘Technical efficiency in the Italian performing arts companies’, Small Business Economics, 51 (3), 609–38. Corning, J. and A. Levy (2002), ‘Demand for live theater with market segmentation and seasonality’, Journal of Cultural Economics, 26 (2), 217–35. Fazzioli, R. and M. Filippini (1997), ‘Cost structure and product mix of local public theatres’, Journal of Cultural Economics, 21 (1), 77–86. Fernández‑Blanco, V., A. Rodríguez‑Álvarez and A. Wiśniewska (2019), ‘Measuring technical efficiency and marginal costs in the performing arts: the case of the municipal theatres of Warsaw’, Journal of Cultural Economics, 43 (1), 97–119. Gapinski, J.H. (1980), ‘The production of culture’, Review of Economics and Statistics, 62 (4), 578–86. Gapinski, J.H. (1984), ‘The economics of performing Shakespeare’, American Economic Review, 74 (3), 458–66. Gapinski, J.H. (1986), ‘The lively arts as substitutes for the lively arts’, American Economic Review, 76 (2), 20–25. Gapinski, J.H. (1988), ‘Tourism’s contribution for the demand for London’s lively arts’, Applied Economics, 20 (7), 957–68. Grisolía, J.M. and K.G. Willis (2011), ‘An evening at the theatre: using choice experiments to model preferences for theatres and theatrical productions’, Applied Economics, 43 (27), 3987–98. Grisolía, J.M. and K.G. Willis (2012), ‘A latent class model for theatre demand’, Journal of Cultural Economics, 36 (2), 113–39. Krebs, S. and W. Pommerehne (1995), ‘Politico-economic interactions of German performing arts institutions’, Journal of Cultural Economics, 19 (1), 17–32. Last, A.K. and H. Wetzel (2010), ‘The efficiency of German public theaters: a stochastic frontier analysis approach’, Journal of Cultural Economics, 34 (2), 89–110. Last, A.K. and H. Wetzel (2011), ‘Baumol’s cost disease, efficiency, and productivity in the performing arts: an analysis of German public theaters’, Journal of Cultural Economics, 35 (3), 185–201. Lévy-Garboua, L. and C. Montmarquette (1996), ‘A microeconomic study of theatre demand’, Journal of Cultural Economics, 20 (1), 25–50. Maddison, D. (2005), ‘Are there too many revivals on Broadway? A stochastic dominance approach’, Journal of Cultural Economics, 29 (4), 325–34. Marco-Serrano, F. (2006), ‘Monitoring managerial efficiency in the performing arts: a regional theatres network perspective’, Annals of Operations Research, 145 (1), 167–81. Moore, T. (1966), ‘The demand for Broadway theatre tickets’, Review of Economics and Statistics, 48 (1), 79–87. Neligan, A. (2006), ‘Public funding and repertoire conventionality in the German public theatre sector: an econometric analysis’, Applied Economics, 38 (10), 1111–21. O’Hagan, J. and A. Neligan (2005), ‘State subsidies and repertoire conventionality in the non-profit English theatre sector: an economic analysis’, Journal of Cultural Economics, 29 (1), 35–57. O’Hagan, J. and M. Zieba (2010), ‘Output characteristics and other determinants of theatre attendance – an econometric analysis of German data’, Applied Economics Quarterly, 56 (2), 147–74.

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Theatre  513 Seaman, B. (2006), ‘Empirical studies of demand for the performing arts’, in V. Ginsburgh and D. Throsby (eds), Handbook of the Economics of Art and Culture, vol. 1, Amsterdam: North-Holland, pp. 416–72. Taalas, M. (1997), ‘Generalised cost functions for producers of performing arts – allocative inefficiencies and scale economies in theatres’, Journal of Cultural Economics, 21 (4), 335–53. Throsby, D. (1977), ‘Production and cost relationships in the supply of the performing arts services’, in K. Tucker (ed.), The Economics of the Australian Service Sector, London: Croom Helm, pp. 414–32. Throsby, D.C. (1990), ‘Perception of quality in demand for the theatre’, Journal of Cultural Economics, 14 (1), 65–82. Throsby, D.C. (1994), ‘The production and consumption of the arts: a view of cultural economics’, Journal of Economic Literature, 32 (1), 1–29. Urrutiaguer, D. (2002), ‘Quality judgments and demand for French public theatre’, Journal of Cultural Economics, 26 (3), 185–202. Werck, K. and B. Heyndels (2007), ‘Programmatic choices and the demand for theatre: the case of Flemish theatres’, Journal of Cultural Economics, 31 (1), 25–41. Werck, K., M. Grinwis Plaat Stultjes and B. Heyndels (2008), ‘Budgetary constraints and programmatic choices by Flemish subsidized theatres’, Applied Economics, 40 (18), 2369–79. Willis, K.G. and J.D. Snowball (2009), ‘Investigating how the attributes of live theatre production influence consumption choices using conjoint analysis: the example of the National Arts Festival, South Africa’, Journal of Cultural Economics, 33 (3), 167–83. Willis, K.G., J.D. Snowball, C. Wymer and J.M. Grisolía (2012), ‘A count data travel cost model of theatre demand using aggregate theatre booking data’, Journal of Cultural Economics, 36 (2), 91–112. Withers, G. (1980). ‘Unbalanced growth and the demand for performing arts: an econometric analysis’, Southern Economic Journal, 46 (3), 735–42. Zieba, M. (2009), ‘Full-income and price elasticities of demand for German public theatre’, Journal of Cultural Economics, 33 (2), 85–108. Zieba, M. (2011a), ‘Determinants of demand for theatre tickets in Austria and Switzerland’, Austrian Journal of Statistics, 40 (3), 209–19. Zieba, M. (2011b), ‘An analysis of technical efficiency and efficiency factors for Austrian and Swiss non-profit theatres’, Swiss Journal of Economics and Statistics, 147 (2), 233–74. Zieba, M (2016), ‘Tourism flows and the demand for regional and city theatres in Austria’, Journal of Cultural Economics, 40 (2), 1–31. Zieba, M. and C. Newman (2013), ‘Organisational structure and managerial efficiency: a quasi-experimental analysis of German public theatres’, Homo Oeconomicus, 29 (4), 497–534.

FURTHER READING Seaman (2006) provides an overview of early studies on theatre demand. The more recent studies that relate to demand for theatre using richer data on price, income and quality are Corning and Levy (2002), Akdede and King (2006), Werck and Heyndels (2007), Zieba (2009, 2011a) and O’Hagan and Zieba (2010). Furthermore, while Zieba (2016) examines the effect of tourist flows on demand of theatres in Austria, Castiglione and Infante (2016) examine the rational addiction demand model for theatre. The important demand studies that use individual-level data and examine both socio-economic and socio-demographic characteristics of theatregoers are Lévy-Garboua and Montmarquette (1996), Borgonovi (2004), Ateca-Amestoy (2008), Willis and Snowball (2009), Grisolía and Willis (2011, 2012), Willis et al. (2012) and Baldin et al. (2018). As for theatre supply, O’Hagan and Neligan (2005), Neligan (2006) and Werck et al. (2008) examine the relationship between the subsidies and repertoire choice for theatres. Other useful recent studies that examine both the production technology and efficiency and/or total factor productivity for theatres are Last and Wetzel (2010, 2011), Zieba (2011b), Castiglione et al. (2018) and Fernández‑Blanco et al. (2019). While Krebs and Pommerehne (2005) provide an important discussion on institutional setting of public theatres with the focus on Germany, Zieba and Newman (2013) empirically examine how the legal form of public theatre affects the theatre outcomes in technical efficiency.

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57.  Video game industry Tylor Orme

INDUSTRY HISTORY While early computers were able to produce simple games that were played occasionally, video games as an art form did not emerge in popular culture until the 1970s. Arcade games, early computer games and the first generation of consoles became commercially available in 1972, and attracted immediate interest. It was not until video game consoles emerged as affordable options for gaming in the home, however, that the industry truly emerged commercially. Large arcade games and early home consoles, such as the Intellivision and the Commodore, dominated the market from 1973 to 1982. These systems, part of what is now known as the golden age of arcade gaming, defined a decade, peaking with coinoperated arcades generating as much as $7.7 billion dollars (Play Meter Staff 1982). This initial boom in commercially viable games created a glut of low-quality copycat consoles, and by late 1983 the video game market in the US, and much of the rest of the world, had collapsed (Donovan 2010). Out of this broken industry, a small Japanese company rose to prominence. Nintendo’s Family Computer (Famicom) was released in Japan in 1983, but did not make its way to the US until 1985. This system, renamed the Nintendo Entertainment System (NES) for its US release, revitalized the US gaming industry, providing affordable and highquality gaming in the homes of the average consumer. While the NES dominated the US and Japanese markets, Sega, Commodore and other companies produced consoles that achieved significant success in Europe and elsewhere globally. All told, by 1989 the market for home video games was over $2 billion. This series of consoles, often called the third generation (following the first generation arcade boxes, and second generation home consoles in the 1970s), established many of the conventions and game series that still dominate the market. In the 1980s and early 1990s, Sega and Nintendo further solidified their place as dominant powers in the industry with follow-up consoles Sega Genesis and the Super Nintendo Entertainment System (SNES). Both upgraded the hardware of the previous generation of consoles and paved the way for significant technical and artistic improvements. This same period saw Nintendo release the Gameboy, the first handheld game console to achieve commercial success. The era also saw the emergence of online personal computer (PC) gaming, including the earliest examples of what would eventually become the industrydefining Massively Multiplayer Online Role Playing Games (MMORPGs), games in which thousands of players were able to simultaneously interact in a shared world. In the 1990s and early 2000s a stable pattern emerged. Every five to eight years a new generation of consoles would be released, dramatically improving the quality of the hardware and providing the opportunity for a shake up in the sales dominance of the major companies competing to win the console wars. Sony and Microsoft joined Nintendo as 514

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Video game industry  515 the dominant hardware manufacturers of game consoles, with Sega declining console production, to instead be primarily a producer of software. This relatively stable cycle of hardware production still continues. While the industry has long been framed and discussed in terms of game consoles, PC gaming and mobile gaming have continued to play an integral role in the industry. Massively Multiplayer Online Role Playing Games have seen enormous popularity, particularly with Blizzard Entertainment’s World of Warcraft, and have generated enormous revenues not just in game sales, but in monthly subscription fees. With the launch of application (app) stores in 2008, mobile gaming also emerged as a major driver of revenue for the games industry, with recent industry figures showing that mobile games generate more revenues than PC and console games combined (Entertainment Software Association 2018). New technologies have also continued to shape the games industry. Websites such as Twitch now specialize in streaming videos of players, both professional and amateur, playing games for a global audience. E-sports have emerged, as games have developed professional leagues similar to traditional sports, generating nearly a billion dollars in annual revenues from ticket sales and advertisements. Virtual reality and augmented reality gaming have also been incorporated in increasingly sophisticated ways, and may soon emerge as key drivers of innovation in the industry.

STRUCTURE OF THE INDUSTRY The market for video game console sales is a perfect example of an oligopoly market structure. While the players in the industry have changed over time, the number of producers of consoles has stayed relatively stable, with currently three major producers: Sony, Microsoft and Nintendo. Competition between these rivals for market share is fierce, both in console sales and in attempting to secure games that will only be released for a single console, that is, exclusive titles. Software development involves a much larger number of firms of varying sizes. While there are large, horizontally integrated firms that produce multiple large games per year, such as Activision Blizzard and Electronic Arts, there are also an enormous number of medium to small-sized firms producing games. Game production companies typically handle the development and coding involved with producing games and they contract with a larger company for distribution. Some of the largest firms will serve as both producer and distributor for their own content, but many midsize firms rely on either major studios or third-party companies (for example, Apple) to distribute their content, both in physical stores and digitally. The most common categorization of production comes not at the level of studio, but in categorizing games. While the majority of video games are produced by relatively small teams and build their audiences by word of mouth and reviews, some games are designed to take advantage of massive budgets and huge marketing campaigns. These games, AAA games, are analogous to a blockbuster film in Hollywood. Budgets of these games can be massive, with those of some games reportedly well over $100 million (Fritz 2012). These games can require millions in sales to break even, and are considered to be large risks for game studios, albeit risks that often pay off handsomely, as many hit games sell well over 10 million copies.

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516  Handbook of cultural economics Most games that are not AAA titles would be categorized as being independent, or indie, games. Relatively small development teams usually produce these games, which are commonly published through third-party services. For console games, these independent games rely on large studios to provide publication. On PC and mobile platforms, however, a number of third-party services have emerged whose primary role is to publish and make available games. Steam, a client developed by Valve Corporation, has emerged as the largest publisher of digitally distributed PC games, with even some AAA titles available through its service. The Google app store and Apple app store serve similar roles in the mobile market.

BUNDLES AND PRICE DISCRIMINATION One of the key features of the video game industry is the near perfect complementarity of games and the devices on which they are played. Games require either a console, PC or smartphone to be played, and consequently these games have their success or failure directly tied to whether there is a large number of users of the platform the game will be released on. This high degree of complementarity between games and platforms creates opportunities for a large amount of strategic decision making by console and game manufacturers looking to increase profits. One major strategy is to bundle games with consoles at a combined price lower than if both products were bought individually. These bundles usually revolve around offering a new AAA release of a popular title bundled with a game console. These bundles usually only appear in the mid to late stage of a console’s life cycle, probably because hardware manufacturers are confident that customers will purchase their early product at full price without the need for a discount. Late in the console life cycle, however, bundles are quite common, with dozens of different bundles available for every major console since the early days of the NES (VGChartz.com 2019). This increasing willingness to reduce the cost of products late in their life cycle is also typified in the pricing strategies of game publishers. While there is a nearly universal price of $50–60 for a new release major game, the suggested retail price tends to decline significantly after the game’s release. Most games follow a typical pattern of a reduction to $40 when sales begin to decline, and often a further decline in price to $20–30 towards the end of the game’s life cycle. While some of this decline in price is almost certainly a result of competitive pressure from increasing availability of used copies of the game, there is also probably some incentive for firms to slowly reduce the price as a method of price discrimination. Although early adopters must pay the full price of $60, those willing to wait are not excluded from purchasing, but instead are offered a lower price later in the life cycle, thereby increasing the overall profit available to game studios and publishers (Liu 2010).

NETWORK EFFECTS AND GAMES AS SERVICE Given the necessity of a console or PC for running most major games, one of the key economic factors dictating the state of the video games industry is the presence of

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Video game industry  517 ­ etwork effects. Network effects are phenomena where an increased number of particin pants improves the value of a product. For video games, these effects come as a result of consumer benefits derived from having a large number of other players utilizing the same hardware to play games. These network effects can be both direct and indirect. The direct network benefits of using the console that has the highest number of users is primarily derived from the availability of more participants in multiplayer games (Gretz 2010). This effect has been dramatically magnified in recent console and game generations, as multiplayer games are increasingly popular, and online gameplay is now a main focus of many AAA titles. The indirect network effects are derived as a result of increased production, marketing and support for consoles with a large number of users. Toward the end of console generations the dominant console tends to receive significantly more exclusive releases than consoles that have not established large user bases (Clements and Ohashi 2005). These network effects result in intense competition to become the dominant console of each generation, as this dominant console has enormous benefits in the market. The console wars have become a defining part of the industry, as each console generation eliminates any network effect gained by the previous generation of consoles and allows the console producers to compete on a level playing field. The gains from this console generation are enormous, with scholars even concluding that customers prefer consoles that have lower hardware quality, as long as they generate large network effects (Gretz and Basuroy 2013). This creates a massive incentive that has led to huge marketing budgets and years of expensive research and development, with the goal of gaining a small edge at the initial release of a console generation that may snowball dramatically if a large network of hardware adopters can be created (Shankar and Bayus 2003). This focus on network effects at the console level has also shaped the way that games are developed and marketed, particularly in the past decade. As online gaming has become more feasible owing to faster Internet speeds, the industry has focused increasingly on online gaming and multiplayer games. While multiplayer games were feasible even during the NES era by having multiple controllers connected to the same console, the genre of multiplayer games has exploded in the wake of online multiplayer.1 Both competitive online games, such as Call of Duty or Battlefront, and cooperative online games, most notably MMORPGs, take advantage of network effects by allowing individuals to derive large value from a game only if it has a large player base. This creates a boom-or-bust system in which the value of the game is dependent on the number of sales it receives early in its life cycle, often necessitating an AAA release for any game with multiplayer options. Game developers are increasingly attempting to take advantage of these effects by designing games to encourage players to stay with games over long periods. Instead of producing games that are finished after a certain number of objectives are complete, the industry is designing games that evolve and grow after their initial release. Downloadable content (DLC) is now one of the defining characteristics of many games, allowing players to pay an additional fee to unlock new content not available at release (Grubb 2018). Even more recently, many studios have moved toward what is known as the games-as-service model, in which instead of producing a single game that is played and then finished, they produce games that have free or low-cost DLC every few months. The goal is to get players to commit to a game for years, instead of for just a few months. The new content

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518  Handbook of cultural economics is costly to the firm producing it, but ensures that the network effects of a large pool of users continue to be present over time. This large user base over a long period of time has increasingly been financed either by using DLC, or through a new strategy known as micro transactions. Micro transactions characterize a number of modern games, in which small in-game items, often cosmetic, are available for purchase using real currency. Charging anywhere from $0.25 to $10 for optional items and cosmetics currently generates enough revenue for the game industry that they are able to distribute games using the games-as-service model without having to charge for new content. Some games, such as the massively popular Fortnite, are free to play, with the entirety of their revenue generated through micro transactions and purchasable cosmetic items that have no influence on gameplay itself (Coldeway 2019).

DIGITIZATION AND STREAMING Together with increasing online play, new platforms have emerged which allow gameplay to be monetized, independent of the sale of games. Individuals broadcast videos of themselves playing games, often with commentary, on sites such as YouTube or Twitch, the latter of which is dedicated exclusively to video game streaming. Streamers generate revenues through advertisements, or by encouraging fans of their content to subscribe for a monthly fee. In the past five to ten years, streaming has emerged as a major source of revenue within the industry, with total revenues approaching $6 billion per year (NewZoo 2019). Of this amount, nearly $1 billion comprises streaming of e-sports content in which professional ‘athletes’ play games competitively. E-sports has emerged as a key driver for many major production studios, with some companies, such as Activision Blizzard, designing entire games around the idea of generating competitive leagues. The rising popularity of streaming has created numerous emerging areas of economic study that are still too new to have a significant academic literature. From a legal perspective, streamers exist in a grey area. They are making use of copyrighted material, but possibly in a way that falls within fair use provisions. To date, streaming networks enforce Digital Millennium Copyright Act (DMCA) shutdown letters from content holders who object to their games being streamed. As a consequence, there is no case law that has officially determined in what situations a streamer is violating the game creator’s copyright. Most game studios perceive streaming as a strong complement to their games, serving as a form of free advertising. There are a limited number of studios, most notably Nintendo, who perceive streamers as copyright violators, and who issue DMCA shutdown letters to all streams of their games. These production studios are concerned that streams may act as substitutes, with potential players unwilling to play a game, especially a narrative game, that they have already seen streamed. Evaluating the relative substitution and complementarity effects of streaming is of crucial importance to the industry in the long term.2 In addition to these legal and economic questions, there is also a rising sense within the industry that games are being designed with streaming in mind. Commentators contend that the recent rise of certain game genres, such as battle royale games or multiplayer online battle arenas (MOBAs), may be a result of game developers attempting to create games that are particularly suited to streaming and e-sports.

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NOTES 1. This practice is now known as couch co-op or couch competitive and has received a recent slight increase in interest. 2. As of the time of this printing, only preliminary working papers have analyzed this question, for example, Orme and Orme (2019).

SEE ALSO: Chapter 14: Creative industries; Chapter 26: Digitization in the cultural industries; Chapter 43: Orchestras; Chapter 46: Performing arts.

REFERENCES Clements, M.T. and H. Ohashi (2005), ‘Indirect network effects and the product cycle: video games in the U.S., 1994–2002’, Journal of Industrial Economics, 53 (December), 515–42. Coldeway, D. (2019), ‘Free to play games rule the entertainment world with $88 billion in revenue’, Tech Crunch, January, accessed 10 December 2019 at https://techcrunch.com/2019/01/18/free-to-play-games-rule-the-enter​ tainment​-world-with-88-billion-in-revenue/. Donovan, T. (2010), Replay: The History of Video Games, Hove: Yellow Ant. Entertainment Software Association (2018), ‘Essential facts about the computer and video game industry’, accessed 10 December 2019 at www.theesa.com/wp-content/uploads/2018/05/EF2018_FINAL.pdf. Fritz, B. (2012), ‘Star Wars: The Old Republic — the story behind a galactic gamble’, Los Angeles Times, 20 January. Gretz, R. (2010), ‘Hardware quality vs. network size in the home video game industry’, Journal of Economic Behavior and Organization, 76 (2), 168–83. Gretz, R. and S. Basuroy (2013), ‘Why quality may not always win: the impact of product generation life cycles on quality and network effects in high-tech markets’, Journal of Retailing, 89 (3), 281–300. Grubb, J. (2018), ‘Microtransactions, DLC make up 62% of Take-Two’s first quarter revenues’, VentureBeat, accessed 10 December 2019 at https://venturebeat.com/2018/08/02/microtransactions-dlc-make-up-62-of-take​ -twos-first-quarter-revenues/. Liu, H. (2010), ‘Dynamics of pricing in the video game console market: skimming or penetration’, Journal of Marketing Research, 47 (June), 428–42. NewZoo (2018), ‘Global games market report’, accessed 10 December 2019 at https://newzoo.com/solutions/ standard/market-forecasts/global-games-market-report/. Orme, T. and S. Orme (2019), ‘Semi-legal semi-substitutes: the impact of Twitch and Lets Play on game sales’, paper presented at the 2019 Mallen Conference on Filmed Entertainment, Emerson College, Los Angeles, CA, 8 November. Play Meter Staff (1982), ‘State of the industry report’, Play Meter Magazine, December, 42–6, 51–2. Shankar, V. and B.L. Bayus (2003), ‘Network effects and competition: an empirical analysis of the home video game industry’, Strategic Management Journal, 24 (March), 375–84. VGChartz.com (2019), ‘Global hardware sales data’, accessed 10 December 2019 at www.vgchartz.com/.

FURTHER READING For a history of video games, see Donovan (2010); the Entertainment Software Association (2018) provides data on the Acts relating to the computer and video game industry.

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58.  Welfare economics Mark Blaug

The arts are subsidized to some extent in every country in the world and yet the standard tools of welfare economics do not readily provide convincing arguments for public funding of the arts. Typically, economists base a case for public subsidies of a sector or industry on the existence of market failure, meaning a violation of one or more of the conditions for competitive efficiency. The most frequently cited examples of market failure are (1) externalities or spillovers, whether of production or of consumption; (2) economies of scale, such that unit costs fall as output increases; (3) public goods, that is, goods which are non-rivalrous in consumption and non-excludable in their benefits; and (4) endemic consumer ignorance about technically complex goods, for example, the demand for healthcare. When it comes to the arts, however, these are frequently supplemented by special arguments about: (1) equality of opportunity, according to which cultural goods are necessarily experience goods, that is, goods that are only demanded by those who have inadvertently experienced them; (2) the option value of a cultural heritage maintained at public expense across the generations; and (3) the straightforward, self-demonstrable merit of the arts independent of any instrumental value (see Chapter 1 in this volume). It does appear, therefore, that we need something more than standard welfare economics if we are going to talk meaningfully about an economic rationale for public funding of the arts. I label this ‘something more’ Pigovian welfare economics to distinguish it from standard Paretian welfare economics. Pigovian welfare economics is steeped in partial equilibrium analysis, the type of thinking that Alfred Marshall bequeathed to his leading disciple, A.C. Pigou. Paretian welfare economics, however, is steeped in general equilibrium theory, which descended from Leon Walras to his principal disciple, Vilfredo Pareto. Paretian welfare economics is orthodox welfare economics expounded in every modern economics textbook and is marked above all by its claim to analyse economic welfare without appealing in any way to the equality or inequality of the distribution of income among individuals.

PARETO OPTIMALITY Walras virtually invented general equilibrium (GE) theory in 1871. Its object was to demonstrate the possibility, and even the likelihood, of simultaneous multi-market equilibrium in a capitalist economy. Walras hoped to show, not just that GE is possible, but that it is good, but he never got much beyond the idea that voluntary exchange between two traders improves the welfare of both of them – otherwise, why would they have traded? What is true of bilateral exchange, Walras thought, will also be true of competitive exchange between a large number of traders if individual producers cannot themselves set prices, so that all consumers face identical prices for identical homogeneous goods. This is 520

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Welfare economics  521 precisely what happens in a state of perfect competition. Thus, as has been demonstrated: perfect competition maximizes social welfare. Pareto carried on where Walras left off. He, too, was convinced that GE is good for everyone but, as a follower of Ernst Mach in philosophy, he hated such behavioural assumptions as maximizing happiness, utility, welfare, or call it what you will, and he strenuously objected to interpersonal comparisons of utility (ICU) on the grounds that such comparisons cannot be made operational. Pondering these issues, he realized that the one circumstance that avoids ICU is a social state which meets with unanimous approval or at least with the absence of conflict in which one person is only made better off at the expense of another person. That is, we want a state which is so efficient that there is no surplus, no waste, no slack, ‘no such thing as a free lunch’, that can be handed to one person without taking it away from someone else. Is not perfect competition just such a state? Yes and no. It may leave some people rich and some people poor, but that will be the consequence of the individuals starting with unequal endowments in our economy – some people are born clever and some people have rich parents – but, given those endowments that are not themselves explained by GE theory (no theory ever explains everything), the GE model will grind out the rental prices of all the services of land, labour and capital as well as the prices of all goods produced with those services. Once we have somehow arrived at the end state of perfectly competitive equilibrium, it will be impossible to make one person better off without making another person worse off, except by interfering with the initial endowments of agents, say, by giving some people more inherited wealth. In this way, Pareto thought that he had finally found an admittedly narrow definition of the beneficial effects of competition that was totally free of those inherently objectionable ICUs; objectionable since there appears to be no objective way of resolving disagreements about such comparisons. The idea, only later named Pareto optimality, fell into oblivion as soon as it was announced, but was resuscitated together with Walrasian GE theory in the 1930s by John Hicks and Nicholas Kaldor. They extended the scope of Pareto optimality by arguing that any economic change, whether from a position of competitive equilibrium or not, was welfare improving if the gains to beneficiaries of that change were large enough to enable them, at least in principle, to bribe the losers voluntarily to accept the change. The existence of such potential Pareto improvements (PPI), as they are now called, still involves no ICU because it is grounded in the voluntariness of market exchange: only the judgements of gainers and losers themselves are involved in describing it as an improvement. In summary, Hicks and Kaldor (with prodding from Lionel Robbins), remained faithful to the Paretian conception of how an economist should study welfare economics. At first glance, the Hicks–Kaldor compensation test does seem virtually to pull a rabbit out of a hat, but further reflection soon shows that the achievement is semantic, not substantive. Why a potential and not an actual Pareto improvements? The moment we try to implement PPI by encouraging gainers and losers to negotiate a compensation payment between themselves, they will engage in strategic bargaining and, even without fancy game theory, it is easy to see that they may never reach an agreement. If the change has political significance, the state may then intervene to force the parties to agree – in which case we have said goodbye to our taboo on ICU. No matter how we slice it, in the end we cannot avoid (1) a qualitative judgement from on high of the size of the PPI – remember that there is no objective way short of a voluntary transaction to measure the magnitude of a gain

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522  Handbook of cultural economics or a loss to the parties concerned – and (2) an interpersonal comparison of that gain and loss to the respective parties. All that brings us back to Pigou, whose Economics of Welfare (1921) contained none of Pareto’s compunctions about ICU and was perfectly content to declare that a pound sterling taken from a rich man or woman by a progressive income tax hurts him or her less than the pleasure it gave the recipient of government expenditures. We have not quite reached the end of this story. Paretian welfare economics was furnished in the 1950s with Kenneth Arrow’s proof of what he labelled the first and second fundamental theorems of welfare economics. The first theorem demonstrates that every competitive equilibrium in a decentralized economy is Pareto optimal, which we have already discussed, and the second theorem demonstrates that a Pareto optimum can always be achieved via perfect competition if lump-sum taxes and transfers are feasible, so that, whatever are the original endowments of agents, we can still make everyone better off with a perfectly competitive economy. Immense pains are taken in every textbook of microeconomics to persuade readers of the validity of those two theorems. And they are valid – as mathematical exercises. Lump-sum taxes and transfers are changes which do not affect economic behaviour and even the most ingenious modern welfare economists have never been able to provide convincing examples of such things: for example, in order for them to be unanticipated and therefore not to affect behaviour, they would have to be randomly assigned to individuals or else made to reflect some personal non-economic characteristic, such as more consonants than vowels in an individual’s last name. I think we may safely conclude that the first and second fundamental theorems of welfare economics are just mental exercises without the slightest possibility of ever being practically relevant. They are what Ronald Coase called blackboard economics, an economics that is easy to write on a blackboard in a classroom but that bears no resemblance to the real world outside the classroom.

WHY IS COMPETITION GOOD? I contend that perfect competition is a grossly misleading concept whose only real value is to generate examination questions for students of economics. It is misleading because it breeds the view that economics is a subject similar to Euclidean geometry, whose conclusion may be rigorously deduced from fundamental axioms of individual behaviour plus some hard facts about technology. However, this does not imply that competition is bad. I believe, along with most economists, that competition is good, and the more competition the better; but if perfect competition is misleading and Pareto optimality almost impossible, what is the basis of this belief in the desirability of competition? It is based on a concept of dynamic efficiency, the results of market operations, and not the static efficiency of Walras, Pareto and the first and second fundamental theorems of welfare economics. The economy is never in a state of general equilibrium and is riddled with second-best departures from first-best perfect competition in the form of taxes, tariffs, monopolies, regulatory constraints, and so on. We name these departures second best, but they might as well be named tenth best or hundredth best because, once we are not in a first-best state, being near or far from first best has no meaning. That was precisely the point of Richard

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Welfare economics  523 Lipsey and Kevin Lancaster’s general theory of the second best. Given the existence of governments which levy taxes and collect revenues, it follows that we are never at first best. We know from Lipsey and Lancaster that we cannot prove that, say, the removal of a tax that prevents some business enterprise from pricing its products in accordance with their marginal costs of production – as they should in first-best competitive equilibrium – would improve social welfare; but that is ‘prove’ mathematically in the language of Paretian welfare economics, in the light of the maxims of static efficiency. It does not mean ‘prove’ in terms of dynamic efficiency: a particular tax might be statically inefficient but dynamically efficient in that it promoted the process of economic growth over time. Whatever the limitations of Paretian welfare economics, we are constantly faced with the problem of evaluating concrete proposals for taxing or subsidizing specific activities, including the visual and performing arts.

PIGOVIAN WELFARE ECONOMICS I label the welfare economics we employ for those purposes ‘Pigovian welfare economics’ because it owes to Pigou the willingness and even the eagerness to engage in rough-andready comparisons of the welfare of individuals endowed with unequal incomes. This is particularly pertinent in respect of arguments for public support of the arts because, as has been amply documented, the typical consumer of the arts is almost always richer and wealthier as well as better educated than the average taxpayer. If we stick to Pareto and avoid any and all ICU, we should, if we are honest, maintain a studious silence about subsidies to the arts. Pigou, however, emphasized, indeed overemphasized, the first of our four ‘market failures’, namely, external economies and diseconomies in production and consumption. In all such cases where the various production functions are interdependent rather than independent, the Pareto optimum welfare conditions must be replaced by Pigou’s golden rule of welfare maximization: equalization of marginal private and marginal social costs and benefits of all resources and all alternative uses; the national income is maximized if and only if this equalization is obtained. The touchstone of all of Pigou’s many policy prescriptions to deal with externalities is the transference of wealth from the rich to the poor; if this transfer does not diminish the growth of national income, it must, Pigou argued, improve social welfare. The reliance of such an assertion on ICU is too obvious to call for discussion. The stress on the growth of rather than the level of income reminds us of the inherently dynamic flavour of much of Pigou’s policy recommendations. By eschewing the very name of Paretian welfare economics with its debt to static GE theory, we are more liable to pay attention to intertemporal welfare arguments for, say, subsidizing arts education in schools or supporting heritage maintenance expenditure for future generations. Paretian welfare economics is grounded in the principle of consumer sovereignty: every individual is the best judge, and indeed the only judge, of his or her welfare. Without abandoning that principle entirely, it must be emphasized that the arts can only be appreciated by those who have experienced their consumption; that is, consumer sovereignty must be the sovereignty of the experienced consumer. If that is a value judgement, so are ICUs, and of course, the very notion of welfare economics without value judgements is an absurdity. No doubt labels are only labels and not arguments, but by adhering to the label of

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524  Handbook of cultural economics Pigovian welfare economics we advertise a distinct heterodox approach to the evaluation of arts spending.

RECENT DEVELOPMENTS IN WELFARE ECONOMICS Even Pigovian welfare economics, however, remains indebted to Jeremy Bentham and John Stuart Mill rather than to Aristotle and Kant, that is, to the eighteenth-century philosophy of ethics known as utilitarianism. As Amartya Sen (Sen and Williams 1982) has famously argued, utilitarian reasoning is grounded on three axioms: (1) welfarism, namely, that every social state must be evaluated only in terms of utility interpreted as personal happiness or the fulfilment of desires; (2) consequentialism, namely, that alternative social states must be appraised in terms of their consequences for utility rather than their moral imperatives like duty or obligation; and (3) the summing of utilities, that is, that the utilities of different persons must be appraised by simply adding them up arithmetically regardless of their distribution. These axioms ruled and dominated traditional welfare economics until the past decade or so. Recently, a different approach to social evaluation has appeared, under the umbrella term of eudaimonism. Eudaimonism takes its name from daimon, the Greek word for nature, and it denotes the belief that individual well-being or welfare consists, not in the maximization of personal satisfaction à la Bentham, but in fulfilling an individual’s ‘nature’. Eudaimonism, most famously expressed in Aristotle’s opaque words, is less an end-state definition of what it means to be happy than a definition of the active process of flourishing, a striving for perfection, a series of activities that culminate in the realization of an individual’s true potential. Nussbaum and Sen (1993), in a book about the quality of life, suggest that there is really no conflict between utilitarianism and eudaimonism, so that we can ‘have our cake and eat it too’. However, it seems to me that these two strands of ethics are very difficult to reconcile and, in terms of arguments for subsidizing the arts, eudaimonism is deeply subversive of the traditional scepticism of utilitarianism to any state intervention in the arts that is not grounded in clearly expressed market demand. According to eudaimonism, the very process of experiencing the arts is welfare enhancing and you cannot have too much of it. It is difficult to see how this approach would provide an arts administrator with a quantitative guide to a subsidy policy. The open-ended quality of eudaimonism is highlighted when we link it to Sen’s ‘capability’ approach. The capability approach stemmed originally, not from Aristotle, but from Sen’s concern with Third World poverty and the desire to provide the poor with basic needs, such as food, housing, medical care and schooling. However, Aristotle’s conception of welfare suggests that well-being requires much more than the provision of such essentials, calling in addition for personal autonomy, control of an individual’s own environment, access to social groups, family life, participation in political activity, and so on. Some have questioned whether the capability approach is actually operational, and have insisted on the need to list precisely the capabilities that the state ought to support. However, Nussbaum and Sen (1993) have resisted providing a precise list of essential functionings, arguing that such a list would infringe the very freedom of agents that is central to the capability approach.

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Welfare economics  525 On the one hand, Sen insists that individuals themselves should decide what is good for them. On the other hand, he is highly critical of utilitarianism, which derives its idea of social good precisely from what is good for the individual. Moreover, he underlines his conviction that capabilities are both intrinsically heterogeneous and incommensurable, so that the maximization of well-being is an activity similar to Herbert Simon’s concept of ‘satisficing’, that is, it is only achievable relative to constantly shifting levels of aspirations. Welfare economics in this approach does not achieve a complete ordering or ranking of different possible social states, and even if it does achieve a partial ordering, it is a fuzzy ordering and nothing like the precise quantitative ordering provided in the Benthamite tradition. Perhaps I have now written enough to suggest that it is by no means obvious how to answer the mundane questions of arts policy with the aid of the philosophy of eudaimonism. Suffice it to say that it points the way in almost direct opposition to standard welfare economics. It remains to be seen what policy implications follow from this approach.

SEE ALSO: Chapter 1: Application of welfare economics to the arts; Chapter 42: Non-profit organizations; Chapter 50: Public support.

REFERENCES Baumol, W.J. and C. Wilson (eds) (2001), Welfare Economics, vol. 1, Cheltenham, UK and Northampton, MA, USA: Edward Elgar, pp. xv–xliv. Blaug, M. (1997), Economic Theory in Retrospect, 5th edn, Cambridge: Cambridge University Press, pp. 570–95. Hennipman, P. (1995), ‘Hicks, Robbins and the demise of Pigovian welfare economics’, in D.A. Walker, A. Heertje and H. van den Doel (eds), Welfare Economics and the Theory of Economic Policy, Aldershot, UK and Brookfield, VT, USA: Edward Elgar, pp. 272–90. Nussbaum, M. and A. Sen (eds) (1993), The Quality of Life, Oxford: Clarendon Press. Pigou, A.C. (1921), Economics of Welfare, London: Macmillan. Sen, A.K. and A.B. Williams (eds) (1982), Utilitarianism and Beyond, Cambridge: Cambridge University Press. Sloman, J. (1997), Economics, 3rd edn, London: Prentice-Hall, pp. 316–57.

FURTHER READING For a comprehensive survey of the old and the new welfare economics, see the Introduction in Baumol and Wilson (2001). For a less demanding journey over the same territory, see Blaug (1997), and for really introductory textbook review of welfare economics as economists see it, consult Sloman (1997). Pieter Hennipman’s (1995) chapter attempts to purge welfare economics of all its subjective aspects. Whether successful or not, this introduces students to the classical Aristotelian conception of welfare, which throws a radical new light on the old question of state support for the arts.

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Index 3R (ratings, reviews and recommendations) systems 187–8, 426, 427, 466–71 Abbing, H. 52–3 actors 257–8, 340 adaptation rights 119–20 Adler, M. 187, 486–7, 488, 489 admission fees, museums 353 adverse selection 108–9, 305 advertising 73, 90–91, 131, 218–19, 325, 331–2, 422, 424 agglomeration and agglomeration economies 175, 176, 177–80 Alacovska, A. 52 anchoring effect 26 Anderson, C. 186, 221, 490 Aristotle 524 Arrow, Kenneth 107, 522 art export restrictions 481 international trade in 313 and marginal utility 486 motivations for buying 29–30 museums 264 understanding of 326 art dealers 29 changing infrastructure of art market 35–6 competition among 29–30 demand creation 33 market anomalies 34–5 segmenting art market 30–32 art fairs 35–6 art galleries 304–8 art market 30 anomalies of 34–5 and artificial intelligence (AI) 43 and artists’ resale right (ARR) 56–8, 59–63, 317 changing infrastructure of 35–6 demand creation 33 global 32, 61–2, 63 government intervention in 316–17 and non-profit organizations 384 segmenting 30–32 artificial intelligence (AI) 38, 44 and art market 43 and audio-visual sector 42–3 and broadcasting 76

data and data regulation 38–40 and music 41–2 role in making appropriate decisions 40–41 artists and art dealers 31–2, 33 and art galleries 304, 305–8 and consumption capital 486 creativity 146–8 cultural entrepreneurs 195 definition of 46–7 geographic clustering 149–50 income 47–53, 147–8, 200, 453 labour markets 46–53, 146–8 resale rights 56–63, 317 rights 66–70 statistics for 199–201 ArtistShare 160, 161 arts, rationale for public funding of 9–11 arts councils 242, 384, 499, 500 Ashenfelter, O. 24, 25 asymmetric information, see information asymmetry attachment 290–91 attendance and participation statistics 201–2 attendance (cultural participation) 401 auctions anchoring effects 26 auctioneers and accurate information 25–6 competition among auction houses 22–4 competition between auction houses and art dealers 32 declining price anomaly 24–5 English auctions 19–22 global market 32 public auction system 26–7 audiences 332 audio-visual sector, and artificial intelligence (AI) 42–3 Australia broadcasting 77–8 non-profit organizations 387–8 authoritarianism, and support for arts 456 authors 460 authorship and work-for-hire 122–3 awards and nominations 154, 219, 238 Bakhshi, H. 208–9 Bala, V. 314–15

527

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528  Handbook of cultural economics Baldin, A. 47 Banternghansa, C. 57 Bathelt, H. 176 Baumann, Robert 249, 250 Baumol, W.J. 4–5, 130–31, 193, 256, 415, 416–17, 509 Becattini, G. 175–6 Becker, G.S. 217, 218, 399, 400, 401 behavioural political economy 431 Belussi, F. 175 Benghozi, P.-J. 87 Benjamin, Walter 257, 258 Bertaux, N. 396 bias and quality 155–6 selection 188 Bille, T. 47, 48–9, 51, 52 biodiversity 171 Black, D. 432–3 blockchain 231, 367 Bohm, S. 209 Borowiecki, K.J. 150, 151 Bowen, W.G. 4–5, 256, 415, 509 brands 325 broadcasting 72 contemporary policy responses 77–9 digital revolution 75–7 economic analysis foundations 74–5 market failure 335 music 372 public 73, 78–9, 334, 379, 387 traditional 72–3 see also media economics Brooklyn Academy of Music (BAM) 256–7 Brooks, Diana 25–6 built heritage 279–85, 295 regulation 475–81 bundling 444, 516 bureaucrats 437, 455 business models 82, 91–3, 143 basics of 87–91 cultural industries 85–7 event cinema 260 music industry 85, 365 music publishers 372, 374 platforms 422, 423, 425–7 topicality of 82–5 buying art, motivations for 29–30 ‘buzz’ 176 BY Experience 254, 259 Calabresi, G. 67 Caldari, K. 175 cameras 257–8 Canoy, M. 459–60

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Canterbery, E.R. 316 Cantillon, R. 192 capability approach 524–5 capacity constraints, theatre 508 capital 168, 416 consumption 217–18, 311–12, 486 natural 170–72 social 212, 311 see also cultural capital Cassou, Jean 61 Castiglione, C. 504–5, 507, 510 casting, movies 340 Caves, R. 51, 140–41, 143, 360 censuses 199–200 charitable contribution deductions 385, 495–6, 497 choice experiments (CE) 96, 101 Christie’s 19, 20, 21, 22, 23, 24, 25–6 Chung, K. 487–9 cinema 342–3, 344, 372–3 and demand for theatre 505 event cinema 254–60, 419 see also movie industry cities 174, 243 clusters 149–50, 174, 175, 176, 180 Coase theorem 66, 75, 122, 123 collecting societies 59, 60, 361, 372 collectors, art 33, 34, 35, 43 and art galleries 304, 305–6, 307–8 Collins, R. 330 collusion, auction houses 24, 25–6 commercialization, creative industries 138 committees, decision-making in 432–3 common goods 298 competition benefits of 522–3 music industry 365 composers 150, 151, 374, 375, 396–7 concentration, market 131–3, 185, 335–6, 376 congestion costs 485 consumer market 322 consumer sovereignty 523 consumers attention 427 lack of information 452 and superstars 49–50 consumption 217, 400 books 461, 462–3 and cultural diversity 299 and digital technologies 223 homogeneity versus heterogeneity 218 legal and illegal 229, 230, 231 music 358–9 statistics 201

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Index  529 uncertainty and information asymmetry 218–19 consumption capital 217–18, 311–12, 486 consumption value 242, 243 contingent valuation (CV) 95–6, 210, 243, 246–7, 251, 268 application of 100 and cultural policies 101–2 developments in 101 pros and cons of 98–9 structure of a CV study 96–8 usefulness for cultural economics 99 contracts and copyright 107, 117 and inalienability 67–8 for information goods 106–7, 108, 109–14 joint venture 108 licensing 110–12 movie industry 141, 340, 342–3 music publishing 374–6 time and risk 110–12 and uncertainty 141 copying and independent duplication 119, 366 copyright 13, 52, 66, 107, 109, 288–9 authorship and work-for-hire 122–3 benefits of protection 116–17 collectives 361 contributory infringement 124–5 costs of protection 117 and creative industries 142–3 and creativity 148–9 current controversies 125–6 and digital technologies 7, 126, 143, 461 doctrines limiting protection 119–21 duration 123 emerging threats 231 indirect liability 124–6 infringement 121–2 licence pricing 15–17 and licensing 110–12, 118, 125 music and music industry 366, 372, 373, 374, 375–6 and risk 110–12, 113–14 separation of ownership 118 USA 112, 123, 126, 288–9, 518 vicarious liability 125, 126 video game industry 518 copyright management organizations (CMOs) 361, 372, 375–6 Corporation for Public Broadcasting (CPB) 379, 387 cost–benefit analysis 69, 70, 102, 169, 478 ‘cost disease’ 4–5, 256–7, 264, 298, 392–4, 415, 416–17, 418, 419, 453–4, 509

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costs 2, 129–34 built heritage 282 congestion 485 creative industries 140–41 festivals 263 for-profit and non-profit organizations 381 information goods 289 marginal 2, 12, 14, 116, 117, 129, 130, 132, 133, 289, 330–31, 352, 353, 394, 441–4, 446, 452 museums 352 orchestras 392–3, 394, 396 and prices 129–30, 132, 133, 417, 418 public funding to lower 452 reductions due to digitization 235–6 of regulation 479 sunk 12–13, 14, 130–31, 132–3, 140, 394 switching 469 of tax concessions 497–8 theatre 509 travel cost method 243, 247, 508 see also transaction costs Cox, R. 487–9 craftsmanship 297 creative industries 3, 137, 143 commercialization 138 and copyright 142–3 and digital revolution 7 economic characteristics 139–40 empirical research on 7–8 gate-keeping 141–2 industrial organization 140–41 measuring 139 policy support 208–9 creativity 145, 151 artists 146–8 cities 243 enhancing 148–51 and intangible cultural heritage (ICH) 300–301 music industry 358 criticism 154–6 and measurement of quality 238, 239 movie industry 344–5 crowdfunding 158, 367, 427 and cultural economics 163–4 empirical research 161–3 online platforms and models 158–61, 162, 165 outlook 164–5 crowding out 247, 248, 249 crowding theory 146 cultural and creative industries (CCIs) discourse 208

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530  Handbook of cultural economics cultural capital 168–9, 172, 212, 213 and cultural districts 177 and cultural participation 400–401, 402 and cultural value 169–70 and education 507 parallels with natural capital 170–72 cultural discount 221–2, 315–16 cultural districts 174–80 cultural diversity 171, 183–9, 221, 299–300, 469–71 cultural economic geography 210 cultural economics, as field of study 1 cultural entrepreneurship 193–6, 365 cultural events 211–12, 248, 250–51 evaluation and economic impact of 266–73, 276–8 festivals 211–12, 212–13, 262–4, 268 cultural expressions 185–8 cultural goods, definition and nature of 1–2, 168, 176 cultural heritage (CH) 279–85 and contingent valuation (CV) 100 regulation of, and information asymmetry 476, 477, 478 role of experts in decision-making process 437, 476, 477 tangible 294, 301–2 value of 209 World Heritage List (WHL) 295, 300, 301–2, 436, 480–81 see also intangible cultural heritage (ICH) cultural identity 184–5, 315 cultural indicators 203 cultural industries business models 85–7 cultural entrepreneurs 195 statistics for 197–8, 208 cultural participation 201–2, 399–405, 418, 419, 453 cultural proximity 313 cultural quarters 177 cultural reputation 11 cultural statistics 197–204, 208, 313 cultural value 168–70, 206 instrumental and intrinsic values 207–10 public good characteristics and socially constructed value 211–14 Cultural Value project (UK) 213 Cunningham, S. 208–9 customer relations 91, 92 customer service 325–6 data analysis techniques 41 artificial intelligence (AI) 38–44

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availability and quality (performance indicators) 412 Google Trends 266, 269–73, 276–8 growing importance of 336 marketing 323 de Boer, W.I.J. 251 deaccessioning 383 dealer-critic model, art 33 decision-making, in committees 432–3 demand 216–17, 223 aggregate 244, 385 creation, art dealers 33 and criticism 154 cultural discounting 221–2 and cultural proximity 313 digital disruption 223 estimation of, and consumption capital 217–18 for festivals 262–3 income elasticity of 217, 395–6, 506–7 influence of historical demand 150 international 311–12 and market failure 450–52, 453 museums 350–52 non-market 451 orchestras 395–6 performing arts 418 price elasticity of 217, 351, 395, 444, 462, 504–5 and pricing 442, 443–4 statistics 201 for superstars versus niches 219–21 theatre 504–8 under uncertainty and information asymmetry 218–19 democracy 455–6 direct 432–4 representative 434–6 derivative works rights 119–20 descriptive performance indicators (PIs) 411 differentiation (marketing) 325 digital convergence 333 digital economy and business models 82–7, 88–93, 143 and cost of production 129–34 and globalization 138 digital literacy 462, 463 Digital Millennium Copyright Act (DMCA) 126, 518 digital piracy 228–31, 235 movies 229, 231, 344 music 359, 366 digital technologies and digitization 7, 235–9 and art market 35 and broadcasting 75–7

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Index  531 and copyright 7, 126, 143, 461 and criticism 154, 155, 156 and cultural participation 400, 403–4 and demand 223 and diversity of cultural expressions 186–8 and event cinema 260 and heritage 284–5 impact on markets 322–3 Internet as threat 83 measuring cultural trade 198 and media 331–2, 333, 335–6 and movie industry 235–6, 343–5 and museums 350, 351 and music industry 359–60, 361–2, 365–7 and music publishing 376 and orchestras 395 and performing arts 415–16, 418, 419 and price-setting 446–7 and publishing 236, 237, 457, 459, 460–61 and reviews 219 and superstars 489–91 and video game industry 515, 516, 517–18 see also platforms disclosure paradox 107–8 discounting and discount rate 57, 69, 111, 169 disengagement (cultural participation) 404 distributional issues, public funding 9, 102, 283, 452, 453 diversification, product 186 diversity, cultural 171, 183–9, 221, 299–300, 469–71 donors 321, 382, 385; see also tax concessions Downs, A. 434 droit de suite 68, 317 dynamic agency theory 146 dynamic pricing 447 econometric models and studies 41, 42, 43, 249–51, 268 economic impact of the arts 207, 209, 241–2 conventional economic impact models (EIM) 244–6 cultural events 266–73, 276–8 errors 247–8 evaluation and recent developments 246–51 methodological approaches 243–4 types of impact 242–3 economic theory, and cultural economics 2–5 economies of scale 131–2, 140, 312, 314 and diversity 185 media 330–31, 335 movie industry 315–16, 344 museums 352 theatre 509 economies of scope 186, 314, 315, 331, 335

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education and artists’ labour markets 50–51 and book production 459–60 and cultural participation 401–2 and demand for theatre 507 efficient component-pricing rule (ECPR) 15, 16, 17 electoral competition 434–6 emotions, and creativity 151 employment, statistics for 198–9 enterprises, for-profit and non-profit 194 entrepreneurship 192–6, 365 equality of opportunity 10 eudaimonism 524 European Capitals of Culture, analysis of 250–51, 270–73, 276–8 event cinema 254–60, 419 Everitt, S. 246 experiments 268 experts, role in decision-making process 437, 476, 477 export restrictions, art 481 externalities 451, 453 beneficial 10 broadcasting 74–5 cultural events 211–12 geographic clustering/cultural districts 150, 177–80 heritage 280–81, 283 media 335 museums 350, 351, 353 Pigou on 523 façadism 283 Facebook 421, 422, 424, 426 fair use 66, 120–21 Felton, M.V. 394, 396 festivals 211–12, 212–13, 262–4, 268 Filimon, N. 488, 489 film industry, see movie industry filter bubble 188 financing 2 of broadcasting 72, 73 and contingent valuation (CV) 100 heritage 284 movie industry 340–41 museums 352–4 non-profit organizations 379–80, 381–3, 385–7 orchestras 393–4 performing arts 418–19 see also crowdfunding; public funding; subsidies Flanagan, R.J. 393–4, 395, 396 Florida, Richard 174, 210, 243

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532  Handbook of cultural economics formative assessment performance indicators (PIs) 408–10 Framery, N.F. 156 Framework for Cultural Statistics (FCS) 204, 208 France artists’ resale right (ARR) 59, 60, 61 European Capitals of Culture 271, 272, 276, 277, 278 music festivals 270 non-profit organizations 379–80 Francois, P. 314 Frank, J. 156 fraud 34–5 Frederiksen, L. 177–8 free-riding 6, 98, 431, 432 freedom of expression, economic approach 69–70 Frey, B.S. 46–7, 146, 383, 384, 437 Galenson, D.W. 148 Gapinski, J.H. 509 Garnham, N. 208 gate-keeping 141–2, 218–19, 236, 437 gender 322, 403 general equilibrium (GE) theory 520–21 geographic clustering, artists 149–50; see also cultural districts Germany artists’ resale right (ARR) 59–60, 61 theatre 504, 506, 508, 509, 510, 511 Giles, D. 488 Giorcelli, M. 149 globalization 84, 138, 299, 314 Gómez-Vega, M. 397 Google Trends data 266, 269–73, 276–8 government 430–32, 433, 434, 435–6, 437 accountability and transparency 478 interference 498–9 intervention, failure 454–5 and private donors 500 role of 321 Graddy, K. 24, 26, 27, 57 Grampp, W. 382–3 grants 52, 69, 335, 353, 354, 383, 498–500 Grokster 126 habit formation 507 Hall, Peter 174 Hamlen, W. 487, 488 Hansmann, H.B. 380, 381, 382 Hanson, G. 316 happiness 211 hedonic pricing/values 209, 242, 243, 281, 342 Heilbrun, J. 381

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Hellmanzik, C. 149–50 heritage, see built heritage; cultural heritage (CH); intangible cultural heritage (ICH) Herrero-Prieto, L.C. 397 Heyndels, B. 504, 505, 506, 508 Hicks, John 521 Hollywood 178–9, 315, 333 hyperchoice and hyperoffering 84–5, 88–9, 187–8 ICET (information–communication/ community–enjoyment and expression– transaction) model 404 ideas, and copyright 119 imperfect competition, and public funding 452 inalienability 58, 67–8, 283 income artists 47–53, 147–8, 200, 453 and artists’ resale right (ARR) 56–7, 58, 59 and demand for theatre 506 generation 454 superstars 485–6, 487, 489 taxation 497 income elasticity of demand 217, 395–6, 506–7 indicators, cultural 203 Indiegogo 160, 161 industrial districts 174, 175–6, 177, 179 industrial organization 140–41 industry structure, music industry 365 Infante, D. 504–5, 507 information art dealers 32 auctioneers 25–6 bias, contingent valuation (CV) 98 and crowdfunding 163 and cultural diversity 469–70 lack of, consumers 452 on policies 432 sharing 221 and superstar model 187 and value creation 89–90 information asymmetry 108 art market 34–5, 305, 307 and crowdfunding 163 and cultural districts 177 and demand 218–19 moral hazard 112–13, 146, 305, 354, 427 and online consumption 40 and political economy 431 and principal–agent model 354 and regulation of cultural heritage 476, 477, 478 information goods 106–7, 291–2 abundance 289–90 access 288–9

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Index  533 attachment 290–91 contracts for 109–14 intellectual property (IP) protection 107–9 properties of 287–8 information-pull and information-push 467 infrastructure, externalities 178 innovation cultural districts 178, 179 and cultural diversity 184–5 demand for 148 entrepreneurship and cultural entrepreneurship 192, 193, 194 and grants 500 and marketing 325 music industry 365 platforms 426 sunk costs 12–13 input–output models 244–5, 267 institutional cultural districts 177 institutions 431–2 externalities 178 and regulation 479–80 instrumental and intrinsic values 207–10, 212, 213, 242, 297, 478 intangible cultural heritage (ICH) 294 and creativity 300–301 and cultural diversity 299–300 policy interventions 300–302 potential disappearance of 297–8 safeguarding, economic approach 296–7 versus world cultural and natural heritage 295–6 intellectual property (IP) 13, 39, 107–9, 288–9, 302; see also copyright interest/pressure groups 436, 455, 477 intermediaries and intermediation 89, 92, 141–2, 186–7, 321–2 art galleries 304–8 music industry 361 music publishers 374 platforms 423, 467 international trade 311 demand for cultural goods 311–12 export restrictions, art 481 government intervention 316–17 media 335 movies 315–16 reproducible cultural goods 313–15 statistics on 198 supply of cultural goods 312–13 unique art 313 Internet, see digital piracy; digital technologies and digitization; platforms Internet Protocol television (IPTV) 231

M4863-TOWSE_9781788975797_t.indd 533

intrinsic and instrumental values 207–10, 212, 213, 242, 297, 478 irrationality 452 Islam, M.Q. 250 Italy artists’ resale right (ARR) 59, 60, 61 creativity 148, 149, 150 industrial districts 175–6 opera 195 theatre 504–5, 507, 509, 510, 511 Janeba, E. 314 Jenner, Kylie 491 Jensen, S. 51 job satisfaction 48 joint venture contracts 108 Kaldor, Nicholas 521 Kervern, G.Y. 87 key performance indicators (KPIs) 409 Keynes, John Maynard 244 Kickstarter 160, 161, 162–3 Kiva 160 Klamer, A. 212 knowledge, tacit 176–7 Kodi 231 Kremer, M. 13 Krueger, A. 489 Kumar, V. 210 labour and capital 416 market, externalities 178 productivity 298, 416, 417, 452, 453–4, 509 labour markets, artists 46 and creativity 146–8 definition of artists 46–7 future research 53 low average income and work preference model 47–50 public policy 52–3 role of education 50–51 working conditions 51–2 Lancaster, Kevin 523 Land, C. 209 Landes, W.M. 66 Lange, M. 394, 395 languages 297, 313 Lazrak, F. 209 Lazzeretti, L. 174 Lehmann, E. 489 Leontief, Wassily 244 Lévy-Garboua, L. 507 liability rule 67 libraries 409–10, 462, 463

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534  Handbook of cultural economics licensing 15–17, 67, 110–12, 118, 125, 361, 375–6 Lipsey, Richard 523 listing 282–3, 475, 477, 478 World Heritage List (WHL) 295, 300, 301–2, 436, 480–81 literacy 461–2, 463 lobbying 436, 499 localization economies 177–8 long-tail hypothesis 138, 186, 187, 221, 365, 469, 470, 490 Lorenzen, M. 177–8 Luksetich, W. 394, 395 MacDonald, G. 486, 489 machine learning 38–9, 41, 42, 43, 76 macroeconomics 3 majority rule 432–3 marginal cost 2, 12, 14, 116, 117, 129, 130, 132, 133, 289, 330–31, 352, 353, 394, 441–4, 446, 452 marginal revenue 441, 442, 443 marginal utility 311, 486 market concentration 131–3, 185, 335–6, 376 market entry 14, 140 art dealers 29, 36 and crowdfunding 165 market failure 77 and superstar model 486, 487 and technology 83 market failure 450–54, 520 adverse selection 108–9, 305 broadcasting 74–5, 76–7 free-riding 6, 98, 431, 432 media 334–6 quality 156 and regulation 334–5, 474 significance of 455 under-provision of cultural goods 211 see also externalities; information asymmetry market power, platforms 422, 427 marketing 320–27 markets, and institutions 432 Markusen, Ann 174 Marshall, Alfred 175, 176 Marvasti, A. 316 Matheson, Victor A. 249, 250 McGrath, T. 393, 394 McKeever, B. 385 media economics 329–31 key themes 331–3 regulation 334–6 median voter model 385, 432–3, 434 Melamed, D.A. 67 merit goods 7, 11, 75, 222, 452

M4863-TOWSE_9781788975797_t.indd 534

metadata 39, 40, 41–3 Metropolitan Opera (Met), live broadcasts 254–5, 258, 259, 419 micro transactions 518 microeconomics 2–3 Microsoft 514–15 Miller v. Civil City of South Bend (USA) 69 Montmarquette, C. 507 moral hazard 112–13, 146, 305, 354, 427 Moser, Petra 149 motion-picture industry, see movie industry motivation 146, 147 for crowdfunding 162, 164 for cultural entrepreneurship 193–4 movie industry characteristics of 315 contracts 141, 340, 342–3 cultural entrepreneurs 195 digital piracy 229, 231, 344 digitization 235–6, 343–5 government intervention in 317 international trade 315–16 measurement and comparison of quality 239 output and quality 237–8 output measures 236 prediction and artificial intelligence (AI) 42–3 risk 333, 340–41 sequels 219, 333 structure of 141 subsidies 382 theatrical distribution and exhibition 341–3 traditional movie production 339–41 USA 178–9, 314, 315–16, 333, 341–3, 382 multi-homing 423, 426 multi-sided platforms 421–3, 424, 425, 426 multipliers 244, 245, 247, 267, 451 Museum of Modern Art (MoMA) 242 museums 349–54, 380, 381, 382–4, 386 definition of 411 income generation, and loss of non-profit status 454 performance indicators (PIs) 409, 410, 411, 412 and private investors 437 special exhibitions 264 music and artificial intelligence (AI) 41–2 hyperchoice and hyperoffering 85 music festivals 262–4, 270 music industry basic characteristics 358–9 business models 85, 365 cost reductions due to digitization 235 cultural entrepreneurs 195

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Index  535 digital piracy 228, 229, 230–31, 235, 359, 366 ebbs and flows 359–60 functions and organizations 360–62 measurement and comparison of quality 238–9 output and quality 237 output measures 236 summary and outlook 367 superstar effect 487–9, 490 trends and topics in academic economic literature 362–7 music information retrieval (MIR) systems 41–2 music publishing 371–7, 458–9 Napster 126, 228, 235 National Endowment for the Arts v. Karen Finley (USA) 68–9 natural capital 170–72 natural experiments 268 natural heritage 295 natural language processing (NLP) 38–9, 42–3 Netflix 86, 231, 238, 260, 344, 423, 470–71 Netherlands access to research results 461 data availability 412 Giro d’Italia 251 reading and book consumption 462 network economies 76, 133 network effects 140, 221, 290, 335 art galleries 304, 306–8 libraries 463 platforms 91, 421–2, 424, 425, 426, 427, 468, 469 video game industry 516–18 network externalities 220, 314 network goods 289 networks 290–92 and diversity 185 Netzer, D. 498, 500 new art forms and organizations 10 Newman, C. 511 niche products 186, 221, 469, 470, 490 Nintendo 514–15, 518 Noah’s Ark problem 299–300 nominations and awards 154, 219, 238 non-market demand 451 non-profit organizations 194, 208, 379–88, 446, 454 non-use values 99, 171, 242, 247, 297 Noonan, D.S. 100 normative and positive economics 4–5 normative approach to regulation 74 NT Live 254, 255, 256, 257–8, 259, 260, 419 nudging 476

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Nunes, J. 490 Nussbaum, M. 524 O’Hagan, J. 400, 504, 505, 506 Oliver, J. 315 Olympic Games 249 online platforms, see platforms opera 195, 371–2, 453 as event cinema 254–5, 258, 259, 419 orchestral works 374 orchestras 392–7 Ordanini, A. 490 organizational infrastructure 89–90 outcomes, measurement of 409 output government, supply of 437 input–output models 244–5, 267 measurement of 236, 417, 477 and quality 237–8 Pareto optimality 353, 354, 430, 520–22 parity-pricing 15–17 parody 66, 121 participation 201–2, 399–405, 418, 419, 453 patents 13, 107 Patreon 160, 161 Peacock, A. 283, 284, 437 peer effects and peer crowding 150 performance indicators (PIs) 408–13, 417 performing arts 415–19 revenue sources, USA 386–7 performing rights 125, 149, 372, 373, 375 personalization 188 Piarowski v. Illinois Community College District 515 (USA) 69 Pigovian welfare economics 520, 522, 523–4 piracy digital 228–31, 235, 344, 359, 366 printed music 371 place, and marketing 324 platforms 421–7 and 3R (ratings, reviews and recommendations) systems 187–8, 426, 427, 466–71 crowdfunding 158–61, 162, 165 see also digital piracy; digital technologies and digitization political business cycles 435–6 political economy 430–32, 437 direct democracy 432–4 representative democracy 434–6 supply of government output 437 political expression 70 politicians 454–5 Pommerehne, W.W. 46–7, 384

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536  Handbook of cultural economics Porter, M. 175 positioning (marketing) 325 positive and normative economics 4–5 positivist analysis 74 Posner, R.A. 66, 69 prediction 40–41 and artificial intelligence (AI) 41–3 preferences 431, 432–4, 437 Prendergast, C.J. 146 present value 111 preservation and restoration, built heritage 282–4, 475, 476–7, 479, 480 pressure/interest groups 436, 455, 477 price agreements, books 462–3 price discrimination 13–15, 117, 381–2, 394, 426, 441–2, 443–6, 516 price elasticity of demand 217, 351, 395, 444, 462, 504–5 prices 12, 324 and artists’ resale right (ARR) 56–8, 59 auctions 19–27 and costs 129–30, 132, 133, 417, 418 and multi-sided platforms 422 orchestras 394, 395, 396 rock concerts 489 theatre 504–5, 508 and Value Added Tax (VAT) 496–7 pricing 99, 441–7 asymmetric 425 broadcasting 76–7 copyright licensing (parity-pricing) 15–17 efficient component-pricing rule (ECPR) 15, 16, 17 hedonic pricing/values 209, 242, 243, 281, 342 heritage 281 of information access 289 museums 353 Pareto optimal 353, 354, 521 platforms 425–6, 470 principal–agent model 155, 353–4, 381, 383, 395, 431 printed music 371–2, 373–4 printing 457–9 probabilistic voting models 434–5 product, definition of 323–4 production function 349, 352, 416–17, 509 productivity 298, 416, 417, 452, 453–4, 509 promotion 325 property rights 66, 67, 122, 283, 288 public art 210 public broadcasting 73, 78–9, 334, 379, 387 public funding 3–4, 5–6, 449–56 arguments for and against 450–56, 520 and cultural value 206, 208

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distributional issues 9, 102, 283, 452, 453 and economic impact studies 242, 243–4 economic justification for 69 government buyout of intellectual property 13 heritage 281, 282, 284 levels of 321 and market failure 450–53 media 334, 335 and median voter model 385 orchestras 393, 394 and output measurement 417 performing arts 418–19 pricing as alternative 99 and principal–agent model 354 statistics 202, 449–50 tax concessions 385, 450, 494–501 unconstitutional conditions 68–9 and under-provision of cultural goods 222 Value Added Tax (VAT) reductions 463 welfare analysis and rationale for 9–11 see also subsidies public goods 6–7 compensation for suppliers 12–13 copyrighted works as 116, 117, 123, 133 culture as 10, 99, 164, 211, 385, 451 global 280 heritage goods 280–81, 283 information/information goods as 110, 288 intangible cultural heritage (ICH) as 297 media output as 330–31 and non-profit organizations 380 properties of 11 public support for funding 449–56 public value 79 publishing 236, 237, 457–64 music 371–7, 458–9 quality art 305–6, 307 and criticism 155–6, 238, 239 and crowdfunding 164 and demand 218–19, 220 heritage 283 and income 485–6 and income generation 454 measurement and comparison of 238–9, 417 movies 342 music 359–60 orchestras 396–7 and output 237–8 and pricing 444–5, 447 theatre 505–6 video games 427

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Index  537 quality of life 211–12, 524 quantity discounts, tickets 445–6 Ramsey theory 15, 17 random utility theory (RUT) 212 randomized experiments 268 rational addiction theory 217–18, 222, 507 rational individualism 430 rationality 431, 434 Rauch, J.E. 314 reading 461–2, 463 recommendation systems 187–8, 426, 427, 466–71 redistribution artists’ resale right (ARR) 59–60 and non-profit organizations 380 by public funding 9 referenda 433–4, 435, 455 regulation 474 broadcasting 73, 74–5, 76, 78 built heritage 282–3, 284, 475–81 costs of 479 crowdfunding 165 of data 39, 40 decision-making process 476–8 economic effects of 478–9 intangible cultural heritage (ICH) 298 international 480–81 media 334–6 and monopoly characteristics 140 music venues 263 policy 479–80 soft and hard 282 tools 475–6 regulatory impact assessment (RIA) 477–8 reporting restrictions 78 reproducible cultural goods 312, 313–15 reputation, art galleries 305–6 resale rights, artists’ 56, 62–3, 317 inalienability and retroactivity 58 and place of transaction 61–2 and prices 56–8, 59 redistributive effects 59–60 transaction costs and collecting societies 59 reseller platforms 423 restitution of heritage goods 280 restoration and preservation, built heritage 282–4, 475, 476–7, 479, 480 revenue, business models 90–91 reviews 120–21, 154, 219, 344–5, 466, 467–71 rights 400 artists’ 66–70 see also resale rights, artists’ risk 110–14 and criticism 155

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crowdfunding 163 movie industry 333, 340–41 new products 324 risk aversion 25, 49, 57, 111–12 risk-taking, artists 49 Rosen, B. 255, 258 Rosen, S. 49, 187, 220, 485–6, 487, 489 Rushton, M. 68, 69 Sabel, David 255 Salaün, J.-M. 463 sales displacement, and digital piracy 228–30 Santagata, W. 176–7, 179–80 satellite accounts 203–4, 245 Schulze, G. 313, 433, 489 Schumpeter, Joseph 192–3, 194 Schuster, M. 408, 410, 413, 496 Scott, Allen J. 174, 178–9 Seaman, B.A. 209, 217, 246, 382, 403 Sega 514, 515 segmentation, markets 325 selection bias 188 self-employment 51, 52 self-publishing 236, 237, 460 Sellaband 160, 161 Sen, Amartya 524–5 sequels 219, 333 single-homing 423, 426 skewed income distribution 48–9 Smith, Adam 9, 192 social capital 212, 311 ‘social contagion’ effect 291 social media 77, 162, 209, 221, 332, 366–7, 421, 422, 424, 426, 459, 491 socialization 402 soft power 437 songwriters 374, 375 Sony 514–15 Sony v. Universal City Studios 125–6 Sotheby’s 21, 22, 23, 24, 25–6 South African Cultural Observatory (SACO) 213 special-interest politics 436 sponsors 321 sports events 248–50, 251 superstars 489 Spotify 231, 236, 361, 362, 366, 423, 426, 427, 467, 470 Srakar, A. 250–51 stage-to-screen and screen-to-stage models 257 stakeholder engagement 477–8 standardization of products 185–6 Stanley, D. 248 stars, as signal of quality 219

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538  Handbook of cultural economics state, see government statistics, cultural 197–204, 208, 313 Stephens, P. 494 Stigler, G.J. 217, 218 Stirling model (cultural diversity) 183–4 stream ripping 231 subjective well-being 211 subscription video-on-demand (SVOD) 344 subscriptions 73 subsidies and creative industries 139 for-profit and non-profit organizations 380, 381, 382, 384, 386 orchestras 394 theatre 504, 510–11 see also public funding substitutability, art 30 summative assessment performance indicators (PIs) 410 sunk costs 12–13, 14, 130–31, 132–3, 140, 394 superstars and superstar model 49–50, 133–4, 187, 219–21, 291, 365, 485–91 supply and business models 87–9 of cultural goods (international trade) 312–13 excess 52–3, 147, 323 festivals 263–4 of government output 437 and market failure 452–4 museums 352 surveys 200–201, 202, 210, 211, 269, 322, 403; see also contingent valuation (CV) sustainability and sustainable development 171–2 Sustainable Development Goals (SDGs) 412, 413, 462 Sutton, J. 131 Swedberg, R. 193–4 switching costs 469 Symbid 160, 161

television 72, 76 cultural entrepreneurs 195 digital piracy 229, 231 Internet Protocol television (IPTV) 231 measurement and comparison of quality 239 output and quality 238 Tepper, J. 58 theatre 503 cultural entrepreneurs 194 day-of-show tickets 445 demand 504–8 effect of event cinema on 258–9 as event cinema 254, 255–6, 257–8, 260 for-profit and non-profit 384 management 510–11 NT Live 254, 255, 256, 257–8, 259, 260, 419 organizational form 511 price discrimination 381 production and cost of 509–10 Throsby, David 48, 146–7, 212, 384, 505–6, 509 time and cultural participation 401, 402–3, 404, 453 and marketing 324, 327 and risk, contracts 110–12 time allocation model, household 401 time-series econometrics 268 Towse, Ruth 149, 371 trade barriers 316, 335 trade unions 263 trademarks 279 transaction costs art market 34, 35, 305 and artists’ resale right (ARR) 59 and copyright 118, 120, 122, 123, 125 crowdfunding 159 festivals 262 and property rights 66 travel cost method 243, 247, 508 Trindade, V. 314 two-part pricing 442–4, 446

talent 49, 220, 487 talent shows 156 tangible cultural heritage (TCH) 294, 301–2 Tanguy, M. 210 targeting (marketing) 325 tariffs 314, 335 tastes 156, 470 tax concessions 385, 450, 494–501 taxes, lump-sum 522 teams 184–5 technical efficiency (TE) 509–10 technology, see digital technologies and digitization

UK artists’ resale right (ARR) 57, 58, 59, 60, 61–2, 63 BBC 334 concert revenue 256 Cultural Value project 213 heritage financing 284 listing 282 music publishing 372, 373–4, 375 non-profit organizations 194 NT Live 254, 255, 256, 257–8, 259, 260, 419 uncertainty 141, 177, 218–19, 287, 290, 333, 340–41, 343

M4863-TOWSE_9781788975797_t.indd 538

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Index  539 unconstitutional conditions 68–9 UNESCO and cultural participation 399, 403 and intangible cultural heritage (ICH) 294–6, 299, 300–302 and performance indicators (PIs) 410 World Heritage List (WHL) 295, 300, 301–2, 436, 480–81 unique cultural goods 312, 313 urbanization economies 177–8 USA artists’ resale right (ARR) 56, 58, 62 copyright 112, 123, 126, 288–9, 518 digitization in cultural industries 235–6, 237–8, 239 economic impact models (EIM) 242, 244, 245–6, 248–9, 250 gaming industry 514 Metropolitan Opera (Met), live broadcasts 254–5, 258, 259, 419 movie industry 178–9, 314, 315–16, 333, 341–3, 382 museums 352 music publishing 375 non-commercial broadcasting 379, 387 non-profit organizations 194, 379, 380, 382, 385–8 orchestras 394, 396 superstar effect, music industry 487, 488, 490 tax concessions 385, 494, 496, 500 unconstitutional conditions 68–9 utilitarianism 524, 525 utility 212, 311, 400, 486, 521–2, 523 value of art 33 creation 86, 87, 88, 89–90 information goods 106 intrinsic and instrumental 207–10, 212, 213, 242, 297, 478 public 79 see also cultural value Value Added Tax (VAT) 269, 316–17, 463, 496–7, 501

M4863-TOWSE_9781788975797_t.indd 539

value chain 86, 89, 91, 93, 133, 332–3, 360, 361, 424–5 Van Long, N. 314–15 van Ypersele, T. 314 Vaubel, R. 148 Vecco, M. 250–51 veil-of-ignorance 121 venues 416 video games and video game industry 422, 426, 427, 514–18 voting 385, 431, 432–6, 455 wage rates 417 Waldfogel, Joel 230–31, 235, 343–4 Walras, Leon 520–21 Weinberg, B.A. 148 welfare economics 3, 520–25 instruments ensuring compensation 11–17 and policy 430 rationale for public funding of the arts 9–11 welfare effects digital piracy 230–31 international trade 314, 315 Werck, K. 504, 505, 506, 508, 511 West, E.G. 381 willingness to accept (WTA) 95, 96, 268 willingness to pay (WTP) 70, 95, 96, 97–9, 100, 102, 210, 243, 246–7, 251, 268, 296–7, 443, 444, 445, 446, 508 Willis, K.G. 506, 507, 508 wine auctions 19, 24–5 winner-takes-all model 219–21, 490 work-for-hire 122–3 work preference model 48, 147 working conditions, artists 51–2 World Heritage List (WHL) 295, 300, 301–2, 436, 480–81 Xiang, C. 316 Yermack, D. 380, 381 YouTube 86, 108, 422, 424, 425, 470, 490–91 Yule distributions 487–8 Zieba, M. 504, 505, 506, 508, 510, 511

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