Comparison: A Methodological Introduction for the Social Sciences 9783847421436, 9783847411468

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Comparison: A Methodological Introduction for the Social Sciences
 9783847421436, 9783847411468

Table of contents :
Comparison. A Methodological Introduction for theSocial Sciences
Table of Content
1. Introduction: choosing the question?
1.1 Starting from the key aspect
1.2 Further examples
2. Defining Comparison
2.1 The key questions
2.2 Classic thinkers
2.3 Modern theorists
3 Why compare?
3.1 The goals of comparison
3.2 Nomothetic objectives and generalizations
3.3 Explanation and understanding
3.4 What kind of theory should be adopted in political science?
4. What to compare: the basic units
4.1 Identifying the issue
4.2 Concepts and classes
4.3 Properties and variables
4.4 Operationalization
4.5 The “many variables, small N” dilemma
5. What to compare: space and time
5.1 Dimensions of comparison
5.2 Deciding the space
5.2.1 Case study
5.2.2 Other strategies
5.3 Defining the time
5.4 The problem of multicollinearity
6. How to compare: the key mechanisms
6.1 The available tools
6.2 Ogden and Richards’ triangle
6.3 The rules of conceptualization
6.4 The Tree of Porphyry
6.5 Classificatory strategies
6.6 Mill’s canons
7. How to compare: recent developments
7.1 In search of new rules for conceptualization
7.2 Process tracing
7.3 The configurational comparative method and qualitative comparative analysis
8. Beyond comparison: other research methods
8.1 Data collection and relations between variables
8.2 More about explanation, generalization and theory
8.3 Experimental and non-experimental methods
8.4 The statistical method
8.4.1 The number of cases
8.4.2. Logic
8.5 The historical method
9. Conclusions. The limits of comparison
Bibliographical References

Citation preview

Leonardo Morlino Comparison

Leonardo Morlino

Comparison A Methodological Introduction for the Social Sciences

Barbara Budrich Publishers Opladen • Berlin • Toronto 2018

All rights reserved. No part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording or otherwise) without the prior written permission of Barbara Budrich Publishers. Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages. You must not circulate this book in any other binding or cover and you must impose this same condition on any acquirer. A CIP catalogue record for this book is available from Die Deutsche Bibliothek (The German Library)

© 2018 by Barbara Budrich Publishers, Opladen, Berlin & Toronto ISBN eISBN

978-3-8474-2143-6 978-3-8474-1146-8

Das Werk einschließlich aller seiner Teile ist urheberrechtlich geschützt. Jede Verwertung außerhalb der engen Grenzen des Urheberrechtsgesetzes ist ohne Zustimmung des Verlages unzulässig und strafbar. Das gilt insbesondere für Vervielfältigungen, Übersetzungen, Mikroverfilmungen und die Einspeicherung und Verarbeitung in elektronischen Systemen. Die Deutsche Bibliothek – CIP-Einheitsaufnahme Ein Titeldatensatz für die Publikation ist bei der Deutschen Bibliothek erhältlich. Verlag Barbara Budrich Barbara Budrich Publishers Stauffenbergstr. 7. D-51379 Leverkusen Opladen, Germany 86 Delma Drive. Toronto, ON M8W 4P6 Canada Jacket illustration by Bettina Lehfeldt, Kleinmachnow – Editing: Alison Romer, Lancaster, England Typesetting: Anja Borkam, Jena, Germany

Table of Content Preface ............................................................................................................7 1. Introduction: choosing the question? .......................................................9 1.1 Starting from the key aspect .......................................................................9 1.2 Further examples ......................................................................................10 2. Defining comparison ................................................................................13 2.1 The key questions .....................................................................................13 2.2 Classic thinkers ........................................................................................14 2.3 Modern theorists.......................................................................................15 3. Why compare? .........................................................................................20 3.1 The goals of comparison ..........................................................................20 3.2 Nomothetic objectives and generalizations ..............................................21 3.3 Explanation and understanding ................................................................25 3.4 What kind of theory should be adopted in political science? ...................26 4. What to compare: the basic units ...........................................................35 4.1 Identifying the issue .................................................................................35 4.2 Concepts and classes ................................................................................36 4.3 Properties and variables ...........................................................................37 4.4 Operationalization ....................................................................................40 4.5 The “many variables, small N” dilemma .................................................43 5. What to compare: space and time ..........................................................46 5.1 Dimensions of comparison .......................................................................46 5.2 Deciding the space ...................................................................................50 5.2.1 Case study .......................................................................................51 5.2.2 Other strategies ................................................................................53 5.3 Defining the time......................................................................................55 5.4 The problem of multicollinearity .............................................................59 5

6. How to compare: the key mechanisms ...................................................61 6.1 The available tools ...................................................................................61 6.2 Ogden and Richards’ triangle ...................................................................61 6.3 The rules of conceptualization .................................................................65 6.4 The Tree of Porphyry ...............................................................................67 6.5 Classificatory strategies............................................................................71 6.6 Mill’s canons ............................................................................................82 7. How to compare: recent developments ..................................................86 7.1 In search of new rules for conceptualization ............................................86 7.2 Process tracing .........................................................................................89 7.3 The Configurational Comparative Method and Qualitative Comparative Analysis............................................................93 8. Beyond comparison: other research methods .....................................100 8.1 Data collection and relations between variables.....................................100 8.2 More about explanation, generalization and theory ...............................102 8.3 Experimental and non-experimental methods ........................................104 8.4 Statistical method ...................................................................................106 8.4.1 The number of cases ......................................................................108 8.4.2. Logic ............................................................................................108 8.5 Historical method ...................................................................................109 9. Conclusions. The limits of comparison.................................................113 Bibliographical References........................................................................117 Index............................................................................................................127


Preface This short book aims at offering a simple introduction to students interested in gaining an understanding of what the comparative method is and how it can be applied. Consequently, it is meant to be very simple and easy to be read and understood, but at the same time it intends to grasp and communicate the key meaning and usefulness of a method of empirical analysis, the comparison, which can be used at different levels and with different purposes. The work is a follow up of a previous book I published in 2005 and that later on was translated in Spanish (2010) and French (2013). Thus, there is a long history behind it. I had the first idea of writing a book like this in 1990, my aim being to deepen a reflection on comparison that I had begun together with Giovanni Sartori and a group of Italian colleagues, which brought to the publication of a jointly edited volume (Sartori and Morlino, 1991). However, the initial idea would have remained nothing more than an intention if I had not accepted an offer to teach a course on the “methodology of comparison” at the Institut d’Etudes Politiques in Paris for two years (1992 and 1993). For this I am still very grateful to Stefano Bartolini, who encouraged me to accept that offer even though I had too many academic commitments at the time. Of those two years there have remained my systematic lecture notes, a small booklet of handouts and, above all, wonderful memories of engaged, hardworking students. Although various Italian and foreign colleagues, who knew about these notes and handouts, asked me from time to time if they could see them and circulate them among their students, there were no further developments. But during the 1990s, a number of concrete experiences of comparative empirical research on the field made me more aware of the methodological problems that had to be addressed, and of the need to clarify them above all to myself in a simple manner. The completion of this intellectual task would not have yielded anything more than a “pious wish” if Francesco Raniolo had not offered to sort out the notes and materials himself in order to make a proper book of them. I am very grateful to him, because if I had not started from the new draft version he prepared I would never have managed to produce the work I submitted to the attention of students and colleagues. Stefano Bartolini, Francesco Raniolo, Cecilia Sottilotta and Claudius Wagemann kindly agreed to provide with additional suggestions on how to improve the book, and I would like to thank them for their patience and their very useful comments. I also would like to thank Giovanni Orsina and Daniela Di Cagno for their help in fine-tuning the differences with the historical method and experimentation. To the usual disclaimers about my responsibility about the mistakes in the book still have one additional remark should be added. If despite the help of colleagues and students I was so lucky to receive during all these years the 7

book still presents deficiencies and mistakes then I would be better to change job…although I should admit that it is too late. Rome, May 1st, 2017 Leonardo Morlino


1. Introduction: choosing the question? 1.1 Starting from the key aspect A preliminary part of any research purporting to be “scientific”, even in a broad sense, is a conscious analysis of the methodology. This is also the case when comparative interests are concerned. With the help of existing knowledge, that is, the literature we are aware of, we start by identifying and bringing into focus our interest in and curiosity about a certain topic. Then we pose a question, or research issue, about it. After that, we formulate one or more working hypotheses choose which countries to study and move on to survey and collect the essential data required to provide an answer to the issue by empirically testing the hypothesis or hypotheses. It is essential that explicit and clearly defined criteria are used when choosing the countries or areas on which to conduct research. In reality, the interest in a certain country is often preeminent and exists beforehand, and this on its own determines the topic of research. If so, the sequence outlined above (interest – research issue – working hypotheses – choice of countries – data to collect – empirical test of hypotheses) will be different, with the choice of country coming earlier. Furthermore, any component of a research project can actually come before another one. For example, if the principal goal is to test a hypothesis, this feature will influence every other aspect and choice. The sequence proposed above is therefore often an ex post rationalization. In a different perspective, one aspect influences another: a given research issue suggests which countries to choose; the availability of certain data suggests both the research topic and the countries to choose; and as just said above, an interest in certain countries might influence all the other aspects. If there were any need, this further confirms that the abstract sequence is actually shaped by a number of different aspects. At any rate, to begin with the first point, following a correct procedure entails immediate clarification, right at the start of the research, of exactly what question is being asked. But if the analysis is to be significant, it is very important that the question is of political relevance. An honest and self-critical appraisal of what has been done in political science since the Second World War requires an acknowledgement that in some cases undue prominence has been given to minor and relatively unimportant themes. This has happened everywhere, due both to a certain hyper-specialization and to the difficulty of tackling the real and most significant problems. In seeking to describe the irrelevance of some research, one author has called it the “tragedy” of political science (Ricci 1987).


To better understand what this means, an example can be given of a hypothetical research project. It is a widespread view that Italy has been beset in recent decades by a reduced capacity to govern, which can only be overcome by introducing adequate institutional reforms. The criticisms and proposals regarding this issue intensified above all after the 1994 elections. In relation to this theme, two questions must be asked: 1) Is the issue of sufficient political relevance to justify consideration? 2) How should it be studied?

There can be no difficulty in answering ‘yes’ to the first question. The research can then be tackled by exploring and analysing the role played by institutions, legal norms and electoral systems, and the way and conditions in which they have functioned in major Western democracies. A research design based on comparisons will therefore need to be devised, from which the most suitable lessons or “recipes” for Italy can be drawn. Box 1.1 In order to empirically test a one or more hypotheses, the first question to ask is if the issue is politically relevant. Clarification will then be required about how to go about studying it. Depending on the nature of the issue, the second step may entail choosing and comparing two or more countries.

1.2 Further examples The potentially great importance of comparison can thus begin to be appreciated. But as what interests us is more than merely a common sense view of comparison, it is worth looking at five further examples. 

   


First: Since the early 2000s democracy appears to have been established in various areas of the world, from Southern Europe to Latin America and Eastern Europe. But which democracies have consolidated and how can this process be defined and explained? Second: The year 1989 marked the beginning of the collapse of the non-democratic regimes in Eastern Europe. What profound political crises and changes have actually occurred in those authoritarianisms? Third: How can the delegitimation of parties and the fading away of party organizations in most democratic countries in different areas of the world be explained? Fourth: How did the 2007–2014 economic crisis affect European democracies? By leading to a reshaping of welfare assistance? If so, how? Or did it instead change the parties and party systems of the countries involved? Fifth: How has globalization affected democracies, directly and indirectly? What kind of political reactions did such a phenomenon trigger?

Many more examples could be given, but these should suffice to grasp that comparison is always particularly useful for achieving the goals that are set. This is the case: a) whatever the level of generality of the question (very high in the first and last examples, less so in the second and in the fourth); b) whatever the original interest – explanation (first and third example), knowledge (second example) or more explicitly application-based aims (fourth example); and c) whatever the point of view, more strictly national (third and fourth example) or referring to varyingly broad phenomena (first and fifth example). As regards the third example (the delegitimation of parties and the fading away of party organizations in most democratic countries), only careful comparative analysis will enable us to explain the decline in parties: it is only through comparison, in fact, that the similarities and differences between the different characteristics and levels of decline can be discerned, thus guiding the researcher towards a more in-depth analysis of the differences. As far as the fourth example is concerned (how the 2007–2014 economic crisis affected European democracies), here too only a broad investigation of the experiences of other countries will yield – mutatis mutandis – suggestions for the cases in which there is greatest interest. Basically, when addressing key aspects of the investigative process, such as the formulation of new research hypotheses and the explanation of a given phenomenon, comparison produces particularly significant results. And while other methods can also be employed to check empirical hypotheses (see chap. 8), the possibility of testing the formulated hypothesis is characteristic of the comparative method. Above all, when the issue at stake is explaining a certain phenomenon, and deciding which of several equally plausible hypotheses is the most reliable one, comparison alone, through the empirical testing of a number of cases, makes it possible to support a given hypothesis rather than another. Consider the third example on the delegitimation of parties and the fading away of party organizations. If only one case is examined, how will it ever really be possible to say whether the decline or resilience of a party can be explained by the force of ideology, the internal organization or relations within the party system, or other factors? There will be various hypotheses, all equally plausible, and the tendency will most likely be to regard them all as acceptable, and hence to superimpose them. By contrast, the further, decisive empirical support offered by comparison with other cases will point towards the most reliable hypothesis, to be preferred to the others. Comparing, therefore, is important. And it is important to the point that we often, implicitly or even unconsciously, make comparisons in our everyday activities. In this sense, comparing is a basic part of every activity of inquiry. But to stop here is to remain in the realm of the obvious, of the already-known, insofar as it is part of our own direct experience. The concern of this book, instead, is to establish a good general definition of comparison (chapter 2), to


understand the reasons for comparison, in other words, ‘why compare?’ (chapter 3), to bring into focus ‘what to compare’ (chapters 4 and 5), to specify the essential mechanisms and the spatiotemporal limits of comparison, that is, ‘how to compare’ (chapters 6 and 7), before moving on to compare the comparative method itself with other research methods (chapter 8), concluding with a realistic appraisal of the limits of comparison (chapter 9). Box 1.2 Whatever the level of generality of the question the researcher wishes to answer, whatever the original interest – explanation, knowledge or more explicitly application-based aims – and whatever the point of view, more strictly national or referring to varyingly broad phenomena, comparison is invariably very useful for achieving research goals.

Questions:   


What kind of questions does comparative research answer? Can you provide some specific examples of such questions? Why is comparison useful?

2. Defining Comparison 2.1 The key questions When trying to define comparison, the first and most obvious question to ask is what we are trying to define. In fact, comparison can be analysed from three different perspectives. First, it is a common way of thinking about and looking at the reality we live in. Indeed, it is probably the most recurrent one. As is well known, we compare all the time in our everyday lives: to check whether it is night or day, to distinguish one colour from another, and of course in more sophisticated intellectual operations, like comparing the behaviour or personality of one individual with that of another. This mode of comparison also influences our behaviour and usually shapes our individual actions, both private and public. The second perspective already belongs to the realm of the social sciences. In fact, a substantive part of sociology, political science or history is the fruit of comparison. This is what might also be called comparative sociology, comparative politics or comparative history. For example, it is evident that sections on electoral systems or parties or welfare policies in a handbook of political science are the result of a set of – usually descriptive – comparative analyses, But what is of interest in this book is a third perspective, one which examines all the different aspects and procedures of comparison as a method. How can it be defined? And, as will be seen in the following chapters, why, how and what should be compared? This third notion of comparison has a very long tradition in Western thought, going all the way back to Aristotle’s classification of political regimes. But what is of greatest interest here is the conscious use and methodological awareness of comparison, rather than the activity of comparison as such. To better explain this issue we need to build up a picture of it, starting from the answers to two key questions:  

What are the traditions of the comparative method? How can the comparative method be defined?

In one of his first books, Lettres Persianes (Persian Letters, 1721), Montesquieu offered an insightful analysis of his country – France – as viewed from an external perspective. In this work, and later on with his direct knowledge of a number of European countries, above all, the United Kingdom, the author was already not only engaging in comparison, but also beginning to reflect upon the comparative method, an aspect that would receive growing attention during the Enlightenment. In the same vein, Tocqueville (1835) demonstrated the increasing importance of observing what happens in other countries. Great importance was also attributed to the comparative method by the most eminent authors of classical sociology, such as Durkheim, Pareto, Weber and Mosca. 13

An attempt can be made to answer these two questions by clarifying how the different authors considered in this chapter – both the “classic” and the “modern” ones – emphasize one or more of the options regarding these two crucial questions: a) comparison as a logical procedure or as a conscious, explicit (but also implicit) and systematic research method; and once this second solution has been chosen, b) comparison as referring to the context of justification (or testing) of hypotheses or (also) to the context of discovery, that is, the refinement of concepts and the elaboration of new hypotheses. Box 2.1 When seeking to define comparison, two key questions need to be asked first: What are the traditions of the comparative method? And how can the comparative method be defined? Reference will then be made to how classic and modern authors answered them.

2.2 Classic thinkers In terms of methodological awareness we can begin our historic survey with Descartes and his school of logic (Arnould and Nicole 1662): Comparison is regarded as being between a “more” and a “less”, between a “better” and a “worse”. In this form of comparison, normative elements of judgment play a very important role. For John Locke (1690), comparison is the “foundation and origin of all mathematics and every demonstration and certainty”. It begins, then, to be presented as a testing procedure: when he talks of “comparing one idea with another with regard to extension, degree, time and place of the circumstances”, he makes the various aspects of comparison explicit, offering a much more complex analysis than that of Descartes. For Friedrich Hegel (Hegel, 1812–16), comparison, besides being a relationship between a “more” and a “less” (in the Cartesian tradition), involves a shift from equality to inequality, from similarity to difference and vice versa, in line with the thesis-antithesis procedure that lies at the heart of much of his philosophy. With Auguste Comte (1864) comparison is explicitly understood for the first time as testing, as a “moment of checking an inference empirically”. It is viewed both as the “comparison of neighbouring states in various parts of the Earth” (comparison in a spatial, synchronic sense), and as the “historic comparison of cognitive states of the same society” (comparison in a temporal, diachronic sense).


One or two remarks also need to be made about Alexis de Tocqueville, Emile Durkheim and Max Weber. Tocqueville (1835–40) was one of the first authors to scrupulously adopt the comparative method, as was quickly pointed out by Mill in his comments on Democracy in America. Tocqueville’s comparative strategy is fairly complex. He juxtaposes different forms of comparison: a comparison of two nations in which different causes are associated with different effects; an intra-national comparison where, likewise, different causes are associated with different effects; an intra-national comparison with the addition of the temporal variable; the resort to a third case to reinforce the comparison between the first two; and the identification of shared characteristics and of differences to validate explanations he sustains. Durkheim (1895), on the other hand, focuses above all on classification as the principal aspect of comparison. The method of concomitant variations is the comparative procedure he employs most often, although he resorts to other logical procedures such as deduction, analogy, imaginary experiment and, on occasion, the method of differences theorized by Mill. Although he did not explicitly deal with comparison in his methodological writings, Max Weber (1922) turned to it in relation to a vast number of historic or everyday “processes” that are homogeneous in very disparate ways, but different on a decisive point, that is, the reason for or the “occasion” on which the investigation is taking place. Weber began to develop an analysis regarding the procedures of comparison (and other methods). There is, then, a profound difference between Durkheim and Weber, just as there are differences between these two authors and Tocqueville. Weber prefers the method of differences and concordances, while Durkheim prefers that of concomitant variations, and Tocqueville the much more complex strategy described above. In any case, all three draw on the rules of comparison devised by John Stuart Mill (1843), who can be considered one of the scholars who uses comparison in the context of discovery as well (see chapter 6). Box 2.2 While comparison had already been discussed by Descartes, Locke and Hegel, it is with Comte that it is first explicitly understood as being about testing an inference empirically. Durkheim, Weber and Tocqueville all draw on the rules devised by Mill to use comparison within the context of discovery as well.

2.3 Modern theorists No major steps forward have been taken since the eminent authors cited in the previous section, either in terms of the use of the comparative method or the


definition of the concept. There have just been clarifications and specifications regarding a number of aspects. H. D. Lasswell (1968) equates the scientific method with the comparative one, in that for him the scientific method is effectively and inevitably comparative. He affirms, in fact, that “an independent comparative method seems redundant”. S. Eisenstadt (1963) argues that comparison is not a distinct method, but rather “a particular attention for the macro-dimensional, interdimensional and institutional aspects of society and of social analysis”. There is a shift in focus, then, from an analysis of the method to an analysis of the content. When dealing with certain issues at a macropolitical and institutional level, the only way of doing so is to use comparison. G. A. Almond (1956), one of the most influential scholars in political science, simply reiterates the claim of his mentor, Lasswell, that comparison, as a scientific method, is the key element of political science: “If it is not comparative it is not political science”. In other words, it is both a testing method and a useful way of discovering new aspects. One might, however, object that there is also scope for a non-comparative political science, even while recognizing that it is absolutely essential for the themes indicated by Eisenstadt, and therefore that in those areas – but not in others – Lasswell and Almond are right. According to Giovanni Sartori (1971, 8), “comparison is a method for testing our generalizations, predictions or laws of the ‘if… then’ kind”. It is not a strong testing method: there are other, stronger methods, starting with the statistical one. However, the statistical method may run up against effective limits of application (see chapter 6) in political science, while this happens far less frequently in comparison, the distinct significance of which remains that of being a “scientific testing method”. Sartori formulated his definition in the cultural and scientific context of the 1960s, and the issue of a search for generalizations or laws was influenced by the methodological approach of those years. But comparison serves not only to test hypotheses (context of justification); it can be used to formulate new ones (context of discovery). So why did the authors from the classical tradition (but contemporaries as well) emphasize testing above all else? According to Sartori, the distinctive aspect of comparison, which brings us closest to “scientific knowledge” (then at the centre of the debate about the social sciences), is precisely testing. This can be explained if it is recognized that the definitions considered privilege the activity of scientific research, insofar as it is an activity that highlights relations between variables (and especially cause-effect relations): all efforts are directed towards understanding, reinforcing and pinning down these relations. It is clear, then, why the most important phase is not discovery (the creative phase), but testing, in other words, justification.


Abraham Kaplan (1964), regarded as an exponent of methodological orthodoxy, held that giving an exhaustive explanation of a phenomenon is equivalent to formulating a prediction. From this perspective, it is not hard to grasp the connection between explanation, prediction and law: predictions are laws insofar as they are explanations of past phenomena that are expected to be repeated in the future. In the mid 1970s, Arend Lijphart (1975, 164) defined comparison as the “method of testing hypothesized empirical relationships among variables (…) in which the cases are selected in such a way as to maximize the variance of the independent variables and to minimize the variance of the control variables”. The influence of N. J. Smelser can be discerned in this definition, with the relative emphasis on the statistical method as a heuristically more “powerful” tool for the social sciences (see chapter 7). It is worth examining this definition in detail: 1) Comparison is seen as a testing method (Lijphart continues Sartori’s line of argument): while not denying the importance of the context of discovery, emphasis is placed on the context of justification; comparison is thus the method that enables us to choose between equally plausible hypotheses; 2) The reference is to “hypothesized empirical relationships among variables”: No mention is made of generalizations or laws, but of hypotheses that could relate to several cases and which we test empirically, identifying, on the basis of reasoning, causes and effects; testing is therefore carried out on the relationships, or rather, on the hypotheses that certain specific relationships exist; 3) The second part of Lijphart’s definition concerns the comparative procedure. Here it is important to distinguish above all between: a) independent variables (the causes); b) dependent variables (the effects); c) intervening variables or control variables.

“The cases are selected in such a way as to maximize the variance of the independent variables…”: increasing the number of cases will inevitably result in greater diversity, that is, an increase in the way in which the same phenomenon presents itself with respect to the same property (variance). If, notwithstanding the increase in the number of cases, and hence the maximizing of what are considered to be the causes, the hypothesized cause-effect relationship is not invalidated, it will be possible to affirm that the relationship has been tested, and that relationship will therefore be a stronger one. This will take us back towards the elaboration of generalizations, previously refused. It is, however, also necessary to “minimize the variance of the control variables”: by increasing the cases, and changing the way in which the cause presents itself, other factors enter into play; these can act as concomitant causes of the final effect, disturbing the purity of the cause-effect relationship we are trying to establish. We must, therefore, try to reduce them to a minimum, that is, to minimize the variance. For example, if we are interested in studying the voting behaviour of a given social category in a multi-ethnic society, and we 17

believe there is a relationship between voting behaviour and place of residence (outlying areas or urban centres), we will have to choose outlying areas or cities that are homogenous in terms of size and ethnic composition (thereby eliminating two intervening variables). In the 1980s, the neo-positivist premises still present in the work of the authors that have been briefly mentioned seemed to give way to different positions, sometimes described as “constructivist”. In this new context the emphasis on comparison as a control method was played down. So, for example, Alberto Marradi (1982, 13) argued that comparison is a “mental operation to compare two or more distinct states, one or more objects, in relation to the same property”. In this definition, both the focus on testing, and on generalizations, predictions or laws have disappeared. Around a decade elapsed between the definitions by Sartori and Lijphart and this one by Marradi: in this period of time scholars gradually lost faith in the effective possibility of arriving at generalizations, predictions or laws of any kind. A certain methodological ‘relativity’, a greater degree of latitude regarding methodological positions, gained ground instead. A deep gulf thus opened up between scholars. On the one hand, there were those who still stressed the importance of comparison in the context of discovery: even if the goal is explicative, they sustained, such explanations do not necessarily have to be general (applicable to more than one case), far less predictions or laws. They need only be partial explanations, holding good for the single issue being studied – the “local theories” of Boudon. On the other hand, there were those who used comparison in terms of justification, setting the formulation of generalizations, predictions or laws as an objective. If the goal is explicative in nature, the research must move in that direction, something which did effectively happen in fields like electoral studies or policy studies. This rift is aptly described by Almond (1990), who spoke of political science as “a divided discipline”. Subsequently, Sartori himself wrote that “testing has not been talked about for years, while, all things considered, testing is important” (1991, 24–28). His position softened, then: he no longer spoke of generalizations, predictions or laws. But in order to see which is the right hypothesis (taken from the context of discovery), one must necessarily test it. Following this brief survey, the following definition may now be proposed: comparative politics is a method for testing hypothesized empirical relations between variables in different cases. Usually, the cases pertain to different national contexts, but may also be units or subunits of the same national context, for example when comparing regions or other types of local government within the same country. This definition does not deny the importance of comparison in the context of discovery: The questions and the issues themselves can only be tackled if different realities are compared, but the possible hypotheses are extremely varied. This definition focuses on the most relevant aspect of the 18

comparative method: the possibility of testing the hypothesized relations empirically. In other words, the comparative method is empirical testing plus explanation. This is still a preliminary general definition, and will be followed by a second one in chapter 3, which will examine what to compare. But we have moved away from the view of comparison as a logical procedure recurring at different levels, from common sense to a more specialized level, in order to begin to see what comparison is in a specialist sense. So what, from a specialist’s point of view, are the problems to address, the choices to make and the procedures to adopt when dealing with research issues like the ones mentioned in the introduction? To answer these questions, the best way to proceed is to step into the shoes of a researcher and to ask the three classic questions about comparison: Why? What? How? For the purposes of this work the answer to these three questions will help us to build up a picture of the “minimum knowledge” of the comparativist, namely the crucial aspects of comparison that need to be taken into account. These questions are important for students, scholars and more generally for all analysts of political and social reality. The answers to these questions concern all practitioners of the social sciences. Political science does not have its own comparative logic, with separate ones for sociology, for economics and the other social sciences. The choices and decisions faced by scholars from one sector of the social sciences will also be pertinent to or assumed by other social scientists as well. When comparing, the problems of the explanation and analysis of time are not exclusive to political science and uninfluential for the other disciplines. Indeed, the very investigation of certain developments in comparison, principally conducted in political science, also suggest the reciprocal influences between the different social disciplines. Box 2.3 Following in the footsteps of classic authors, contemporary theorists such as Lasswell, Eisenstadt, Almond, Sartori, Kaplan, Lijphart and Marradi have provided clarifications and specifications about the use of the comparative method and the definition of the concept. In particular, Lijphart’s definition of the comparative procedure identifies: a) independent variables (the causes); b) dependent variables (the effects); and c) intervening variables or control variables. In the light of the contribution of these authors, comparative politics can be defined as a method for testing hypothesized empirical relations between variables in different cases.

Questions:       

What are the traditions of the comparative method? How can the comparative method be defined? What was the contribution of the “classic” authors? What was the contribution of the “modern” authors? What are independent variables? What are dependent variables? What are control variables?


3 Why compare? 3.1 The goals of comparison A start can be made on answering the question posed by the title of this chapter by looking at the key tasks performed by comparison. As Finer (1954) stressed, there are at least three: a) cognitive b) explanatory c) interventionist

The first goal is very simple: the realities of various countries are investigated or analysed in order to better understand the phenomena involved. The aim is descriptive, without any other kind of ambition. The second one is explicitly explanatory: research is conducted on other countries and their related phenomena in order to come up with explanations which, as they are common to different cases and result from similarities and differences between them, are considered more robust than ones that do not resort to comparison. Above all else, in fact, the analysis of more than one case permits the testing of different explanations and the establishment of more cogent and well-argued grounds for preferring one explanation (or explanations) to others. In this sense, comparison serves to test equally plausible hypotheses and to single out the most convincing ones, or even to formulate new and more in-depth ones. The third goal is interventionist: when dealing with political problems and the policies best suited for tackling them, a study can be made of similar problems in other countries and the steps taken to solve them. Strictly speaking, the goal here is both explanatory and interventionist: in order to propose solutions it is important to have a fairly precise idea of the impact of certain policies in other similar or perhaps even different contexts. The first and second goals are also common to other disciplinary fields, while the third pertains to that of institutional reform and public policy, and for this reason recurs more frequently in the domains of interest to us here. Given the importance of the explanatory goal as a reason for comparing, it is worth illustrating. If we are just concerned with one country, be it Italy, the United Kingdom, the USA or whatever, why resort to comparison in the first place? The answer is evident: without an awareness of the political realities of other countries, it would not even be possible to formulate a relevant issue relating to the country that interests us. For example, in Norway and Sweden the social democratic party has been the dominant or majority party since the end of the Second World War, with the communist party garnering barely 1% of votes; in the United Kingdom the communists have never been more than small groups of isolated extremists, and so on. In the United States, despite 20

acknowledgment of the important role played by socialist parties in Europe, nothing similar has ever managed to establish itself there. It is clear, then, that the question itself and its possible political relevance derive from comparison with the reality of other nations. What is more, without comparison it would not be possible to provide an appropriate answer to our question either. Referring to the example of the Italian Communist party, it might be hypothesized that the Italian communists were stronger than the socialists because of their specific and structured ideology, which attracted the electorate and acted as a force of aggregation. This hypothesis appears reasonable and plausible. But if we look outside the Italian context it is immediately apparent that it cannot be correct: a similar ideology was adopted by communists in other countries as well. An alternative argument is that the role played by the Italian communists during the Resistance determined their subsequent prominence. This answer also seems to be basically plausible. But again we only need to examine another country, like France, where the communists had a very important role in that same historic period, to realize that this is not a very convincing hypothesis either. Clearly, then, comparison can serve to test and select from among equally plausible hypotheses or explanations. It can also, as previously said, be used to suggest new and more in-depth ones. For example, examining France shows how the run-off (double ballot) electoral system, complemented by the semi-presidential regime with the direct election of the head of the state (the two key reforms approved with the Fifth Republic), are much stronger explanatory variables. This suggests the need to look at the salience of the highly proportional system complemented by a parliamentarian democracy in Italy. Accordingly, it will be possible to reconsider some traditional analyses of the Italian case, which focused on the variables mentioned above, such as ideology and its role during the Resistance. Box 3.1 Comparison may have cognitive (information gathering), explanatory (testing of different hypotheses) or interventionist (generating actionable knowledge) goals.

3.2 Nomothetic objectives and generalizations The primary objective of comparative research is to provide an explanation for a given phenomenon, that is, to establish a causal connection between the states of one or more property or variable. From here to generalizing (as an explanation applicable to a number of cases) is but a short step: so what stance should be taken in relation to laws-generalizations? It might be that a generalization will be reached, but that would only be a further result and not the primary 21

objective. The author who best shows this is Raymond Boudon (1984), who sums up his thesis in a formula (ibid, 44ff.): M = Mm S M' where: M = phenomenon to be explained Mm = set of individual actions S = situation of the actors M' = data defining the situation

The formula is simple and, I believe, effective: the phenomenon requiring explanation is clearly the result of the interaction between the three elements considered: the set of individual actions, the situation in which the actors find themselves and the data defining the situation. What Boudon wants to show is that the search for laws, generalizations or, more simply, regularity, is not the primary objective of analysis. The eventual generalization that might be attained is just a secondary aspect. At this point, however, a number of questions need to be asked: 1) Why, despite what has been said, has there been a (quite insistent) search for laws in the social sciences, political science included? 2) If nomothetic knowledge exists, how should it be used? 3) If the goal is not nomothetic knowledge, what is the ultimate goal of our research?

Boudon offers good answers to these three questions as well, and it is worth looking at what he has to say. Why has the search for laws continued for so long? a) “The search for laws is the result of the influence of the naturalistic conception of the social sciences” (ibid, 101). The model of the natural-physical sciences has long been imitated in the social sciences, particularly in economics. Many years ago (1976) Almond showed how the dominant criteria for doing research came from the naturalphysical sciences. Yet he himself noted how, after the discoveries of Einstein, Heisenberg and others, those sciences had shed their rigid oversimplification, traces of which remained, however, in the way in which the social sciences had absorbed the very notion of science. b) “We are often only too ready to reduce the aggregation of individual actions to a mere adding up.” Boudon (1984, 77) himself gives an example: “If every consumer wants less of a product, the overall demand for it will fall. If everyone is more discontented, the result is not the same kind of increase in collective discontent, for the ‘sum’ of individual discontents is one thing, and the collective expression of discontent is another.” The relation between micro and macro, individual and collective, is a very delicate one for the social sciences. On the one hand, the aggregation of individual actions implies the conviction that strong and confirmed regularities can be obtained from the results. On the other, researchers have often proceeded on the assumption that it is possible to move from the micro to the macro on the basis of a simple summation. But such an operation is only acceptable in certain cases (for example, in opinion polls), and always with great caution.


For example: the case of Spain is emblematic of the political use of opinion polls. In 1982 the PSOE won the elections with a programme that included taking Spain out of NATO and closing American bases on Spanish territory. Once in government, however, the socialists realized that this position was untenable, so they changed direction and explained their new stance in the press and on television. This was accompanied by constant monitoring of the public mood by means of opinion polls. These polls, together with propaganda work to press home the need to remain in NATO, enabled the left to choose the most suitable moment to put the issue to voters in a referendum, and to win it. If on the one hand opinion polls indicate the propensity to act (or rather, to accept or take on board certain government measures), on the other hand they consider the set of individual positions by producing a mere sum. For this reason, opinion polls are unable to gauge the intensity of the various individual positions. Without mentioning, of course, the major problem of correct sampling. c) “The third reason why the search for laws is attractive lies in the influence of the holistic view of social movements. In social movements, the individual fades away, and an individualist analysis which considers the movement to be an aggregated effect of individual actions is not relevant. All research can do in this field is to determine the collective circumstances of collective action” (ibid, 102). Certain holistic conceptions prompt, help and facilitate the search for laws, which then prove to be mistaken. We might recall here the best-known holistic conception of the past, Marxism, and its influence on the destiny of millions of people over decades.

If nomothetic knowledge exists, how can it be used? Boudon acknowledges the existence of nomothetic knowledge in the social sciences, that is, a kind of knowledge with features of generality. But it remains in the background, to be drawn on in using concepts, framing hypotheses and formulating “local models or theories”. If generalization is not the most important objective of research, what is? The answer to this question lies precisely in local theories: “The data for which we try to find an explanation constitute a well-defined set; this implies that the theories relating to these data can only be local or partial” (ibid, 246). Nomothetic knowledge should not be excluded then – not even the most idiographic historian, that is, a person interested in reconstructing specific, unique events, would do that. But it is important to be aware that such knowledge is not about searching for full-blown generalizations, perhaps of the “if…. then” kind: it relates to the concepts, the models and the theoretical framework we use. In a certain sense, it concerns an initial phase of the research. In fact, when we look for explanations we can only have partial theories or analyses of individual cases conducted through the same theoretical framework (see 3.4 below). At this point it is worth reiterating the relativity of the concepts – and thus of the associated nomothetic knowledge – linked to the issues tackled, even in political science. In this as in other social sciences, a local theory is basically the only possible theory for “scientifically” explaining a phenomenon that has a very precise and well-defined sphere of data. If we can refute a hypothesis it 23

is because we are able to obtain the empirical data needed to test the hypothesis. Through this we can arrive at an explanation of the phenomenon we are analysing. But that does not authorize us to say that the explanation in question holds true for all other cases.1 We are a long way off generalizations or nearlaws of cause and effect extrapolated from a series of experiments. Research in the last few decades has shown that the only acceptable explanation that can be defined as “scientific” is one that refers to a spatially and temporally defined set of data. As an example, the degree of legitimacy or acceptance of a certain kind of political regime can be analysed. During and after the 90s, a very high percentage of people in the Southern European countries (around 70–80%) stated that democracy is preferable to other kinds of regime. But what lies behind these responses? If correlations are made with the age of the interviewees, nothing significant emerges. Doing so with level of education yields the same result. If we hypothesize a connection with residency, some modest results are obtained. If we hypothesize a correlation with religion, more interesting results are forthcoming for Spain. But if the same operation is performed with the left-right dimension, things become significant for all four countries. Examining earlier studies conducted in the post-war years, in particular ones from the 70s and 80s, it becomes apparent that the “left-right” concept has two dimensions: on the one hand, a value dimension, a system of beliefs, also in terms of ideologies; and on the other, a party dimension, relating to the structures of parties and their elite. If these two dimensions are transformed into hypotheses and tested, it will be found that they are effectively relevant and of great significance. Mention has been made of conditional generalizations (that is, of the “if… then” variety), in which efforts are made to exclude variables of space and time, even if reference is made to specific data gathered in a precise moment in time in certain countries. It is not, then, a matter of nomotheticity, but of a first step towards the elaboration of a “local theory”. The same nomothetic concepts used were elaborated in relation to particular phases and situations. Returning to Boudon’s formula (M = Mm S M’), it is now clear that the second term indicates precisely the delimited and defined ambit which, in relation to the phenomenon, permits us to formulate the local theory.

1 By resorting to “local theories” it is possible to reduce, if not to overcome, the risk of getting caught up in what Daalder called the Zanzibar expedient, whereby every generalization based on a case might run up against the objection that things are different in “Zanzibar”. Lewellen (1983) notes that in anthropology this form of criticism of undue generalizations is known, not without irony, as “Bongo-Bongoism”.


Box 3.2 For a long time comparativists have tried to achieve nomothetic knowledge, that is, the formulation of general laws governing socio-political phenomena. However, efforts in this direction have inevitably fallen short of the formulation of general laws like the ones produced within experimental settings in the natural sciences. Building on the work of Boudon, it can be concluded that the only possible theory for explaining a phenomenon “scientifically” is a local theory referring to a very precise and well-defined sphere of data.

3.3 Explanation and understanding In this framework it is necessary to understand that explanation and understanding (or interpretation) can be closely connected in the social sciences. Boudon (2000, 245) correctly points out that “we can find ourselves in an interpretative situation even when posing problems of a causal nature: indeed, the causality of certain states of things is so complex that we cannot presume to fully reconstruct the causal web responsible for it, even less to evaluate the relative importance of individual causes in an objective manner”. In short, modern hermeneutics is wrong to sustain that every interpretation is purely subjective, denying any relationship with explanatory activity; but it is also a mistake to regard explanations as objective and exhaustive. There are effectively explanations when we analyse partial correlations. If we try to obtain broader macro-political explanations instead, the interweaving of explanation and understanding inevitably emerges. It can thus be empirically demonstrated, for example, that a factor such as American foreign policy actions is partially responsible for democratization processes in some quite specific Latin American countries or in other areas. But a complete explanation of democratization in those same nations prompts us to present an empirically supported web of factors, the relative importance of which are the subject above all of opinions backed by argumentation, and therefore of interpretation. At any rate, the most convincing position regarding this issue seems to be that of Runciman (1989), who breaks understanding down into what he refers to as its “primary, secondary and tertiary senses” (ibid, 15 ff.):  

“The first of these is the understanding necessary for the reportage of what has been observed to occur or be the case”: it is, then, the description of the observed phenomenon; “the second is the understanding of what caused it, or how it came about”: in other words, explanation in the true sense (that is, explanation of the causes underlying a given phenomenon) and explanation-description. This second meaning shows how description and explanation often overlap. Kaplan (1964), on the other hand,


made a clear-cut distinction between the two, but when we attempt a macro-political analysis (for example, on the subject of democratic installation, consolidation and so on), description and explanation overlap. “the third is the understanding necessary for its description in the special sense here given to that term […] the observer must always understand the meaning of the terms in which agents themselves characterize what they think, feel, say and do”. When studying (describing/explaining) a certain phenomenon, we must try to grasp how the actors understand what they are doing. This is important both for descriptive and explanatory purposes; “the agent is privileged in his own awareness of what he thinks, feels, says and does”. The scholar must be able to understand “what it is like to think, feel, say and do it”, that is, to look at things from the perspective of the actors.

It should be clear at this point that there is not one method that works well for all the problems of political science or sociology or other social sciences. Runciman’s position is the one that appears most useful for our ends. In particular, in relation of macropolitical issues, which have a markedly qualitative dimension, some methodological positions appear more useful than others. It makes no sense, then, to talk about “the” social science method. There are just more thorough and aware ways of studying certain problems. This awareness lies at the heart of what is called moderate positivism, to which we will return in chapter 7. Box 3.3 Modern hermeneutics is wrong to sustain that every interpretation is purely subjective, denying any relationship with explanatory activity; but it is also a mistake to regard explanations as objective and exhaustive. Following Runciman (1989), it can be said that description, explanation and subjective interpretation of a certain set of events by the agents involved in them are crucial to studying macropolitical issues.

3.4 What kind of theory should be adopted in political science? At this point it would be appropriate to follow an empirical approach ourselves. If the fundamental reason for comparison is explanation, and consequently the development of different ways of theorizing, the question that needs to be asked is what has happened in political science in this regard. At the end of the 1950s, in an article reviewing the contribution of comparison to political science, Sigmund Neumann wrote, with ill-concealed enthusiasm, “in the beginning was Comparison” (369, 1957), using a capital “C”. That affirmation would sound too ambiguous today, and ultimately misleading. First of all, various general theories were developed in the 1960s, which came in for criticism at the time and were subsequently forgotten. However, 26

some of the elements of those theories still form part of the background – we might say, of the nomothetic knowledge – of many political scientists. This is not the place to review the best-known general theories of the 60s: systemic theory, structural-functionalism, group theory, the theory of rational choice. There are already many works that do this, with authors often taking the opportunity to develop a certain approach and to criticize all the others. For a reconstruction of this phase of study, see Sola (1996). What is more, the demand for a general theory, a strong and widely shared goal in the 60s (see Dahl 1961), has now virtually disappeared. Instead, the key point to emphasize is precisely the fact that they left a permanent mark on the majority of macropolitical analyses carried out subsequently. The current legacy concerns above all: 1) 2) 3)

4) 5)

the impossibility of considering institutions in purely formal terms: any analysis of institutions must also make reference to their informal dimensions; the emphasis on the ties between the various aspects and phenomena analysed: such connections can no longer be ignored, but must be considered important or even vital for every empirical analysis; the fact that some concepts, even though their definition may not always be unambiguous, are now part of the theoretical legacy of the political science of recent years: think, for example, of the notion of support and its many related notions (confidence, legitimation, trust and so on); or of performance and the related concepts of efficacy and effectiveness; or that of feedback; an enduring functionalist influence in much contemporary analysis, starting with studies inspired by economic principles; a fifth aspect of the legacy, and worthy of attention in its own right, concerns the rational choice approach, and its presence and developments in political science.

It should be recalled though that in those same years many scholars continued working on and developing traditional institutional concepts. Some of them did so in an effective and original manner, as demonstrated by the likes of Duverger, Huntington and Kirchheimer. Tracing the work done in the following decades by these and other scholars clearly reveals the presence of the legacy outlined above, but also of various different theoretical alternatives within comparative politics. It is worth looking more closely at what happened. Some of the most influential authors of the 70s and 80s had already risen to prominence in the 60s. Other lesser known figures attracted attention through research conducted in these years. For our purposes, the best way to proceed is to make very selective direct reference to these authors, rather than offering a general and necessarily less specific survey of existing approaches and theories. Accordingly, some of the most influential and widely cited scholars of those years have been selected and divided into two groups: one formed by Almond and Sartori, the other by Rokkan, Finer and Linz. Almond’s work, especially in the 70s, was distinguished by an attempt to formulate a general theory of politics, drawing on contributions from other disciplines as well. Almond embraced James C. Scott’s suggestion that “if half of 27

your readings do not lie outside the bounds of political science, you risk extinction, just like every subspecies” (1995, 37), and practiced it even more fully than Scott himself. However, institutions are not taken into consideration, though they are indirectly saved on the empirical plane, thanks to the functions they perform within his theory. Moreover, his eclecticism undoubtedly contributes to the originality of his work, besides requiring great powers of intellect. Almond is the author who better than any other embodies the spirit and cultural background of the 60s. As proof of his importance, it is worth adding that, especially during the 60s, a great many works were published which explicitly or implicitly drew inspiration from Almond’s work. Among these mention might be made of the volumes in the series he edited for Little, Brown and Co. Sartori’s work on political parties also combined different approaches, especially the systemic one and the rational choice approach as developed by Antony Downs (1957). The originality of Sartori’s Parties and Party Systems (1976) is based to a large extent on the empirical translation of certain aspects of the two combined approaches. It was one of the most widely cited works at the end of the 70s and in the following years as well. The first scholar of the second group is Rokkan. Conceiving an ambitious project like the European macro model entails a broad knowledge of languages and cultures, and an extraordinary analytical intelligence, which Rokkan certainly had. In his theoretical framework, the influence of Parson, Barrington Moore and Hirschmann do not diminish the role and importance of institutions and rules. On the contrary, they continue to be central elements of his theoretical framework, further enriched by more specific hypotheses about democratic development. The same holds true for the work of Finer. We need think only of his final three-volume work, History of Government (1997): “no finer work of political science”, wrote a reviewer in The Economist, “has been published in this century”. The key factor analysed by Finer is the centrality of institutions, within a very bare analytic frame combined with several specific theoretical hypotheses. Finer (1969) was also the author of one of the most radical and destructive critiques of the systemic approach and of the work of Almond. Rokkan and Finer took institutional analysis to its highest level. They seemed to ignore the legacy of the theories developed in the 60s, but not the first two points considered earlier. Linz adopted a traditional approach combining a focus on institutions with a sociological perspective in the tradition of Weber. The most important results of his approach can be found in his works on fascism, Spanish Francoism and the typological analysis of political regimes. Analysis of a third group of scholars belonging to a later generation confirms the shift towards middle-range theories, which can be considered full-


blown local theories, have a limited scope, explains a specific set of phenomena, and is opposed to a grand theory such as functionalism or system analysis. Think, for example, of Rose, Lehmbruch, von Beyme and Schmitter. Lehmbruch in particular shows the potential originality associated with the explanation and analysis of cross-sectoral and transverse processes. In it there emerges, on the one hand, the relationship between value systems and the process of building institutions, and on the other the relationship between policies and institutional orders. According to von Beyme (1997), the focus on the role of actors in middle-range theories constitutes an essential way of studying politics. Schmitter has stressed the importance of interest groups and how they are structured, even if drawn from the study of a single case. His further works on neo-corporativism, some in collaboration with Lehmbruch (1979 and 1982), corroborate this point very well. More generally, the majority of the most important political scientists working in the field tend to stress the key role of institutions. One exception is Almond, but not Sartori, who, though using the systemic and rational choice approaches, that is, generalizing approaches that downplay institutions, then devoted his most important work to an intermediate institution and to middlerange hypotheses: the political party within the party system. This analysis is perfectly coherent with the widespread conviction that one of the functions of comparison is to evaluate the success of institutions and policies and to “contribute to the debate on institutional and other reforms, which are the continual collateral manifestation of any political activity or analysis” (Finer 1954). This goal, established by Finer in the 50s, has more recently been reaffirmed by Gerlich (1997) as well. But we are still in the sphere of middle-range and not general theories. Since the start of the new millennium there have been many changes in comparative empirical theory. The first is the broadening of research to include previously unstudied nations and other research issues. A wider range of countries are now being subjected to closer and more systematic comparison, in particular the Latin American and Eastern European nations and some areas of Asia and Africa. Due to authoritarian crises and processes of democratic installation in these areas of the world, themes associated with democratization have become fundamental, attesting to the enormous growth of a sub-sector which, from a quantitative point of view, is perhaps now the richest of them all. Research into democratization has maintained a strong degree of continuity with the past: the many different analyses of democratic processes – such as transition, installation, consolidation and sometimes crisis as well, or other processes and sub-processes – and the related institutions refer to problems and questions already present in classic research carried out by the previous generation of scholars. The same can be said of the renewed interest in authoritarian regimes and transitions toward authoritarianisms in countries such as Russia, other nearby nations and Turkey and Venezuela as well. 29

In this ambit, studies of constitutional engineering and government institutions have yielded significant new results. The biggest differences here, due principally to the new empirical material with which experts have had to work, have been overcome by a certain basic continuity provided precisely by the institutional approach. The essential points of such research are as follows: traditional themes are now reformulated in different conceptual terms and with a different language; in analysing such themes the focus is often on the role of the actors, their choices and the processes of change in which they are involved, rather than on the basic socio-economic conditions; they are also formulated and expressed essentially through a qualitative and middle-range comparison, carried out on the basis of a limited number of cases, and often by research groups bringing together experts from different countries and hence able to better understand specific national characteristics. Another new element in the sector is the extraordinary growth of policy studies. This growth had already been broadly anticipated in the second revamped edition of Almond and Powell’s Comparative Politics (1978), published with a different subtitle. It was also highlighted by Daalder (1993, 27– 28), who listed the key features of this emphasis on political performance and public policy: a new interest in the role of the state; the development of neocorporative analysis; and an accentuation of interest in the comparative developments of the welfare state. In an appraisal of developments in comparative politics, Mair (1996, 321) also refers to this turning point in the discipline, when he underlines the shift in attention towards the outputs and outcomes of the political process, and the impact of political institutions that take on the role of independent variables. The most specific characteristics of comparative studies of public policies are discussed by Ferrera: he evidences the recent convergence of this sector with “a more careful analysis of comparable cases” and with “qualitative historic comparisons” (1996, 64), and observes that the use of “rational comparative research projects”, not just in macro-analytic but also in micro-analytic research, remains the most fruitful aspect of the field. There is another important development that must be underlined, and which is of direct relevance here. In comparative empirical theory there is a clear-cut division in the way researchers theorize about public policies and about democratization, the two sectors comprising the majority of empirical research in comparative politics in recent decades. The whole subsector of public policy analysis, which is particularly influenced by rational choice and by rational institutionalism, openly and explicitly pursues precise theoretical objectives, where possible in relation to several cases. By contrast, in democratization studies, where the institutional approach prevails, and the rational choice approach is virtually inexistent (with the exception of Colomer and some works by Przeworski), scholars do not search for theories, even middle-range ones,


but theoretical frameworks instead. In other words, they are looking for indicators of dimensions and factors, perhaps even full-fledged variables, useful for research and analysis that can then be related to specific cases. One of the best examples of the theoretical ambitions of the first sector, that of comparative public policies, can be found in path dependence. Paul Pierson (2000) is the author who most clearly develops and presents the main hypotheses of this theory, which has emerged in recent years and is particularly suited to this field of political science. His essential theoretical propositions are as follows: it is particularly important to bear in mind the timing and sequences of events; a broad spectrum of social effects may often arise from a similar cause; important consequences may be the result of minor and contingent events; particular courses of action, once introduced, are difficult or impossible to modify, even if the consequences are evidently disastrous; political development is characterized by “critical circumstances” and phases that define fundamental aspects of social life; and finally, politics is distinguished by a high institutional density, by the central role of collective action, by complexity and opacity, but also by the temporally limited horizon of politicians and the inertial force of institutions. As regards democratization studies, the other sector considered here, in 2000 Valerie Bunce produced an overview covering many research studies (Bunce 2000). She began by distinguishing between theoretical propositions with a high level of generality (of a nomothetic kind) and propositions of regional scope (local theory) referring to a group of spatially contiguous nations. In relation to the first group, Bunce lists five main general propositions: 1) a high level of economic development offers a guarantee of democratic continuity; 2) political leaders are decisive in designing and creating a democracy; 3) a parliamentary institutional set-up offers greater advantages for the continuation of a democracy than a presidential set-up; 4) solving national and state problems is important for the survival and quality of democracy; 5) in a developed democracy it is essential that the law be respected. The generalizations of regional scope relate to: 1) the importance of agreements and compromises in the democratic transitions of Southern Europe and Latin America; 2) the advantages of a break with the past for Eastern Europe; 3) the strong correlation between democratization and capitalistic economic reforms in Eastern Europe; 4) the dangers to democracy in Latin America and post-socialist Eastern Europe caused by inadequate respect for the law. Irrespective of the fact that some propositions in the first group may coincide, partially or totally, with others from the second, it is evident that they could not be used to construct any theory either at a more general level or at a regional one. Some of the best known and most widely cited researches in the field confirm this observation as well. The work of O’Donnell, Schmitter and Whitehead (1986), complemented by that of authors contributing to the same re-


search by dealing with specific cases, focuses on: the characteristics of the previous regime; the role of agreements or “pacts” between elites on the institutions to set up; the reactivation of civil society; the limited role of parties; the importance of achieving a consensus, even if only a “contingent” one, about the institutions that are created; the significance of the first elections; and finally the uncertainties of the whole transition process. Their analysis thus explicitly denies the possibility of devising a theory about the issue: on the first page of their conclusions, O’Donnell and Schmitter (1986, 3) clearly affirm that they did not have a theory at the beginning and they do not have one at the end. Instead, they propose a theoretical framework, or scheme of analysis, in which actors, institutions, times and the very notion of process play a central role. Moreover, the framework in question is formulated with particular reference to two specific areas: Southern Europe and Latin America. In The Third Wave (1991, 30), Samuel P. Huntington explicitly declares that he has temporally and spatially defined explanatory goals, referring to the transitions of the 70s and 80s, the so-called third wave. The five main explanations in the thirty-odd countries he studies are: 1) the deepening of problems of legitimation for the previous authoritarian regimes, partly due to the negative results of policies; 2) the unprecedented global economic growth in the 60s; 3) the marked changes in the teachings and activities of the Catholic Church after the Second Vatican Council; 4) the foreign policy changes of some actors, from the USA to the European Union, and the mutations in the Soviet Union of Gorbachev, with its subsequent break-up; 5) a demonstrative effect enlarged by the mass media (Huntington 1991, 45–46). Huntington thus explains the transitions to democracy in those years in terms of a set of specific cultural, economic and international changes. The search for a middle-range theoretical framework was pursued more systematically by Linz and Stepan (1996), who referred to the main variables to be singled out in five key arenas: civil society, political society, the rule of law, state apparatus and economic society. Linz and Stepan analysed sixteen countries in Southern Europe, Latin America and Eastern Europe. At the same time they finished developing a theoretical framework for the analysis of these sixteen nations, devoting an entire chapter to each case and accompanying it with a careful taxonomy of the previous non-democratic regimes. The various attempts to elaborate models of transition-installation also reflect a propensity for theoretical frameworks. Stepan (1986), Share (1987), Karl and Schmitter (1991), Munck and Skalnik Leff (1997), and Berins Collier (1999) are among authors who have managed to devise the most interesting models of transition-installation. On the one hand, their works differ in part: while Stepan and Berins Collier refer to quite a few classic Southern and Eastern European cases, Share basically concentrates on a single transition, that of Spain in the 70s; and Karl and Schmitter, or also Munck and Skalnik Leff (1997), look both at the Latin American transitions of the 80s and the more 32

recent ones in Eastern Europe at the end of the 80s and in the decade that followed. On the other hand, all the authors concentrate essentially on two macro variables: though characterized in partially different ways, all the transition models are pieced together and interpreted on the basis of the actors-authors of the transition (the authoritarian elites in power or those in opposition, that is to say, the elite actors or those of the masses) and the strategies pursued, hinging on compromise or on the resort to force, in other words, on agreement or conflict. Even in this sector of democratization, then, which started from general theories like the systemic and functionalist ones in the 60s, the prevalent choice concerns the preparation of theoretical frameworks, followed by the search for specific explanations. No attempt is made to elaborate a more general theory of regime change, aside from a few very general background indications that are regarded as givens, or proposed simplified models of transition like the ones mentioned above. As in the case of public policies, the underlying reasons for the choice are relatively simple: irrespective of the approach and method that is followed, there is concern about the complexity and enormous richness of the empirical reality in the different cases analysed; at the same time the goal is to embrace that richness without making excessively distorting simplifications, which in any case are inevitable. In this sense, a theoretical framework, understood also as an indication of the crucial and recurring variables on which models and typologies are elaborated, offers the possibility of constructing empirically interesting comparative frameworks without blunting the specificities too much. Some conclusions can now be drawn on the basis of what has been said in this chapter, with the addition of some further considerations relating to recent years. It will be recalled that comparativists inherited their “dream” of building a theory of politics from the founders of social theory (Lichbach and Zuckerman, 1997). In the last few decades, in the two main sectors that have employed comparison, policy studies and democratization, researchers have moved in two different directions when it comes to formulating theories. While the analysis of public policies made, and continues to make, a special effort to develop new middle-range theories, studies of democratization have instead stressed the importance of analysing specific cases more deeply by elaborating theoretical frameworks. The search for a more structured, articulated theory has been a recurrent characteristic of policy studies, whereas the prevalent feature of democratization studies has been to escape it in favour of looser theoretical frameworks. In both sectors, the conclusion is in the end perfectly coherent with what has been seen in the previous sections of this chapter: the formulation of spatially and temporally defined theories, or, alternatively, when wishing to consider a larger number of cases, the elaboration of a broader grid of concepts that form part of the nomothetic knowledge discussed earlier and which is at any rate elaborated in certain specific areas. 33

Any theory is ultimately the result of explanation. From this perspective, as seen at the beginning, explanation has remained the main task of comparative politics over the years. In the same period, however, the cognitive and interventionist tasks have also received a great deal of attention. The development of social science knowledge, from both a quantitative (with new statistical techniques) and a qualitative viewpoint, combined with rapid advances in computer technology, has led to two major outcomes. The first is the construction of large data banks by public international institutions such as the United Nations, the World Bank and the European Union, or by private ones like Freedom House and the Bertelsmann Foundation. Secondly, better qualitative knowledge of different political realities has also provided opportunities to pursue the interventionist task. A demonstration of this is the management of the 2008–14 economic crisis (see, for instance, Bermeo and Bartels 2014), when the political authorities of the European Union member states reviewed their labour, pension and other economic policies. Box 3.4 Various general theories were developed in the 1960s, but soon came in for criticism and were subsequently forgotten. However, some of the elements of those theories still form part of the background of many political scientists belonging to three groups of influential scholars: the first comprises Almond and Sartori, who share a methodological eclecticism and the ambition to develop general theories; the second includes Rokkan, Finer and Linz, who pursued more limited goals focusing on the study of institutions and rules; the third group, including scholars such as Rose, Lehmbruch, von Beyme and Schmitter, confirms the shift toward local theories. More recently, the focus of comparative research has broadenend to take in nonEuropean nations and other research issues, dealing with themes linked to democratization (Huntington 1991, Bunce 2000), constitutional engineering, policy studies (Daalder 1993) and path dependence (Pierson 2000).

Questions     


What are the main goals of comparison? What do we mean by the “nomothetic objectives” of comparative research? Why is it difficult to formulate general theories in the social sciences? What is a “local theory”? What are the most recent developments in comparative research?

4. What to compare: the basic units 4.1 Identifying the issue The problems and choices involved in comparative research can now be addressed. The first step is to identify the research issue, that is, the question we want to ask, the goals we intend to set ourselves, what we are interested in knowing, describing, explaining or understanding. As mentioned in the introduction, if the research is to have significance, it is important that the “question” should have political salience. The examples we gave suggest a first important point: albeit with certain variations, a number of specific criteria need to be respected in order to formulate a good research issue. The main ones are outlined below. 

Interest in the issue. This criterion concerns a particular sensibility and a wholly individual choice on the part of the researcher. Often deriving from personal experience and values, the essential aspect of this criterion lies in the underlying values and attitudes of the researcher with regard to the chosen theme. We are touching here upon the theme of value-neutrality, as a virtue of the scientist, first illustrated and explored by Weber. More specifically, argues Bobbio (1971, 377), “value-neutrality is the virtue of the scientist, just as impartiality is the virtue of the judge: no one would think of suggesting to a judge that, as it is difficult to be impartial, you might as well not be so”. And, he goes on, a scholar wanting to conduct research seriously “makes use of all the research techniques that help to eliminate, as far as this is possible, the realm of the approximate into which personal evaluations most readily slide” (ibid). Relevance of the theme. This concerns the potential, even if only remote, that a piece of research might form the basis for political decisions or might influence political opinions and the attitudes of elites or groups, or, in any case be relevant, sometimes only indirectly, to a large number of people. In short, this criterion prompts the researcher to examine and investigate themes and issues that have importance for collective life, for the future of politics at a national or even international level. Knowledge of the literature. Formulating the research issue inevitably involves looking at what is already known about the potential subject of investigation, and therefore, at the existing literature on the topic. Scholars, especially if they are young, commonly take an interest in a theme because they have learnt about it through published research, or an article, essay or book read in a library, or even from a lecture. It is less likely to be due to stimulus arriving directly from surrounding reality. Empirically precise formulation. An empirically precise issue requires both an indication of the space in which the phenomenon is situated and the time span we wish to cover. It also presupposes that the meanings of the terms used are clearly understood. Empirical testability of the formulation. Formulating the issue so that empirical analysis is possible is equally essential if we are to talk in some way of “science”.


Basically, this means refraining from postulating issues or hypotheses which, however fascinating or stimulating, cannot be empirically tested.

Just listing these criteria makes it immediately clear that what we called the “first step” is actually the outcome of a sometimes long path. It is in any case a decisive moment in any research. When formulating the research issue it is important to have both a basic knowledge of the future topic of study and a clear idea of which methodology will be applied, in other words, whether the intention is to describe, explain or understand; if we are looking for general hypotheses of the kind illustrated in the previous chapter; and what the main objective of our research is. Even if it remains implicit, this process – which leads to heightened methodological awareness – must necessarily take place, in that the methodological choice will have direct repercussions on the research. In the appendix to The Sociological Imagination, C. Wright Mills talks about the “conscious thinker” when referring to the intellectual craftsperson’s growing awareness of their tools. Box 4.1 The first step in comparative research is to identify the research issue, that is, the question we want to ask. At least five criteria have to be met in order to successfully perform this task: 1) an interest in the issue; 2) relevance of the theme; 3) knowledge of the literature; 4) empirically precise formulation; 5)empirical testability of the formulation.

4.2 Concepts and classes Right from the outset, in formulating the research question and then deciding which cases to include and which variables to analyse (see next sections), the conceptual aspect is crucial. Hence the importance given to the formation of empirical concepts in the social sciences. It is not just a matter of having a clear idea of what we want to study, and of defining the properties and attributes, but also of classifying effectively in order to single out the variations of the phenomenon in different realities. Sartori’s “lesson” on this point (1971, 1984; 1991) is unequivocal: the “cat-dog” exists chiefly due to a defect of conceptualization (conceptual stretching) and classification (misclassification). In the researcher’s concrete experience it is impossible to say whether firming up the concepts and the classification come before or after the choice of which cases or time span to analyse. Quite simply, it might be one or the other, and more often than not there is a mental process involving a to and fro between data and theory. Basically, it is a question of moving from the ideas to the empirical evidence (Ragin 2000). Conceptualization and classification will be dealt with at greater length in chapter 6, where the key mechanisms of 36

comparison will be introduced. It will suffice here to remember that there is a strong connection between the two intellectual operations. Both, in fact, enable that firming up of concepts which permits the identification of comparable cases. Devoting adequate attention towards comparable cases, as will become apparent further on in the chapter, is one of the recommendations made by Lijphart (1971) and picked up on by Collier (1991), and its importance hardly needs stressing. Essentially, as was mentioned in the previous section and is once again being emphasized here, to conduct comparative research it is vital to elaborate a theoretical structure or at least a series of hypotheses. These may even simply be taken from previous studies. However, the more rigorous and developed the theoretical structure, the greater chance there will be of being able to focus clearly on a precise and limited number of hypotheses. Though parsimony is a costly virtue, because it places limits on the research, it is a necessary one if the researcher is not to get bogged down in long and often useless lists of sometimes alternative hypotheses. A good theoretical construct provides excellent orientation in selecting hypotheses, in focusing the research and thus in using energies more effectively. Box 4.2 The conceptual aspect is crucial in formulating the research question and then deciding which cases to include and which variables to analyse. Conceptualization and classification help to firm up concepts, thus enabling the identification of comparable cases.

4.3 Properties and variables As seen, the devising of concepts is the initial logical procedure that enables comparable units – that is, the types of objects or events a given comparative research is interested in – to be clearly identified. The research is defined simply by the possibility of considering the empirical realities that we wish to study within the conceptual categories (or classes) themselves. Comparability, then, is due in the first place to the formulation of correct empirical concepts and, as a consequence, to the construction of classes. In this respect, it is linked to the other question of how to compare (see chapter 6). Different realities like dogs and cats can therefore be compared if they are included in a significant way within the same category of pets. However, determining what is comparable also involves singling out (selecting) the properties, that is, the set of characteristics or “aspects” of the units or cases considered to be relevant for the research. From a formal-logical point of view, information relating to a research subject, broken down into 37

cases and properties, can be expressed through a data matrix, for example, a 2X2 table, where, in general, the rows indicate cases and the columns indicate properties. This provides the first two analytic dimensions, i.e. units or cases and properties, of every comparative research, enabling the researcher to identify different types of comparison. For the sake of clarity, if at this point we look at Figure 5.1 (see chapter 5), we will see how we are now looking at those two dimensions (the part of the figure in the foreground), whereas in the next chapter a third dimension (time) will be added, with the related methodological consequences (see Bartolini 1991), together with the different strategies of comparison on the basis of the number of cases (space). Finally, the “cells” identified by the intersection of rows and columns indicate the state,2 or value, of every given property for each case. As will be seen in the next section, operationalization then transforms, directly or through relations of indication, the properties of the research cases into variables, prone, when possible, to “measurement”. One further observation can be made about this point: the chosen variables, whether few or large in number, are measured by quantitative data if they are genuine variables, otherwise they are defined by qualitative data and the variation is identified through classification. With this procedure it is basically irrelevant whether the variables are accompanied by quantitative data or soft or qualitative data. The comparative procedure will be the same. It should be added straight away, however, that in all the cases, even in a “simple” gathering of “numbers”, the theoretical aspect is necessarily to the fore, even when obtaining one number rather than another. Once again, then, we come back to the theoretical dimension. But what exactly does it mean to compare two or more different realities? As has just been said: to compare two or more phenomena brought together under the same conceptual category. To put it more precisely, it means we compare the properties, that is, the specific characteristics, similar or otherwise, of two or more phenomena; or rather, we compare the values or modes (types) that the similar properties or variables take on in two or more phenomena. We likewise compare the properties, states and values assumed by those variables in a given moment (synchronic comparison) or in two different moments (diachronic comparison) (see chapter 5). Finally, we can compare the causes of these phenomena, to see whether they are the same or different. It should also be remembered that a problem faced constantly by comparativists is that it is not possible to isolate some properties from others or from the context of the phenomenon being studied. In comparison it will inevitably be necessary to recompose all the properties or states and their respective values, tying them in with the studied phenomenon, both in order to 2 The state of a property means the particular way in which a property presents itself (for example, if the property in question is party membership, this may be spread across the territory or concentrated in certain areas).


conduct a more effective comparison and to provide a more in-depth explanation. A fairly simple example will help to clarify this: the comparison of electoral systems in a number of nations. Over and above the unique and general notion of the electoral system, understood as the transformation of voters’ preferences into seats and the elected, consideration is given to the main properties of electoral systems, such as the electoral formula, the size of constituencies and the existence or otherwise of thresholds for the dividing up of seats. Comparison will be conducted on each of these properties, and it will be qualitative in nature, also in terms of the presence or absence of the properties. If, subsequently, we want to compare the degree of proportionality of each electoral system, indexes will be formulated and the value of each index for each country compared. This can be done for the same electoral system in different periods. Finally, we can focus on the causes of a state or value of a property in different electoral systems. For example, why do some parliamentary election systems with certain properties, which may even be similar, produce different effects? Is it due to a particular party system or to the existence of a head of state elected directly by the people? Or for some other reason? The previous analysis and these last observations suggest two further, and complementary, answers to the question of what to compare. The first one returns to the distinction proposed by Przeworski and Teune (1970) between research strategies of the “most similar systems” kind, which compare most similar systems or cases, enabling a wide series of factors to be taken into consideration (for example, the France of the Fourth Republic and pre-90s Italy); and “most different systems”, the strategy preferred by Przeworski and Teune, which compares systems that differ widely except for a few shared elements that act as independent variables (such as Japan and post-war Italy). The second answer, discussed further in chapter 6, distinguishes between quantitative comparison, which places emphasis on the variables, and qualitative comparison, which stresses cases. Using the terms of Ragin and Zaret (1983), we can speak respectively of “statistical” comparison, stemming from the Durkheimian tradition, and “historical” comparison, which goes back to the Weberian tradition. Finally, both pairs of research designs, as will be seen in chapter 6, can be traced back to the logical canons of Mill. We can now try to offer a synthesis of what has been said so far. If we regard the search for resemblances and differences as a more precise goal of comparison, and the phenomena analysed by the last two types of comparison to be described as cases or sets of variables, we obtain the four results outlined in Table 4.1.


Table 4.1: Results of comparison according to objectives and units of analysis phenomenon seen as objective


set of variables


identification of hypotheses applicable to a number of cases

theoretical propositions relating to the variables of the phenomena considered


specification of the unique properties of a certain case

temporal and spatial specification with respect to a certain phenomenon (survey)

Box 4.3 The initial logical procedure that makes it possible to clearly identify comparable units is the definition of concepts. However, determining what is comparable also involves selecting the properties, states and values assumed by the variables of interest in a given moment (synchronic comparison) or in two different moments (diachronic comparison). It is important to distinguish between quantitative comparison, which places emphasis on the variables, and qualitative comparison, which stresses cases.

4.4 Operationalization Before moving on, however, another question needs to be addressed. Many concepts, especially in politics, are not directly observable or empirical. In other words, they have no immediately corresponding and straightforwardly perceptible realities – they are theoretical, non-observable concepts. While it is a commonplace occurrence to see a cat or some other animal or thing, and therefore a straightforward concept exists for them, it is a very different matter when we talk of a political system, a democracy, an authoritarian regime, the state, bureaucracy, or of parties, interest groups and many other theoretical terms used continually in the specialist language of political science, but also in common political parlance. In these cases we are dealing with concepts of a very high level of generality that are not directly observable. Other terms as well, such as ‘elections’ or ‘cabinet’, though lying at a lower level of abstraction, are still several steps removed from being directly and perhaps immediately observable. The key point here concerns the path between meaning and empirical referents, or, to put it in other terms, how to specify the analytic steps lying between connotation and denotation (see chapter 6). This path can be covered by using working definitions and empirical indicators. An operational definition incorporates the specification of the field of empirical referents of the concept. That is, it states how we propose to label, detect, measure or otherwise identify a particular empirical concept. But not 40

all concepts lend themselves to an operational definition. When such an operation is more complex, the researcher can resort to one or more indicators. An indicator is the expression of semantic tie between the more general concept and a more specific concept for which an operational definition can be produced (see, for example, Lazarsfeld 1958, Gerring 2012, 142–3, and others). See Figure 4.1.

Figure 4.1: The operational definition and the relationship of indication

The first fundamental step, then, is to articulate a certain general concept in terms of dimensions – so-called segmentation (Dogan and Pelassy 1990, chap. 13) – and to affirm the existence of a tie of indication between that conceptual dimension and a directly observable element. For example, one definition of democracy refers to competition and participation as necessary conceptual dimensions. One of the indicators of participation is the percentage of people that actually voted in the last elections in the country or countries to which the concept of democracy is being applied. This example alone helps us to grasp the importance of indication. Some aspects of it can now be looked at more closely. The first, essential aspect is the recognized and accepted existence of a theoretical link, namely the existence of theoretical pertinence: going to vote is widely accepted as a form of political participation. Secondly, usually more than one indicator is useful, if not indispensable, for analysing a given phenomenon empirically. For example, many very different forms of political participation exist besides the electoral variety (in parties, in movements, in specific demonstrations). Consequently, it will be appropriate and sometimes inevitable to resort to more than one indicator to empirically test the existence of a complex phenomenon. Thirdly, the theoretical goals themselves, and, above all, the research question itself, impact on the use of a certain indicator rather than another. If the relevant electoral participation for affirming the existence of a democracy is the potential participation, the most pertinent indicator will concern the average percentage of voter participation in more than one election. This, in fact, would indicate that the right to vote really does exist, in turn an important 41

element for evaluating that potential participation. As can be understood in this case, various analytic steps would need to be taken before arriving at the indicator we empirically require: from democracy to a dimension of it, namely participation; from participation in general to the potential electoral one; from potential electoral participation to concrete respect of the right to vote; from concrete respect of the right to vote to the actual average voting percentage over a given number of years. Fourthly, the tie of indication is strictly linked to the context in which the indicator is detected: electoral participation is an indicator of democratic participation if there are other indicators of some level of competition, the principal indicator of which might be the existence of more than one party. If the existence of competition were not demonstrated, the percentage of voters might be an indicator not of democratic participation, but of participation in authoritarian or totalitarian contests. A fifth observation is that the same indicator could be used for different “ties”. Indeed, the percentage of those voting in a democratic contest, if measured over the years and then transformed at the end into a number of measures of a trend, might also serve to indicate the level of conflictuality existing in a democracy, and, in this sense could be used for completely different theoretical and research objectives. Sixth and last, methodologists correctly argue that for an indicator to be efficacious and valid it must be one-dimensional, that is, it must be connected to just one dimension of the concept-phenomenon we wish to analyse. Granted the need to consciously pursue and, if possible, achieve one-dimensionality, this objective often proves problematic when it comes to concrete research situations. For example, electoral participation may be used to detect levels of participation. In situations of this kind the correct solution is to use the same data, in electoral cases, but to construct a different indicator: for instance, the average number of voters in a certain period, for participation; and voters divided according to party in the same period, for competition. As a result of these difficulties, a number of scholars (see, for example, Marradi 1980, 39) have suggested using a plurality of indicators to measure the same dimension (see above). In this way, even if an indicator is not central and exclusive to a given dimension, the empirical dimension will be detected more accurately due to the adoption of different indicators. However, this recommendation often proves to be problematic as well, because in reality it may be particularly difficult to find good empirical data. Ultimately, then, operationalization indicates the different steps through which an empirical content is attributed to not immediately observable concepts. The entire analytic process was schematized very well by Lazarsfeld (1969, vol. I, 41ff.). Its principal phases can be simplified as follows: the first step is to formulate-define the empirical concept corresponding to the central phenomenon in which we are interested; the next thing to do is to specify the 42

concept itself by identifying the dimensions comprising it; the largest possible number of indicators deemed important for the dimensions are singled out; finally, in cases where quantitative measures can be obtained, the researcher moves on to devise indexes, that is, to find and measure numbers that sum up the quantum of presence of the empirical aspect considered as an indicator (see Introduction). As is known, in many cases political research carries out the first steps but not the last, precisely because it is often qualitative. In this sense it barely needs mentioning that the fundamental phases of quantitative research are no different from qualitative research. Box 4.4 Many concepts, especially in politics, are not directly observable or empirical. In order to measure them we need an operational definition incorporating the specification of the field of empirical referents of the concept. An indicator is the expression of a tie of semantic representation between the more general concept and a more specific concept for which an operational definition can be produced. Ultimately, then, operationalization indicates the different steps whereby an empirical content is attributed to not immediately observable concepts.

4.5 The “many variables, small N” dilemma In the previous section it was seen that some of the concrete decisions that have to be made by the researcher relate to the selection of cases and the relative properties/variables. When dealing with this point, “the problem of the comparative method” is that of the “many variables, small N” (Lijphart 1971, 686), that is how do we cope with the problem that are only few cases to consider and they are complex. Consequently, to be adequately analyzed they involve the inclusion of several variables. As Lijphart observes, this dilemma can be tackled both from the point of view of the variables and from that of the cases (ibid, 686 ff.). Two strategies for dealing with the former are to: a) reduce the “property-space” of the analysis, that is, the number of properties/variables to consider; b) focus on the key variables.

As regards the latter, two further possibilities/strategies are to: c) increase the number of cases as much as possible; d) make comparable cases the focus of the analysis.

This point can be clarified by starting with Lijphart’s recommendation to cut down the number of variables to analyse (strategy a). The purpose of reducing the number of properties and variables is to achieve stronger explanations, because they will be supported by a greater quantity of empirical data, avoiding 43

the difficulty of “third variables” (or intervening variables). Such an operation can be conducted by reducing what Lazarsfeld and Barton (1951) call the property-space, that is, the set of characteristics regarding and specifying a class or type. In concrete terms, the reduction is achieved by combining some classes and placing the cases and the relative data into a smaller number of classes. This can be done by increasing the level of generality (thus bringing us back to the “scale of abstraction”, to which we will return in chapter 6), which also enables us to increase the number of cases belonging to a certain class. This links in to another of Lijphart’s recommendations (strategy c). If, instead, there has been an effective increase in the cases analysed, deliberately reducing the variables offsets the almost inevitable increase resulting from the growth of empirical cases and the effect of the third variables. The reduction of the property-space can also be achieved by resorting to theories, or strong hypotheses, supporting the research, so as to reduce the explanatory factors that need to be considered, thereby attaining greater theoretical parsimony (Collier 1991). In actual fact, this aspect also relates to the second recommendation made by Lijphart (1971): to focus the comparative analysis on key variables (strategy b). In this way, however, we are getting beyond the reduction of the property-space. We simply return to stressing the importance of the theoretical aspect, whose importance for the comparativist must be placed squarely in the foreground. In this phase the researcher is faced with another concrete problem. If the number of cases is increased, and, where necessary, the time span considered is extended and the number of analysed variables is reduced, in order to obtain a good result the researcher’s theoretical-conceptual framework will need to be clearly articulated, the research will require a very well-defined focus, and it will need to draw on previous research as well. If this were not so, that is, if it were not possible to rely on articulated theories or concepts, if a reference literature were not available, and it was a case, therefore, of conducting “new” research, the researcher would inevitably be led to increase the number of aspects to consider and, equally inevitably, would reduce the cases and perhaps the period in question as well. In reality, however, in some sectors the opposite has occurred. For example, Ferrera (1991) shows that the opposite strategy has been followed, perhaps unconsciously, in studies of the welfare state. To analyse one of the most important phenomena in modern democracies, through which efforts have been made to give substantive content to democracy in the Western world, the itinerary of research started from works with very specific hypotheses and quantitative temporal series, before then moving towards qualitative studies of individual cases in which the different relations were analysed better and more thoroughly. In this case, certain criticisms of the limitations and reliability of temporal series, the need for in-depth analysis and, inevitably, the necessity to 44

increase the number of variables considered in order to achieve a fuller understanding of the phenomenon, benefitted from what had been done previously, following a strategy perfectly in keeping with Lijphart’s suggestions. The reference to this final strand of studies enables us, however, to note that in the most recent developments in comparative politics the existence of “small N” is no longer felt to be a problem. Indeed, for some time there has been a tendency “towards a more elaborate justification of the wisdom of concentrating on relatively few cases” (Collier 1991, 119). This tendency, moreover, reflected a shift in the social sciences, starting in the early 70s, towards “interpretative” interests. Characterized by the spread of “configurative approaches”, qualitative research and “dense descriptions”, the limited number of cases provided fertile terrain for growth (see also Mair 1996). Box 4.5 The “problem of the comparative method”, also known as the “many variables, small N” dilemma. relates to the selection of cases and of the relative properties/ variables. According to Lijphart, this dilemma can be tackled from the point of view of the variables and/or that of the cases. Two strategies to deal with the former are to: a) reduce the “property-space” of the analysis, that is, the number of properties/ variables to consider; b) focus the analysis on the key variables. As regards the latter, two further strategies are to: c) increase the number of cases as much as possible; d) focus the comparative analysis on comparable cases.

Questions      

What are the main criteria that can be applied to identify the research issue? What are operative definitions? Why do we often need them in comparative research? What do we mean by “operationalization”? What is an indicator? What is the “many variables, small N” dilemma in comparative research? How can we deal with it?


5. What to compare: space and time 5.1 Dimensions of comparison The issue of what to compare can be dealt with by looking at three different dimensions. The first was discussed in the previous chapter and concerns the properties (or variables) to analyse. The characteristics of the other two can be easily guessed by looking at examples such as government capacity and institutional reforms in Italy; transition to democracy in Eastern Europe; the effective accountability of government and the actual capacity of the governed to punish it. These examples suggest how comparison always entails the specification of: a) a spatial-horizontal domain; b) a temporal-longitudinal span.

The combination of choices relating to these three crucial dimensions of empirical endeavour – units of analysis, space and time – define what can be described as a research strategy. More exactly, if we focus on the second and third dimension we can distinguish between synchronic and diachronic strategies, depending on whether the analysis of cases and their properties is limited to a relatively reduced time span or covers a broader period instead. Moreover (see chapter 6), we can also differentiate between research strategies that are extensive or oriented by the variables, when we consider just a few or even one property in a very large number of cases, and intensive or oriented by cases, when we examine a limited number of cases, maybe even just one, but study a large number of properties (Ragin 1987; 1994). The relations between these three dimensions and the relative research strategies are represented in Fig. 5.1. Taking account of the above dimensions, a definition of comparison can now be proposed: it is the method of examining two or more states in terms of one or more properties, singled out in two or more cases in a specific moment or in a more or less broad time span (see also Fideli 1998, chap. 1). A further “substantive” aspect also emerges from the examples. If we look carefully at the research issues that have been raised we see that they all relate to macropolitics. For ease of analysis, what we are referring to here is the concept of the political system understood as regime, state and political community as a whole, and to the numerous and variegated realities, which may be very different and far removed in space and time, to which the political system relates. A very broad sector of traditional and modern political science has explored the various themes of political systems, or parts, elements and components of them, “carved out” in the most diverse ways. Within such 46

studies a long, consolidated and broad tradition of macropolitical comparison has been developed.

Figure 5.1: Empirical dimensions and research strategies Source: Bartolini (1986, 45).

Consequently, comparison is not just of “whole” (political) systems, or their dynamics of change (installation, consolidation, crisis, collapse), but also of parts, elements or components thereof. These include parties, movements, interest organizations, electoral laws, parliaments, national and local governments, besides policies relating to different ambits (local, national, supranational) and categories (regulatory, constitutive, distributory, redistributory). In other words, macropolitical comparison could concern all the static and dynamic aspects of political regimes, political actors, policies and civil society, and


their reciprocal relations (see, for instance, Morlino, Badie, Berg-Schlosser 2017, chs. 4, 9, 12, 13). The most important aspect of this sort of research is that the topic of analysis – political systems, or parts thereof – influence the method of comparison itself. At a macropolitical level, in fact, the realities we want to compare require us to deal with particular methodological issues that do not pertain just to the object in itself – the political system – but also to some of its characteristics. These issues include the challenge of developing a research design at the macropolitical level, dealing with the fact that the number of cases that can be studied is usually limited and, finally, the qualitative nature of the vast majority of the phenomena under examination. Returning to the main thread of the argument, the first step in comparative research is to establish the research issue (what we want to know, describe, explain or understand), and to clarify the methodological aspects (choice of method, awareness of which procedures to use, etc.). A certain amount of theoretical elaboration is then needed: definition of concepts, formulation of hypotheses and classification. The analysis of new data will force us to reformulate our classifications or typologies and hypotheses. This in turn will lead us to search again for further data (in a continual to and fro between theory and empirical reality). Formulating concepts and the relative hypotheses is very important, because the probability of runing up against an enormous quantity of data when dealing with macropolitics is very high: this may induce a certain disorientation, or lead to an attempt to gather all the data, resulting in paralysis. A good theoretical construct permits greater parsimony and provides orientation in selecting hypotheses and bringing the research into focus. As an example, a start might be made on analysing – even if only intuitively for now – Spain, Portugal and Greece, looking at what happened towards the end of the 70s and the beginning of the 80s, or later with the economic crisis of 2008–14. What emerges straight away is the role of the parties, which altered the political equilibria. Note that political parties are just one theme: this already entails a strong degree of focus in the research. But it is important to analyse the party systems, more than the parties in themselves, otherwise many events would not be explainable (and we have already moved twice from theory to reality and back again). A party is an intermediation structure that performs different roles in relation to civil society. It is represented graphically in figure 5.2.


civil society




interests (also organized ones)



party system mass media

bureaucracy (military)


Figure 5.2: Diagram illustrating the intermediation role of parties

Some of the main macrofunctions of parties are:   

vote-seeking: relates to the party’s position with respect to the electorate and to interests, organized or otherwise; office-seeking: relates to the party’s position in parliament, in government and in connection with organized interests; policy seeking: regards the position of the party in decision-making processes, and is therefore linked to parliament, government, parliamentary committees, ministries and the bureaucracy, namely, to other institutions, including local ones.

This “party-centric” view – confirmation of which can be found in many democracies, including the Italian one – has been borne out by research conducted in various countries. Having started with an overly simplified analysis (where the political party was almost the only independent “variable”), we now find ourselves facing a complex grid of variables. If we consider Portugal between the end of the 70s and the beginning of the 80s, it is impossible to ignore the relations between parties and the military, and the civilianization of the political system. If we consider Italy from the early 1990s through to the present we will have to analyse relations between parties and the judiciary: the absence of a genuine political opposition explains the emergence of “functional substitutes” such as the judiciary (or important newspapers). The number of variables continues to increase. 49

All this requires a reduction of the “property-space” (Lazarsfield, Lijphart) and orientation towards “key variables” (Lijphart), but the complexity remains. On the other hand, excessive simplification could produce sterile results. For example, it would be unthinkable to study democratic consolidation in Portugal without considering the role of the military. The (absolutely necessary) operation of simplification consists of choosing between what is more or less relevant, but it must be justified by theoretical assumptions. Theory, therefore, is not just important from a procedural point of view, but also because it permits orientation towards key variables. Box 5.1 The issue of what to compare can be dealt with by looking at three different dimensions: 1) the properties (or variables) to analyse; 2) a spatial-horizontal domain; 3) a temporal-longitudinal span. Focusing on the second and third dimensions, we can distinguish between synchronic and diachronic strategies, depending on whether the analysis of cases and their properties is limited to a relatively reduced time span or covers a broader period instead. We can also differentiate between extensive research strategies, which are oriented by the variables, when we consider just a few or even one property in a very large number of cases, and strategies which are intensive, or oriented by cases, when we examine a limited number of cases and study a large number of properties.

5.2 Deciding the space The next step, which follows on only in a figurative sense, involving as it does an analytic distinction of the various phases, is to establish the spatial area. This involves deciding how many and which cases to include in the research in relation to the theoretical premises (it has already been mentioned that the choice of cases is suggested both by the research topic and the elaboration of concepts and hypotheses). The choice must be balanced, and in a certain sense intermediate: a high number of cases will produce a very rich analysis, and research with significant and intriguing results, but it will also aggravate the problem of the third variables. Here too an example will be useful: if we are focusing on political parties (variable or independent factor) and we analyse Italy, Germany and Austria, the relationship between parties and the military (variable or intervening factor) is virtually irrelevant. If we consider Spain we see that the role of the military had some importance in certain phases. In Greece it is significant in the limited phase of transition-installation. In Portugal the role of the military remained central until the middle of the 80s. 50

It is clear that by increasing the cases, the reality we are studying is enriched, but the weight of other variables requiring analysis increases at the same time. For this reason, the decision about how many and which cases to investigate cannot be based just on available data, but also on the research hypotheses. The choice must be made by carefully weighing up both the advantages (enrichment of the research) and the disadvantages (both at a procedural level – it is difficult to handle a large number of data – and at a methodological one – the problem of the third variables and parameterization). At any rate, the question of the number of cases gives rise to various strategies of comparison, such as case study, binary or paired comparison, area study and the multi case strategy.

5.2.1 Case study Case study is a particular strategy in comparison, associated by some scholars with the historic method, but Gerring (2007) provided a systematic analysis in political science methodology. Its principal characteristic is that a single case is considered. Being able to concentrate on just one case enables it to be examined in depth, even when the available research resources are relatively limited. At least four main types of case study can be identified (see Eckstein 1975, 96ff.; Bartolini 1986, 73ff.), ordered according to the criterion of leastmost theoretical relevance, especially with a view to generalization goals:    

configurative or atheoretical studies; interpretative studies; hypothesis- (or theory-) generating studies; hypothesis- (or theory-) testing studies: a) theory-confirming studies; b) theory-infirming studies.

The first two groups of studies (atheoretical and interpretative) deal with cases selected out of an interest in the case as such. Atheoretical studies are called what they are because they have no theoretical framework and do not even refer to explicit hypotheses or other more elementary theoretical constructs. This type of case study represents an extreme pole, in that every analysis is in reality guided – perhaps only to a minimal degree – by some vague and occasionally confused theoretical notion. Though they are highly descriptive studies – usually dealing with a single nation – they have great importance above all as elementary data-gathering operations; this is essential for the development of comparative politics, which is hampered by a substantive lack of information. Interpretative studies, though springing from an interest in the case examined, differ from the first group in that they introduce theoretical notions


or constructs to the analysis. They may also make reference to existing hypotheses or theories. However, these references are neither systematic nor, in many cases, very in-depth. They can be regarded as “applied science” studies, because they are concerned with “interpreting” or applying a generalization to a specific case in order to analyse it better. The goal of hypothesis- (or theory-) generating studies is to develop generalizations in areas where no theory exists. They attempt to formulate hypotheses that will later be tested on a larger number of cases. These studies have considerable theoretical weight, and are described by Eckstein (1975, 113) as “crucial case studies”, due to their discriminating value for theoretical ends. Hypothesis- (or theory-) testing studies are of two types: 1) 2)

studies designed to confirm a theory; studies designed to infirm a theory.

These are analyses of individual cases within the framework of existing theories. In this sense, the study of a case is a test of the theoretical proposition, which may be confirmed or infirmed by the case itself. If the case study is of the confirming type, it reinforces the proposition in question. Likewise, theoryinfirming studies may weaken the generalizations, though only marginally so, in that a single case cannot be definitively significant. However, the theorytesting value of both of these types of study increases if the cases are, or tend to be, extremes on one of the variables. In such circumstances, they can be considered to offer important proof of the theoretical propositions. Some authors, including Lijphart (1971), suggest the importance of another case study method: the analysis of deviant cases. This involves studies of individual cases that deviate from largely accepted generalizations. Such cases are chosen to reveal why they are deviant, and can lead to the discovery of important additional variables that had not previously been considered, or even to perfect the (operational) definitions of some, or all, of the variables. From this perspective, deviant case study (like the hypothesis-generating study) can acquire considerable theoretical value. In fact, although it weakens the original theoretical proposition, at the same time it suggests a modified proposition that is stronger than the previous one. Its function may, then, be to refine existing hypotheses, unlike hypothesis-generating studies which serve, as their name suggests, to produce completely new ones. Lijphart also reaffirms how deviant case study and theory-confirming and theory-infirming studies are implicitly comparative analyses, in that the various cases are compared in order to create hypotheses better able to pass the empirical test. However, it should be noted that theory-infirming researches and deviant case analyses basically overlap. What differentiates them is the hypothesis that the deviant case is a sort of


exception in the context of a theory that is not completely disproved and therefore rejected. Bear in mind here that we are still analysing spatially and temporally defined theories. The following table serves as a summary. Table 5.1: Classification of case studies reference to theoretical aspects

identification of the theoretical issue

recourse to hypotheses or theories

testing of existing hypotheses











characteristics case study











5.2.2 Other strategies As already mentioned the other available strategies include binary or paired comparison, area studies and multi case strategy. Paired comparison: concerns two cases. The comparison may be between similar systems with common characteristics (“strategy of most similar systems”) – in this case it has methodological aspects similar to many area studies – or between different systems (“strategy of most different systems”). As regards the latter, the goal is to explain a phenomenon by observing the most distant values or means in each property. The explanation achieved with this strategy is stronger insofar as the great difference existing between the two cases regarding all the main dimensions entails an implicit inference: the explanation should also be valid for all the other cases which are in intermediate positions regarding those same dimensions, or are close to one or other of the two cases examined (see also Berg-Sclosser and De Meur 2009, 20–23). Small-N and area study: between 3 and 8 countries are usually examined in these types of study. However, the small-N strategy involves the choice of a limited number of cases and of a phenomenon with few precise variables and related hypotheses. The area study is more demanding; it considers a particular geopolitical area, including countries with common historic, cultural, linguistic, socio-economic and other traditions. One characteristic is that parameterization is easier in the overall analysis of the nations or of more specific phenomena regarding them. The explanation may take some factors for granted, in that they are common to or very similar for all the cases under consideration. The most widely studied geo-political areas are: the Scandinavian countries (Sweden, Norway, Denmark and then Finland – especially in the 1960s and 1970s); the Anglo-Saxon area (Great Britain, Canada, United States, New 53

Zealand, Australia); recently, the Mediterranean area of Southern Europe (Greece, Italy, Spain, Portugal); Latin America (especially Brazil, Argentina, Peru and Chile); Eastern Europe (in particular Poland, Hungary, Czech Republic, Slovakia); and the Far East (Taiwan and South Korea). Certain area studies – for example those concerning the Anglo-Saxon nations – show that belonging to the same area does not necessarily entail territorial contiguity, but rather the sharing of some traditions and cultural aspects. Other area studies, for instance research into Southern Europe or Latin America, instead show how it is possible to artificially build an area when the same macrophenomenon recurs in the different countries. What makes the “area” in these studies is the research topic, for example the installation or consolidation of democracy, with the goal being to explain the diversity in installation from one case to another. In this regard, it is not necessary that the cases have similar background factors, indeed there may be notable differences in the economy, society and culture of the nations. The logic of the area study is thus reversed: it is not possible to take certain background factors for granted. What is in common is the phenomenon being studied, and the principal aim is to see what differences there are between one case and another, each in its unitariness. In this way, an area strategy ends up being combined with a most different systems strategy, as can be seen in studies of democratic installation in Italy, which is historically very different from the other Southern European countries. Multi-case strategy: this type of strategy covers a large number of cases, usually more than six and up to 20, 30 or even more. Examples include Lijphart’s study of 25 world democracies (Lijphart 1984), Powell’s investigation of certain aspects of 29 contemporary democracies, including civil order, decisional capacity and democratic efficacy (Powell 1982), and Inglehart’s study of some characteristics of the political culture of 43 nations (Inglehart 1997). The high number of units compared poses considerable problems of simplification and makes it difficult to handle the data that need to be collected; at the same time it entails a reduction of the key variables, which can be justified only theoretically. Finally, multi-case research may be both qualitative and quantitative, like that of Lijphart; or carry out a conventional translation into numbers and thus into quantities of qualitative elements (Powell); or again it might be explicitly quantitative when it is conducted by means of surveys (Inglehart). At any rate, the high number of cases does not just mean simplifying the analysis, but also involves giving greater attention to specific dimensions and variables, rather than in-depth investigation of the functioning of “entire systems”. This objective is better achieved with other strategies, in particular a single case study. In conclusion, this discussion of comparative strategies shows that the number of cases is by no means unimportant for the results of the comparison. The decision to investigate just one case, albeit with the aid of comparative 54

hypotheses already present in published literature (case study – see chapter 7), suits certain questions and objectives; the comparison of two cases, in particular ones that are very different (paired comparison), is appropriate for other questions and goals; the analysis of three to five countries belonging to the same geographic area (area study) for others again. Moreover, increasing the number of cases usually also transforms the type of comparison: there is a shift from a prevalently qualitative comparison to a prevalently quantitative one supported by statistical analysis. The dividing line between the two types often lies below or above five to seven cases. The study of democracies by Lijphart (1984) is one of the few works in which an author has managed to reconcile qualitative and quantitative aspects in an area study with over twenty cases. In rounding off this section, it is worth recalling that two important choices need to be made: how many cases to study, and which ones are most appropriate (comparable cases). Box 5.2 Establishing the spatial area means deciding how many and which cases to include in the research in relation to the theoretical premises. The issue of the number of cases gives rise to various strategies of comparison, such as case study, binary or paired comparison, area study and the multi case strategy.

5.3 Defining the time A further step is to define the time frame, the temporal span within which to conduct the research. The most important comparative studies are diachronic, encompassing a more or less broad arc of time, as opposed to synchronic, where time is not considered as a variable. There are essentially two main reasons explaining the prevalence of diachronic comparative studies over synchronic ones. Firstly, synchronic research is such precisely insofar as time is artificially reduced to a unit and kept out of the analysis. From this point of view it is inevitably less significant. In fact, and this is the second reason, foregoing the temporal dimension precludes an analysis of change; this is an extremely important aspect-dimension in social research, as it concerns all the phenomena that can be studied. Indeed, for many authors (Hirschmann, 1971 and others), it is the most important aspect to study. A couple of examples will help to illustrate what is at stake here. Returning to the hypothetical study of democratic crisis in Spain and Greece, it might be argued that the analysis is synchronic because the phenomena under examination all took place in the same period in the various countries. However,


the importance of reconstructing the process leading to consolidation is quite evident, and can only be achieved by introducing the temporal variable. For the second example, let’s assume that we are interested in analysing the impact that being in government has on parties, observing them in a number of European countries, including Eastern European ones. Time could be reduced to a unit, and we would gain an overall view of that impact. But this would preclude the possibility of ascertaining if and to what extent the duration of government responsibilities has consequences, changing over time, on the parties under consideration (for example, on their organization, leadership, on the relationship between the party apparatus and the elected, and so forth). Something is always forced in synchronic analysis: it never considers a single day, but an arc of time which, even if brief, will necessarily cover a few years. The problem, then, is to define the relevant temporal units. In other words, when dealing with the definition of time, the issue of periodization into phases or sequences always arises. It is a question of getting away from the scheme of a simple account of events, and of analytically singling out moments of transition, moments in which an accumulation of quantities is transformed into a qualitative change, according to a well-known intuition by Marx. Subdivision into temporally defined phases is a very common mode of analysis, and many authors have resorted to it. In economic development, for example, Marx distinguished between a phase of primitive accumulation, a phase of the mercantile economy and a phase of the industrial economy. Black (1966) identifies four distinct phases in modernization, possibly covering very long periods: the challenge of modernization; the consolidation of the modernizing elites; industrial economic changes; and the integration of society. In literature on regime change as well, there is the phase of authoritarian crisis, the phase of transition, the phase of democratic installation and the phase of consolidation, but each one has a briefer time span. At any rate, it is a question of carefully pinpointing the elements and duration of the various chronologically successive phases. When we talk about a sequence we mean something different: what is involved here are phases between which a causal relation has been established. Between the various sequences there is not, then, just a simple temporal succession but a link of cause and effect. For example, in the period around the 60s, a group of scholars (Binder et al 1971) concentrated their efforts on developing a theory of crises. They observed that recurrent crises had taken place during the shaping of the Western democracies, that is, profound turning points in various spheres (identity, legitimacy, participation, distribution). Their underlying hypothesis was that connections or causal relations existed between the crises, and that the empirical referents were the case of America and the European cases of stable democracies. The elements in the sequence were, in their view: nation building; state building; a crisis of legitimation; a


crisis of participation and, finally, a crisis of distribution (of income between different social groups). Also of importance is the resort to time series, covering a span of twenty to forty years, or even much longer, in order to identify turning points, changes, growth, decline, etc. But achieving a full comparative analysis on the bases of these data is not simple, and often it needs to be enriched in qualitative terms. Another useful notion, in which there is the idea of quantitative change becoming qualitative as well, is that of the threshold. First proposed by Deutsch (1962), it was then developed by Rokkan (1970) and by other authors. The threshold is the point at which an accumulation of quantitatively measurable changes leads to changes in the qualitative characteristics of the studied phenomenon. For example, according to Rokkan, when, through gradual widening of limited suffrage, universal suffrage is reached, a fundamental “threshold of incorporation” is crossed. The threshold thus marks the boundary between two phases considered to be in a close sequence, although the term can also be used independently in a simpler sense. With regard to the issue of periodization, then, projects may range from the more ambitious and complex threshold analysis to an intermediate-level analysis based on sequences, and, finally, a simpler phase analysis. In actual fact, sequence analysis is often connected to the analysis of phases; and threshold analysis presupposes or encompasses the other two. The choice of the type of analysis will also depend on the available tools and on our empirical knowledge of the studied phenomena (see Figure 5.3). In the last few years an additional way of analyzing the time dimension has become relatively more widespread. This is so-called process tracing, which will be illustrated in chapter 7. Box 5.3 The time frame is the temporal span within which the research is conducted. The most important comparative studies are diachronic, encompassing a more or less broad arc of time, as opposed to synchronic, where time is not considered as a variable. Common modes of analysis include 1) the subdivision into temporally defined phases; 2) the resort to time series, which unfold over a span of twenty to forty years or longer, in order to identify turning points, changes, growth, decline, etc; 3) the identification of a threshold, that is the point at which an accumulation of quantitatively measurable changes leads to changes in the qualitative characteristics of the studied phenomenon; and 4) so-called process tracing, which will be analysed in chapter 7.



5.4 The problem of multicollinearity The great importance of the temporal dimension in comparative macropolitical research was already evident by the end of the 1960s (see, for example, Moore 1966). Equally evident – then and in the following years – were certain interdisciplinary characteristics of such research. Once again, Rokkan’s study provides a good example.3 The 70s and 80s witnessed the development of a sector which gradually became, at least quantitatively, one of the most important strands of comparative research: it concerned the democratization of political regimes, in which the longitudinal dimension is absolutely essential. For example, crucial aspects of any study of the transition from authoritarianism to democracy in Spain in the 1970s will be an analysis of the Francoist regime, its premises and consequences, together with the evolution of the new democracy. The same could be said about the Chilean transition of the 1990s in connection with the Pinochet regime, and about a number of other cases. In this specific sector of macropolitics, in order to study the change, researchers have often resorted to the concept of “process” (see above and chapter 7). This makes it possible to analytically break down the various dimensions of the change, and, through phases, sequences or even thresholds, to hypothesize different and successive relations between the explained variables. The phenomenon is then recomposed into a single whole, and its differences from other cases are observed. In this form of study, time is a truly fundamental dimension of comparative analysis. Finally, mention must be made of a recurrent issue in macropolitics: when studying the evolution of complex macrophenomena that unfold over time – for instance, social or political modernization, or democratization – it is necessary to address and overcome the problem of multicollinearity. This term refers to the distorting effect, in the causal reconstruction, of a complex macrophenomenon that, in turn, is made up of many other more specific phenomena that take place at the same time and vary in parallel. The difficulty is to find the correct relations among the different phenomena – what causes what – or the causes of the macrophenomenon itself: in fact, as it is generalized, how can its cause or causes be identified? It should not be forgotten that a synchronic variance between the units or subunits that does not also translate into a parallel variance of the whole spectrum of phenomena is not available to us here. The solutions proposed by those who have devoted particular attention to this problem (see, for example, Bartolini 1991, 197) are the following: to start not from the explanation of the general trend, but from that of the individual cases that deviate from that trend; to move on to more systematic planes of synchronic comparison of different cases over time; by accumulating clues and 3 See the publication of the work of Rokkan (1999), edited by Peter Flora.


hypotheses, to reach general hypotheses about the causes of the macrophenomenon in question. In short, to yoke together diachronic research and synchronic research between different units. After all, this is the most logical path to take, in that comparison in itself entails a spatial analysis concerning one or more properties in more than one case/unit of analysis. When this is complicated by the temporal dimension, both dimensions obviously need to be considered. The problem becomes more specific (and technical): how best to combine time and space, above all in the most complex contexts, that is, when multicollinearity is present. Box 5.4 By multicollinearity we mean the distorting effect, in the causal reconstruction, of a complex macrophenomenon that, in turn, is made up of many other more specific phenomena that take place at the same time and vary in parallel. A solution to this problem can be to yoke together diachronic research and synchronic research between different units.

Questions      


What are the three main dimensions of comparison? What is the meaning of space in comparative research? What is the meaning of time in comparative research? What are the main strategies for dealing with the space dimension? What are the main strategies for dealing with the time dimension? What is multicollinearity?

6. How to compare: the key mechanisms 6.1 The available tools Having examined the temporal and spatial aspects of comparison we can now move on to the final question: how should we compare? Some very important analytical mechanisms have been devised by the comparative tradition to answer this, and other tools and research strategies have been added over recent decades. They can be grouped under the following eight headings: 1) 2) 3) 4) 5) 6) 7) 8)

Ogden and Richards’ triangle The rules of conceptualization The Tree of Porphyry Classificatory strategies Mill’s canons In search of new rules for conceptualization Process tracing Configurational Comparative Method.

The first five topics – the principal and more classic ones – will be analysed in this chapter, and the other, relatively new developments in the next.

6.2 Ogden and Richards’ triangle In a treatise on logic published in 1946, Ogden and Richards described the essential components of a concept, delineating the relationship between the term (the word used), the associated meaning and the empirical referent (the object referred to by the word) with a triangle (see Fig. 6.1): Figure 6.1: The “structure” of a concept


Any empirical concept has a triangular ‘structure’. More precisely, constructing a concept presupposes that the three aspects, or rather the three sides of the triangle, are specified appropriately. This is in order to avoid the problem of ambiguity, which arises if there is no clearly fixed and unequivocal connection between term and meaning; of vagueness, caused by the failure to determine the empirical object to which the meaning refers; and of banality and the formation of untidy concepts, which can come about if the meaning is poorly articulated and organized with regard to the term and the referents (Sartori 1984, 34). For example, the term ‘political party’ is ascribed the meaning of a “coalition of men seeking to control the governing apparatus by legal means” (Downs 1957 and 1985, 24). Entities with these characteristics are recognized as political parties, such as the Labour Party and the Conservative Party in Britain, the Partito Democratico and Forza Italia in Italy, and innumerable cases in other democratic nations. In everyday usage the relations between these three elements are often confused, in that different meanings and different empirical referents may correspond to the same term. In scientific language, however, the elementary rule that corresponding to each term is a single meaning and a single set of empirical referents is fundamental. This rule – deducible from Ogden and Richards’ triangle – is very important, because, in the concrete experience of research, enormous tension can be created between the referent and the meaning. A corollary of this suggestion is that in scientific language there can neither be synonyms (different terms with the same meaning) nor homonyms (the same word used with different meanings). This corollary evidences a substantial difference between everyday language, in which there are synonyms and homonyms, and special or “scientific” language, which aims to have, for each term, a concept with its own well-defined meaning and precise empirical referents. We need to keep this point firmly in mind, despite being fully aware, as many authors have stressed, that a rigid neopositivist division between the two types of language is not entirely sustainable (Collier 1991). Indeed, the difficulty stemming from the use of the same terms with different meanings and empirical referents came very much to the fore with the growth of international cultural relations. The difficult relationship between term, meaning and referent lies at the heart of conceptualization, that is, of the formation of empirical concepts. Good conceptualization must succeed in taking account of the far from simple relations underpinning Ogden and Richards’ triangle. The knotty problems do not so much concern the empirical concepts in a narrow sense – we have already mentioned operationalization in chapter 3 – as the normative ones, whose existence on the empirical plane, even to a partial extent, we wish to detect. These concepts concern ideals and values, and referring to indicators and good empirical referents will not suffice for these. Instead, we need well62

developed conceptual constructs that are also able to detect the different degree of presence of a certain aspect. It should be mentioned in this regard that many very important concepts in the social sciences relate to ideals. Some have a dual value: empirical and ideal. And this dual value needs to be maintained, because, in analytic terms, it is useful to stick as closely as possible to the current usage of the word, in order to give greater heuristic – that is, interpretative – force to the concept. For example, the concept of democracy is a ‘dual’ term, and one that has challenged dozens of authors, prompting a particularly significant and still ongoing debate (see Morlino 2003). This debate teaches us, at the very least, that many normative definitions are conditioned by the historic and cultural context. For example, the term ‘democracy’ will suggest different empirical referents to a Western European, an American and a Russian. Dahl coined the term ‘polyarchy’ to get round the problem of choosing an empirical definition for democracy (preserving its normative one). But the neologism did not become part of the political debate, and it remained marginal in the scientific debate itself, despite formal acknowledgments of Dahl’s attempt. To clarify the relationship between the empirical and the ideal value of a concept, in the democracy example we can use the distinction between the ‘minimum’ and, as it were, the ‘maximum’ definition of democracy. In conducting an empirical analysis of democratic transitions and installations it is important to provide a minimum definition spelling out a few essential, and readily testable, aspects, which can be used to establish a threshold beneath which a regime cannot be considered democratic. In this perspective regimes are regarded as democratic if they display at least: a) universal male and female suffrage b) free, competitive, recurrent and correct elections; c) more than one party; d) different and alternative sources of information. An important aspect of this definition is that if just one of these aspects were absent or were to disappear we would no longer be talking about a democratic regime, but of another political-institutional arrangement, possibly an intermediate one characterized by varying degrees of uncertainty and ambiguity. Finally, it is again worth stressing that the minimum definition should focus on the institutions characterizing democracy: elections, competing parties (at least potentially), pluralism in the media. In this way they can tie in with classic definitions like those of Schumpeter, Dahl and Sartori, but the level of abstraction of those definitions can be shifted onto the more immediately empirical plane of institutions that are indispensable for a democratic regime. The minimum definition logically implies that there can also be a maximum definition. If we remember that democracy has the characteristic of being at once a descriptive and a prescriptive term, the maximum definition must necessarily take ideals or principles as its point of departure, rather than concrete institutions, as the minimum definition does. A maximum definition, if formulated effectively, would be particularly useful precisely for the analysis 63

conducted here, which sees a further phase of the democratization process in the growth of “democratic quality” (Morlino 2003). In fact, on the basis of such a definition, appropriately operationalized empirically, we could understand both the distance of individual, real democracies from the maximum one, and the degree of democraticity of the regimes that have exceeded the minimum threshold indicated above. A maximum definition does not however exist as such. Indeed, it is not possible either to fix the point or points of arrival of principles and ideals that are also constantly evolving. In a more limited way, also in pursuit of the objectives indicated above, we can provide a definition that indicates the possible directions of development of contemporary democracies, bearing in mind the principles or ideals that inform them in the relatively fuller realization of the ‘power of the people’. To cite Sartori (1987, 719), the problem of the maximization of real democracies is, in effect, more precisely that of optimization, once the ideals and directions of development have been established and efforts are made to gradually attain them. We have thus returned to a definition of democracy better described as ideal or normative. The efforts of various authors to order and measure real and existent democracies (e.g. Freedom House, various years) therefore seem of little use. Instead, we need to start from the principles underpinning democracy. From this point of view, a broad consensus could be found for the affirmation that the two values which should realize a contemporary democracy are freedom and equality. Whether this leads to the autonomy of the individual, and whether individual autonomy is ultimately the crucial aspect of democracy, as Held argues (1989, especially chapter 9), seem not to be essential issues in the definition of an ideal democracy, which can be specified in the simplest way as the regime that creates the best institutional opportunities for achieving freedom and equality. And where, therefore, the problem can become an empirical problem: that of detecting the quantum of freedom and equality actually existing in a given country in a given moment (see Diamond and Morlino 2005). Box 6.1 Ogden and Richards’ triangle describes the relationship between the term (the word used), the associated meaning and the empirical referent (the object referred to by the word) of a concept. The triangle is a tool that can be used to tackle the problems of ambiguity, vagueness and banality in scientific language, in which there should be neither synonyms (different terms with the same meaning) nor homonyms (the same word used with different meanings).


6.3 The rules of conceptualization The problem, then, concerns above all the formation of concepts, the attempt to precisely specify the meaning and empirical referents. In this regard, do the indications that emerged in the previous section prompt us to suggest some rules for defining a concept? In a strict sense, such rules do not exist. We have different definitions instead: declarative or analytic definitions, which are descriptions of the use of a certain term on the basis of an empirical test; stipulative ones, which create a new meaning useful in a certain way for some theory; and explanatory ones, partly declarative and partly stipulative, which draw on the more or less current use of a concept without eliminating the formation of a meaning theoretically useful for a new observed reality. In any case, the most important recommendation is that of Sartori (1975, 7– 8), who urges researchers to follow a number of elementary rules. a) First of all, it is necessary to maintain a terminological anchoring, making reference to the etymology (for example the Latin and Greek roots of the word) and above all respecting the central meaning as conveyed by the original use of the term. For example: the term ‘dictatorship’ originally referred, in ancient republican Rome, to a temporary, elected magistracy set up to deal with an exceptional moment of crisis. In the common-sense understanding of the term, but also in refined definitions, the word’s meaning gradually and completely changed. Other terms fared similarly. b) A historic anchoring also needs to be maintained, by observing what use the word actually had and has. The evolution of a term’s meaning in history needs be observed, avoiding the trap of “total conventionalism” – the attempt to link all language to convention, to replace at all cost the original meaning with the conventional one – into which it is easy to fall. In short, formulating concepts requires knowledge by the person using a certain term of the past vicissitudes of the word.

John Stuart Mill warned that, when comparing, it is important to make continual connections between hypotheses and empirical aspects, in other words to move to and fro between theory and reality. This is all the more necessary when dealing with important and complex concepts such as the process of democratization, transition, installation and consolidation. Reality is extremely rich and complex, so it is indispensable to choose correctly formulated concepts. An example of an erroneous formulation of a concept is represented by the term ‘party government’. Originally used by Schattschneider in 1942 to indicate the US government system, the expression proved popular, and ended up being used with a meaning so vast that it could include all the current democracies – despite the fact that the role and importance of parties has been, and is, very different in Italy, France, other European countries and in the United States. It is probably worth recalling that a concept has sense if its use enables us to ‘cut’ reality, rather than ‘grasping’ it all. An all-inclusive concept is hard to 65

use, and requires further specification. A useful concept is one that allows us to distinguish between possible empirical referents, in other words, one that helps us to make a selection from the many existing cases. For example, almost all regimes nowadays profess to be ‘democratic’, and indeed more and more of them satisfy a minimum definition of democracy. This means that the term is no longer adequate, and it is not possible anymore to distinguish between regimes in terms of a simple contrast between democracy and non-democracy. What emerges on the one hand is the normative aspect, linked to the ideal definition of democracy (what it should be); and on the other, two empirical aspects: the more ‘modern’ one concerning the specifications necessary to define democracy in its different concrete realizations, often with notes of ambiguity (‘protected’ and ‘limited’ democracy, for instance), and the ‘classic’ aspect (how to distinguish democracy from authoritarianism). c) A final suggestion for a correct empirical definition of concepts is to take account of the meanings attributed to similar concepts, obviously on the basis of the two kinds of anchoring mentioned above. It should be borne in mind, then, that no definition is given in a void, and it must always be linked to the various contiguous concepts forming part of the same “semantic field” (Sartori 1984).

There are at least two concrete advantages to proceeding in this way. The first is that a piece of research that then proposes relations and possible explanations for similar phenomena can be articulated with much greater clarity. For example, if we define and appropriately distinguish between democratic consolidation and political stability, we can gain a better understanding of the relations between the consolidation process and one of its consequences, namely stability, in the empirical cases studied. The second is that no superfluous work is done, with duplications of the meaning or referent. If we define consolidation in the same way in which stability is usually defined in specialist literature, we will have done work there was no need for, in that the second concept would have been sufficient for our research. In this sense, then, it is best not to have any juxtapositions of meaning between different terms or concepts; this will also prevent overlaps between the associated empirical referents. However, the word–meaning–referent triangle involves another aspect useful for the formulation and treatment of empirical concepts. To clarify this point we must introduce a second essential mechanism of comparison, the Tree of Porphyry. Box 6.2 We have different types of definitions, which may be declarative, analytic, stipulative or explanatory. According to Sartori, at least three rules should be followed: maintaining a terminological anchoring, a historic anchoring and remembering that as no definition is given in a void, a concept must always be linked to the various contiguous concepts forming part of the same semantic field.


6.4 The Tree of Porphyry The Tree of Porphyry, named after an ancient neo-Platonic philosopher and reworked by Cohen and Nagel (1936) (see also Goertz 2006, chapter 3), helps us to understand the fundamental rule whereby the connotation and the denotation of a concept are inversely related What does this mean? To answer this, it is worth returning to Ogden and Richards’ triangle. The side linking the term to the meaning regards what we can call the connotation or intension of the concept, namely the set of essential defining characteristics and properties. The side connecting the meaning with the empirical referents (or objects) defines the overall denotation, known or expected, that is to say, the empirical extension possessed by the concept in question, in other words the set of empirical referents to which it applies. The connotation of the concept of the political party, for instance, will be delineated by its being an institution made up of a more or less organized group of people, who are at the centre of elections, as they recruit candidates, form lists and participate in the election campaign; of government, in parliament or the cabinet or in other informal decision-making bodies at a central and local level; and of the drawing up of policies in a broad spectrum of sectors. Evidently the term has a complex connotation. The corresponding denotation is simpler, identifying in the different democratic systems the institutional actors to which those connotative properties apply. Connotation and denotation are, then, very important for delineating the level of generality of a concept and, above all, the possibility of obtaining, with a certain logical clarity, concepts with lower levels of abstraction. The Tree of Porphyry helps to make this point clearer. Schematically – and with a certain liberty compared to the binary formulation proposed, in my view effectively, by the philosopher – the Tree of Porphyry can be represented as follows, as a tree with upside-down branches (see figure 6.3). It clearly illustrates the logical procedure of the ladder of abstraction, also called the ‘ladder of generality’, which moves from the more general to the more particular, and vice versa; it shows, as a consequence, the connection between connotation and denotation. If framed in the logical procedure of the distinction per genus et differentiam ― or classificatory logic ― it is evident that there is an inverse relation between empirical referent and meaning, between the ambit of extension and the ambit of connotation: the bigger one is, the more limited the other must be, and vice versa. The Tree of Porphyry, then, is connected to Ogden and Richards’ triangle: the latter shows the fundamental mechanism of the definition of an empirical concept; the former its articulation through the ladder of abstraction.


Figure 6.2: The Tree of Porphyry

Lazarsfeld, as we have seen, takes the two conceptual operations into account when he talks of the property-space (all the significant aspects of a concept), trying to single out the empirical referents falling within that space: the broader the property-space, the more limited the empirical referent. It is worth stressing this rule because, though fundamental, it is very easy to neglect it when formulating concepts. Faced by the operation of conceptualization, researchers generally try to increase the connotation, specifying the meaning of the term as much as possible, but at the same time they try to increase its empirical reality, thereby amplifying the referent. In short, there is a tendency to maximize connotation and denotation at the same time, in the hope of obtaining more significant and important concepts. The risk here, as Sartori points out, is that of conceptual stretching – broadening the extension or denotation of a concept without a corresponding reduction of the intension or connotation, namely the characteristics or properties of meaning – which, as we have seen, is the principal cause of a certain misclassification. For example, the notion of consociational democracy propounded by Dutch scholar Arend Lijphart corresponded to a series of precise characteristics that included a referential culture and a society divided by ethnic, linguistic, religious and other cleavages. However, with the diffusion of the term in the political lexicon, and its increasingly widespread use, it lost its original meaning, and the empirical referent broadened out of all proportion, resulting in the problem of conceptual stretching. For example, the term has also been used for Italy, in reference to the period of national solidarity in 1978–79 , or even to the previous period of the communist ‘abstentions’ of 1976. From the point of view of comparative politics, there is, then, an issue of ‘good classification’. It is therefore wise, for classification purposes as well, to return to the rule already used to obtain a good conceptualization. When moving from the empirical concept to classification, the point of departure can be a general notion, such as democracy; we single out different dimensions for this notion (segmentation), and for each dimension pinpoint the most specific


aspects (specification), proceeding if necessary through genus et differentiam, from the more general to the more specific. In this ambit, closely linked to classificatory activity, as we have seen, lies the correct use of the ladder of abstraction or generality. Sartori, it will be remembered, makes it a central point of his proposal on how to compare. The use of the ladder of generality is also crucial for comparison precisely insofar as it makes it possible to carry out, with greater rigour, the subsequent testing of the hypotheses at the same level of generality for all the cases under examination, and then at different levels of greater or lesser abstraction. It thus permits researchers to formulate more general, but often also less significant, hypotheses, or, on the contrary, to construe the same hypotheses, specifying them as they gradually go into the details of the cases and the variables considered increase, while the potential empirical referents diminish. In short, the Tree of Porphyry helps us to tackle and solve this problem, permitting the elaboration of a good classification. Indeed, it constitutes the graphic representation of a ladder of generality, which, once again, can be depicted as follows: Figure 6.3: The Tree of Porphyry and classification

Why, then, is the ladder of generality so important? Because it offers the opportunity to pursue two goals at the same time: a) A cognitive-exploratory goal (note that some sciences, such as biology, are exclusively classificatory), which represents the basis for achieving a good classification, when passing from the genus to the differences. b) an explanatory goal, by means of parametrization, the necessary and essential operation through which a factor is rendered constant in order to analyse the variation of other factors. Parameterization is used in statistics, but can be more relevant in comparative politics. Smelser (1976), for example, makes parameterization a central element of comparison.


Parametrization is one of the most interesting analytic operations available to researchers, especially when comparing cases that can only be treated qualitatively. If we do not want to resort to a fairly weak mental experiment, how can we evaluate the impact of a given factor on another one that we want to explain? If we were in the field of statistics, the operation would be obvious: to parameterize, that is, to make constant or invariable all the other factors that might potentially influence the phenomenon we want to explain. For example, if we want to understand the impact of gender on voting behaviour, all we need to do is to render constant, that is without influence, all the other factors that might have an impact, such as age, place of residence and social class; and within sub-classes so determined, that is, sub-classes comprising people who live in the same or similar areas, are close in age and have a similar culture and social class, but a different gender, to see what differences, if any, there are in voting behaviour between men and women. If at this point in the analysis the differences disappear, then gender is not determinant for voting behaviour, while if they remain or are accentuated, it is. It is evident from the example above that classification plays a key part in parameterization in a statistical or ‘quantitative’ treatment. But at a qualitative level too, parameterization is obtained through classification. More precisely, classification is carried out in such a way as to render constant the criterion used to distinguish between one class and another. Then, within each class, the ladder of generality is used to identify sub-classes with which the hypotheses that interest us can be tested. Another example should help to illustrate the advantages of parameterization in comparative analysis conducted with qualitative data. Suppose we want to explain the electoral success of parties in different countries. First of all, we can classify the chosen parties on the basis of organization, and then see whether, of those parties with a similar organization, some have been successful and others not. If so, then organization, which has been parameterized, is not pertinent for explaining the electoral success, and we will need to consider other explanations, such as media relations, the role of the party leader(s) and so on. But each time we can parameterize through careful classification and test the impact of the chosen factor we keep as a variable. In short, classification and the ladder of generality can serve to empirically test hypotheses about as yet undemonstrated causes by means of parameterization. There is however a concrete problem: while, in descending the ladder of generality, we may be able to explore a certain relationship in the ambit of a given class, we may also run the risk of having too small a number of cases, only finding confirmation for weak relations. To be pregnant with meaning, classifications require a broad empirical background. For example, from a general and minimum definition of democracy it is essential to move on to precise and differentiated definitions – such as the definitions of consensual or majoritarian democracy (see below). 70

Box 6.3 The Tree of Porphyry helps us to understand the fundamental inverse relation between the connotation and the denotation of a concept. This relation has also been described by Sartori as the “ladder of abstraction or generality”. The connotation or intension of the concept is its set of essential defining characteristics and properties, while the denotation or empirical extension of the concept is the set of empirical referents to which it applies.

6.5 Classificatory strategies As known, classification is the “systematic arrangement in groups or categories according to established criteria” (Merriam-Webster Dictionary). In other words, it is the operation of singling out a distinctive criterion for differentiating between different realities and for attributing those realities to individual classes. It should be added, however, that political macrophenomena such as parties, pressure groups, parliaments, governments, electoral laws, participation and so on do not readily lend themselves to being distinguished on the basis of a single criterion. The classificatory result is poor and basically a distortion. More frequently in political science resort is made to typologies, that is, intellectual operations describing and surveying reality, previously defined on the basis of more than one distinctive criterion. Although the vast majority of typologies use two criteria, some use three or, in a very few instances, four. Why this happens is fairly clear. A two-criteria typology with three classes for each criterion is already a typology with nine cells and, therefore, types. One example might be contemporary democracies, which could be distinguished on the basis of two criteria. One might regard the relations between the executive and legislative bodies, distinguishing between 1. president-leader of the elected executive not supported by parliament; 2. prime minister and government dominant over a parliament that expresses its confidence in the government, and 3. equilibrium between the executive and parliament, which enjoys autonomy in the legislation that is approved. A second criterion might concern the electoral law, and distinguish between: 1. majoritarian laws; 2. two-round majoritarian laws; and 3. proportional systems. Applying the two criteria together, we would have a typology with nine different cells, which would already be a complex result. If there were three or four distinctive criteria, that quantum of parsimony belonging to a typology would disappear. Clearly, therefore, elaborating classifications or typologies is not a simple operation, and to do it well a number of basic rules must be respected. The first is the necessity to choose the dimension or dimensions considered to be essential in the field of study – the relevance of the criterion – maybe only in 71

relation to the purposes of the research. This was discussed in chapter 4. We might add here that a criterion is effectively discriminant and significant if the cases considered are distributed fairly regularly between the different resulting classes. That is, if, for example, a classification of interest groups entails that the majority of groups lie only in one or two classes then the proposed basic criterion can be judged to be not very discriminant, and therefore ill-suited for a correct classification. We might also add the two classic rules postulated by Mill (1843 and 1967), exclusiveness and exhaustiveness. The first rule envisages that the classification must be formulated in such a way that a certain reality belongs exclusively to a class and cannot belong to another one at the same time. In other words, the distinctive criterion assumed to be essential in a certain classification must have a strong discriminating power. Exhaustiveness means that each class deriving from the formulation of that criterion must include all the assumable objects or realities. Overall, a good classification of public policies must give rise to different classes into which all public policies fall. If, instead of a classification, we want to construct a typology, a fourth and very important rule needs to be added: the second, third or, at any rate, the last criterion used in constructing the types must not overlap in the slightest with the first criterion. It must, that is, concern different aspects with respect to the first criterion used. If in addition to the relations between the executive and legislative branches we were to use the system for electing the head of the executive as the second criterion for distinguishing between democracies there would be a partial overlap, considering how that criterion was formulated above. Classifications and typologies pose various problems, but at least two deserve particular mention. The first is that the classes, or types, must be situated at the same level of abstraction. The ladder of generality placing denotation and connotation in an inverse relation must be respected. Classes regarding a more particular level should not be included. For example, a democratic typology cannot distinguish between majoritarian, presidential and consensual regimes, because presidential regimes are, if anything, a sub-type of majoritarian ones. The second problem stems from the fact that a typology, and even more so a classification, greatly simplifies reality in that it filters complex, multidimensional realities like democracy, parliament, government and so on through two or three criteria at the most. The loss of information and empirical richness is enormous. One way to get around this, at least in part, is to elaborate complex classifiers. So, for example, behind the criterion of the relations between the executive and the legislature there are more specific dimensions that are recomposed in the resulting classification, which therefore exists as such in a rather forced manner. The more specific dimensions are in the proposed example: the mode of formation of the executive (direct, indirect or parliamentary election of the head of the executive); the presence/absence 72

of a relationship of confidence, which may not coincide; a monocratic executive or collegial executive. In this sense the proposed criterion was composite, and in turn concealed a typology. The other way of maintaining a greater wealth of information is to resort to multidimensional models. In the social sciences the term ‘model’ has been used in very different ways (Bruschi 1971). Here, we will attribute to it the same meaning proposed by Weber for his ideal type. The German sociologist (1922 and 1958, 211) understood this term as a “one-sided accentuation of one or more points of view and by the synthesis of a great many diffuse, discrete […] phenomena, which are arranged according to those one-sidedly emphasized viewpoints into a unified analytical construct. […] This mental construct cannot be found anywhere in reality and its purpose is to single out the key features that recur in most cases of the phenomenon under scrutiny. In this perspective, the notion of the ideal type effectively corresponds both to how an empirical concept can be formed – it barely needs saying that the Weberian ideal type constitutes a different way of constructing concepts compared to what we said in chapter 3 – and to the characteristics of a ‘model’, that is, to a more specific notion in which different dimensions or aspects are joined together within a certain phenomenon, without there being a genuine classification or typology as such with an explicit indication of discriminating criteria (on this topic see also Goertz 2006, 83–88). Thus, there are also ideal types or models of democracy, like the majoritarian and consensual ones proposed by Lijphart, who considers and groups together ten dimensions; there are models of authoritarian regimes, resulting likewise from the inclusion of various dimensions; and there are models of parties. In short, the undoubted advantage of using models is that of avoiding the strictures imposed by a correct use of the classificatory logic and its rules, which we outlined above. From this point of view, the most correct research strategy is one that employs classifications and typologies alongside models, in relation to different and specific research goals, in order to obtain the best possible results. To this end, two different and complementary directions can be followed: the first, which is a strategy by way of polarities, or, more succinctly, a polar strategy (Lijphart 1984 and 1999), isolates two models with opposite characteristics; while the second, which can be called the strategy of multiple typologies (see, for example, Morlino 1998, 42–49), represents the mechanism of the classical typology, but enriches it with multiple significant criteria, in contrast to more traditional typologies, which do not refer to more than two dimensions. The polar strategy involves singling out a certain number of dimensions assumed to be relevant (from four to six), fixing the poles of each one, and then


analysing the complex case, seeing where it is situated. Schematically, the logical procedure can be represented as follows: __________________________________________________________________________ dimensions I-----X------------------------------------------------------I I----------------X-------------------------------------------I I--------------------------------------------X---------------I I--X---------------------------------------------------------I I------------------------------X-----------------------------I I---------------------------------------------------X--------I X = case studied ___________________________________________________________________________ Figure 6.4: Polar strategy

We can now look at a concrete application. In his ‘polar’ proposal, Lijphart (1984 and 1999) started from the premise that the institutional ‘forms’ of democracy are inspired by two principles, which may be pure or mixed: the majoritarian principle and the consensual one. Each of these two basic principles influences all the significant dimensions of a democratic regime, which can be grouped into two sets, one regarding the executive and parties, and the other concerning the unitary or federal arrangement of the regime. The first set includes the following aspects: 1. single-party or coalition government; 2. dominance of the executive over the legislature, or equilibrium between the two powers; 3. number of parties and significant party system issues; 4. majoritarian or proportional electoral system; 5. pluralistic or neocorporative composition of interest groups. The second comprises: 6. degree of unitariness or federal decentralization; 7. strong or weak unicameralism or bicameralism; 8. a rigid or flexible constitution, to which the author adds other aspects concerning the role of central banks and constitutional courts. A further separate dimension could be the degree to which instruments of direct democracy, such as the various kinds of referendum, are used in that regime. The first polar model of democracy that emerges by combining the different dimensions is called the Westminster model, and is characterized by: the concentration of executive power in one-party governments with slim majorities; the fusion of powers (legislative and executive) and the domination of the government; unicameralism or asymmetric bicameralism (one chamber has greater powers and a different base of representation to the other); a biparty system, with just one significant dimension of conflict, the class one dividing right from left; a majority electoral system (plurality); pluralism of interest 74

groups; centralized, unitary government; flexible constitution and parliamentary sovereignty; exclusive existence of forms of representative democracy (absence of direct consultations). The most important aspects of the second, consensual model are: governments formed by several parties and broad coalitions; formal and informal separation of the executive and legislative branches, to the point of reaching a balance between the two powers: symmetrical bicameralism and a possible over-representation of minorities; multiparty system with many significant dimensions of conflict in addition to the right-left divide (for example, religion, difference between the centre and periphery of the country, environmental issues, profound differences over foreign policy); proportional electoral system; neo-corporativist arrangements, that is, more or less formalized and stable agreements on various economic policy issues between government and organized interests, especially trade unions and business associations; decentralization of powers and a federal structure; written constitution and the power of veto of minorities. In Table 6.1, we can try to schematize Lijphart’s proposal. Table 6.1: The typology of polar models of democracy (Lijphart) Structural features

Majoritarian model

Consensual model

First dimension: Executive power and party system 1. Characteristics of government

single-party governments; slim majorities

coalition governments; generally superabundant

2. Executive-parliament relations

fusion of powers and domination of government

formal and informal separation of powers

3. Party system and political divisions

bipartyism, unidimensional political space

pluripartyism and multidimensional political space

4. Electoral system



5. Representation of interests

pluralistic representation

neocorporativism, bargaining

Second dimension: Unitary or federal structure of the political regime 6. Organization of the State

centralized and unitary government

decentralized and federal government

7. Features of the legislature

asymmetrical bicameralism or unicameralism

symmetrical bicameralism

8. Constitution

flexible and unwritten; sovereignty of the majority; absence of constitutional control

rigid and written constitution; power of veto of minorities; presence of constitutional control

9. Role of the central bank

dependent on the executive

independent of the executive

Third dimension (non discriminating): Instruments of direct democracy 10. Referendum

absent or of little importance



The advantages of the distinction between two polar models are evident. Compared to traditional typologies, much less information is lost because more dimensions are considered; quantitative data can be combined with qualitative data, thereby gaining rigour and precision; finally, within each dimension we can see more clearly how each country is characterized. But above all, the substantive change of one or more of those aspects shows us how the democracy being examined has shifted over a certain period of time from majoritarian to consensual solutions, or vice versa, to a greater or lesser degree according to the number and characteristics of the dimensions involved. In this sense it is a very useful instrument for detecting and analysing democratic change, perhaps limited and partial but nonetheless significant. The difference, which is also a disadvantage compared to multiple typologies, lies, that is, in restricting itself to considering just two models of democracy (majoritarian and consensual), leaving unidentified all the intermediate solutions, which are actually the majority of concrete cases. In other words, its purpose is more to say how much a given case is closer or more distant from the majoritarian or consensual model, or if the change in one of its dimensions is in one direction or another. By contrast, as we shall see, multiple typologies ultimately make it possible to put together more specific models, be they majoritarian or consensual, and in this respect display greater precision in identifying a democracy with respect to the dimensions considered most important. Both strategies are useful. One should not prevail over another. If anything they should be perfected, as in fact Lijphart himself did between 1984 (see 1988) and 1998 (see 1999). The second strategy, that is, building multiple typologies, follows the traditional method of formulating a typology, but with more dimensions and ultimately with more types. For this purpose it is essential to refer to the many important studies of institutional aspects in recent decades (Powell 1982; Lijphart 1984, 1999; Linz and Valenzuela 1994; Sartori 1994; and others). One of the lessons to be learnt from these works is that the electoral system – considered in terms of the essential majoritarian and proportional alternatives, to which we can add, for its effects, a system with reduced proportionality – and the rules at the basis of government in turn form a ‘system’ with various dimensions that coexist and interact with the institutional structures of executive and legislative powers, namely the four institutional types of presidentialism, semipresidentialism, semiparliamentarism and parliamentarism. So, with some simplification and selection that highlights only the empirically significant combinations, the two macro-variables that emerge from this literature can be classified and combined as follows: a1) a2) a3) a4)


Presidentialism and majoritarian electoral system; Semi-presidentialism and majoritarian electoral system; Semi-presidentialism and proportional electoral system; Semi-parliamentarism and majoritarian or reinforced proportional system;

a5) Parliamentarism and proportional electoral system; a6) Presidentialism and proportional electoral system.

In semi-presidentialism, a concept developed by Duverger (1980), the head of state is elected by direct universal suffrage and the prime minister must maintain the confidence of parliament. The consequence of this diarchic structure is that the power of the president is weakened or rendered null by a different parliamentary majority which is strong and united. Semi-parliamentarism is the so-called chancellor democracy, with an institutional arrangement in which the prime minister and his or her cabinet play a much stronger role in legislative initiatives than the parliament. The best-known example of the first type is the Fifth French Republic, while the United Kingdom is generally cited as an example of the second type. Furthermore, it is worth highlighting the specific kind of arrangement in which presidentialism exists alongside a proportional system for the election of parliament. This is the most recurrent institutional solution in Latin America (see Jones 1995). In addition to the aspects concerning executive and legislative powers, a third institutional dimension can help to provide a better definition of the institutional model of a democracy. This is the degree of decentralization in the distribution of power between the central government and peripheral authorities. The chief variables to consider here are: representation of local units on a par with that of the central level, irrespective of their size, through a specific branch of parliament; the autonomy of local units in many areas of policy; and the fiscal autonomy of local governments. Forms and modes of decentralization can be found in each of the four types outlined above (presidentialism, semi-presidenzialism, semi-parliamentarism and parliamentarism). The second set of characteristics defining a democracy concerns the party system. Some authors make a clear historical and logical connection between political parties and democracy (see, for example, Pomper 1992), or even define democracy in party terms (see Sartori 1993, 41). As intermediate institutions, which are at one and the same time vote-seeking, office-seeking and policy seeking, according to the effective classification proposed by Strom (1990), parties (and the party system) can be observed in relation to the performance of various functions. For example, their efforts to obtain (electoral) consensus and mass support; or when they hold government and parliamentary posts at a central or local level; or in the formulation of policies, supported by the parties in government and fought by those in opposition; but also in their relations with the bureaucracy, the armed forces and the magistracy, albeit at the level of elites. The number and relative sizes of parties, some of their specific organizational aspects, and the composition, homogeneity or heterogeneity of the party coalition supporting the government, are the main characteristics that define


the party system in a democracy. Drawing on these elements, a simplified typology inspired by the work of Sartori (1976) can be proposed here: b1) Predominant cohesive party system, with a strong leader and single-party governments; b2) Bipartyism and single-party governments; b3) Homogeneous multipartyism and coalition governments; b4) Heterogeneous multipartyism and coalition governments.

It should be obvious that in each case there may be competition of different forms and degrees. It may change, in fact, due to the impact of various institutional rules: the threshold of access to the political arena, especially the electoral one; the difference between the main parties in terms of votes and seats; the magnitude of electoral volatility in the party system, for which there may be different causes; certain characteristics of the electoral law or of the decision-making process in parliament. However, there is also another set of factors that are essential for understanding a democratic regime. Although this dimension is not generally considered in typological analyses of democracy, its salience should be borne in mind. On the one hand, in fact, it gives expression to more substantive elements of democratic regimes, with social and economic implications; on the other, if the analysis of democracy is linked to the processes of change under investigation, it is useful precisely in the analysis of consolidation, crisis and even installation. This dimension concerns the relations between political institutions and civil society, and it can be placed succinctly along an autonomycontrol continuum. With the qualification that various dimensions are woven together in such a continuum, four possibilities or types can be presented: c1) c2) c3) c4)

Autonomy; Semi-autonomy; Semi-control; Control.

Simplifying the presentation, society can be regarded as autonomous with respect to public institutions, parties included, when the following are found together at the same time: a society with a well-structured associative level, with significant industrial elites, intellectual groups, media, various kinds of association, including strong unions; a relatively limited public sector economy; and parties that do not condition or hegemonize associations and sectors of society itself. On the contrary, there is control when, with an extensive public sector economy, marked by significant and recurrent government intervention in the economy, and a poorly structured society in associative terms, perhaps due to a long period of authoritarianism, parties play a dominant role compared to the few existing interest groups, including that of the industrialists, if there is one; parties are able to condition such groups in various ways,


one of which is through party patronage nominations in public sectors of the economy. Semi-autonomy and semi-control are intermediate types. The first is characterized by civil societies and elites that have a certain autonomy from strong parties present, with a significant public sector economy. The second has a broad public sector and parties capable of conditioning issues and decisional outcomes with respect to a society that is fairly weak, though not crushed by the parties themselves and by the related political elites. It is these intermediate types that are the most interesting, and the ones to which the largest number of empirical cases can be related. Their constitutive ambiguity, insofar as they are intermediate, can be better overcome by making the empirically significant distinction between a society that displays a certain degree of autonomy of its own, at least through business associations and unions with a political line and conduct distinct from that of the government and the parties, perhaps even in opposition to them, and a society that submits to the conditioning of the government and administration and not just of the party elites. Table 6.2: Multiple typology of democracy A. Government institutions

B. Party system

C. Civil/political society

a1. Presidentialism and majoritarian electoral system a2. Semi-presidentialism and majoritarian electoral system a3. Semi-presidentialism and proportional electoral system a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system a5. Parliamentarism and proportional electoral system a6. Presidentialism and proportional electoral system

b1. Cohesive, predominant party with a strong leader and single-party governments b2. Bipartyism and single-party governments b3. Homogeneous multipartyism and coalition governments b4. Heterogeneous multipartyism and coalition governments

c1. Autonomy c2. Semi-autonomy c3. Semi-control c.4 Control

The complete framework is presented in Table 6.2, in which all the main variables are listed. For the purposes of formulating a democratic typology, the combination of the variations of the three macrofactors yields different types or models of democracy. It is therefore opportune to make a selection which, simplifying the overall picture, identifies the most empirically significant types of democracy. First of all, there is majoritarian democracy, resulting from the combination of semi-parliamentarism with the reinforced proportional electoral system or with a majoritarian system, bipartyism and a single-party government, and further characterized by autonomy. The combination of presidential institutions with a majoritarian electoral system, with bipartyism and singleparty government, and the autonomy of the executive with respect to the legislature, can give rise to a different majoritarian model. This means that a strong and autonomous civil society establishes the limits and boundaries of a 79

majoritarian institutional arrangement, designed to ensure greater decisional efficacy. Two other important models can be identified: plebiscitary democracy and strongly majoritarian democracy. The first is the outcome of presidential institutions and a majoritarian or a proportional representation electoral system for electing parliament, a solution very common in Latin America (see Diamond 1996 and Jones 1995); of a very heterogeneous multipartyism or of a dominant but poorly organized party, and of a strong leader; and of a society whose main sectors can be controlled or almost controlled. The second model results from the combination of presidential institutions with a majoritarian electoral system, or of semi-presidentialism or semi-parliamentarism with a majoritarian electoral system, with a dominant, cohesive party and a singleparty government or with a homogeneous multipartyism and a coalition government, and with control of society, which does not however go so far as to counterbalance and impose limits on the political institutions. The fourth empirical model of a majoritarian democratic regime is weakly majoritarian democracy. The main features of this model are: parliamentarism and a proportional electoral system, or presidentialism and a proportional electoral system; a dominant, cohesive party and a single-party government or a dominant party, a strong leader and a single-party government; there may also be a relatively autonomous civil society, more or less marked in nature and placing limits on institutions. Among the non-majoritarian models we can establish a continuum between proportional democracy and conflictual democracy. The former is distinguished by a basic coherence between the three levels: in a parliamentary system, elected with a proportional system, a fairly homogeneous multipartyism is created; the most obvious result is a coalition government, with the extensive presence of autonomous groups in society in the shape of unions and other associations. In conflictual democracy there is not the same coherence: parliamentarism or presidentialism and the proportional electoral system are accompanied by a heterogeneous multipartyism. In this case there may be a certain party control of civil society, enabling such a democracy to function. Within this model, a growth in the autonomy of society might cause problems and a probable crisis as well. Table 6.3 sums up the six models that have just been identified and described. These combine the essential aspects of the constitutional design with the ones relating to parties and to relations between political institutions and civil society, also bearing in mind that the concrete functioning of the former is conditioned extensively by the other two groups of aspects.


Table 6.3: Models of democracy Majoritarian democracy a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system; or a1. Presidentialism and majoritarian electoral system; b2. Bipartyism and single-party governments; c1. Autonomy. Plebiscitary democracy a1. Presidentialism and majoritarian electoral system; or a2. Semi-presidentialism and majoritarian electoral system; or a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system; or a6. Presidentialism and proportional electoral system; b1. Predominant, cohesive party, with a strong leader and single-party governments; c4. Control; or c3. Semi-control. Strongly majoritarian democracy a1. Presidentialism and majoritarian electoral system; or a2. Semi-presidentialism and majoritarian electoral system; or a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system; b1. Predominant, cohesive party, with a strong leader and single-party governments; or b3. Homogeneous multipartyism and coalition governments; c4. Control. Weakly majoritarian democracy a3. Semi-presidentialism and proportional electoral system; or a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system; or a6. Presidentialism and proportional electoral system; b1. Predominant, cohesive party, with a strong leader and single-party governments; 2. Semi-autonomy; or c3. Semi-control. Proportional democracy a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system; or a5. Parliamentarism and proportional electoral system b3. Homogeneous multipartyism and coalition governments; c1. Autonomy; or c2. Semi-autonomy. Conflictual democracy a4. Semi-parliamentarism and reinforced proportional or majoritarian electoral system; or a6. Presidentialism and proportional electoral system; b4. Heterogeneous multipartyism and coalition governments; c.4 Control; or c3. Semi-control.


Box 6.4 Classification is the “systematic arrangement in groups or categories according to established criteria”. Typologies are often used in political science, that is, intellectual operations describing and surveying reality, previously defined on the basis of more than one distinctive criterion. Classifications and typologies pose at least two problems. The first is that the classes, or types, must be situated at the same level of abstraction. The second stems from the fact that a typology, and even more so a classification, greatly simplifies reality in that it filters complex, multidimensional realities like democracy, parliament, government and so on through two or three criteria at the most.

6.6 Mill’s canons Among the canons that appear in John Stuart Mill’s System of Logic (1843 and 1967), there is that of concomitant variations, considered to be one of the foundations of statistics. Employed by Durkheim in his researches, this canon analyses and considers the quantitative variations of operative variables. Although Mill himself construed his canons in relation to the inherent logic of the physical and natural sciences rather than the social ones, the canons that interest us because they are pertinent to comparative analysis are 1) the canon of agreement; and 2) that of difference; to this we might add a third canon, the joint one of agreement and difference. It is important to grasp the analytic mechanism that lies behind these two canons, because it can help us to conduct a better comparison (see Table 6.4). The canon of agreement states that “if two or more instances of the phenomenon under investigation have only one circumstance in common, the circumstance in which alone all the instances agree is the cause (or effect) of the given phenomenon” (Mill, 1967, 255). This shows how the central problem is still the explanation of the phenomenon. Indeed, the different aspects of the given phenomenon need to be fathomed with precision and accuracy, and doing so will require great analytic and theoretical clarity in approaching the phenomenon. The method of difference states that “if an instance in which the phenomenon under investigation occurs, and an instance in which it does not occur, have every circumstance in common save one, that one occurring only in the former; the circumstance in which alone the two instances differ is the effect, or the cause, or an indispensable part of the cause, of the phenomenon” (Mill, 1967, 256). This canon is complementary to the previous one, and the method of concomitant variations is, in effect, only a more sophisticated version of it.


Table 6.4: The two canons for comparative analysis The method of agreement Case 1

Case 2

Case 3

a b c

d e f

g h i

Overall differences

x y

x y

x y

Crucial similarity

The method of difference Positive Case

Negative Case

a b c

a b c

Overall similarities

x y

not x not y

Crucial difference

X = causal variable Y = phenomenon to be explained Source: Skocpol (1984, 379).

The method of similarity and the method of difference essentially represent two different ways of looking at the same problem. These two canons reaffirm the need for analytic clarity with regard to all the dimensions of the phenomenon: on the plane of concrete facts it is important to possess the maximum amount of information about the phenomenon. A third relevant canon of Mill is the so-called joint canon of agreement and difference. It combines the method of similarity and the method of difference, and does not therefore add very much more. We can say, then, that in making a comparison we generally start by identifying the common circumstances, but it is then the analysis of the differences that will enable us to gain a more in-depth knowledge of the phenomenon. A couple of examples should help to clarify how to use the two main canons. Firstly, a very important phenomenon, common to some fifteen European nations, was the birth and development of workers’ parties in a certain moment of the history of democratic institutions. We could analyse this phenomenon by pinpointing the circumstances common to the different countries, or by identifying the differences that led to the different results. We can see, then, that adequate analytic clarity will be needed in order to single out the eventual agreements and differences contributing to defining the parties at the level of size, electoral force, organizational structure and so forth. Secondly, subsequent to the process of democratization – and with equal diffusion – the welfare state developed in many countries. Some scholars 83

prefer to underline the common circumstance of the various countries; others privilege an analysis of the divergent ones. It can be observed, though, that the analysis of additional circumstances (i.e., differences) permits a better understanding of the phenomenon, and the definition of something new and more significant, avoiding overly vague common sense generalizations. We can say, then, that in developing our analysis we often tend to stress differences rather than similarities: the method of difference seems therefore to be more recurrent and, in a certain sense, more effective than that of agreement. However, the shared objective of both canons is to reach a more precise explanation of the phenomenon under investigation. In conclusion, Mill’s canons enable us to repropose the distinction between two comparative strategies. They represent two completely different approaches to comparison, and can be traced back respectively to Durkheim and Weber. The first one, the Durkheimian tradition – of quantitative or statistical comparison – is characterized by hypotheses in which the quantitative values of each variable are compared in several cases. The second one, the Weberian tradition – of qualitative or historic comparison – is based instead on the systematic comparison of the cases and the relative properties on the basis of their presence or absence, to determine the resemblances and differences. In this type of comparison the explanation centres on the different combinations of causes. However the two forms of comparison are not mutually exclusive, but supplement each other. Mill’s canons do, however, require a substantial caveat in order to be understood more fully and appropriately, as emerges indirectly from the examples given and how we presented them. More specifically, if understood on the basis of what Mill actually states, both canons entail very strong assumptions: 1. we take for granted that we are able to specify and empirically detect all the elements that come into the explanation of the phenomenon; 2. the explanation is ‘deterministic’ and not probabilistic; 3. it is presupposed that only one cause exists; 4. there are no interactions between the causes that transform the effect; 5. we have the same mechanism which has the same outcome, as it is able to specify and detect all the data in the different cases (see also Lieberson 1992). These five assumptions deserve examination. The first represents a legitimate desire and must be the researcher’s commitment, being understood as such – not, therefore, as an assumption – without creating any blind illusions. Second, comparative explanation is of a deterministic nature if we have a limited number of cases, and Mill’s two canons indirectly recall this. It is wise to be aware of this when conducting comparative analysis. Instead, it is known that with a high number of cases and the use of statistics the explanation becomes probabilistic. Third and fourth, as anyone who has done research knows, multicausality and interactions between explanations must be accepted and subjected to careful research, and in this sense the two relative assumptions should be rejected and the canons understood in a much 84

less rigid sense. Finally, we must take into account conjunctural multicausality (see section 7.3), in which the effect itself may be the result of a different combination of causes and in many cases can only be resolved through a careful application of process tracing (see section 7.2). In this sense, the final assumption can be ignored. All this being said, Mill’s canons point to two models of comparative explanation (see above) that we must bear carefully in mind in our research. Box 6.5 The canon of concomitant variations proposed by Mill considers the quantitative variations of operative variables. The canons that are pertinent to comparative analysis are: 1) the canon of agreement; 2) that of difference; and 3) the joint one of agreement and difference. Mill’s canons represent two completely different approaches to comparison. The first one, the Durkheimian tradition – of quantitative or statistical comparison – is characterized by hypotheses in which the quantitative values of each variable are compared in several cases. The second one, the Weberian tradition, is based on qualitative or historic comparison.

Questions      

What is Ogden and Richard’s triangle? What are the rules of conceptualization, according to Sartori? What is the Tree of Porphyry? What is the ladder of abstraction, according to Sartori? What is the purpose of classificatory strategies? What are Mill’s canons and why are they relevant to comparative research?


7. How to compare: recent developments 7.1 In search of new rules for conceptualization When looking back over the developments in comparative methodology since the end of the 1980s, the most meaningful advances have been made not only thanks to the new statistical techniques that are available, but also due to the efforts comparative scholars have put in to build more accurate, rigorous and reliable qualitative research able to meet the same standards as quantitative analysis. According to some comparativists, this means adopting the key rules of quantitative analysis (see King, Keohane and Verba 1994), while for others (see especially Brady and Collier 2004) a more moderate, distinctive position is possible. When we ask exactly what these advances amount to, and selectively focus on the main results rather than presenting a full-fledged overview, as Berg-Schlosser (2012) very effectively does, we should include at least the following:    

a rethinking of the rules for conceptualization; the successful development of process tracing; some attempt (albeit not always successful) at formalization; and the configurational comparative method, with a focus on qualitative comparative analysis (QCA).

This section is devoted to the first issue. But before starting, it should be recalled that decades of empirical research have made us aware that on some occasions a term may change meaning because of a change in the empirical referents, while another term might become outmoded, empirically applicable to the past but no longer relevant for contemporary realities. Two examples will serve to illustrate this. Consider the word ‘democracy’: until the first decades after World War Two, even cases in which white voters only or male voters only were allowed to vote were included under this term. Think of the US, for instance, until the civil rights movement of the 1960s, or Switzerland, where the female vote was only introduced in 1971, following a referendum. After the 1970s, these kinds of political regimes started to be regarded as authoritarianisms in political science literature. For example, Linz considered South Africa before the Mandela democratization years as an authoritarianism sub-type, labelled as a “racial democracy” (see Linz 1975). Until 1971, Switzerland could also have been considered an authoritarian regime with a limited vote. This change of categorization is the result of a change in the meaning of the same term, in our example ‘democracy’, with effective universal male and female suffrage becoming a necessary and key requisite. Alternatively, a term may become a historical one, due to the disappearance of the realities to which it refers. A good example of this is ‘mass integration party’, which used to be 86

a highly organized party with a strong ideology and a large number of militants. But when the traditional socialist and communist parties changed radically, or even disappeared altogether, the term was effectively consigned to history. Moreover, when considering empirical research on non-European countries also characterized by basic changes of contextual culture, whether democracies or not, the developments in empirical analysis in a variety of realities highlight the limits and constraints of the traditional categorization that Sartori codified so well. The classic categorization derived from the rule of thumb of inverse relationships between denotation and connotation, and the use of the ladder of abstraction or generality (see 6.4) became a Nexus shirt for comparative politics by being a too strict rule. Of course, as will be recalled, there is a conceptual overstretching if the broadening or narrowing of the extension or denotation of a concept is not complemented by a related reduction or broadening of the intension or connotation. This is the key rule for correct categorization, and it is very hard to abandon, as violating such a rule entails conceptual overstretching and misclassification. But in response to new and changing realities an important methodological question was addressed: is there a way to elaborate other, less stringent rules that are more open to new forms of categorization? Collier and Mahon (1993) were greatly influenced by Sartori, but at the same time were acutely aware of the need for new comparative research. Collier in particular was already a renowned expert on Latin America. As a result, they proposed to consider two further ways to develop a categorization in addition to the classical one: family resemblance and the radial concept. Family resemblance “entail[s] a principle of category membership different from that of classical categories, in that there may be no single attribute that category members all share […] there may be no trait that all family members, as family members, have in common” (Collier and Mahon 1993, 847). With strong simplification, we can build a category with several attributes (e.g.: A, B, C, D), and under that category we may include cases that share only some attributes and not others, such as for example, A and B, A and C, B and D, and so on. An important example suggested by the authors, and one which is definable through a number of attributes, is the concept of ‘corporatism’, which characterized labour relations in some Latin American countries “despite variation in the features of corporative structuring, subsidy, and control of groups” (ibid). The notion and the advantages of a family resemblance categorization can be better grasped if we think of it as a reworking of the Weberian ideal type (see 6.5), an analytic model the researcher does not expect to be the precise description of each empirical case, which in turn is only a partial approximation to the model. The second new kind of categorization is the radial concept, where “the overall meaning of a category is anchored in a ‘central subcategory’”, which is always present in each case while other attributes can also be present in those 87

cases and other subcategories can be built (Collier and Mahon 1993, 848). Table 7.1 suggests a radial categorization using the term ‘democracy’, and shows how participatory democracy, liberal democracy and popular democracy are all characterized by effective political participation as the primary category, but at the same time may have different secondary categories. To better understand the usefulness of such a categorization, which at first sight might appear similar to classical categorization, two observations are necessary. First, the central, recurring attribute should be present, while some of the other attributes, if they exist, may be present to varying degrees. Second, when adding a secondary category it is possible to obtain a broader denotation (i.e., number of cases) despite the broader connotation. Put differently, the rule of thumb of inverse connection is violated. A good example is ‘electoral democracy’ visà-vis ‘democracy’, where the first category is broader than the second one in terms of denotation or extension as well as connotation. This is so by virtue of the way the terms are adopted, as according to some authors ‘electoral democracy’ can be said to exist when there are elections and a minimal, even manipulated, degree of competition, while the definition of ‘democracy’ entails higher standards. Table 7.1: Example of the radial concept: Democracy category


primary category



secondary category

participatory democracy


liberal democracy


popular democracy





Notes: A = effective political participation; B = limitation of state power; C = social and economic outcomes of relative equity. Source: Collier and Mahon 1993, 850.

On the whole, the two new or revamped strategies of categorization point to a less rigid implementation of classical categorization in the use of the ladder of generality. At the same time, they try to respond to the new requirements of empirical research, with its different and changing realities. We can now move on to discuss another research strategy that also responds to the demand for advances, which have been coming in particular from the field of qualitative research.


Box 7.1 In recent times, two further ways to develop categorization have emerged to complement the classical one: family resemblance and the radial concept. Family resemblance involves a different principle of category membership to that of classical categories, in that there may be no trait that all family members, as family members, have in common (Collier and Mahon 1993, 847). The radial concept is based on the idea that the overall meaning of a category is anchored in a ‘central subcategory’, which is always present in each case, while other attributes may also be present in those cases and other subcategories can be built (Collier and Mahon 1993, 848).

7.2 Process tracing The notion of process was mentioned back in chapter 4. Now it is time to suggest a more developed definition of it, as a ‘set of recurring interactions among individual and collective actors within changing structures, which is spread out over time, may or may not unfold into an expected result, is on occasion unilinear, but is always open ended’. It is worth adding that in this definition of process there is room for mechanisms minimally defined as ‘recurrent links or connections’ (see Morlino 2012, 20). At the core of this way of analysing reality is time, timing and sequences. The focus is on the coming into being, changing features and transformation of events, together with their related connections. Tracing requires scholarly skills in reconstructing the details of that process or processes of change. In this perspective Collier (2011, 823) rightly stresses how intensive, “careful description is a foundation of process tracing”. Description may be of different kinds, and rely on a number of sources. An event or set of events, some of them recurring, can be described. The description may be qualitative, but also qualitative or mixed. The sources include official documents, memoirs, mass surveys, in-depth interviews and all the other types we adopt in our research. When relating the two terms – process and tracing – the additional important step which eventually identifies this strategy becomes apparent: we have a research strategy, which is potentially very effective for both comparative analysis and case studies (see chapter 5) and can be defined as the attempt to deduce relations and sequences of causality through the identification of causal mechanisms (George and Mckeown 1985). This implies a focused attention on hypotheses that enlighten the possible connections and the related empirical controls. In this perspective, for example, the strategy can be especially rewarding for analysing all democratization phenomena, such as the processes of transition to democracy, consolidation, crisis and also the worsening or deepening of democracy, where time and sequences are so relevant. There may, for example, also be a focus on different interactions, often unexpected or unwanted 89

ones, between individual or collective actors, and different strategies within a given or changing context, sometimes with unexpected and unwanted results. The two authors who contributed most to the development of this research strategy (see especially George and Bennett 2005), with the guidance of a senior scholar (Alexander L. George) framed it within a view of comparison as structured and focused:. “‘structured’ in that the researcher writes general questions that reflect the research objective and […] these questions are asked of each case under study to guide and standardize data collection, thereby making systematic comparison and cumulation of the findings of the cases possible […] ‘focused’ in that it deals only with certain aspects of the historical cases examined” (George and Bennett 2005, 67). Basically the attention to key, broader questions, a focus on specific aspects, the collection of data and the accumulation of knowledge make explicit the classic mainstream feature of the comparative method by enhancing the awareness of comparative scholars, especially those committed to qualitative analysis. It accounts for the success of this research strategy as well, at least in terms of endorsement by a large number of scholars, reflected also in the blossoming of the literature on the subject (e.g., Beach and Brun Pedersen 2013, Bennett and Checkel 2015, Gerring 2007, especially chapter 7). Process tracing entails two ways of analysing causality relations. They are process verification and process induction or, in other words, theory testing and theory generating or theory development. The first tests whether the observed processes in a case confirm what has been sustained by previous theories, if, that is, there is ‘congruence’ between the results of a case, with its different dimensions, and the expectations of the proposed or existing theory. The second involves inductive observation of evident causal mechanisms, which are transformed into interpretative hypotheses for subsequent empirical testing (see Bennett and George 1997). Both ways of understanding process tracing involve the reconstruction of an unbroken causal chain from the independent to the dependent variable, and may entail reference to many causal mechanisms. In this perspective we could say that process tracing is a specific method that can be employed both by hypothesis-generating or theory-generating and hypothesis-testing or theory-testing comparative analysis, even inside case studies (see 5.2.1). It should be added that Beach and Brun Pedersen (2013, 18–22) envisage a third possibility, which they call “explaining outcome”. This is case-centric rather than comparative: it sets out to explain a particularly puzzling historical outcome through a minimally sufficient explanation, and attempts to trace a case-specific composite mechanism, by means of an inference that is minimally sufficient for the explanation. This third variant of the strategy is, however, relevant only for a single case study, and not for comparative research. For what is most relevant here, the first two variants are more important, and on the whole the strategy of process tracing provides small-N comparison with 90

focus, greater awareness and possibly systematic stringency, accuracy and precision (see 5.2.2). In illustrating the features and assets of process tracing, George and Bennett (2005, 210–1) also indicate the varieties of more specific strategies that can be adopted. The simplest and relatively most straightforward one is detailed narrative, that is, the presentation, in the form of narrative, of a highly specific story describing how an event took place, without using any theory, hypothesis or theory-related variables. Second, the use of hypotheses and generalization, where the narrative is embedded into explicit causal hypotheses or makes reference to some generalization that supports the explanation. Third, analytic explanation, where a historical narrative is transformed into a causal analytical explanation that makes explicit reference to theory. Fourth, a general explanation, built when this is the objective of the research or because the data for a detailed explanation are missing. We can see here that process tracing can be applied to macro-politics, but also to micro-politics. In other words, an individual level of analysis is not necessary. Within these four varieties of process tracing, where the level of abstraction and the salience of theory increase from the first to the fourth one, we can single out different types of causal processes. They include: linear causality, characterized by a straightforward chain of events; the convergence of “several conditions, independent variables or causal chains” (George and Bennett 2005, 212); interacting causality, where variables are not independent from one another and complex interaction effects are identified; path dependency, where key decisions are identified, a sequence of events is singled out and, because of that sequence, the probability of an outcome becomes much higher. It might legitimately be asked whether, in some of its variants, process tracing is not just a good, accurate historic reconstruction that connects the facts, piecing together the causal relationships in great detail (see also 8.4). According to Bennett and George (2005, 225–30), the difference between the historic method and process tracing lies in the fact that process tracing requires a “conversion” from the historic narrative into an analytic articulation that produces an explanation based on theoretical variables clearly identified in the research design. However, it can be added that a number of scholars who define themselves as historians actually have theoretical research objectives and strategies that are similar to those of scholars who are considered political scientists. The overlapping of research strategies and, at the same time, the distinction of disciplinary identities are possible and can be realistically admitted. On the whole, process tracing can be used very effectively in comparison, but here one of its main problems arises: it requires a great deal of information to be applied adequately, and if there are non-accessible data it may prove weak as an analytic tool. In any case, this means that process tracing can be used where, perhaps, a research team is at work, if they are effectively and highly organized in their empirical research and for a limited number of cases. It is 91

actually not suitable for application to, let’s say, more than five or six cases. And if it is used with reference to a single case it presents the typical weaknesses of the case study (see 5.2.1), which suggests hypotheses that remain wholly confined to that case until possibly other cases are incorporated into the research. On two related points, however, process tracing demonstrates its superiority. The first is that it is particularly useful if there is equi-finality, that is, when similar results are obtained in reality through different processes and, therefore, probably point to at least partially different explanations. If this is so, only the qualitative details we can detect with this research strategy are able to let us understand the differences, and consequently to reconstruct a more accurate and in-depth explanation. Process tracing is also indispensable when the same causal factor produces different results. Here too it is an irreplaceable way to specify and investigate any case study and comparative research as well. On these points, process tracing helps to avoid spurious relationships. Finally, as Mahoney (2003, 365) points out, it is a particularly useful tool in those researches, including comparative ones, in which the explanatory variables and the results are separated by a very long period of time. However, in cases like these the difficulty already mentioned above as a weakness of the instrument is accentuated, namely the need for a large quantity of accurate data, which are much harder to come by when applying this method of analysis to a broad time span. The advantages of process tracing can be seen very clearly when analysing the impact of some policy or other, as is often done. When we have a cause, such as a policy that has been decided and implemented, and we would like to assess the impact of that policy on people to correct or even to stop it, process tracing is the best possible research strategy. In fact, with a research goal like policy impact, George and Bennett (see 2005, chapter 12) are particularly conscious that the only way of achieving an accurate assessment of the effective impact of a given policy and consequently of reaching politically relevant conclusions is through a detailed, accurate process tracing that reconstructs an interrupted chain of connections from the moment the policy has been decided, to the possible phase where regulatory directives has been decided, to the different steps of implementation, to the outcome and reactions of the people who have been affected by that policy. In this way, unexpected and undesired consequences can be monitored step by step, keeping a close eye on what should be corrected.


Box 7.2 Process tracing can be defined as the attempt to deduce relations and sequences of causality through the identification of causal mechanisms. Process tracing involves two ways of analysing causality relations. These are process verification and process induction or, in other words, theory testing and theory generation or theory development. Process tracing is particularly useful in cases of equi-finality, when similar results are obtained in reality through different processes, and also when the same causal factor produces different results.

7.3 The configurational comparative method and qualitative comparative analysis If considered a scientific advance, is a logical formalization of the comparative method possible? And if so, how can it be achieved? Answers to these questions have been forthcoming over the last few decades due to the development of the configurational comparative method (CCM) (see, in particular, Rihoux and Ragin 2009). For the sake of clarity it is worth immediately stressing that the configurational comparative method is far removed from statistical analysis (see next chapter), as it is grounded on a deterministic conception of reality, not a probabilistic one, that is, a conception based on the method of necessary and sufficient conditions mentioned in the previous section. Moreover, especially in its actual use, CCM has been adopted in macro-political research with middle-range theoretical goals. Third, because of the requisite and in-depth knowledge of the method it seems best suited for a small-N comparative strategy (see chapter 5). However, it could also be used for a large number of cases and at a micro-level. Under the more general CCM there are three relevant techniques in particular: crisp-set qualitative comparative analysis (csQCA), multi-value qualitative comparative analysis (mvQCA) and fuzzy-set qualitative comparative analysis (fsQCA) (see also Schneider and Wagemann 2012). As regards csQCA, we can basically refer to Boolean algebra and its formalization as proposed by Ragin (1987). Expressed in simple terms, the proposed formalization is by way of truth tables, to which Boolean algebra and Mill’s canons are applied. The latter were discussed in the previous chapter. We can now recall the method of: 

sufficient cause/s, that is, cause/s whose presence suffices to justify the production of an effect; in other words, a condition is sufficient for a result if the result/effect always occurs when that condition is present, but the result may also be the outcome of other conditions; and necessary cause/s, that is, those cause/s that are always present when the result occurs, and without which a given phenomenon does not occur; these cause/s,


however, might not be sufficient to produce the phenomenon (in that only some necessary causes arise and not others).

An analysis of sufficient and necessary conditions is important for explanation, albeit with all the intuitive limits that such methods have in qualitative comparative analysis: it is not always possible to understand if certain causes are necessary and sufficient and new causes might prove to be so. By contrast, Boolean algebra is based on binary logic, characterized by the presence, or rather the absence, of a certain phenomenon. An initial application can be seen in Table 7.2. Table 7.2: Representative truth table with four causal conditions Condition







0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1

0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1

0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1

0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1

0 0 1 0 1 0 1 1 1 1 0 0 0 1 0 1

Number of instances

8 6 10 5 13 7 11 5 9 3 12 23 15 5 8 6

Source: Ragin (1987, 88)

What are the advantages and the drawbacks of resorting to such formalization? In schematic terms, there are a number of main advantages: firstly, the possibility to clearly highlight conjunctural causality, that is to say, to identify the different combinations of causes that can lead to the phenomenon being studied; secondly, emphasis can also be placed on multi-causality, which crops up very frequently in the comparative analysis of macro-political phenomena; and thirdly, as regards process tracing, we can also detect the equi-finality, that is, similar outcomes as the results of different combinations of conditions; fourthly, this formalization obliges us to proceed with a rigour and systematic precision that otherwise would be harder to attain. There are however also a number of significant drawbacks. Above all, it forces us to simplify and schematize the research, the risk being that we could lose information and move even further away from the reality being studied. 94

The second drawback is the large amount of work required to elaborate precise and pertinent truth tables. The third negative aspect, linked to the others, is the objective difficulty of elaborating truth tables that are not banal but significant. These final two shortcomings are the opposite of the third advantage mentioned previously. Table 7.3 offers a concrete example of the possible advantages and disadvantages of formalization. As can be seen, the researcher might decide not to resort to formalization, because the available data do not permit it, or because in their view the drawbacks outweigh the advantages. However, the logic governing the formalization must essentially be maintained every time we do not explicitly resort to the elaboration of full-blown truth tables. Table 7.3: Hypothetical truth table showing three causes of regime failure Condition

Regime failure





0 1 0 0 1 1 0 1

0 0 1 0 1 0 1 1

0 0 0 1 0 1 1 1

0 1 1 1 1 1 1 1

Number of instances

9 2 3 1 2 1 1 3

A: conflict between older and younger military officers; B: death of a powerful dictator; C: dissatisfaction with the regime Source: Ragin (1987, 90).

One of the most relevant criticisms to csQCA was that only dichotomous variables could be inserted into truth tables. This limitation seemed to be a simplification ill-suited to the reality of social and political phenomena. For example, it is not often possible to decide in a dichotomous manner whether a political regime is or is not democratic. Indeed, the existence of various types of democracy and various degrees of democratic quality calls for a scale which, though qualitative, takes account of the gradualness of political phenomena. The attempt to reply to such a criticism resulted in the proposal of multivalue qualitative comparative analysis (mvQCA), where the key difference between csQCA and mvQCA lies in the fact that the second technique allows multi-value variables rather than just dichotomous ones. Basically it can be considered as an extension of the first technique. Consequently, data set analysed with csQCA can also be processed with mvQCA. Multi-valued conditions can be the result of a multi-categorical nominal scale, an ordinal scale, or the use of multiple thresholds for interval data (see Cronqvist and BergSchlosser 2009). The decision about what scale to adopt or what threshold to 95

set is justified by the empirical knowledge we have of the phenomenon under scrutiny and the related theoretical decisions we make in analysing the most relevant conditions. A commonsensical decision is not to set more than threefour values or threshold per condition. An additional step forward along the same logical path is fsQCA, which also arose as a constructive development in response to the criticisms based on truth tables and Boolean algebra. Charles C. Ragin, who had already developed an algorithm and software for the analysis of dichotomous truth tables (Ragin 1987 and more recently 2008a), tried to answer this criticism by turning to a new approach used in computing (Zadeh 1965; 1968), that of fuzzy sets. A fuzzy set is a ‘set’ with ‘flexible’ boundaries. In other words, it is not necessary to declare immediately and dichotomously whether a given country falls within the democracy set or not, because it might be that it only fits in partially. We need only think of the ‘hybrid regime’ (Morlino 2012 and below) and democracies in transition for it to become evident that democracy itself is almost never a dichotomous phenomenon. Thus, fsQCA characterizes the degree of belonging of the case to the category, that is, the degree of membership, through so-called calibration. In a nutshell, calibration implies a specification of threshold values for full membership, full non-membership and the crossover point/s, and it is based on the “researcher’s broad groupings of cases according to their degree of membership in the target set […] the researcher performs an initial sorting of cases into different levels of membership, assigns these different levels preliminary membership scores, and then refines these membership scores using the interval-scale data” (Ragin 2008, 190). Of course, a more precise calibration of the values of the interval scale involves strong empirical bases for the qualitative assessment of set membership as well as theoretical knowledge (see also Ragin 2009, 89–111). FsQCA is based on the arithmetic rules of fuzzy set algebra (Klir et al. 1997). The algorithm is comparable to that of the minimization of the ‘classic’ truth tables (those just with dichotomous values). However, the mathematical process that is applied is much more sophisticated than the one used in Boolean algebra (Ragin 2000, 171ff.; Ragin 2004). Above all, for an application of fuzzy set algebra we need to redefine the key concepts of the analysis of truth tables, that is to say, the necessary and sufficient conditions (Ragin 2000 and above). Moreover, software has been created to analyse these non-dichotomous truth tables with the help of a computer, given that the algorithm is so complex that it is no longer possible to find a causal equation without the help of one (see also Ragin 2009 and again Schneider and Wagemann 2012). To give a simple example, full democracies could be given a fuzzy value of ‘1’, while quasi-democracies (Morlino 2012, chapter 3) would get a fuzzy value of ‘0.8’, and so on. In this way, a scale of fuzzy values consists of two


qualitative extremes (democracy – not democracy), with quantitative intermediate steps (= degree of belonging of the instance to the category). Another example would be the degree of belonging of a nation to the European Union. While formal membership suggests a dichotomy, it would be reasonable to evaluate Switzerland’s degree of belongingness to the EU in another way (fuzzy value > ‘0’) vis-à-vis that of China (fuzzy value ‘0’). In fact, a very complex and highly differentiated social reality makes it necessary to graduate observed phenomena. Even the categories introduced by Lijphart (2001 and chapter 6), which help to classify a democracy on the basis of polar types, could be transformed into fuzzy scales. Obviously, there is a risk of this encoding process becoming arbitrary, especially if the fuzzy scale is highly differentiated. Maximum transparency is therefore absolutely indispensable for encoding. According to Ragin, formal analysis must be preceded by an intense commitment to encoding the instances, respecting the theoretical approaches as well (Ragin 2000, 7; see also 2008a). In this way, the analysis remains strongly qualitative, because one of the most important features of this approach is the researcher’s familiarity with the cases, which permits the development of an encoding scheme. Obviously, the number of instances must be fairly low in order to ensure familiarity with individual cases. Although some criticism, above all about the intricacies in the implementation of the technique, is possible and even reasonable, fsQCA is one of the most systematic and formalized techniques in comparative analysis. Consequently, it can be regarded as a further step forward in the development of comparative methodology. It also shows us how methodologies undertake to improve analytic techniques, in this case by attempting to overcome the limitations resulting from the dichotomization of data. From this point of view, it is worth noting that the possibility of using computers has not only improved the applicability of quantitative analysis, but of the comparative method as well. The main goal of all three QCA techniques is explanatory. However, as we already found when reflecting on parametrization (see section 6.4), embedded in a good classification is the same logic as explanation. Consequently, mvQCA and fsQCA can also be applied in a less orthodox way to achieve better classifications and accordingly to overcome some of the problems that we have been analysing with the multiple typologies (see section 6.5). An example from the analysis of hybrid regimes can help to clarify this point (see Morlino 2012, 60–67). On the basis of a data set built using Freedom House data the profiles for the 35 cases of hybrid regimes were sketched out. In a first implementation of a fsQCA, a truth table with seven different variables (conditions) led to 17 different possible categories, with some of them including just one case. In other words, there were too many classes containing too few


cases for meaningful classification. One way of reducing the number of categories is to see if, when applied to the cases, some key conceptual elements emerge from the seven original variables. To this end a factor analysis was carried out and three components emerged with great clarity: a first component where electoral process, political pluralism and participation, freedom of expression and beliefs, freedom of association and organization are closely grouped together; a second component where rule of law and personal autonomy and individual freedoms are also strongly connected; and a third component, conceptually close to the second one, where state functioning stands alone. When considered in its entirety, the lack or the evident weakness of the first component can be considered a key aspect of limited democracies, while the lack of weakness of the second component can be regarded as a key element of democracies without law and the lack or weakness of the third component the result of inefficient democracy. If we consider that the second and third components are conceptually contiguous (see above), we can group them in just one category that could be labelled as democracies without state. With these indications we go back to the fsQCA method. In particular, profiting from the strong correlations that emerged from our previous principal component analysis, we can build a truth table where: 1. the lack or evident weakness (0) of a new component with the four sets of indicators, that is, absence/weakness of electoral process and/or political pluralism and participation and/or freedom of expression and beliefs and/or freedom of association and organization, shape a limited democracy; 2. the lack or evident weakness (0) of a new component with the two sets of indicators, that is absence/weakness of rule of law and/or personal autonomy and individual freedoms, depicts a democracy without law; 3. the lack or evident weakness (0) of a component with one set of indicators, that is absence/weakness of state functioning, depicts an inefficient democracy. When the related truth table is applied, the results are very meaningful and empirically relevant (see Table 7.4). First of all, there are several cases with at least a weak presence of all three components or characteristics. Evidently, in the light of these new results a new category or class is required, which can be labelled quasi-democracies. Out of the 15 cases of quasidemocracies, 6 are European, 5 African and only 3 Asian, with one additional case in Latin America (Colombia). There is also a sizeable group of limited democracies, as expected, and half of them are African. Third, because of the conceptual contiguity and limited presence of real cases (only Armenia and Morocco), the class of inefficient democracies can be merged with democracy without law into a new more effective democracies without state with 10 cases; most of these (7) are from Africa.


Table 7.4: Classification and cases of hybrid regimes (2010) categories

Quasi- democracies

Limited democracies

Democracies without state


Albania Bosnia Herzegovina Colombia Georgia Macedonia Madagascar Malaysia Moldova Mozambique Seychelles Singapore Sri Lanka Tanzania Turkey Zambia

Bangladesh Comoros Fiji Guatemala Guinea-Bissau Jordan Nicaragua Paraguay Sierra Leone Tonga

Armenia Burkina Faso Central African Rep. Ethiopia Gabon Kuwait Morocco Nepal Nigeria Uganda

This example should prove that, on the whole, QCA has been an effective advance in comparative methodology, as a profitable implementation is possible beyond the purpose of explanation. In fact, QCA has contributed to developing a better and more solid typology precisely in a domain where the main issue is to develop this kind of analysis, allowing for a step forward in our knowledge of the examined phenomenon. Box 7.3 The configurational comparative method (CCM) is grounded on a deterministic conception of reality, not a probabilistic one, and as such it is best suited for a small-N comparative strategy. Under the umbrella of CCM. there are three relevant techniques: crisp-set qualitative comparative analysis (csQCA), multi-value qualitative comparative analysis (mvQCA), and fuzzy-set qualitative comparative analysis (fsQCA). CsQCA is based on truth tables, to which Boolean algebra and Mill’s canons are applied, mvQCA allows multi-value variables rather than just dichotomous ones and fsQCA is based on the arithmetic rules of fuzzy set algebra.

Questions     

What do we mean by ‘family resemblance’ in the context of the rules for conceptualization? What do we mean by the ‘radial concept’? What is process tracing? What is the Configurational Comparative Method? What is Qualitative Comparative Analysis and what are its three sub-categories?


8. Beyond comparison: other research methods 8.1 Data collection and relations between variables Operationalization, classification and the formulation of descriptive models already entail an engagement with the reality we aim to investigate. The phase of constructing and collecting data will therefore already have happened or will be under way, bearing clearly in mind the research goals and resorting to at least six different sources and methods. First of all, data collection can be carried out by drawing on secondary sources. This might involve taking data from existing databases, such as those available from national institutes of statistics, or turning to other published researches. Alternatively, or in addition, the data can be constructed and collected from primary sources. These might be open-answer interviews with elites, or mass surveys, which usually have pre-determined multiple-choice answers. Two further ways of constructing and collecting data are finding/examining documents, or even so-called participant observation, where the person present at the event/phenomenon to be studied obviously decides which aspects are pertinent to their research goals. Clearly, participant observation can bring to the fore problems relating to the influence of personal values and beliefs, but the answer to this remains the one suggested in section 3.1, where the issue was considered when dealing with the theme of “value-neutrality”. These previous phases lead us to formulate hypotheses, that is, to make conjectures and preliminary affirmations regarding the ways in which the studied phenomena or its most specific aspects are connected to other phenomena or characteristics for which we also have operative definitions, which may be either qualitative or quantitatively operationalized ones. Where models have been developed, hypotheses about issues that interest us may often have already emerged, perhaps even explicitly. Figure 8.1: Basic relations between variables


For the sake of simplicity, the relations between factors or variables, in a broad and not necessarily quantitative sense, can be specified by identifying the dependent variable (A) as that which we have directly studied and for which we want an understanding of how it has been produced, in short “the effect”; the independent variable(s) (B) as what, in the formulated conjecture, could be “the cause” or one of the causes; and the intervening variable(s) (C) as a second or other variable that contributes to better explaining the variable dependent (A), as it might in turn be an effect of the independent variable (B). It is called “intervening” not because it came along in a later phase to determine A, but because it is considered by the researcher at a later time for ease of analysis (see Fig. 8.1). Obviously, there might be hypotheses that do not specify the role of the different variables, but simply postulate that they are related. Such hypotheses are just the first step in specifying relations. For obvious reasons, making some conjectures about the direction of influence is ultimately necessary. But hypotheses about the relations between variables are usually much more complex in at least two respects: both insofar as there are many and not just one independent and intervening variable, and because two-directional relations can be hypothesized, namely that B influences A, but also that A influences B, perhaps on certain conditions and with differing force. In other words, the dependent variable may also be the independent variable, and vice versa. In a number of actual comparative research designs the intertwining of different variables can be more complex. For example, when analysing the political consequences of the 2007–14 economic crisis, Morlino and Raniolo (2017a, chapter 2) proposed to assess the impact of the economic crisis in terms of a ‘catalysing effect.’ More explicitly, contrariwise to the classic Schumpeterian hypothesis in economics that crises bring about innovative destruction, they hypothesize that in politics an economic crisis magnifies and accelerates latent or less latent trends and factors already present within the political system. Thus, there is an impact to detect empirically, there is a set of previously existing background conditions that are present within the examined democracy, and the effects of the crisis in terms of declining resources and citizens’ discontent are seen in connection with those conditions. Consequently, there are a number of connections and consequences that need to be analysed empirically and assessed in relation to those background conditions. In this vein economic crisis is seen as the catalysing factor of already existing phenomena. The hypotheses will have to be empirically tested, that is, confirmed or falsified on the basis of at least one of the existing testing methods that will be dealt with in the course of the chapter, obviously using the available data for clearly defined countries and time periods. In concrete terms, this means that there will be very few highly general hypotheses, but above all that we cannot believe in universal hypotheses that exist irrespective of time and space. We will return to this point in the following section. 101

Box 8.1 In order to empirically test hypotheses, it is possible to rely on data gathered from secondary sources. Data can also be constructed and collected from primary sources. In hypothesis testing, the dependent variable (A) is what we have directly studied, in short “the effect”; the independent variable(s) (B) is what, in the formulated conjecture, could be “the cause”; and the intervening variable(s) (C) is another variable that contributes to better explaining the dependent variable (A), as it might in turn be an effect of the independent variable (B).

8.2 More about explanation, generalization and theory The testing of the hypotheses leads to the final step, which is to obtain results. In the social sciences, and in political research in particular, as we mentioned in chapter 3, these results basically consist of: limited (or “local”) generalizations and theories (or “quasi-theories”). Believing that generalizations and theories are always, or almost always, supported by “common sense” as well is a recurrent fallacy in the social sciences. On the contrary, the value of those results often lies in their being counter-intuitive, that is, in revealing traps and distorting simplifications which common sense can lead us into precisely in the fields of political research, economics and social studies. In any case, at the heart of scientific research and consequently of the results we wish to attain there is the explanation of a phenomenon, or, in a more limited way, the indication of a partial correlation between variables and the indication of the direction of causality. The first result of any scientific endeavour, then, consists of some generalization. Here too, though, we need to be clear about what we mean. As should now be established (see chapter 3), in the social sciences we have limited generalizations, that is, statements that describe aspects or properties, or express relations, always on the basis of a spatially and temporally defined set of data. In this sense, as has been pointed out on various occasions, making broad generalizations that go beyond the known data, or even arguing for the existence of laws, as has often been done due to the powerful influence of the naturalistic conception of the social sciences, is deeply mistaken (once again, see chapter 3). It is equally erroneous to imagine that future events can be predicted on the basis of laws. Serious political and social research always looks back, never forward, in the sense that the congruousness between hypothesis and reality is always tested against reality, which must necessarily have already occurred and been transformed into “reality data” to be treated with one of the testing methods mentioned above. Even with limited generalization we need to be careful to avoid confusion. The fact that laws do not exist as such does not mean there is no nomothetic 102

knowledge, with a high level of generalizability and ample scope for use in many other situations (chapter 3). Here, once again, it will help if we turn to the ladder of generality (see chapter 6). Nomothetic knowledge exists, and regards concepts with a high level of abstraction with a reduced connotation and a very broad denotation. In this sense, it lies at the beginning of our reflection and empirical research, as an essential basis for continuing along the path of scientific research. The other aspect requiring specification forms one of the key issues in this chapter: what does theory mean? In general terms, a theory is a set of related statements with an explanatory or interpretative-explanatory content. The legacy of the 1960s (see chapter 3) suggested that theory is a set of related generalizations and explanations whose purpose is also to enable predictions (see, among others, Kaplan 1964). As sustained thus far, a theory in political science, and more generally in the social sciences, can only be a local theory, to use the expression found recurrently in Boudon (1984). Such a theory is based on spatially and temporally defined empirical data, and, above all, entertains no false nomothetic or predictive pretensions. A local theory alone can “scientifically” explain a phenomenon that has a very precise and welldefined sphere of data and may be falsifiable – see also chapter 3. In macropolitics, then, this all means that the “theory” is distinguished by some broad hypotheses relating to a given geopolitical area in a given historical period, with a well-defined socioeconomic context and political-cultural tradition. According to this latter definition, a theory is not a set of propositions with a high level of abstraction, but rather a set comprising a few well-defined hypotheses situated at a much lower level of abstraction. In fact, a hypothesis can only be falsified by obtaining empirical data that enable us to test it. A theory must therefore be able to be appraised essentially in terms of its congruence with reality. However, a theory may also contain propositions that cannot be subjected to direct empirical testing or to a congruence check. If this is the case, such propositions must at least be “acceptable, in the sense that they can be referred to in order to explain other phenomena” (Boudon 1999, trad. it. 2000, 236). The overall position taken in this book derives from the wide experience of empirical research accumulated by several scholars over recent decades, and can be defined as one of moderate positivism. It basically accepts all the limitations and difficulties encountered in concrete research, yet it does not give up on scientific knowledge as knowledge which aims to describe and explain the empirical world as we are able to detect it through our senses. In this vein we have to be ready to accept alternative approaches to knowledge (e.g. Moses and Knutsen 2007), and different, complementary or alternative methods. In the following sections of this chapter the differences between comparison and the other most important methods – the experimental, quasi-experimental, statistical and historical methods – will be illustrated. 103

Box 8.2 Only limited generalizations are available to us in the social sciences, that is to say, statements that describe aspects or properties, or express relations, on the basis of a spatially and temporally defined set of data. A theory is a set of related statements with an explanatory or interpretative-explanatory content.

8.3 Experimental and non-experimental methods We have finally reached the heart of the comparative procedure: the empirical testing of hypotheses. Though it is not the only aspect of comparison, it is the most important, central and distinguishing one: whether we are searching for a more or less circumscribed generalization, trying to produce a local explanation with regard to a specific and clearly defined reality, or just attempting to explain links between a dependent variable and several independent variables. However, comparison is not the only method a researcher can turn to in order to test hypotheses. There is a typology of scientific methods applicable in research contexts: one of the first systematic contributions in this area was that of American sociologist Neil J. Smelser (1966), who proposed the following list: the experimental method, statistical analysis, the comparative method, the historical method and the ethnographic approach. Here, in Figure 8.2, a different scheme is suggested, as inspired by Lijphart (1971). Figure 8.2: Scientific method and its specifications

The key aspect of the experimental method is the “intervention by the researcher in the data-generating process (DGP). […] We call the data generated by such intervention experimental data. Nonexperimental empirical research involves using only data in which all the variation is a consequence of factors outside of the control of the researcher. […] We call this data observational or nonexperimental data” (Morton and Williams 2008, 341). In terms of its essential design, the experimental method is characterized by four steps. First, on the basis of the research goals, two groups of individuals are allocated randomly. 104

Second, a pre-test measures the outcome variable in both groups. Third, after the theoretical hypotheses have been designed, one of the two groups, the experimental one, is subjected to a stimulus, while another group, known as the control group, is not. Fourth, by comparing the attitudes and behaviours of the two groups, who may be kept in the laboratory or allowed to leave, the impact of the stimulus is deduced and the causal explanation reconstructed (for more, see, for instance, Halperin and Heath 2012, 187–201). The evident appeal of this method lies in the possibility of exerting rigorous control over the causes. According to several scholars, in fact, it is the most robust scientific method we can use in social science. In the words of Box-Steffensmeier, Brady and Collier (2008, 15), experiments “are the gold standard for establishing causality”. The use of such a method is limited in political research. The mechanism of activating a stimulus in a clearly defined moment is inapplicable to macropolitical research in its entirety. However, as shown by Morton and Williams (2008, 340) over the last fifty years a growing number of articles in political science journals (and also social psychology and economics ones) have been adopting the experimental method for various micropolitical themes, such as individual mobilization, voting, electoral campaigns, identity, international negotiations and so on. Thus, for example, if we want to understand what elements might influence a given electoral campaign, the experimental method could be the most suitable one. In this example, we can neatly see the point that needs to be grasped: this method makes it possible to precisely identify the relationship between two variables with the confidence that other variables have not intervened in that relation. In this respect, it enables the rigorous specification of a given causal relation. And this causal connection is precisely what is most difficult to determine with all other methods, especially the comparative one, despite the importance the latter has in political research. It is worth remembering that David Collier (1991) took a fresh look at this method, pointing out that it could also be of some interest in sociological and political research, especially when analysis departs from the ‘rigid’ conditions envisaged by the protocol of the experimental method. This would be the case of the so-called quasi-experiments, that is “’observational’ studies that include some event or choice that has a form analogous to an experimental intervention, but that occurs in in a ’natural’ setting”” (Collier 1991, 19). Obviously, the causal impact of an intervention can be assessed, but there is no random assignment of the two imagined groups. An excellent example of a quasi-experiment is the case of the evaluation of the impact of a public policy intervention. In fact, in terms of monitoring and assessing the impact of a specific policy the quasi-experimental method is very promising when the right conditions are in place. While the difference between comparison and experimentation as methods should be evident at this point, an important additional question is if there are connections and possible cross-fertilization between them. More specifically, 105

are some research projects characterized by an experimental method that later on or even within the same research design are complemented by comparison? Or do they actually run on parallel courses, with the scholars who adopt the first method ignoring the others? Or, from an opposite perspective, can comparative scholars gain some advantage by implementing the two paths to knowledge? Before replying briefly to each question, the main lesson we can learn is that to achieve results both experimentation and comparison need theory or at least some articulated hypotheses. Without them, as we learned in the previous chapter on the analysis of comparison, we would achieve very poor results, if any. Second, advances in internet technology have the potential to make experimentation for political science in general and also for policy makers a more widespread method. Coming to our questions, there is also the possibility of enriching the research results by carrying out comparative experiments synchronically or diachronically in different countries or different areas of the same country with similar hypotheses. But research carried out with such a multi-method design is almost non-existent in politics, though it is probably more developed in economics. Thus, although potentially there is the possibility of such developments, experimentation in politics is usually not complemented by comparison and the possible advantages are poorly or non-exploited. Box 8.3 The experimental method is characterized by four steps. First, on the basis of the research goals two groups of individuals are allocated randomly. Second, a pre-test measures the outcome variable in both groups. Third, after the theoretical hypotheses have been designed, one of the two groups, the experimental one, is subjected to a stimulus, while another group, known as the control group, is not. Fourth, by comparing the attitudes and behaviours of the two groups, the impact of the stimulus is deduced and the causal explanation reconstructed. The use of such a method is however limited in political research.

8.4 The statistical method The adoption of the statistical method presupposes, first of all, that the available data are numerical, that is, the result of a process of quantitative measurement or rendered such, and that the instances or states of the properties in the different cases are numerous. Only if these two conditions are in place will it be possible to efficiently apply some of the different statistical techniques in existence, and consequently to discover concomitant variations, to use Mill’s expression (see chapter 6.6), and the relations between the different 106

variables. Moreover, while with the experimental method the direction of the causal relation emerges clearly from the application of the ‘stimulus’ at a given moment and from the observation of the ‘response’ in the experimental group, with the statistical method the direction of the relationship is sustained on the basis of theoretical arguments. As with the experimental method, the influence of the so-called third variables can be quite effectively isolated with the statistical one as well. If, for example, we want to test the influence of age on voter participation, a third variable that might be of considerable importance is the level of education, which in many researches has proved significant for political behaviour in general. The influence of education is cancelled out by parameterizing it, that is, by converting the variable itself into a parameter, into a fixed constant. This is done in concrete terms by considering a sample of individuals with the same level of education; using this sample, the influence of age on electoral participation is then analysed (see section 6.4). Some further considerations can be made about the statistical method. Above all, a number of different statistical analysis techniques have been developed in recent decades. In particular, the use of the computer and of certain ‘bundles’ has made it much easier to use these techniques. Obviously for some themes, including all those relating to political culture, for which there are quantitative data obtained from polls, or electoral themes, or others for which there are solid statistics, the use of computers and programmes employing statistical techniques is frequent and desirable. Greater doubt exists now compared to a few years ago about transforming qualitative data into quantitative data by attributing basically arbitrary numerical values to qualitative variables. Such procedures give an appearance of scientific rigour, but the results are relatively less reliable, despite the intellectual endeavour and hard work involved in obtaining them. What needs to be said about the relationship between the statistical method and comparison? It is worth looking again at the definition of the comparative method proposed by Lijphart (1975, 164; 1971): “method of testing hypothesized empirical relationships among variables on the basis of the same logic that guides the statistical method [my bold], but in which the cases are selected in such a way as to maximize the variance of the independent variables and to minimize the variance of the control variables”. Lijphart, then, argues that the same logic underpins both methods, as what distinguishes each of them is the scientific possibility of empirically testing the hypothesized relationships. I believe that an alternative view is methodologically more correct: the statistic method and the comparative method differ from each other, at the very least in the number of cases they deal with, and at the most, precisely in their logic.


8.4.1 The number of cases Even if we accept for the sake of argument all of Lijphart’s logical presuppositions, the comparative method immediately appears to be different from the statistical one: the research and procedures used will inevitably differ, because the number of cases considered by the two methods is different. The comparative method in particular can involve different strategies of comparison in relation to the number of cases. As we saw in chapter 5, the following research strategies can be distinguished: 1) case study; 2) paired comparison; 3) small-N and area comparison; 4) multi-case strategies. So it can definitely be affirmed that, even if the sole difference between the comparative and the statistical method were the number of cases, that difference is very relevant and would, and has, profound implications for the procedures and goals of the empirical research.

8.4.2. Logic Some authors hold that even the logic underlying the statistical and the comparative methods is different. Scholars like Ragin and Zaret (1983) argue that they are distinguished by widely differing strategies: the one we follow when we do statistical analysis relates to the canon of concomitant variations, whereas when we compare, we refer to Mill’s canons of resemblance and difference (see section 6.6). As stressed in the previous chapter, the comparative method is basically different from statistical analysis as the former is ultimately grounded in a deterministic conception of reality and the latter in a probabilistic one based on the necessary and sufficient conditions discussed in the previous chapters. It should be added, however, that the clear-cut and systematic differentiation between the two kinds of logic is blurred somewhat in research. Practical research experience teaches us in fact that some statistical techniques are used together with the comparative method. In other words, although the statistical method obeys a different logic vis-à-vis the comparative one, in practice this aspect loses much of its relevance, because research statistical techniques are often used within comparison. Box 8.4 The statistical method can be applied when the available data are numerical, that is, the result of a process of quantitative measurement or rendered such, and when the instances or states of the properties in the different cases are numerous. As with the experimental method, the influence of the so-called third variables can be quite effectively isolated with the statistical method as well. The statistical and the comparative methods differ from each other, at the very least in the number of cases they deal with, and at the most, precisely in their logic.


8.5 The historical method The basic point underlying our analysis of the comparative method and the historical method can be summarized as follows: in comparative analysis it is probably not so important to assume the historical method – which most likely does not exist as an autonomous method – as it is to assume the centrality of the temporal dimension. Even more, “historical enquiry has always been central to the field of comparative politics” (Mahoney and Villegas 207, 73). That is, it has been central to comparative research. An initial step in this direction was taken by Ragin and Zaret (1983), when they declared that it is possible to have a statistical comparison and a historical comparison. The first involves ‘numerical’ aspects, employs quantitative techniques and is oriented towards the study of variables – that is, one, two, three or more variables are taken into consideration, the relationships between them are observed in the different cases and the results are quantified. The second one, instead, involves the analysis of qualitative aspects, and is case oriented. It considers just a few realities, analysing the different components, which, all together, characterize the case; obviously, even if we analytically break down the individual realities to study them better, they still represent, and are analysed, as a whole. The fundamental difference is that in statistical comparison we start with a hypothesis (a hypothesized relationship between variables) and then test it by analysing the cases – with the use of quantitative techniques. In historical comparison, on the other hand, we start with a case and a certain unit of research and then compare it with other cases, trying to highlight the different existing relationships, beginning with that of cause and effect, and adopting a qualitative strategy (see Rossi 1990). It would seem, then, that the historical method does not really exist, because it is incorporated into the comparative one. The best way of illustrating the irrelevance of the historical method and the centrality of ‘time’ for the purposes of comparison is to look at how comparison was employed by some of the great classic thinkers. Tocqueville, Marx, Pareto, Mosca and Weber used the temporal element to formulate hypotheses and, above all, to reinforce their hypotheses, that is, cases taken from the past were used as examples to support the hypothesis. When Sartori (1971) – from a generalizing, methodologically orthodox perspective – raised the issue of the historical method, what he had in mind above all was historical testing: the subtitle of his work on comparative politics is in fact “comparative testing and historical testing”. “The political scientist”, writes Sartori, “is not a historian: he is interested in historical testing, that is, a treatment of history designed to verify laws […] or to formulate generalizing hypotheses” (Sartori 1971, 9). Here we are basically back to generalizations, 109

predictions and laws. “Historical testing”, continues Sartori, “is a more imperfect (or less satisfying) test than all the others” (ibid.). And this is chiefly because historical testing poses two problems: a) the availability of cases; b) the extensive application of the ceteris paribus clause, namely the broader application of parameterization, when we consider the longitudinal dimension (time) and, therefore, different contexts.

In short, “comparative testing is usually done along a divide, in synchronic terms […], while historical testing is such precisely because it calls into question a vertical, diachronic divide” (ibid., 10). It is, therefore, a weaker form of testing. Sociology has addressed the problem of history with greater awareness than political science has. Political studies often take this issue for granted. Instead, sociology has explicitly placed it at the centre of many reflections: from Durkheim and his declaration that “history does not exist” to Wright (1971) and Giddens (1976), several sociologists have argued that it is impossible to distinguish between history and sociology. If sociology is interested in structuring processes (Berger and Luckman 1966) and in change, it is quite clear that sociology and history are indistinguishable. This is also the case because sociologists are sometimes not looking for generalizations, and historians are not pursuing purely idiographic research goals. Over the past decades scholarly debate has become very heated (e.g. Burke 1980 or Abrams 1982). What is distinctive and characteristic about the historical method? We might observe that there is a rich and multi-stranded historiography with a very important role in Western European culture. French historiography can be said to have absorbed the social sciences. In the AngloSaxon tradition, instead, the opposite happened, with sociology and political science absorbing history. For example, some subfields of traditional English political science were simple analyses of political events. In Germany there was a high fragmentation both in sociology and other social sciences, and in the relationships of those disciplines with history. In Italy there were various strands of historiography. One was dominated, especially in the past, by the philosophy of Benedetto Croce, another was a Marxist historiography, while contemporary historiography struggled to emerge over the last few decades. This brief digression shows that the academic traditions of the various countries are largely determined by chance, or rather, are characterized by the mindset of the scholars who have worked and published in those countries. Looking in this direction for a definition of the distinctive nature of the historical method therefore appears to be rather fruitless. Nor does the historiographic method have a clear and precise identity in terms of the procedures it uses. Historiography cannot simply be a matter of archive research; it cannot just boil down to content analysis, but it requires intuition, experience and professionalism (the result of years of hard work) that 110

are not easy to codify or relate to schematic rules. Basically, the only aspect purporting to be distinctive is the centrality of the longitudinal dimension: time. But the fact that the historical method is a temporal analysis is not distinctive at all: if we were to look at the sociological and political science tradition and remove the temporal dimension, we would end up losing some of the most important bodies of research. In other words, historians do not have a monopoly on time, which explains the sense in which sociologists use expressions like “there is no difference between sociology and history” or “history does not exist”. Moreover, it is no longer possible today to accept Sartori’s distinction between the comparative method as a synchronic method and the historical method as a diachronic method – especially in the light of developments in comparative politics in recent years. By the end of the 1960s, the most important comparative works – for example, Barrington Moore (1966) – were already showing the centrality of the temporal dimension. Another very significant aspect of a few comparative analyses is their interdisciplinarity. For example, scholars such as Reinhard Bendix, Stein Rokkan, Charles Tilly and Theda Skocpol come immediately to mind, as does the entire historical institutionalism approach of Pierson (2000) and the salience of the past in the explanation of current events. What is more, the 1970s and 1980s saw the development of one of the most important strands in comparative research: the study of regime changes, with transformations in a democratic or authoritarian direction and more often of democratizations. Within this line of research the longitudinal dimension is fundamental. Moreover, it is crucial to consider the background of a state, which consequently makes the temporal dimension of paramount importance (see chapter 5). And again, in the whole subfield of comparative politics known as the empirical theory of democracy, which has been flourishing over the years with the investigation of processes of transition, consolidation, crisis, and deepening or worsening of democracy (see Morlino 2012), the crucial dimension under scrutiny is time. In conclusion, and despite some limits, the only possible way to single out the difference between the historical method and the comparative method in the attempt to go beyond the different specific disciplinary traditions is to look at the crucial, central role that theory and theory building has in comparison vis-à-vis the limited if existing presence of theory in the historical method. To be more precise, developing explicit theoretical hypotheses is the key procedure when conducting the comparative method. This is also the reason why we devoted so much attention to all the conceptual and theoretical issues dealt with in chapters 6 and 7. In the historical method – even more so with configurative or atheoretical studies, or also interpretative studies (see section 5.2.1) – formulating explicit hypotheses and attending to the related theoretical develop-


ment are not considered a necessary part of historical practice. Although several historians have done so, the crucial point is that theory is not the key procedural aspect of the historical method. We might add however that even this way of singling out the difference between the two methods can be questioned by both historians and political scientists. Some of the latter, for example, consider historical analysis as a “leading orientation in the field of comparative politics”, which “embodies a distinctive set of techniques for the assessment of causal hypotheses, for the study of temporal processes, for the analysis of data […] along with the pursuit of the valid explanation of particular outcomes in specific cases” (Mahoney and Villegas 2007, 86). Of course, what Mahoney and Villegas have in mind is a diachronic comparative politics, where the past is a crucial aspect of research and the mainstream aspect of historiography is stressed, that is, an analysis that is focused on explaining specific cases. This chapter has considered the differences and overlap between key methods in the social sciences, helping us to set the comparative method within a broader frame. It is now time, in the concluding chapter, to make some final, important remarks. Box 8.5 In historical comparison we start with a case and a certain unit of research and then compare it with other cases, trying to highlight the different existing relationships, beginning with that of cause and effect, and adopting a qualitative strategy. Historical testing poses two major problems: 1) the availability of cases; and 2) the extensive application of the ceteris paribus clause when we consider the longitudinal dimension (time) and, therefore, different contexts.

Questions      


What is the difference between primary and secondary sources? What is the difference between the experimental and non-experimental testing of hypotheses? What are the main features of the statistical method? Under which circumstances can the statistical method be applied? What are the main features of the historical method? What are the main limitations of the historical method?

9. Conclusions. The limits of comparison After what has been said in the previous chapters, we might be tempted to see comparison as a deus ex machina, a panacea for every kind of research. Care needs to be taken however, because not everything is comparison and comparing does not serve every purpose. We have seen how comparison can be useful for testing plausible and likewise acceptable explanations for the same political macrophenomenon (context of justification). But also how it can serve as an instrument for building new and more original hypotheses (context of discovery). However, the claim, sustained by some authors, that “if it is not comparative it is not political science” (Almond 1970, 254), in other words that comparison is a conditio sine qua non of political research, is not correct. To affirm this, in fact, is to confuse comparison as a basic logical procedure with comparison as a more elaborate and complex method for studying political phenomena. In this work we have been interested in this second kind of comparison, which – as we have seen – is distinguished by rules and procedures that need to scrupulously observed. Furthermore, at this point it should also be evident that comparison is difficult. As Sartori points out (1971, 7), the theoretical component of comparison is hard to “handle”: “anyone sailing without a method and without a compass risks running aground at any moment”. For this reason too, comparison has not developed more in political science. What is more, in the face of a broad majority of ideographic and atheoretical scholars, comparativists themselves are divided over what constitutes an acceptable explanation in the social sciences, in a context in which political knowledge is not highly cumulable, and its object is frequently redefined and transformed. This division, and the limited cumulability, relate once again to different views about the best way of doing political science, highlighted in the field of comparative studies by the two main strategies (statistical and historic comparison) indicated by Ragin and Zaret (1983), and by the positions of those who tend to play down the difference between those strategies. Besides the difficulty of comparing, due to the trickiness of using concepts and the ladder of generality correctly (Sartori), to the challenge of gathering data on many cases and to the differences between comparativists, there has perhaps also been an ‘excess of goals’, a desire to set overly ambitious research objectives. This has ended up, above all, in the perfectionistic and utopic pursuit of impossible models of science. Such an ‘excess of ends’ (and hopes) has ultimately proved counterproductive, driving away many disappointed scholars who felt unable to share the ambitious and abstract objectives.


Thus, not only is comparison difficult and not necessary for everything, but, like the patient intellectual artisan about whom Wright Mills speaks, the comparativist must also be fully conscious of the limits of comparative research. So let us, by way of conclusion, consider the four most recurrent ones. First, in an increasingly interdependent world, in which the flow of communication is becoming ever more intense and countries can no longer declare themselves to be politically independent, the reconstruction of the conditions, the inherent and original causes and the effects of certain phenomena is becoming more and more difficult. And even when we are dealing with our own particular issue, we cannot neglect to evaluate the impact that external events have on our field of study. This is essentially Galton’s problem, named after the anthropologist who first raised it: explaining a phenomenon is becoming increasingly difficult due to the presence of diffusion, imitation and importation phenomena, that is, to the reference to and the influence of other political cases when looking for politico-institutional solution deriving precisely from political interdependence and the easy availability of information. This is particularly evident if we emphasize the aspect of explanation as the search for generalizations or laws. Moreover, during recent decades, we can safely say that Galton’s problem has been becoming increasingly relevant. In other words, the assumptions that comparative analysis should emphasize domestic aspects, can ignore international ones and may gloss over the intertwining between different domestic and international factors, as Mill was actually implying with his canons, have, as suggested by Galton, always been wrong. Today, and in the foreseeable future, they are even more so, and would constitute an effective “hindrance to understanding”, as Hirschman (1970) used to say of certain paradigms in social science. When we consider the consequences of globalization, complemented by those of Europeanization (namely, the effects of integration processes in individual countries), we immediately see how the boundaries of old, traditional comparative politics have become blurred with regard to international relations and European studies, with large areas of overlapping. Back in the 1990s Keohane and Milner (1996, 3) were already pointing to this phenomenon by stressing how “we can no longer understand politics within countries – what we still conventionally call ‘domestic politics’ – without comprehending the nature of linkages between national economies and the world economy, and changes in such linkages”. And, we might add: without comprehending the linkages between different kinds of domestic and international factors. The point to grasp here, however, is that contemporary research cannot ignore these phenomena, which are magnifying what was already going on. And that this is a challenge to strive for a better, more adequate and more conscious research design that takes more carefully into account the methodological suggestions outlined in the previous chapters. Put differently, a more complex reality is complicating a comparative research that still


has the same methodological tools. A good example of this is the study of processes of transition towards democracy, where international external factors have become so significant in the recent past. This is even more evident when considering transition processes in the Eastern European countries, where integration and European Union membership is a key aspect of the process itself. A second aspect to take into consideration, linked with the previous one, is called the learning process, and it is the cause of a further difficulty associated with the testing of hypotheses. We have a positive learning process when lessons are learnt from past or contemporary events in other countries and are applied to action in the present. A good example is the experience of the Weimar Republic. On the basis of this lesson modern Germany established mechanisms to stabilize government, such as the constructive vote of noconfidence and the direct election of the chancellor by the Bundestag. Other legal systems learnt from it as well. For example, the Spanish Constitution of 1978 introduced both of these institutes. There may also be a negative learning process, when the lesson learnt from certain events is, by contrast, oriented towards inaction. For example, the failure of socially or politically radical regimes like the Second Spanish Republic led to exaggerated moderation among political leaders and in the political culture of Spain and Portugal during the second half of the 70s. Furthermore, the death of Salvador Allende in Chile in 1973 was an extremely important lesson for the whole of the European left, and for that of Italy in particular. The difficulty introduced by the learning process is that it indicates the importance of certain cultural factors, but they remain empirically elusive. Galton’s problem and the learning process clearly highlight the complications present in a research design which, in searching for generalizations at any cost, must neither be over-naïve nor ignore aspects of diffusion or learning. To overcome the problems posed by these two phenomena, it will suffice to devise a suitably careful research design. But how can we overcome a third limitation that is attributed to comparison? This is the argument that comparison is a ‘strained’ conceptual operation in the best of cases, and in the worst gives banal and indeed superficial results. More than limitations, they appear to be basic objections that we need to deal with straight away. The argument that comparison is conceptually strained stems from the conviction that the empirical concepts used are incommensurable (Feyerabend 1975). Essentially, the argument goes, every well-formulated empirical concept is so profoundly and inextricably bound up with the context and the object for which it is elaborated that it cannot be exported or applied to another reality, which is only apparently similar. In other words, to compare a socialist party in one country (and the relative theoretical notion) with that of another country is to ‘force’ matters. They are very different notions and realities. When, despite everything, we carry on anyway, the results are superficial if not completely banal. 115

The objection regarding the incommensurability of concepts can only be answered by a careful use of the ladder of generality and of other fundamental mechanisms of comparison (see chapter 6 in particular). Using this elementary tool of logic enables us to overcome so-called incommensurability in macropolitics as well, even though superficiality and obviousness may still characterize the results of the comparison. But that depends on the limits of the researcher rather than of the method used, though it is evident that “comparative investigation sacrifices understanding-in-context – and of the context – to inclusiveness and generalizing proportions” (Sartori 1991, 39). We should, then, try to use comparison without any false illusions, with great care and a clear perception of the problems, difficulties and goals we are setting ourselves. A fourth, final problem of comparison is so-called conjunctural causality. This term denotes the fact that the same phenomenon may have different causes. Its importance lies in the difficulty of obtaining a satisfactory explanation – even though, as we have seen in the course of this book, there are various strategies a researcher can adopt to deal with this difficulty as well. In brief, comparison requires great care and attention, moderation and a sense of limits, but if carefully managed it offers a reliable, effective way of acquiring knowledge, and one we really need in order to understand the complexities of the world in which we live. Box 9.1 It is important to remember that not everything is comparison, and comparing does not serve every purpose. There are at least four major limitations of the comparative method: 1) in a context of political interdependence, explaining a phenomenon is more and more difficult due to the presence of diffusion, imitation and importation phenomena; 2) learning processes may indicate the importance of certain cultural factors, but they remain empirically elusive; 3) according to some critics, the empirical concepts used are incommensurable; 4) the same phenomenon may have different causes, a concept defined as conjunctural causality.

Questions    


Is it possible to apply the comparative method to every kind of research question? What are the main limitations of the comparative method? What is Galton’s problem? What is conjunctural causality?

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Index abstraction, ladder of 67, 69, 71, 85, 87 area study 51-55 case study 51-55, 90, 92, 108 causality, conjunctural 85, 94, 116 causality, interacting 91 causality, linear 91 classification 13, 15, 36-38, 48, 68-73, 77, 82, 97, 98, 100 cognitive goal 20-21 comparison, binary 51, 53, 55 comparison, qualitative 30, 34, 38-40, 54-55, 84, 85 comparison, quantitative 34, 3840, 54-55, 59, 84-86, 97 configurational comparative method (CCM) 61, 86, 93, 99 discovery, context of 14-18, 113 equi-finality 92-94 experimental method 104-108 explanation 11-12, 15, 17-26, 29, 33-34, 39, 53, 59, 70, 82, 8485, 90-92, 94, 97, 99, 102-106, 111-114, 116 explanatory goal 20-21, 32, 69 family resemblance 87, 89, 99 Galton’s problem 114-116 generalization 16-18, 21-24, 31, 51-52, 84, 91, 102-104, 109110, 114-115 historical method 7, 103-104, 109-112 hypothesis testing 102 indicator 31, 40-43, 45, 62, 98 interventionist goal 20-21 justification, context of 14, 1617, 113

law 16-18, 21-25, 31-32, 47, 71, 78, 98, 102, 109-110, 114 Mill’s canons 61, 82, 84-85, 93, 99, 108 multi-case strategy 54, 108 multicausality 84-85 multicollinearity 59-60 nomothetic knowledge 22-25, 27, 31, 33, 103 Ogden and Richard’s triangle 85 operationalization 38, 42-43, 45, 62, 100 parametrization 69-70, 97 path dependency 91 prediction 16-18, 103, 110 process tracing 57, 61, 85-86, 8994, 99 qualitative comparative analysis (QCA) 86, 93-95, 99 radial concept 87-89, 99 scientific knowledge 16, 34, 103 single case 29, 51-52, 54, 90, 92 sources, primary 100, 102, 112 sources, secondary 100, 102, 112 space 24, 35, 38, 50, 60, 68, 75, 101 theory, local 18, 23-25, 29, 31, 34, 103 theory, middle-range 28-30, 3233, 93 Tree of Porphyry 61, 66-69, 71, 85 understanding 16, 25-26, 35, 45, 66, 78, 84, 90, 101, 114, 116 variable, dependent 17, 19, 90, 101, 102, 104


variable, independent 17, 19, 30, 39, 49-50, 90-91, 101-102, 104, 107


variable, intervening 17-19, 44, 50, 101, 102