Candidates and Voters: Ideology, Valence, and Representation in U.S Elections 1316649601, 9781316649602

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Candidates and Voters Candidates and Voters extends our understanding of voting, elections, and representation by elaborating a simple theory of voting choice based on voters’ interest in policy and in the suitability of candidates to hold elective office (“leadership valence”). Voters’ choices must be understood in the context of the choices between opposing candidates they are offered on these two dimensions. Drawing on extensive analysis of U.S. House races, Stone shows that although voters lack the information that many analysts assume they need to function in a democracy, they are most often able to choose the better candidate on the policy and valence dimensions. In addition, candidates, when they decide whether and how to run, anticipate the interests that drive voters. The book shows that elections tend to produce outcomes on policy and leadership valence consistent with voters’ interests, and challenges skeptical views of how well the electoral process works. Walter J. Stone is emeritus Professor of Political Science at the University of California, Davis. Prior to joining the UC Davis faculty, he was Professor at the University of Colorado, Boulder, and Visiting Professor at Stanford University.

Candidates and Voters Ideology, Valence, and Representation in US Elections

WALTER J. STONE University of California, Davis

University Printing House, Cambridge cb2 8bs, United Kingdom One Liberty Plaza, 20th Floor, New York, ny 10006, USA 477 Williamstown Road, Port Melbourne, vic 3207, Australia 4843/24, 2nd Floor, Ansari Road, Daryaganj, Delhi - 110002, India 79 Anson Road, #06-04/06, Singapore 079906 Cambridge University Press is part of the University of Cambridge. It furthers the University’s mission by disseminating knowledge in the pursuit of education, learning and research at the highest international levels of excellence. www.cambridge.org Information on this title: www.cambridge.org/9781316510216 doi: 10.1017/9781108225021  C Walter J. Stone 2017

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To Emma and Riley; Jesse and Kai; Lyle and Juniper.

Contents

List of Figures List of Tables

page ix xi

Acknowledgments

1 2

xiii

Introduction Candidates, Voting Choice, and Election Outcomes

1 14

Design and Data: District Informants and the Study of Congressional Elections

52

3 4 5 6 7

Polarization in Congressional Elections Since 1952 Ideological Proximity, Valence, and Voter Choice Correct Voting on Proximity and Valence Anticipated Reactions and Challenger Entry The Proximity and Valence Rules in District Voting

72 84 106 122 136

8 9

District Ideological Representation Getting it Right? Valence and Ideology in District Representation Conclusion

147

Appendix: Issues in the Use of Expert Informants References Index

vii

167 185 205 211 223

Figures

1.1 Spatial Model of Candidate and Voter Ideological Positions in District j page 16 1.2 Hypothetical Utilities from Proximity and Valence Rules 35 1.3 Hypothetical Utilities from Proximity and Valence with Variable Valence Weights 37 1.4 Implications of Leeway and Alignment Hypotheses for Candidate Differentials 44 3.1 Median-Voter and Party Models of District Representation 75 3.2 Representative by District Ideology in Selected Midterm Elections 80 3.3 Partial Coefficients on Incumbency Estimating Effects on Incumbent Vote Share, 1952–2010 82 4.1 Candidate and Party Identifier Ideological Distributions 86 4.2 District and Candidate Ideological Positions for Random Subset of Districts 86 4.3 Distributions of Candidate Valence Differentials and Ideological Cut Points 88 4.4 Valence Differentials and Candidate Valence Scores for Random Subset of Districts 89 4.5 Effects of Proximity and Valence Differentials on Voting Choice by Party Identification 94 4.6 Effect of Proximity Differential by Awareness of Candidates’ Ideological Positions 96 4.7 Effect of Proximity Differential by Awareness of Party Ideological Positions 97 ix

x

List of Figures

5.1 Correct and Incorrect Voting by Voter Distance from Ideological Cut Point 5.2 Effects of Party Identification and Incumbency as Proxies on Proximity Voting 6.1 Informant-Based Estimates of Incumbent Prospects as Predictor of Incumbents’ Party Winning 8.1 Responsiveness vs. Proximity in District Ideological Representation 8.2 Ideological Map before the 2010 Elections 8.3 Candidate Positioning and District Preferences, 2010 8.4 Relationship between Opposing Candidates’ Ideological Cut Points and District Ideology 8.5 Incumbent and District Ideology after the 2010 Elections 8.6 Direct and Selection Effects of District Ideology on Representative Ideology 8.7 District Effect on the Party of the Representative after the 2010 Elections 8.8 Models of District Ideological Representation, 112th Congress 9.1 Effect of Incumbency on Correct Proximity Outcomes by whether the District is Aligned or Cross-Pressured 9.2 Relationship between Valence and Proximity Candidate Differentials 9.3 Additional Evidence for the Alignment Hypothesis: Partial Effect of Valence Advantage on Proximity Advantage of Winning Candidates Compared with Losing Candidates, 2010 C.1 Ideological Distance Effects for Republican and Democratic Candidates by Party Identification A.1 Replicating Figure 5.1 with Opposite-Party Informants A.2 Replicating Figure 8.3 with Opposite-Party Informants A.3 Replicating Figure 9.2 with Opposite-Party Informants

113 119 127 149 151 153 155 156 158 159 164 177 181

183 198 207 209 209

Tables

2.1 Explaining Constituent Perceptions of Candidates’ Valence Qualities page 64 3.1 Partisan Polarization in the Electorate and in Congress by Decade, 1952–2010 77 4.1 Breakdown of Ideological Distances between Party Identifiers and Candidates in Each Party 87 4.2 Logit Models of Voting Choice, 2010 92 A.4.1 Logit Models of Voting Choice Based on the Latent Ideology Measure of the Proximity Differential, 2010 102 A.4.2 Regression Models of Constituents’ Perceptions of Candidates’ Ideological Positions 104 5.1 Type of Correct Voting by Whether Voters were Cross-Pressured 111 5.2 Examples of Proxy Overlap and Correct Voting 114 5.3 Logit Analysis of Proximity Voting among Aligned and Cross-Pressured Voters 116 6.1 Explaining District Informants’ Judgments of Incumbent Prospects 128 6.2 Strategic Behavior in the 2010 House Elections 130 6.3 Campaign and Leadership Valence by Incumbent Prospects 131 6.4 Candidate Extremism and Proximity to District by Incumbent Prospects 133 7.1 Regressions of District Republican Vote Share, 2010 138 7.2 Explaining the Effects of Proximity and Valence on Republican Vote Share 140 7.3 Prospects and Anticipated Reactions in 2010 144 xi

xii

List of Tables

7.4 Assessing Effects of Spending Differential on Republican Vote Share 8.1 District and Candidate Ideology by District Party Outcome, 2010 8.2 Regression Analysis of Candidate Ideology on Party and District Ideology, 2010 8.3 Probability of Republican Victory and Expected Candidate Ideological Positions, 112th Congress 9.1 Breaking Down the Sample by Outcome on Proximity and Valence Dimensions 9.2 Mean Valence and Proximity Scores by Outcome 9.3 Logit Analysis of Correct Proximity Outcomes by District Electorates 9.4 OLS Analysis of the Quality of District Ideological and Valence Representation C.1 District Groups and Incumbent Ideological Placements A.1 Replicating Table 4.2 with Opposite-Party Informants A.2 Replicating Table 7.2 with Opposite-Party Informants

145 157 160 162 168 169 174 178 193 206 208

Acknowledgments

When I began this research project with a pilot study in the 2006 mid-term elections, I counted myself among scholars and social scientists skeptical about the ability of voters to pursue their fundamental interests, especially in relatively low-visibility elections like those for a seat in the House of Representatives. The reasons for my skepticism included the power of incumbency and money in House elections – the “resource asymmetry” hypothesis that emphasizes the advantages in financial backing one candidate, usually the incumbent, has over his or her opponent. They extended to the polarization in American electoral politics, and the general inattentiveness and disengagement of most voters. This research project has changed my mind. I have a much more optimistic view about voting, elections, and representation in US politics as a result of this project. The reasons for my optimism are the basis of this book – reasons that persist in the face of evidence other scholars have taken to support their skepticism about the capacity of voters in democratic politics and about how well elections work. I have been fortunate to have the support I have needed to conduct this research, carry out the analysis, and write up my conclusions in this book. Generous start-up funding from the UC Davis Division of Social Sciences, the expenditure of which was delayed by other research and administrative obligations, enabled me to conduct the 2006 pilot study without the distraction of seeking outside support. That phase of the study helped frame the National Science Foundation grant (SES-0852387) that supported the 2010 phase of the study, which is the basis of this book. My good fortune extends well beyond the financial support I received for this project. I could not ask for a more stimulating and supportive xiii

xiv

Acknowledgments

environment in which to work than the UC Davis Political Science Department. Colleagues, graduate students, and undergraduates in the department have been a constant source of ideas, humor, and friendship. I am especially grateful to Jim Adams and Ben Highton. Two more sustaining, challenging, and appropriately skeptical colleagues and friends could scarcely be hoped for. Among many other contributions, Jim has been a constant guide through the literature that wrestles with the implications of valence in spatial models; Ben’s critical eye has suggested multiple analytic tests and implications that would not otherwise have occurred to me. Many other scholars have contributed to this project directly or indirectly by virtue of their comments on papers or at conferences where various permutations of this project have been presented. These include seminars and talks at UC Berkeley, UC Davis, Texas A&M, UC Merced, Colby College, the College of William and Mary, and a variety of other conferences and presentations. For their comments and suggestions at several critical points, I thank Gary Jacobson, Sarah Fulton, and the anonymous referees for Cambridge and Michigan presses. I am grateful to Doug Rivers and Samantha Luks for their assistance and flexibility in supporting the district-based survey sample for the 2010 UC Davis module and the identification of the expanded informant panels in the 2010 study. UC Davis graduate students have participated in this project, helping with all aspects of data collection and management, and as collaborators and provocateurs. They include Christy Cahill, Nathan Hadley, Jordan Kujala, Debra Leiter, Danielle Joesten Martin, Rolfe Peterson, Matt Pietryka, and Beth Simas. I want especially to thank Matt Buttice, whose involvement in many aspects of this research was essential to its present form. Matt was a close collaborator in the early stages of this project, and his contributions to the finished product are evident to me, as I hope they are to him. Two UC Davis undergraduates – Trevor Lowman and Jeremy Hauser – were especially engaged as research assistants and, in Trevor’s case, as a coauthor. Their participation was supported by a Research Experiences for Undergraduates supplement from the National Science Foundation. I have benefitted from collaborations with colleagues on related projects that tutored me (slowly, I know) in many matters that informed this project. Of particular note is my experience with the Candidate Emergence Project, originally conceived and developed with Sandy Maisel, and joined and advanced by our collaboration with Cherie Maestas. Without our work together on the CES, this book would not have been possible.

Acknowledgments

xv

Sandy first suggested and field tested the use of expert informants to identify strong potential House candidates; Cherie suggested the expanded definition of expert observers employed in this project. In many ways, this project investigates questions that were first developed and shaped by my experience on that project. I would also like to thank friends and colleagues who have generously commented on various drafts of this book. They include Jim Adams, Scott Adler, Larry Bartels, Cheryl Boudreau, Ben Highton, Adrienne Hosek, Ron Rapoport, Paul Sniderman, and Rob Van Houweling. I would like to thank Ron for his persistent support and friendship throughout our long and productive collaboration on other projects. I have learned a great deal with and from Ron, and he has been a patient and supportive critic on this one. Sara Doskow has been an enthusiastic supporter and expert facilitator of this project as Political Science Editor at Cambridge. She and Claudia Bona-Cohen have been responsive, informative, and patient with the many questions I’ve thrown at them. I am grateful for their expertise and confidence in this project throughout the review process and as I prepared the final manuscript. Finally, I would like to thank my wife, Ann Cassidy-Stone. As we approach the close of our first half century together, I am constantly reminded of how much I depend on her love, generosity, and support. As the “real scientist” in the family, her thoughtful suggestions on the manuscript have been of great value. Together we raised three wonderful children, each of whom has two amazing children of their own. It is to these six grandchildren that I dedicate this book in the confident hope that their lives will contribute to and benefit from a better politics.

Introduction

Put bluntly, rule by demagogues is not an aberration. It is the natural condition of democracy. Demagoguery is the winning strategy as long as the electorate is prejudiced and credulous. – Bryan Caplan (2007) The people’s verdict can be no more than a selective reflection from among the alternatives and outlooks presented to them. – V.O. Key (1966, 2) We shall have to consider the possibility that supportive constituents may want extrapolicy behavior from their representatives …They may want ‘a good man’ or ‘a good woman,’ someone whose assurances they can trust, as much as they want good policy. – Richard Fenno (1978, 240–41) Election outcomes turn out to be largely random events from the viewpoint of contemporary democratic theory. – Christopher Achen and Larry Bartels (2016, 2)

When asked by friends or family members who are not political scientists what my book project was about, my stock answer was something like “how elections work better than you think.” If pressed (most friends and family members have more sense than to press), I would say, “for instance, election outcomes are not all about which candidate has more money.” If pressed further (!), I would say, “Voters do a pretty good job of choosing the candidates who best represent their interests, and are not usually led astray by things like how much a candidate spends, which 1

2

Introduction

party she’s in, or whether she is an incumbent.” By now, I usually would get a polite “That sounds interesting,” and the conversation would shift to other topics. If questioned further, I would have said that as much as political scientists know about topics related to voting and elections, there are still fundamental questions that have not been adequately addressed. This may seem surprising, especially since many political scientists would say that we know more about voting and elections than most other topics the discipline addresses. The gaps in our knowledge that this book addresses are in the connections between the choices voters are offered and the choices they make, and the consequences of voters’ choices for electoral and representative outcomes. Charles Franklin’s observation, twenty-five years on, is still on point (1991, 1211): As we have become adept at studying voters, it is ironic that we have virtually ignored the study of candidates. Yet it is in candidate behavior that politics intrudes into voting behavior. Without the candidates, there is only the psychology of the vote choice and none of the politics.

In a nutshell, the attention of the discipline has not been adequately focused on the political context to which voters react in elections, especially aspects of that context that relate to choice. A related problem is that much of the literature that focuses on choice relies on voters’ perceptions of – and ability to report on – the choices before them. Since the prominent studies of voting and elections conducted at the University of Michigan in the 1950s, the bulk of research on the behavior of voters has relied on a social-psychological framework for understanding the mechanisms explaining voter choice. That framework emphasizes the importance of voters’ perceptions to explain their behavior rather than the actual differences between candidates, whether or not voters can report on them in surveys. The alternative, rational-choice, approach puts more emphasis on the political context shaping voter response in the policy differences between candidates, but has also been limited in its empirical application, as discussed in Chapter 1. To be clear, I think we have learned a great deal about voting and elections from the Michigan approach.1 But, like any approach to complex phenomena, it has its blind spots. In particular, the methodological premise of this book – that we must study voting choice based on 1

Full disclosure: I earned my Ph.D. at Michigan; my advisor was Warren Miller, one of the giants of the Michigan School approach to political behavior studies. Two of the classic Michigan studies of voting are Campbell et al. (1960) and Campbell et al. (1954).

Introduction

3

equivalent measures of opposing candidates’ policy stands and suitability for office independent of voters’ perceptions – addresses what I see as a major blind spot in what is known as the Michigan School. The plain, endlessly documented fact is that voters are rather poor at reporting on candidate characteristics and policy stands, mostly because they don’t seem to be paying attention. Voters come up short in their awareness of the choices they face, especially in elections that are not hotly contested and highly visible. As a result, many political scientists are skeptical about voters’ ability to function effectively as monitors of candidates’ and officeholders’ behavior, and as enforcers of their own interests in elections. In fact, beyond the mountains of evidence about voter ignorance, there are good theoretical reasons to believe that voters are caught in a collective-action dilemma that means they have few incentives to make an effort to be informed or organize their political thinking in a systematic way, assess their choices carefully, and cast reasonable votes based on their private interests and their conceptions of the public interest. I discuss these arguments for “rational ignorance” in more detail in Chapter 1.2 So, to reiterate, here is the starting point for this book: there is much to be learned about voting, elections, and the outcomes of elections by focusing on the choices between opposing candidates vying for electoral support in elections. In this endeavor, it is essential to measure the critical dimensions of choice by means other than voter perceptions, which put too much weight on voters’ ability to recall and report on candidate differences in surveys. We must be able to assess the choices to which voters respond based on measures that are equivalent for each of the opposing candidates, else we are left with a distorted picture of the nature and quality of those choices. Understanding the choices voters make is only the beginning. We must also assess the consequences of these choices for electoral outcomes, including political representation. Only then can we know whether elections “work better than you think” or whether election outcomes are “largely random events” when compared with democratic theory. Why are voter perceptions inadequate as measures of the choices they confront? After all, if voters don’t understand the differences between the policy positions of candidates, how can they choose on the basis of those differences? No one doubts that politics and elections are remote from 2

The theoretical argument that voters have no incentive to be informed about political choices does not trace back to the Michigan School, but to the rational-choice approach. The classic statement of this approach is Downs (1957).

4

Introduction

the daily concerns of most citizens. Because the individual is part of a huge mass of voters in the electorate, she knows at some level that her individual choice is unlikely to affect the outcome. Thus, voters may not be paying sufficient attention to the choices they face to be able to report confidently on the elements of those choices. Does that mean the choices they make are usually of low quality, unrelated to the factors we would hope motivate their votes? Possibly. But, there are reasons to believe that the quality of the choice voters make is not dependent on the amount of information they can report to survey researchers. Three basic answers have been offered to the choice problem voters face: (1) they may take cues from others who are better informed and likely to share their interests; (2) they may use other decision shortcuts that enable them to approximate the decision they would make if they had more information; and (3) they may not keep track of the considerations that feed into their choice, but rely on a “running tally” of factors relevant to their choice. For the most part, my focus is on the differences between candidates on two dimensions, comparing the choices voters actually make with the choices they “should” make given their interests as I define them. Furthermore, I explore the implications of these choices for politicians’ behavior, and for the representativeness of election outcomes. I pose and attempt to answer two questions: Do voters and electorates choose the better candidate? And, how well do winning candidates actually represent their electorates’ interests? By now all sorts of warning bells should be sounding in the reader’s head. How does Stone know what the criteria for good voting choices are? Who is he to determine how citizens should vote? How can he think that he can determine whether electorates choose the better candidate? At this point, some sort of demurral would seem to be in order to assure the reader that I have not signed up to play God in judging the quality of voters and election outcomes. Scholars familiar with the debate on voter capacity may recall a quote by E.E. Schattschneider (1975, 132): One implication of public opinion studies ought to be resisted by all friends of freedom and democracy; the implication that democracy is a failure because the people are too ignorant to answer intelligently all the questions asked by the pollsters. This is a professorial invention for imposing professorial standards on the political system and deserves to be treated with extreme suspicion. Only a pedagogue would suppose that people must pass some kind of examination to qualify for participation in a democracy. Who, after all, are these self-appointed censors who assume that they are in a position to flunk the whole human race?

What are Voters’ Interests?

5

Schattschneider would seem to agree with my claim that we should not give too much weight to survey evidence that voters are disengaged, misinformed, and subject to prejudices that distort their choices. However, have I fallen into the same trap by defining what counts as a good way for voters to choose and for assessing the outcomes of elections?

what are voters’ interests? Am I guilty of imposing “professorial standards” that effectively “flunk the whole human race?” It should already be clear that I would “pass” the human race and give voters a substantially higher grade than many skeptics about the capacity of voters to function in a representative democracy. The charge that I am substituting one set of standards – professorial or otherwise – for another is more interesting. It seems clear that voters and the politicians who seek their support have a ready answer about what voters want: policies that they think are good in the sense that they will help advance their own private interests and/or their conception of the public interest, and candidates who meet fundamental standards of competence to do the jobs to which they aspire and who have the traits and characteristics associated with personal integrity and dedication to public service. In other words, voters want good policy and “a good man” or “a good woman.” Virtually all of the rhetoric in political campaigns turns in one way or another on policy differences and on defense or attacks based on a candidate’s personal qualifications, commitment, and integrity. Campaigners spend their resources trying to persuade voters of their fitness for office, the wisdom of their policy proposals, and the folly of their opponents’ policies. They also try to persuade voters that their opponents are incompetents or scoundrels in the pocket of special interests. The reason for all this effort is that politicians know that voters care about policy and the suitability of candidates for high office. I make this argument about voters’ interest in more detail in Chapter 1. The “policy” component is referenced by ideological differences between candidates because these differences capture the most important and enduring differences between opposing candidates’ policy commitments. The “suitability” component referencing voters’ interest in officeholders who can be trusted and who are competent to hold elective office is described by “valence” differences between candidates. I explain in Chapter 1 the reasons for using the term “valence” to refer to the qualities, traits, and skills voters care about in elected officeholders. For now,

6

Introduction

it is enough to recognize that voters care about these two things when they vote – candidates’ policy commitments and their personal suitability to hold office – and that the more a candidate reflects a voter’s desires on these two dimensions, the higher the “quality” of the candidate. Furthermore, the higher the quality of a candidate relative to his opponent, the more likely she is to vote for that candidate. Thus, we have a definition of voter’s interests – policies the voter sees as best and the personal suitability of the candidate to hold office – which provides criteria for assessing the quality of candidates and officeholders, and deciding whether voters are acting on their interests when they choose between opposing candidates. If they choose higher quality candidates over lower quality candidates, they vote with their interests.3 If they are dissuaded from voting for the higher quality candidate by factors such as party, incumbency, or candidate spending, these factors can be said to “distort” the vote and, potentially, the election outcome. If we have a defensible definition of the voter’s interest in elections, it is straightforward to extend it to election outcomes and representation: elections select the “right” candidate when they result in the higher quality candidate winning. They make the “wrong” choice when they choose the lower quality candidate. Moreover, higher quality candidates are more representative of voters’ interests (by definition) than lower quality candidates, and the higher the quality of the winning candidate, the better the electorate is represented.

what is representation? I put “right” and “wrong” in the previous paragraph in quotes to indicate that these terms apply to the definitions and concepts motivating this book. It is possible by other frameworks to assert different voter interests, and therefore different criteria for desirable voting and election outcomes. One example is organized around responsible party theory. This theory was developed as a critique of the Madisonian system of American national government, in defense of something like a party-centered parliamentary system. The Madisonian system tends to focus on individual office holders and their constituencies as the mechanism for checking 3

This statement ignores the possibility that one candidate may be better on policy while the other is better on valence, a significant complication discussed in Chapter 1 and throughout the analysis in this book.

What is Representation?

7

actions by government that are not supported by a sufficiently wide swath of the public. In fact, the ties between individual politicians and their constituencies, in combination with other differences among the major policy-making institutions, is a primary mechanism for assuring that “ambition will check ambition.” Responsible party theorists point out that the Madisonian system is anti-majoritarian, and that it hamstrings government on the grounds that government action is a threat to produce “tyranny.” Party advocates stress that government inaction can be just as much a source of tyranny as government action, and that political parties are essential institutions for building policy-making coalitions and enforcing responsibility to the public in elections. Thus, a responsible party theorist would put much less emphasis on individual candidates’ policy commitments and suitability, and much more emphasis on party differences.4 Such an approach would come to different standards of “right” and “wrong” outcomes and a different concept of representation. While other standards for assessing voting and representation are possible, my choices are not arbitrary. As the argument progresses, I will consider in more depth political parties because of their importance in explaining the results under study. In the meantime, I offer the standards of voter interests – policy (ideology) and the suitability of individual candidates for office (valence) – as productive places to start, even if it will be prudent to consider their relationship to party theory once we have the evidence in hand. These standards lead in a straightforward way to my concept of representation: representation occurs when electoral outcomes reflect their electorates’ fundamental interests. Representative outcomes occur when elections result in winning candidates aligned with their electorates’ policy interests and when competent, highly suitable candidates for the office win. Stated as a comparison between the candidates competing for an electorate’s support, the greater the policy agreement the winning candidate has with the electorate compared with the losing candidate, the greater the policy representation; the better qualified the individual candidate who wins compared with the losing candidate, the greater the “valence” representation. Far from being random in their outcomes, election results reflect democratic expectations as framed in this book rather well. 4

For succinct statements of responsible party theory, see APSA (1950) and Ranney (1962). For a more contemporary general defense of political parties, see Aldrich (1995).

8

Introduction

a note on method A truism in empirical research is that what we find depends on where and how we look. The careful study of how well elections work requires us to make some choices. Which elections will be the focus of study? What about these elections will be our focus? How can we design a study to address the skeptics about elections and provide evidence related to the performance of elections as institutions of democratic governance? Which elections should we study? American elections can be classified into three categories: elections to chief executive positions (president, governor, mayor), elections to seats in a legislature (House and Senate in Congress; state legislatures; city councils and other governing boards), and elections involving voters as law makers (initiatives and referendums in which the result makes law as a direct consequence of the election outcome). Which type of elections to study is partly a matter of taste and partly a matter of access. Because my interest is in representation in American national politics, I excluded from my focus state and local elections, including elections characterized by direct democracy. Presidential elections have two major drawbacks from the perspective of this research: (1) there are too few of them to study using the tools of modern political science – that is, there is insufficient data available on presidential elections to study the effects of candidates’ positioning and variation in leadership valence across elections;5 and (2) presidential elections are unusually high in the attention they receive, their level of competitiveness, and their visibility to ordinary citizens. This leaves as the possible focus congressional elections for the House and Senate. In these elections, voters select between competing candidates a winner, who then acts as an agent for their interests in government. I chose to study House elections because of the variation in races for House seats. This means we can observe the effects of candidate qualities, policy positions, and behavior along with the effects of individual voters’ characteristics and perceptions. There are also many more House races in a given year than there are Senate races, so it was possible to study a large number of elections in a single year (2010). There are 155 House campaigns included in the sample for this study, 150 of which were contested by candidates from both political parties. To study the 5

For example, we have reliable survey data about voters and electorates only since the presidential elections after World War II. This means there are severe limitations on the available data for all but the seventeen most recent presidential elections between 1948 and 2012.

A Note on Method

9

same number of Senate campaigns would require about five election cycles, which would have been beyond the resources available for this research.6 What is the focus of this research? The questions behind this research relate to the choices voters are offered by candidates in elections on policy and candidate suitability for office; the responses of voters to these choices; and the implications of these choices for electoral outcomes and representation. As noted, studying the choices between opposing candidates means that we must have comparable measures of opposing candidates’ policy commitments and their suitability as leaders. To assess the nature of voter response to the ideological differences between candidates, candidate and voter ideological positions must be measured on the same scale. Several recent studies have addressed this problem of equivalent measures of competing candidates’ and voters’ ideological positions on a common metric. However, no study I am aware of also includes comparable measures of opposing candidates’ individual suitability for holding office. Thus, a major contribution of this study is to combine analysis of the policy interests of voters with their interest in the valence quality of candidates. How is the study designed to address these questions? The details are in Chapter 2, the appendix, and supplementary materials, but the unique aspect of this research is that it includes panels of expert observers in each district in the sample who reported on the candidates’ ideological positions and measures of their suitability to hold office.7 We had an average of thirty-one observers in each district, and the measures employed are aggregations of their reported ratings and observations about the candidates and their campaigns. The advantage of this approach is that it produces measures of the ideological positions and valence quality of the two candidates opposing one another in each district contest included 6

7

I do not include primary elections in this study, though not because they are unimportant. Primaries shape the choices voters are given in general elections, and are implicated as an important cause of the polarization characterizing contemporary electoral politics in the United States (Kujala 2016; Hill 2015; Brady et al. 2007). A study of primary elections using the methodology I employ would be productive, but would require a substantially different design. I use the term “panels” to refer to the collections of expert observers in each district to avoid the term “sample.” District observers or informants were selected because they were knowledgeable about the politics in their district, rather than as samples of some larger population. They were independently surveyed as individuals, so they were not part of panels in the sense that they communicated with one another about the ratings and observations we asked them to report.

10

Introduction

in the study. In addition, surveys of constituents in each of the districts provide measures of how constituents voted, among other measures such as their ideological preferences. That we have measures of candidate positions and valence skills and characteristics independent of voter perceptions enables us to observe how voters respond to candidate differences without the concern that the differences are due to their own biases and misperceptions of candidate policy positions and valence characteristics. We can also observe their responses to candidate differences whether or not they were able to answer questions about those differences. Subject to the reliability and validity of the district observers’ ratings, we can assess whether voters’ choices reflect the quality of candidates when they vote, consistent with their interests as I define them. Moreover, we can assess the quality of outcomes of elections on those same interests. This enables a richer investigation of the concept of representation than has heretofore been possible because we can assess electorates’ ability to choose the better candidate not only on policy, but also on leadership-valence qualities and skills. It will permit us to determine whether factors such as party, incumbency, and candidate spending distort or advance voters’ interests. Furthermore, it will enable an investigation into the relationship between the valence and policy dimensions of representation.

a cautionary note All empirical studies of political phenomena are limited by the quality and availability of the data on which they are based. Even assuming that the measures employed in this study are without error, it is important to recognize the substantive boundaries and limits of the study. I am interested in how well elections work by the criteria I have summarized. Elections are the primary institutional mechanism for aligning the interests of citizens with the behavior of politicians in and close to government. Because elected officeholders are accountable to electorates, the democratic hope is that they have the incentives and resources necessary to control vast reaches of government that are not elected and to pursue policies and outcomes consistent with popular interests. The question of how well elections work, important as it is, has limits if the larger point is to understand the functioning of American democracy. This study is designed to address questions about how voters and electorates react to the choices facing them in elections. By and large, the results support my claim that “elections work better than you

Overview of the Book

11

think.”8 However, this does not negate significant problems in Congress and other institutions in the US national government. Elections to the House of Representatives could work perfectly (even if the conclusions of this study are optimistic, they fall well short of perfection), while Congress fails to meet even minimal standards of performance. It is possible that because elections work well, Congress as an institution does not, at least by contemporary standards. Although I touch on this question again in the concluding chapter, the functioning of Congress as an institution is not within the purview of this research. The study could have been of other elections in other institutions, and addressed the questions of interest equally well (the answers might have differed, at least to some degree).9 I have chosen to study US House district electorates because they provide the opportunity to address fundamental questions about voters and elections. Each district electorate is like a laboratory in which it is possible to observe critical aspects of the electoral process. The laboratories are not amenable to experimental manipulation, but they do permit careful observation of differences across candidates, electorates, and voters. The hope, then, is that the presence of multiple such electorates provides enough analytic leverage to support interesting conclusions, even if our confidence in causal inferences must be lower than if the electorates truly were laboratories that afforded full experimental control. Understanding complex political phenomena can be advanced in experimental settings, but we also require carefully conducted observational research in real-world settings. It is in that spirit that this study contributes to our understanding of voting, elections, and representation in US politics.

overview of the book Here are the major contributions of this book, along with chapter references that address and elaborate these contributions:

8

9

This, of course, depends on how well “you think” elections work. Although there is plenty of skepticism in the scholarly literature and popular discourse about how well elections work (see Achen and Bartels 2016 for a recent skeptical statement), there is a literature that is more optimistic. For examples of works that express various forms of optimism about voters and elections, see Buchler (2012), Popkin (1994), Wittman (1995), Key (1966), and Sniderman (2000), not to mention Schattschneider (1975). For a comparison of elections to the House and Senate that strives for an integrated approach, see Gronke (2000).

12

Introduction

r To understand voting choice, we must recognize the choices voters are offered (Chapters 4, 7). This means our models of voting choice, whether of individual voters or electorates, must include the differences between the candidates on critical dimensions of choice: ideological proximity to the voters’ and electorates’ preferences, and the suitability of the candidates on the leadership qualities voters value in elected leaders. r The quality of voter choice and of representative outcomes that result from electorates’ choices must be assessed against the choices they are offered (Chapter 5, 8, 9). For example, individuals may make a “correct” choice within my framework even when they vote for a candidate who is distant from their preferences if, in making that choice, they support the better of the two candidates. Similarly, while it is appropriate to assess representative outcomes by the quality of incumbents who won the last election, it is also important to understand representation against the standard of whether electorates select the better of the candidates running, even when the better candidate may, in absolute terms, be a poor representative. This perspective is especially important when thinking about the capacity of voters in democratic systems since voters can only be expected to choose wisely from among the choices they are offered (Sniderman 2000). A low-quality incumbent does not necessarily mean voters chose poorly. r We must have measures of the choices voters are offered on ideology and valence that are directly comparable for both candidates, and that are independent of voter perceptions (Chapter 2). It may seem odd that political scientists would study voting choice without including extensive data on the choices they are offered. However, it is difficult to get comparable data on opposing candidates without relying on voter perceptions, which are subject to bias and rationalization effects. We cannot assess the valence differences between candidates unless we have measures of the leadership qualities of both candidates that are measured on the same scale. We cannot observe whether voters and electorates select the more desirable candidate on policy unless we have measures of both candidates’ ideological positions on the same scale and on the same scale as voters’ and electorates’ ideological preferences. This is the first observational study of elections in the United States designed to meet these requirements. r Voters influence election outcomes in two ways: by their behavior on Election Day, and by virtue of the strategic calculations candidates make, anticipating the reactions of voters when they decide whether

Overview of the Book

13

and how to run (Chapters 6, 7). While a focus on what voters do on Election Day is important, how candidates and potential candidates anticipate the reactions of voters is also a mechanism whereby voters exercise quality control, albeit indirectly. This means the choice voters are offered when they vote is also partly the result of politicians’ expectations about how voters will choose. This introduces a kind of circularity into our study of voting and elections that can be difficult to resolve, a difficulty I address even if I cannot claim full resolution. r Even in the context of a highly polarized party system, the positions and leadership qualities of individual candidates matter to voters and electorates (Chapters 3–6, 7–9). As the parties have polarized, many scholars have noted the “nationalization” of congressional elections, although these elections take place in local districts. This nationalization around their policy platforms divides the parties, their candidates, and (to a lesser extent) voters who identify with the parties. Party perspectives on policy are shared by Democrats regardless of their locality and by Republicans no matter where they live. This polarization is an increasingly important aspect of the political environment, including in 2010 when the data for this study were collected. Despite this polarization around national party platforms, however, the differences between locally competing candidates on policy and leadership valence affect voting choice, election outcomes, and the nature of representation produced by the electoral process. In the concluding chapter, I summarize the argument made throughout the book, note some anomalies and remaining questions, and speculate about possible answers. In the next chapter, I develop the ideas broached in this introduction and link them to the extensive research by political scientists and others who have thought deeply and creatively about them.

1 Candidates, Voting Choice, and Election Outcomes

The theory of elections places expectations on voters and politicians. Voters are supposed to know their interests and vote accordingly; politicians are supposed to seek elective office by appealing to those interests and pursuing them when they win. This simple relationship between voters and politicians in the institution of competitive elections is the cornerstone of representative government. Of course, in reality things are not so simple – there are many reasons to doubt that elections actually work as they should. My central thesis is that, although there is undeniable slippage when the reality of elections is compared with the ideal, many political scientists and other observers are overly skeptical. The perspective I take emphasizes choice: voters must choose between competing candidates. This may seem an odd thing to emphasize. Of course elections are about choices. However, I will argue that while much of the literature on voting and elections has focused on the choices voters make, it has not devoted sufficient attention to the choices they are offered. This rather lengthy chapter lays the foundation for the analysis in the chapters that follow. It covers extensive ground, ranging from explanations of individual voters’ choices to election outcomes and political representation. I begin by explaining two fundamental rules of choice that reflect voters’ interests in candidates who agree with them on policy and who are strong on leadership qualities. I then move to a discussion of the many reasons scholars have expressed skepticism about voters’ ability to act on their interests as I define them.1 After summarizing my own 1

An excellent recent summary of the arguments for skepticism is provided by Achen and Bartels (2016, ch. 2).

14

Voters and Choice in Elections

15

responses to the skeptics, I conclude the topic of voting choice with discussions of correct voting as I define it and the complicating factor of voters who are “cross-pressured” between their interest in valence and policy because the candidate more appealing on policy is weaker on valence, or vice versa. The chapter winds up with a discussion of election outcomes and political representation. My approach to explaining election outcomes closely parallels models of voting choice at the individual level. This will allow us to observe the effects of voters’ fundamental interests on election outcomes that also parallel the effects we observe on individual voters, including the importance of candidate differentials and electorates cross-pressured between their interests in valence and policy. Representation, however, is not an individual-level concept, even though its conceptual roots are in the interests of individual voters. The discussion here will show how the approach I take informs a new conception of representation based on candidate policy and valence differences. I conclude by arguing for an “alignment” hypothesis about the relationship between the policy and valence dimensions of representation, in contrast to the conventional “leeway” hypothesis in political science. Along the way, I discuss some of the analytic and conceptual challenges facing a study of this sort. This chapter tells a somewhat complicated, multilayered story, but the starting point addresses a simple question: what are voters’ interests in elections?

voters and choice in elections The starting point of this book is that voters choose based on their fundamental interests in good policy and valence outcomes consistent with intrinsically valued traits, characteristics, and skills of their elected leaders. Voters may be faced with two candidates whose policy stands are not ideal, but they must choose the better of the two; the same two opposing candidates may have impressive skills and strong character or they may be incompetent scoundrels. Either way, voters must choose. Voters may also face a choice between policy and valence, as when the candidate more desirable on policy grounds is weaker on valence, or vice versa. The Proximity Rule of Voting Choice The proposition that voters exercise their voting choice in response to policy interests is based on a standard spatial model of voting choice. In the model, voters’ policy preferences and candidates’ positions are summarized by a one-dimensional liberal-conservative ideological scale.

16

Candidates, Voting Choice, and Election Outcomes Lj

Cj Cut point

−3

Very Liberal

−2

−1

0

1

2

3 Very Conservative

x1j

x2j

figure 1.1 Spatial Model of Candidate and Voter Ideological Positions in District j.

The model assumes that opposing candidates and voters can be placed on the left-right scale according to their preferences or, in the case of candidates, their policy commitments. Figure 1.1 illustrates the essentials of the model. The model illustrates the ideological positions taken by the liberal (Lj ) and conservative (Cj ) candidates opposing each other in the US House campaign in district j.2 Throughout this book, liberal positions are assigned negative scores; conservative ideological scores are indicated with positive numbers. The liberal-conservative scale ranges in value from very liberal (−3) to very conservative (+3), with the moderate or centrist position indicated by zero. Individual voters’ ideological preferences or “ideal points” are indicated by xi j . As is standard in spatial models, the distance between a candidate’s position and the ideal point of the voter represents a loss in utility in the policy the candidate is expected to deliver if elected.3 A voting rule based on this logic implies comparisons of the expected policy or ideological losses associated with each candidate’s position relative to the voter’s preferences. Voter 1 in Figure 1.1 votes for the liberal candidate because the loss from that candidate’s ideological position is less than the loss from the conservative candidate’s position, as indicated by the greater distance between x1j and Cj than between the voter’s preference point and Lj . Voter 2 votes for the conservative candidate for the same reason: her policy loss from the conservative candidate is less than the policy loss she would experience if the liberal candidate were elected. Especially 2 3

As an empirical matter, the more liberal candidate running in a district in this study is always a Democrat and the conservative candidate is always a Republican. The spatial model in voting-choice studies rests on early work by Duncan Black (1948) and Anthony Downs (1957). For accounts of the standard model, including assumptions and implications, see Adams et al. (2005) and Jessee (2012).

Voters and Choice in Elections

17

in two-candidate races, voters, however unenthusiastically, may support candidates who are unrepresentative of their personal preferences because the closer of the two candidates on offer takes a position distant from the voter. The ideological cut point between the candidates is the point on the ideological scale equidistant between the candidates. On the assumption that voters’ loss functions are symmetric to their left and right, voters at the cut point are indifferent on policy between the two candidates. Voters to the left of the cut point are closer to the liberal candidate and vote for that candidate; voters to the right of the cut point vote for the conservative candidate. For our purposes the logic of the spatial model of voting choice can be stated as our first voting rule: Proximity Rule : |xi j − L j | − |xi j − C j |

(1)

This expression describes a decision rule that governs individual voters’ choices based on which of the opposing candidates in the district is closer to the voter’s ideological preference (xi j ). When the expression is negative, it predicts a vote for the more liberal candidate running in the district (Lj ); when it is positive, it predicts a vote for the more conservative candidate. The Valence Rule The concept of “valence” as a basis for voting choice was first introduced by Donald Stokes (1963) in a critique of spatial models of voting choice, but the basic idea has been part of political theory as long as thinkers have speculated about the desirable skills and qualities of leaders in government. Stokes pointed out that in addition to “position issues” that form the basis of the spatial model and on which voters, candidates, and parties disagree, “valence” issues, defined as “those that merely involve the linking of the parties with some condition that is positively or negatively valued by the electorate” (Stokes 1963, 373), can have powerful effects in elections. Stokes used corruption as an example since no party or voter takes a position against integrity in government. All are opposed to corruption, but it can become an issue in campaigns when one candidate or party labels the opposition as corrupt. In this rendering, valence issues, whether in the form of valued outcomes such as full employment or those that everyone – candidates as well as voters – opposes such as corruption, crime, or economic decline, do not fit the spatial model because everyone takes the same position for or against these outcomes.

18

Candidates, Voting Choice, and Election Outcomes

Stokes’ critique landed a direct hit on political scientists’ use of the spatial model, especially in presidential elections, because it is apparent that these elections often turn less on the positions candidates and parties take than on who should be credited or blamed for good or bad outcomes. Presidential elections can also turn on the character, experience, and skills of the candidates. These, too, are consistent with the concept of valence because they are qualities universally valued in candidates and office holders. Since Stokes’ article appeared, the concept of valence has been expanded by some scholars to include any advantage that one candidate or party might have over the other not linked to the spatial logic of candidate and voter differences on position issues. These advantages could include credit or blame for outcomes, attributes of parties or candidates that everyone values or abhors such as competence or scandalous behavior, or advantages such as financial backing or incumbency that are not of themselves valued by voters, but that nonetheless confer electoral advantages on candidates or parties (Groseclose 2001; Feld and Grofman 1991). The meaning of valence I employ is in the spirit of Stokes’ concept, but limits valence to attributes, skills, and qualities that voters intrinsically value in candidates other than the policy positions they take. For clarity, this concept is referred to as “leadership valence,” but I use the term “valence” without the modifier to mean leadership valence. Leadership valence includes such skills and attributes as competence for the position to which the candidate aspires, the ability to be an effective leader, and personal integrity. This concept is narrower than Stokes’ emphasis on policy outcomes such as peace and prosperity, but it does capture qualities and attributes that all voters value in candidates and elected officeholders.4 A focus on candidate attributes and skills is appropriate for this study because individual members of Congress are less likely than presidential candidates to be judged by collective outcomes such as the state of the economy.5 Instead, they are judged on their individual suitability to hold office (Fearon 1999; Miller 1990; Hayes 2010). Other non-policy advantages candidates may enjoy such as incumbency and financial resources may relate to this concept of leadership valence, but they may also confer electoral advantages without satisfying the criterion of being consistent

4 5

A related concept has been applied to political parties in a comparative context (Clark and Leiter 2014; Leiter and Clark 2015; Clark 2009). See also Whitely et al. (2013). Members of Congress may be judged by voters on their ability to produce favorable outcomes for their districts (Mayhew 1974; Grimmer et al. 2012).

Skepticism About the Proximity and Valence Rules

19

with voters’ interests. In fact, candidate resource differences may distort elections by undermining voters’ ability to choose based on their fundamental interests. The Valence Rule is based on a comparison of opposing candidates’ leadership valence qualities: Valence Rule : R j − D j

(2)

Because I assume that all voters value leadership valence equally, the expression is a simple candidate difference, where a positive value indicates the Republican candidate in district j is stronger on valence and predicts a Republican vote by individuals in the district; a negative value indicates the Democratic candidate is stronger and predicts a Democratic vote. The Proximity and Valence Rules describe the fundamental interests of voters in elections. Politicians know that voters ultimately care about policy and the leadership qualities of the candidates, which explains why virtually all campaign rhetoric is targeted in one way or another at elements of these two rules.6 Positive campaign messages seek to convince voters of the merits of the candidate’s policy stands and of his or her skills and virtue as a public servant; negative campaign messages attempt to persuade voters of the disastrous consequences of the opponent’s policy commitments, most of which reflect his poor judgment, lack of experience, or subservience to special interests. The presumption of the Proximity and Valence Rules is that these differences between competing candidates are fundamental to voters’ interests in elections in a way that other considerations are not. While this may be true in the abstract, there are a variety of reasons offered by skeptics for doubting voters’ ability to behave consistent with these rules, especially in low-information elections.

skepticism about the proximity and valence rules To the ordinary observer of American politics, the claim that voters care about and act on policy preferences and the relative quality of candidates vying for their support may seem trivially true, but among political 6

Campaign statements aimed at the national party programs and personalities rather than the local candidates are a possible exception. Even such missives, however, imply a policy or valence failing on the part of the local candidate by emphasizing the candidate’s ties to objectionable national leaders or policies.

20

Candidates, Voting Choice, and Election Outcomes

scientists this is far from self-evident. A recent “realist” account by two leading political scientists dismisses the Proximity Rule and related spatial models of voting choice as a “folk theory” of democracy that does not square with a realistic understanding of voter choice and electoral representation (Achen and Bartels 2016). The issues touched on in this discussion occupy vast reaches of the literature in political science, psychology, economics, and sociology as they bear on citizen participation in the electoral process. While a complete discussion of the issues raised by skeptics about the average voter’s capacity to advance her interests in elections would occupy many volumes, it is worth addressing in a summary way these issues because of their bearing on the analysis throughout this book. Why Not Parties? The Proximity and Valence Rules place the emphasis on candidate, rather than party, differences. However, political parties occupy a central place in explanations of both candidate and voter behavior. Almost all candidates who have reasonable prospects when running for Congress seek the Democratic or Republican nomination in the primary stage of the campaign. Likewise, party identification is the single most important predictor of voting choice in the electorate. As a result, districts composed of substantial pluralities of one party tend to be safe for candidates in that party. Party identification is a distorting factor when it causes voters to support candidates who do not share their policy positions and/or who are lower on valence than their opponent. Prominent theories of party identification that emphasize it as a socialized attitude imply that it interferes with voters’ ability to act “rationally,” which usually means that it causes voters to deviate from voting based on their policy interests. Partisan bias may lead voters to perceive candidates as agreeing with their policy preferences when they do not, and to see candidates in their own party as stronger on leadership qualities than candidates nominated by the opposing party. Parties are also a complicating factor for politicians. They provide institutional support as politicians navigate the treacherous waters of electoral politics, and they deliver coalitional support in government as politicians try to make policy. Politicians with liberal policy objectives gravitate to the Democratic Party; conservative politicians seek careers within the Republican Party. At the same time, parties may restrict the ability (or incentive)

Skepticism About the Proximity and Valence Rules

21

of individual politicians to tailor their positions to the interests of their district electorates. For instance, a national party “brand” may interfere with voters’ ability to discern local candidates’ policy positions when they are at odds with national party positions (Snyder and Ting 2002; Kim and Leveck 2013). Party can also be the basis of alternative theories of voting and representation as in responsible party theories (Ranney 1962; Schattschneider 1942; APSA 1950).7 Responsible party theorists argue that voters’ true interests lie less in the choice between individual candidates than between the national parties, although the choice between candidates competing in local elections may be the means to choose between the parties. After all, parties, not individual legislators, create the coalitions necessary to make national policy. The parties, rather than individual candidates, are the focus of collective responsibility in the system (Fiorina 1980).

The Problem of Rational Ignorance A fundamental objection to the Proximity and Valence Rules is the claim that voters lack the resources and incentives to vote on the basis of these sorts of comparisons. Again, this objection, like most discussed in this section, is often seen as having special force in low-information elections like those studied in this book. The primary resource voters lack, in this view, is information, and an important reason is that an individual vote is extremely unlikely to influence the outcome of the election (Downs 1957; Riker and Ordeshook 1968). This creates a collective action problem whereby citizens have incentives to free ride on the efforts of others rather than bearing the costs of becoming informed about choices in the election relevant to their interests. Notice that this objection does not dispute the importance of policy and valence to citizens’ interests; it relates instead to the capacity of citizens to pursue these interests in elections. This logic of collective action that leaves members of large groups like electorates with incentives not to pay information costs presents a potentially devastating critique of electoral democracy. It suggests many or most citizens will not bother to vote, and that they choose based on limited information or prejudices, which they have no incentive to correct. 7

Parties can be a focus of valence voting, especially when a party is associated with undesirable outcomes such as economic decline or an unsuccessful military action. For an innovative study of the effect of valence on the party “brand,” see Butler and Powell (2014).

22

Candidates, Voting Choice, and Election Outcomes

This is Caplan’s (2007) argument in support of his pessimistic conclusions about how democracies work. If my car needs fixing, I may avoid mechanics on the basis of irrelevant prejudices (against mechanics with messy garages or who are of a different race), but eventually my interest in having my car fixed at a reasonable price may cause me to reevaluate and overcome irrational prejudices. Citizens, unlike consumers, have no incentive to correct biases, prejudices, and other types of misinformation even if they distort their voting choices from their true interests because their individual choices have no material impact on the outcome (Kuklinski and Quirk 2000). Unlike getting one’s car fixed, the relationship between getting information about choices and desirable outcomes is severed in elections, where individual voters cannot affect the outcome, but enjoy the benefits (or suffer the consequences) of the election result however misinformed or poorly reasoned their individual choice. The Proximity and Valence Rules seem to require voters to have substantial amounts of information. In keeping with the Downs-Caplan logic, many studies report evidence that large proportions of the American electorate are unaware of basic facts about American government and politics, including the issue and ideological positions of competing candidates in House elections (Delli Carpini and Keeter 1996; Stokes and Miller 1962; Hurley and Hill 1980). Indeed, a majority of respondents to the constituent surveys used in this study were unable to place the ideological positions of the Democratic and Republican candidates running in their district. The collective-action logic explains this ignorance as a reasonable response for individual citizens. How can we expect them to respond to the differences between opposing candidates, as indicated by the Proximity and Valence Rules, if they are ignorant about the candidates? Ideology: Voters Don’t Think That Way An objection related to the rational-ignorance problem is aimed squarely at the Proximity Rule dating to Philip Converse’s seminal 1964 article on belief systems in the mass public. Converse’s paper spawned a huge literature on the sophistication and capacity of the public to meet fundamental expectations of democratic citizenship. He reasoned that elite discourse in American politics revolves around ideological debate between liberals and conservatives and that sophisticated participation in elections requires citizens to have some familiarity with the ideological terms of that debate. However, he found that only a small minority of the public evaluated the

Skepticism About the Proximity and Valence Rules

23

candidates and parties using ideological thinking, and that a substantial majority failed to comprehend the basic meaning of the debate or to assign the proper ideological labels to the two American parties. Converse also showed that voters’ positions on individual issues did not cohere into a pattern of consistency that one would expect of individuals with a latent ideology who might simply be unfamiliar with the covering terms “liberal” and “conservative.” Most telling of all, however, was Converse’s conclusion that many citizens lacked meaningful attitudes on issues that had been debated among elites for decades. His notion of “non-attitudes” (Converse 1975), or responses to survey questions about policy issues that were essentially random efforts to placate the interviewer rather than expressions of policy interests, seemed to undermine the foundations of electoral democracy. As a result of his analysis, Converse (1964, 245) concluded that the average voter does “not have meaningful beliefs even on the issues that have formed the basis for intense political controversy among elites for substantial periods of time. Where any single dimension is concerned, very substantial portions of the public simply do not belong on the dimension at all.” Even scholars who saw Converse’s results as not so grandiose as to jeopardize democratic institutions often interpreted them as fatal to the Proximity Rule, since spatial voting seems to require that citizens have ideological or issue preferences and understand the positions of competing candidates when they vote. A related line of attack against the simple one-dimensional Proximity Rule is that more than one dimension characterizes political conflict in US politics. This objection has been raised by spatial modelers interested in the implications of multidimensional versions (Davis et al. 1970) and by empirical researchers interested in the effect of economic and social issues (Alvarez and Nagler 1998). Much of this work is not based on the idea that voters are incapable of spatial thinking as much as it is on the claim that a one-dimensional model oversimplifies a more complex reality for both voters and candidates. This approach can also be the basis for worries that representative or optimal outcomes lose their meaning or are impossible to achieve. The authors of The American Voter (Campbell et al. 1960, 169–70) specified three conditions for issue voting that have shaped thinking on this question for decades: “(1) The issue must be cognized in some form; (2) It must arouse some minimal intensity of feeling; and (3) It must be accompanied by some perception that one party represents the person’s own position better than do the other parties.” Similarly, in a leading text on public opinion and voting, Erikson and Tedin (2011)

24

Candidates, Voting Choice, and Election Outcomes

state as a condition for issue voting as specified in the Proximity Rule, “voters must be aware of the differences between the policy views of the candidates.” Such descriptions of the information required of voters as a necessary condition for casting a proximity vote constitute the conventional wisdom in political science, and are often referenced as reasons why voting consistent with the spatial model cannot be expected. Although Converse did not ground his work in the logic of collective action, his findings are consistent with it because developing an ideological preference is costly. It makes more sense for citizens to devote their energies to their private lives – to building and maintaining their careers, family relationships, hobbies, and other pursuits where their efforts have direct personal payoffs – rather than to politics where their efforts are lost in a sea of others’ actions over which they have no influence and in which outcomes affect the ignorant and disengaged as much as they do the sophisticated and informed. Candidate Resource Asymmetries Differences between opposing candidates’ resources linked to financial backing and incumbency status are often seen as factors that distort voting decisions from fundamental interests as described by the Proximity and Valence Rules. This expectation results from rational ignorance and the general lack of ideological thinking in the public. Voters unmoored by ideological preferences and low in information about politics and the candidates can be moved by ephemeral concerns such as name recognition and candidate-driven advertising (Cover 1977; Mayhew 1974). It is not difficult to find critics of the American electoral process, especially of elections to the House of Representatives, who lament the effects of incumbency and spending as fundamental pathologies. Incumbents are seen as having huge advantages over challengers, including the franking privilege and staff support as perquisites of their office (resources that challengers must find ways to pay for) that can be converted into visibility with voters and electoral support (Fiorina 1977; Grimmer et al. 2012; Mann and Wolfinger 1980). Incumbents also have advantages in fundraising as they appeal to interest groups and other financial backers concerned with policies over which legislators exert control, often through their committee and subcommittee memberships (Herrnson 1998; Jacobson 2013). In the districts sampled for this study, incumbents running for reelection enjoyed a large advantage in spending over their challengers (see Chapter 7). No wonder incumbents win reelection at such high rates.

Responses to Debates and Objections

25

Valence Interests are Not Distinct from Policy Interests As noted, the concept of valence in political science has been used to include various dimensions of candidate or party electoral advantage, some of which (such as financial backing) are not of intrinsic interest to voters. However, there are also those who have argued that valence, or concepts closely related to leadership valence, are not valued by voters distinct from their policy preferences. William Bianco (1994) provides an insightful analysis of constituent trust in legislative representation by making the argument that trust is rooted primarily in shared policy agreement and priorities between representatives and represented. Trust is a quality closely related to leadership valence because the division of labor between constituents and representatives means that politicians have significantly more information about policy alternatives and their likely effects on citizens. This presents a principal-agent problem, in which principals (constituents) are at risk of the agent (the representative) exploiting her information and other advantages to shirk on policy. For Bianco, the answer to this problem is that constituents “can allow [the representative] to act as she thinks best. That is, they can decide to trust their representative” (Bianco 1994). This concept of trust has a basis in policy agreement (Bianco 1994, 22): “The rationale for trust is simple: compared to the average constituent, the average legislator has better information about the relationship between policy proposals and policy outcomes.” Justin Buchler (2009), in a provocatively titled paper “Competence Schmompetence,” argues that valence and policy are linked in a different way: a competent legislator who takes an opposing ideological position should be less preferred by the voter than a similar legislator or candidate who is incompetent. The incompetent legislator will be less effective in producing policy the voter opposes than the competent legislator, so given a choice between a competent and incompetent conservative, liberal voters should prefer the incompetent conservative. Certainly, to grant Buchler’s point, there are many instances when opposing voters and pundits take obvious pleasure in the foibles, policy failures, and scandals of the opposition.

responses to debates and objections My responses to the debates and objections just discussed are the substance of the remainder of this book. However, it may be helpful to summarize particular responses to these issues before proceeding.

26

Candidates, Voting Choice, and Election Outcomes

Party vs. candidates? Analysis of the electoral process in American politics built around parties would have to confront the reality that candidates are prominent players, just as one (like this book) that begins with candidates must recognize the importance of parties. I begin with candidates because of their importance in the individualistic American political culture and because of their centrality in much of the theorizing about American politics. But parties are a big part of the story, including in the response to skepticism about the applicability of the Proximity and Valence Rules to voter choice. As a result, much of my analysis can be seen as supporting elements of responsible party theory in congressional elections. The centrality of party is a theme that runs through the book and I discuss its place in some detail alongside the candidate-based Proximity and Valence Rules in Chapters 8, 9, and Conclusion. Ideological polarization between the parties is obviously an important – some would say the defining – aspect of contemporary American politics. As demonstrated in Chapter 3, the data for this study are from a time when partisan polarization was at an historic high. This has implications for the results that are important but difficult to test empirically. Equivalent data from elections in which the parties were less polarized along ideological lines would almost certainly show reduced levels of proximity voting because party identification and ideological preferences overlapped to a lesser degree. In addition, polarization reduces the impact of candidate valence differentials on voting choice and election outcomes because polarization focuses more attention on party and ideological differences between candidates, and less attention on other candidate characteristics (Kim and Leveck 2013; Jones 2010). Another effect of polarization is that voters are better able to report ideological differences between the parties, which probably increases their ability to infer the ideological positions of major-party candidates (Abramowitz and Saunders 1998b; Hetherington 2001; Sniderman 2016). Partisan polarization relates, of course, to whether and how parties may distort the voters’ choices and other aspects of the process from ideals implied by the Proximity and Valence Rules. Partisan polarization is also the basis of changes in the system that have shifted national politics closer to the responsible-party ideal (Jones and McDermott 2009; Jones 2010). Rational Ignorance and Non-Ideological Thinking among Voters: Both the theoretical and empirical work supporting these objections place too much emphasis on individual voters, and not enough on the context shaped by the positions and characteristics of opposing candidates to which voters react. What is missing from the theoretical and empirical

Responses to Debates and Objections

27

literatures on individual voters is sufficient attention to the possibility that the political context itself – politicians acting in their own interests; and activists, financial backers, and opinion leaders also attempting to further their interests by advocating for candidates – mobilizes voters and provides cues about how to vote consistently with their interests (Aldrich 1993; Rosenstone and Hansen 1993; Sniderman and Stiglitz 2012). Although election outcomes are collective goods for ordinary voters, they are more than that for candidates, potential candidates, party leaders, and financial backers. Winning the election as a candidate includes private benefits associated with a political career; financial contributors are often interested in access, which is also a benefit that can be restricted. Thus, candidates and their surrogates have incentives to mobilize and inform voters, and often the channels through which these actors work signal partisan or ideological predispositions. In fact, scholars interested in evaluating hypotheses derived from the Proximity Rule have demonstrated strong proximity effects in presidential (Jessee 2012), congressional (Shor and Rogowski 2012; Simas 2013), and even non-partisan city elections (Boudreau et al. 2015). These studies have used a variety of methods to estimate opposing candidates’ and voters’ preferences in a common ideological space, and all find strong effects. These effects will be replicated in this study, as heuristics such as party identification can serve as useful guides to casting spatially correct votes (Joesten and Stone 2014; Lau et al. 2008; Boatright 2008). The use of decision heuristics (Sniderman et al. 1991) can include cues based on who runs (or does not run) such as whether an incumbent receives a serious challenge (Lupia and McCubbins 1998; Gordon et al. 2007, 2009). Joesten and I (2014) showed that heuristics and cues can produce spatially correct votes among voters who cannot report the ideological positions of the candidates. The various ways information costs are displaced to actors other than voters can mitigate the putative effects of rational ignorance (Sniderman 2016). The concept of rational ignorance does not imply ignorance so much as the absence of an incentive to bear information costs. Of course, an important function of campaigns is to reduce or eliminate the costs of information to voters. Indeed, in some campaigns it may be more costly to avoid information (for example, by leaving the room every time a political ad runs on television) than it is to be exposed to campaign information. Candidate Resource Asymmetries: Despite the widespread belief that incumbency and spending differentials are fundamentally distorting influences in favor of the well-endowed against opponents who cannot match

28

Candidates, Voting Choice, and Election Outcomes

their resources, candidates’ ability to attract resources such as financial backing and the experience a candidate may have as an elected office holder are ambiguous in their implications for our fundamental propositions about what motivates voters. Candidates (including incumbents) may have won prior elections based on their resource advantages, or because they were a better fit for their districts’ interests in policy and valence than their opponents. Likewise, the rule of anticipated reactions suggests that if contributors want candidates who can win, they should want candidates whose ideological positions and valence qualities will be attractive to voters. Justin Buchler (2007) makes a cogent argument that reelection success is exactly what should be expected of a well-functioning representative democracy. The reelection incentive encourages responsiveness on the part of elected legislators, which should satisfy voters and lead to high reelection rates. Only when the reelection incentive breaks down will incumbents be vulnerable and elections be highly competitive. In this argument, incumbency is the result of good representation rather than the cause of voters straying from their interests to reelect officeholders because of their visibility or resource advantage (Mondak 1995b; Stone et al. 2010b; Zaller 1998). Valence as a Voter Interest Distinct from Ideology: Bianco’s conception of trust comes close to the concept of leadership valence. Voters care about character and competence in politicians because they cannot monitor every move politicians make and because politicians have more information about the effects of policy. Character and competence foster trust that the representative will do a good job even when monitoring is difficult or impossible. Where Bianco and I may disagree8 is in my claim that valence is made up of personal qualities separate from policy, whereas Bianco’s trust concept is tied to policy agreement when monitoring is not possible. Thus, I suspect that Bianco might agree with Buchler’s argument that competence would be seen as a negative quality among voters who disagree with the legislator. Bianco’s concept of trust and its sources in policy agreement would undermine leadership valence as a distinct dimension of voter interest only if trust is fully explained by policy agreement. Constituents surely want to believe that politicians’ unobserved behavior is consistent with

8

Bianco’s argument about trust is not aimed at broader understandings of valence in concepts of representation, nor is it necessarily at odds with my arguments about valence. I address it because it is an intriguing discussion of the basis of trust in legislator-constituent relationships that can be interpreted as linking valence to policy positions.

Responses to Debates and Objections

29

their public pronouncements on policy, and if they believe there is a difference between stated principles and unobserved policy commitments, the politician’s reputation for leadership valence would be undermined. However, even though the argument that legislators may sometimes have to act against constituents’ opinions in order to make policy consistent with their interests has merit, I assume that constituents’ (and electorates’) ideological preferences are consistent with their interests. In this, I follow in the tradition of spatial modelers and much of the thinking behind liberal democracy (Pitkin 1967). Since individual legislators are less likely than chief executives to be held accountable for policy outcomes, they should be less willing to depart from constituent opinion to advance good outcomes. In the eyes of some, that may not relieve them of the moral responsibility of considering voters’ interests rather than their opinions when they are judged to be in conflict, but it certainly has an impact on the political incentives legislators face. While Buchler’s argument about legislator competence has its appeal, it rests on a vision of voters as highly strategic in their thinking about candidates, and it ignores non-ideological reasons that voters have for valuing high-valence candidates over those with fewer skills or who are of questionable character. There are many aspects of the job of legislator unrelated to ideology, including responsiveness to district and individual interests with claims against the government that do not directly involve national policy-making (Eulau and Karps 1977). Even on ideologically related policy decisions, liberal voters should prefer a high-valence conservative representative to one lower in valence because a skilled legislator of high personal integrity would be more likely to recognize factors that could create opportunities for compromise or provide reasons to depart from ideologically determined policy commitments. Jeffery Mondak links concerns with incumbent valence to the functioning of Congress as an institution (Mondak 1995b, 1043): Given that voters’ political interests conflict, maximization of institutional quality may be the single objective shared by all congressional voters. He may prefer Republicans and she may prefer Democrats, but they both favor the able over the incompetent and the trustworthy over the ethically dubious.

Or, as Pratt puts it (Pratt 2002): “an inept politician creates pure inefficiencies which are costly to all citizens.” Moreover, against Buchler’s results that show no effect of legislative skills on evaluations of incumbent members of the House, there is evidence of valence effects in other studies, especially when somewhat broader measures of leadership valence

30

Candidates, Voting Choice, and Election Outcomes

are employed.9 Mondak investigated incumbent competence and integrity and found effects on challenger entry, incumbent vote share, and constituents’ affect toward incumbents (McCurley and Mondak 1995; Mondak 1995b). Neither Mondak’s nor Buchler’s analysis, of course, tests hypotheses from the Valence Rule because neither study includes opposing candidates’ valence characteristics, although in earlier work based on the 2006 phase of this study, Buttice and I found support for hypotheses consistent with the Valence Rule (Buttice and Stone 2012; Stone and Buttice 2010). Voters are not the only ones who value valence characteristics. Even potential opposing candidates apparently take into account the leadership qualities of incumbents when thinking about whether to run (Stone et al. 2004; Stone et al. 2010). If these speculations are correct, a candidate’s ability to attract resources, win prior elections, and wage an effective campaign – his “campaign valence,” if you will – should relate to his leadership valence. Of course, it is also possible that these skills detract from the efficacy of the electoral process by distorting the perceptions and actions of voters in favor of well-funded incumbents against more qualified and representative challengers who would attract more votes if only they could match the visibility of their better heeled opponents. Assessing the implications of the Proximity and Valence Rules against competing heuristics based on incumbency and candidate spending motivates the analysis of correct voting in Chapter 5. The main point here is that resource asymmetries based on incumbency and spending do not of themselves indicate a pathological or a well-functioning electoral system.

models of voting choice The Proximity and Valence Rules are the basis of a “Fundamentals” model of voting choice that rests primarily on operational measures of candidate differentials based on the two decision rules to explain individual voter choice: p(RVi j ) = logit−1 (β0 + β1 (|xi j − L j | − |xi j − C j |) + β2 (R j − D j ) + β3 (Sample j ) + β4−k (Demographicsi ))

[1]

where p(RVi j ) = probability of voting for the Republican candidate running in the district; xi j = self-identified ideological position of voteri in 9

Buchler’s measure is based on a single item from the Candidate Emergence Study asking district informants about incumbents’ legislative skills.

Models of Voting Choice

31

districtj ; Lj and Cj = the ideological positions of the liberal and conservative candidates running in districtj . β 1 estimates the effect of the candidate proximity differential; Rj and Dj = the valence scores of the Republican and Democratic candidates running in the district. β 2 estimates the effect of the candidate valence differential; Samplej = a design control to reflect whether the district is in the competitive supplement drawn in the 2006 pilot study (coded 1), or in the random cross-section (coded 0); and Demographicsi = demographic characteristics of the individual voter assumed to be exogenous. The Fundamentals model serves as a baseline explanation of voting choice as if candidate differentials based on the Proximity and Valence Rules were the only variables we use to explain voting choice. It treats, in other words, the proximity and valence differentials as virtually the only interests voters have when choosing between candidates. I include a variety of demographic characteristics10 of voters in the Fundamentals model to identify the model because these characteristics and social behaviors are exogenous to the Proximity and Valence Rules (Keele et al. 2015). In the Fundamentals model, β 1 estimates the effect of the proximity differential between opposing candidates in the voter’s district; β 2 estimates the effect of candidates’ valence differentials. From the theoretical perspective developed in this chapter, these two candidate differentials are fundamental, so it is important to estimate their effects in a model that does not include standard explanatory covariates that may mediate their effects on voting choice. The Standard model of voting choice, described in more detail in Chapter 4, includes, among other covariates, party identification, presidential approval, evaluation of health care reform, and candidate resource differentials (experience, including incumbency, and spending). The covariates of greatest interest are party identification and the candidate resource differentials because these variables may compete with the proximity and valence differentials in our understanding of voting choice. That is, they may be endogenous to one or both differentials, and/or they may provide alternative explanations of voting choice at odds with the Fundamentals model. Take as an example party identification, which can be interpreted in several ways at odds with the Proximity Rule. By one interpretation, party identification reflects a psychological attachment to the parties rooted in childhood socialization that predates policy or ideological 10

I provide a description of the demographic variables included in the model in Chapter 4.

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Candidates, Voting Choice, and Election Outcomes

concerns. Such concerns may reflect long-term identifications with a party, as individuals follow the lead of their party and its leaders in adopting policy positions and, possibly, an ideological framework for organizing their policy preferences (Campbell et al. 1960; Green et al. 2002). Another interpretation, consistent with the Proximity Rule, is that party identification tends to reflect ideology, especially in a polarized system (Abramowitz and Saunders 1998a; Hetherington 2001). Highton and Kam (2011) have attempted to untangle the causal relationship between issue positions and party identification. They find that the dominant relationship depends on the larger political context, with party identification being more sensitive to issue positions when the ideological polarization between the parties is high (but cf. Miller 2000; Achen and Bartels 2016). Sniderman and Stiglitz (2012) argue persuasively on the basis of experimental evidence that candidates benefit from a “reputational premium” that motivates voters in their party to see them as representative, under conditions closely related to polarization. If this conclusion applies to the 2010 elections, party identification in the Fundamentals model would depress β 1 when it is included in the Fundamentals model because party identification would intervene between ideological proximity and voting choice. When party identification reflects commitments to the national party rooted in the ideological differences between the parties, it has a place approximately consistent with responsible party theory. It is not possible to sort out in this study the different interpretations of party identification vis-à-vis the Proximity Rule, but by comparing the Standard, Fundamentals, and Combined models we can observe the degree to which the effect of proximity differentials is reduced when party identification and other covariates are included. A similar exercise is possible in understanding the effects of candidate resource differentials, which are open to competing interpretations. Resource differentials may distort voting choice from voters’ fundamental interests, or they may reflect investments previous electorates and other supporters make consistent with the Valence Rule. By including candidate resource differentials in the Standard and Combined models, it will be possible to observe the effect of candidate resources as a possible mediator of valence differentials. Candidate Differentials and “Correct” Voting The Proximity and Valence Rules and the Fundamentals model emphasize the importance of choice since both rules describe candidate differences

Models of Voting Choice

33

on dimensions that ostensibly define voters’ fundamental interests in elections. They also have clear implications for when a choice is correct, or consistent with the voter’s interests: when voters make a choice consistent with the Proximity and Valence Rules, they vote consistent with their interests, as those interests are defined by the framework in this book.11 From this perspective, it will be of interest to ask how many voters vote correctly, and especially what factors seem to assist or hinder voters from casting votes consistent with their interests as I define them. It would seem from the discussion in the previous two sections that many skeptics about voters and elections would expect the rate of correct voting to be low especially in congressional elections, which are below the radar of many voters. Although it is difficult to specify a level of correct voting that would support the skeptics or discourage optimists about elections, if a substantial majority manage to vote consistent with their fundamental interests that tells us something about voters’ ability to pursue their interests. Moreover, we can take a page out of the debate over whether voters possess the wherewithal to vote consistent with the Proximity and Valence Rules to suggest factors that should enhance or impede correct voting. Information is an example. Skeptics assume that because most voters cannot place each of the opposing candidates running for the House in their district, they do not have the capacity to follow the Proximity Rule when voting. This implies that information about the candidates’ ideological positions is a necessary condition for voting correctly on proximity, or at least a strong facilitator of correct proximity voting. Likewise, if candidate resource differentials rooted in incumbency and financial backing distort voting consistent with fundamental interests, we should see lower levels of correct voting associated with these conditions. One response to skeptics about voters’ capacity for making reasonable choices is to emphasize the importance of heuristics or decision shortcuts that permit voters to choose as if they had more information, or in the context of this discussion, to vote correctly even in the absence of facilitating factors such as information. Party identification is perhaps the most common decision shortcut. Under conditions of partisan polarization, it is reasonable to suppose that voting for one’s party will often produce a spatially correct vote. Likewise, candidate resources such as incumbency and financial backing, rather than being distorting, may be 11

Other perspectives and frameworks lead to other definitions of correct voting. See Lau et al. (2008), and Lau and Redlawsk (1997) as examples.

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Candidates, Voting Choice, and Election Outcomes

useful shortcuts to correct voting, especially to choosing the better candidate on valence. Chapter 5 explores these questions based on a model of correct voting: p(CorrectVotei j ) = logit−1 (β0 + βi j (Facilitatorsi j ) + λi j (Proxiesi j )

[2]

Facilitators are factors that increase the probability of casting a correct vote but are not themselves decision rules; proxies are alternative decision rules that substantially overlap with the Proximity or Valence Rules. Facilitating variables and proxy decision rules may be linked to individual characteristics such as information or party identification or to the political context such as resource differences between the candidates running in the district. A Complication: Cross-Pressures Between the Proximity and Valence Dimensions of Choice I assume, following Downs, that voters’ first priority in elections is on policy returns consistent with their interests. This is one reason the Proximity Rule should operate with greater force than the Valence Rule on voting choice.12 However, there is a problem with the Proximity and Valence Rules as indicators of correct voting: what happens if the candidate closer to the voter on ideology is also the valence-disadvantaged candidate? The links between policy and valence can be addressed with a model of a two-dimensional decision space characterized by the Valence and Proximity Rules. Assume for this illustration that both the Valence and Proximity Rules are calibrated on four-point scales of utility: when the Valence Rule indicates the Democratic candidate is much stronger than the Republican candidate running in the district, voters in that district stand to gain up to 2 units in utility from a Democratic victory, whereas in districts where the Republican is stronger, voters gain up to 2 units on the same dimension, depending on the magnitude of the difference between the candidates. The signs of the utility scores indicate the direction of 12

Explanations for a stronger effect of proximity than valence on voting choice besides voter priority include the possibility that primary candidates are vetted for valence strengths and within-party adherence to partisan ideological commitments. If so, candidates in general elections would differ substantially more on ideology than on valence, which could explain a stronger effect of proximity even if voters value ideological proximity and valence equally. I am grateful to Ben Highton for suggesting this possibility.

2

Models of Voting Choice

2

1

0

35

3

4

Closer to Republican

Republican Proximity Voters

Voter's Proximity Differential 0 1 −1

Aligned Republican Voters −1

Cross-Pressured Voters 0

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Democratic Valence Voters −1

−2

Republican Valence Voters

−3

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Aligned Democratic Voters Closer to

Democratic Proximity Voters

−2

Democrat

−4

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−3

−1

−1

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0 Valence Differential

0

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figure 1.2 Hypothetical Utilities from Proximity and Valence Rules Note: Utility = Valence Differential + Relative Proximity.

candidate differences, such that a utility of −2 indicates a magnitude of utility equal to +2 but in the Democratic direction, while zero indicates the candidates are equally strong (or weak) on valence. The proximity dimension of choice also ranges from −2, meaning that the voter is much closer to the liberal (Democratic) than to the conservative (Republican) candidate; voters much closer to the Republican candidate enjoy a maximum utility return on policy of +2. Again, the signs of these values indicate the directionality in the dimension with negative scores signifying the magnitude of utility returned to voters closer to Democratic candidates, and positive scores indicating utility from Republicans. Thus, consistent with the Valence and Proximity Rule expressions, a voter whose expected return is negative votes Democratic; a voter with a positive return votes Republican. A voter at the ideological or valence indifference point between the candidates receives zero utility on valence or policy from a victory by either candidate. Figure 1.2 illustrates the utilities returned to voters depending on their positions in the two-dimensional space defined by the valence and proximity differentials.

36

Candidates, Voting Choice, and Election Outcomes

Voters may be “aligned,” which means they are ideologically closer to the candidate in their district who is also stronger on valence. Voters in this fortunate situation stand to benefit on both dimensions by their vote, up to a total of 4 units of utility by the logic of Figure 1.2. Aligned voters predicted to vote Republican have positive utility scores; aligned voters predicted to vote Democratic have negative utility scores, but voters in the same position in each quadrant realize the same net return in utility. “Cross-pressured” voters, in contrast, are caught between their interest in policy and valence because the ideologically closer candidate in their district is weaker than the opposing candidate on valence. These voters must choose between the two rules. Cross-pressured voters in the figure occupy the other two quadrants. Cross-pressured voters are either in a district with a Republican candidate stronger on valence but who are ideologically closer to the Democrat (the southeast quadrant), or they are in a district with a valence-advantaged Democratic candidate but they are closer to the Republican (the northwest quadrant). The dashed diagonal line divides voters in the cross-pressured quadrants between those predicted to be proximity voters (because, on the arbitrarily set scales in the figure, the utility they get from proximity is greater than the utility they get on valence), or valence voters (because the utility they get from valence exceeds the utility from ideological proximity). Figure 1.3 incorporates the assumption that policy concerns affect voting choice more than valence by weighting valence returns from voting less than ideological proximity. In addition to the heavy diagonal from Figure 1.2 indicating equal weighting of the two dimensions, Figure 1.3 shows valence weights of .5 and .25 of proximity. An effect of reducing the weight on valence is to increase proximity voting among crosspressured voters. Thus, among cross-pressured voters in the southeast quadrant, reducing the weight of valence decreases the number of Republican valence voters with a corresponding increase in Democratic proximity voters. When, for example, valence is weighted .25 of proximity, the utility returned to the voter in a district with a much stronger Republican candidate on valence realizes a return on that dimension of only +.5. If that voter is much closer to the Democrat (for a proximity return of −2), the two dimensions no longer cancel out because the net return on both is −1.5, rather than zero. Conversely, a voter in this quadrant with a large valence differential only votes Republican if the proximity differential weakly favors the Democrat. Thus, most voters in the southeast quadrant vote Democratic on the basis of stronger returns from the proximity than valence differentials. A similar effect, of course, occurs in the

Models of Voting Choice

2

37

Closer to Republican

Republican Proximity Voters

Voter's Proximity Differential −1 0 1

Aligned Republican Voters Cross-Pressured Voters

Democratic Valence Voters Republican Valence Voters Valence weighted .5 Valence weighted .25

Cross-Pressured Voters

Aligned Democratic Voters Closer to

Democratic Proximity Voters

−2

Democrat

−2

Democrat Stronger

−1

0 Valence Differential

1

2 Republican Stronger

figure 1.3 Hypothetical Utilities from Proximity and Valence with Variable Valence Weights

northwest quadrant, with an increased proportion of Republican proximity voters compared to when both dimensions are equally weighted. Keep in mind that the utilities and weights in Figures 1.2 and 1.3 are for illustrative purposes only. However, if the weight of valence is substantially lower than the weight of ideological proximity (.25 of the proximity weight, for example), a simple hypothesis linking the two dimensions to a standard spatial-model representation of voter choice is apparent: valence voting should occur among voters closest to the ideological cut point between the candidates, with the distance from the cut point determined by the weight of valence relative to ideological proximity. This is Groseclose’s (2001) “Stokes region,” which identifies voters who support the valence-advantaged candidate over the closer candidate on the left-right scale. Since the metrics on the proximity and valence scales are hypothetical, we need not be concerned with the precise magnitude of the distance from the cut point. But the hypothesis is clear: valence voting among cross-pressured voters should be at its peak among voters closest to the ideological cut point between the candidates, and decline as voters’ distance from the cut point increases.

38

Candidates, Voting Choice, and Election Outcomes

The possibility that voters are cross-pressured between their ideological and valence interests complicates things because it means that many voters cannot pursue their fundamental interests on both dimensions with their vote. The same problem, as we see in the next section, applies to district outcomes and representation. While in some districts it is possible for an electorate to pursue its interests in ideology and valence by electing the same candidate, when district electorates are cross-pressured this is not possible. Recognizing the existence of cross-pressured voters and district electorates can help avoid errors when inferring that factors related to correct voting and correct election outcomes distort or facilitate outcomes consistent with voters’ interests on one dimension but not the other.

electoral outcomes This book is not only about how individual citizens vote, but what the consequences of their behavior are. It would be incomplete to assume that consequences of interest are purely a matter of voters’ choices because electoral outcomes are dependent on the behavior of voters and politicians (Ashworth and Mesquita 2014). Thus, our understanding of electoral outcomes must embrace the behavior of politicians (principally, candidates for office) as well as voters. Two electoral outcomes are of interest: the vote shares candidates receive and who wins the election as a result; and political representation. In examining these outcomes, there are parallels with and important differences from the discussion of individual voting choice. Explaining Candidates’ Vote Shares The analysis of vote shares closely resembles the Fundamentals model (Equation [1]) of voting choice: Republican vote share = β0 + β1 (|X j − L j | − |X j − C j |) + β2 (R j − D j ) + β2 (Sample) + B4−k (District Demographics j ) + ε

[3]

where Xj = District median ideological preference,13 and all other terms are as previously defined; β 1 estimates the effect of the district proximity differential; β 2 estimates the effect of the candidate valence differential. 13

I assume symmetric district ideological distributions and estimate the median as the district mean on the liberal-conservative scale.

Electoral Outcomes

39

As with the Fundamentals model of voting choice, Standard and Combined models can be estimated to assess how other covariates mediate the effects of the principal terms in the Fundamentals model. The point is to conduct tests of the effects of candidate proximity and valence differentials on election outcomes, and to understand the effects of policy and valence interests on electorates’ behavior. The expectation, based on the logic behind the Proximity and Valence Rules of voting choice by individual constituents, is that electorates enforce their collective interests by rewarding candidates closer to their ideological interests and stronger in leadership valence qualities. Also in parallel to the analysis of voting choice, the Proximity and Valence Rules imply correct choices by district electorates: when election outcomes result in the stronger candidate on valence being selected, and/or when the candidate closer to the preferences of the district median voter wins, it can be said that the election results were “correct” from the perspective of the Proximity and Valence Rules. The discussion of correct outcomes of district elections raises the question of political representation, which is a more complex concept than we encountered in discussing voting choice. Explaining Political Representation The goal of an empirical explanation of political representation is similar to explaining correct voting by individual voters: can we specify the variables associated with correct outcomes and related measures of political representation? It is clear that we are headed toward a two-dimensional concept, in which good representation is linked to the policy and valence interests of voters. However, to provide an explanation of political representation as I conceive it in this analysis, we must first explore how previous work has investigated district representation. This entails a focus on the policy or ideological dimension of representation, which is by far the dominant focus of the literature. Consider again the term designed to capture the Proximity Rule in Equation [3]: District Proximity Rule : (|X j − L j | − |X j − C j |) This expression amounts to a definition of policy representation based on the spatial model’s core idea that as the distance between district preferences and a candidate’s position increases, the quality of ideological representation declines. By this logic, the more representative candidate

40

Candidates, Voting Choice, and Election Outcomes

is the candidate closer to the district’s preferences. The closer candidate’s vote share should be larger than the one whose ideological position is more distant from district preferences, and when the closer candidate wins, the outcome is spatially correct. As noted, this spatial notion of representation has not been addressed in most of the relevant literature for the lack of measures of district and candidate ideological positions for both candidates on the same scale as district ideological preferences. In fact, by far most studies have only two pieces of information: incumbents’ and districts’ ideological positions not on the same scale. In the absence of the data necessary to estimate the components of the District Proximity Rule, political scientists have examined the empirical relationship between the incumbent’s ideological position in each district (Ij ) by some measure, usually based on roll-call votes cast by incumbents, and the ideological preferences of districts (Xj ) based on an indicator such as mean district ideology (Clinton 2006) or presidential vote share (Ansolabehere et al. 2001). The fundamental equation of such studies is: I j = β0 + β1 (X j ) + β2 (IncumbentParty) + ε

[4]

In this setup, β 1 is an estimate of the responsiveness of incumbents to variation in the ideological preferences of their districts, independent of party. Instead of directly comparing the ideological positions of incumbents with their districts, the data limitations of scholars working in this tradition force them to examine the covariance between district preferences and incumbents’ ideological positions: as districts are more conservative, responsive incumbents are more conservative (Achen 1978; Erikson and Wright 2000; Miller and Stokes 1963; Clinton 2006; Stone 1979). The level of responsiveness in the system is estimated by the magnitude of the positive coefficient, β 1 . As discussed in Chapter 8, a responsiveness approach to the study of district representation has several weaknesses, including the exclusion of candidates opposing incumbent office holders and the possibility that legislators can be responsive without legislators being representative as defined by spatial models. In a study of district representation based on the spatial model, one can ask not only how close candidates are to district preferences, but what explains why some are closer than others. This opens questions similar to the study of correct voting: what factors facilitate district ideological representation? What sorts of conditions seem to distort

Electoral Outcomes

41

district representation by being associated with greater distance between candidates and district preferences? If the district-candidate (or district-incumbent) relationship can be understood as the distance between individual candidates’ ideological positions and their district preferences, it is also possible to introduce the concept of valence representation. This is a straightforward application of the Valence Rule to explaining district outcomes, including vote share as in Equation [3]. Indeed, since the Valence Rule for voters is the difference in leadership qualities of the opposing candidates running in the voter’s district, it is exactly the same variable when we shift to explaining district outcomes. The assumption is that district electorates prefer valence-advantaged candidates over opponents weaker on valence, just as individual voters do. Because valence is a fundamental interest of voters and electorates, it is the second dimension of representation. Just as candidates closer to district policy preferences are more representative than candidates whose positions are more distant from those preferences, so also are candidates stronger in leadership valence more representative of district interests than candidates weaker in those qualities. The problem with studies related to valence representation is not theoretical, but empirical. A substantial body of theoretical work addresses the place of valence in understanding the relationship between incumbent representatives and candidates and their electorates (Adams et al. 2005; Ansolabehere and Snyder Jr. 2000; Groseclose 2001). Moreover, leadership valence has been a matter of concern among classical political theorists for centuries. To take an example from David Hume (1987, 39 (1739)): The persons, who first attain [positions in government] by the consent, tacit or express, of the people must be endowed with superior personal qualities of valour, force, integrity, or prudence, which command respect and confidence.

With the Valence Rule as our guide, we consider how well candidates represent their district electorates on valence, and the factors that enhance or impede district valence representation. Complication: Cross-Pressured Districts and the Leeway Hypothesis The discussion of “aligned” vs. “cross-pressured” voters has an obvious parallel for district electorates: candidates closer to the median voter in the district need not be stronger on valence. Recognizing that the

42

Candidates, Voting Choice, and Election Outcomes

ideological and valence interests of the district may not be aligned raises the question of how the two dimensions relate in candidates’ relationships to their electorates. It also means that when districts are cross-pressured, good representation on one dimension necessarily means poor representation on the other (that is, the weaker candidate on the other dimension necessarily is chosen). The conventional view is that valence advantages create opportunities for office holders to shirk on policy. Incumbents are often seen as having resources and skills that give them electoral advantages over challengers because of their status as incumbents. These advantages, in turn, give them leeway to pursue policies more consistent with their own preferences than their districts’ interests. For example, the literature on the “personal vote” that incumbents cultivate frees them from being overly constrained by district opinion on policy (Cain et al. 1987). Fenno (1978) offers an explicit defense of this idea in discussing how incumbents can use the trust they accumulate among constituents to justify casting unpopular policy votes (cf. Bianco 1994, 23): “The credibility of any given explanation probably depends less on the content of the explanation itself than on its compatibility with some previously established perception of the explainer, ‘as a person’” (Fenno 1978, 149). He goes on to provide a classic statement of the leeway hypothesis:14 Presentation of self enhances trust; trust enhances the acceptability of explanations; the acceptability of explanations enhances [roll-call] voting leeway; therefore, presentation of self enhances voting leeway. (Fenno 1978, 151; emphasis in original)

What would this mean for the two-dimensional concept of representation? The leeway hypothesis is based on the assumption that office holders care about more than just getting reelected: they have policy goals they seek to advance. So far, so good. I have no problem with assuming candidates and office holders care about policy, although they also must care about election and reelection in order to pursue their policy goals (Mayhew 1974; Fenno 1978). However, it also assumes the Valence Rule: because voters care about the presumed valence advantage the officeholder has over her opponent, incumbents can trade some of the support they receive based on valence for support they may lose 14

Fenno’s point pertained less to leeway to adopt ideological positions at odds with district preferences than to incumbent trust as a way of explaining an unpopular vote. His logic, however, applies to the broader leeway hypothesis advanced by other scholars.

Electoral Outcomes

43

from disappointing constituents on policy.15 In contrast, I propose an alignment hypothesis based on the claim that the valence and ideological dimensions of representation should be more in harmony than in tension. Tracing the logic of the leeway hypothesis to its implications for the interests of district electorates in policy and valence exposes the reason to doubt that it is true: why would skilled politicians like the average House incumbent give such a powerful strategic opening to challengers (Adams et al. 2005, Appendix 3.1)? The leeway hypothesis has clear implications for how valence-disadvantaged candidates should run against incumbents because it suggests an opening on the ideological dimension for challengers running against high-valence incumbents: adopt ideological positions closer to the district than the incumbent and make the election about policy rather than valence. To give the valence-disadvantaged challenger an opening on policy, in other words, is to court electoral disaster. The alignment hypothesis, in contrast, expects incumbents (or, more generally, any valence-advantaged candidate) to seek electoral returns on both dimensions: candidates strong on valence will also strive to be ideologically representative. If valence-advantaged incumbents seek also to satisfy their district electorates’ ideological interests, what choices do challengers have? Several formal models suggest an answer (Ansolabehere and Snyder Jr. 2000; Groseclose 2001; Aragones and Palfrey 2004): challengers disadvantaged on valence position themselves toward the ideological extreme. They do this in order to focus the campaign away from their disadvantages on valence out of uncertainty about the ideological preferences of the district, and to mobilize activists and financial contributors in their partisan base (Stone and Simas 2010). It is also possible that primary electorates in most challengers’ districts, knowing their candidate will be at a disadvantage on valence, are inclined to nominate more extreme challengers in the hope that their policy preferences will prevail. As a result, the candidate differentials should tend to be positively correlated, with candidates stronger than their opponents on valence also closer to their districts’ ideological preferences. If the leeway hypothesis is true, there should be a preponderance of districts cross-pressured between their ideological and valence interests, or a negative relationship between the two dimensions as illustrated by

15

Adams, Merrill, and Grofman (2005, 195) conclude from one of their models that “as long as policy seeking makes a substantial contribution to candidate motivations, the candidates should diverge significantly in the policy space, and the valence-advantaged candidate should locate further from the median than the disadvantaged candidate.”

Candidates, Voting Choice, and Election Outcomes

2

44

Closer to Republican

Cross-Pressured Districts Aligned Republican Districts

District Proximity Differential −1 0 1

Expected Relationship, Alignment Hypothesis

Expected Relationship, Leeway Hypothesis

Aligned Democratic Districts Cross-Pressured Districts

Closer to

−2

Democrat

−2

Democrat Stronger

−1

0 Valence Differential

1

2 Republican Stronger

figure 1.4 Implications of Leeway and Alignment Hypotheses for Candidate Differentials

the dashed line in Figure 1.4. This is what Barry Burden suggested based on his analysis of incumbent and challenger extremism in the 2000 elections (Burden 2004): “in many districts the winning candidate [usually the incumbent] is further from the center than the loser, but manages victory on the basis of non-ideological criteria that overwhelm the modest effects of ideological proximity.” The result would be to create a choice for district electorates: choose the stronger candidate on valence by choosing the incumbent (who is usually stronger on valence) or the more ideologically moderate challenger. By creating a strategic opening on the ideological proximity dimension for valence-disadvantaged candidates, the leeway hypothesis expects tension between the two dimensions. I assume that candidates – challengers as well as incumbents – want to win the election, and that most want a career in Congress or in electoral politics. This means there is uncertainty because future conditions affecting their ability to win are impossible to predict. One thing is certain: leadership valence will always be valued by future voters, no matter what the office or other variables at play in those elections. There may be uncertainty, however, about the ideological preferences of the electorate in the immediate election, and that uncertainty grows as the politician

Electoral Outcomes

45

looks to the future with possible redistricting, opinion and agenda shifts, and the preferences of electorates in contests for other offices. Under these assumptions, incumbents have powerful incentives to maximize support on both the ideological and valence interests of the electorate. They are unlikely to trade support on policy because they have what may seem to be a comfortable margin on valence in a given election; they are likewise unlikely to hand their opponent an advantage on a dimension of choice as important as ideology or policy. The leeway hypothesis is not only implausible, it has never been tested because no data on opposing candidates’ proximity and valence differentials have been available. Thinking through the implications of the leeway hypothesis for a two-dimensional concept of representation and testing the relevant hypotheses on which it depends are of critical importance to our understanding of political representation. The alternative, alignment hypothesis, suggests that valence-advantaged candidates seek an advantage on ideological proximity to the district, rather than tolerating the tension implied by the leeway hypothesis. The alignment hypothesis expects the two dimensions of representation to be positively related, which, if true, provides a broader basis of support for theories of electoral representation. Complication: The Interdependence of Candidates and Voters Anthony Downs (1957) is generally credited with seeding development of spatial models in political science. One of the appeals of these models is that they incorporate the incentives and behavior of citizens/voters and politicians/parties in the same framework. Downs characterized the relationship between politicians and voters as one of interdependence (1957, 74): Since governments plan their actions to please voters and voters decide how to vote on the basis of government actions, a circular relation of mutual interdependence underlies the functioning of government in a democracy.

The “circular relation of mutual interdependence” applied to the study of congressional elections means that politicians anticipate how voters will choose on Election Day and decide on that basis whether and how to run. If the Proximity and Valence Rules describe voters’ interests in elections, politicians with strong reputations and skills decide to run when their ideological positions and valence characteristics put them in a strong position to win; when their ideological positions or valence

46

Candidates, Voting Choice, and Election Outcomes

characteristics are expected to leave them at a disadvantage compared to their opposition, they refrain from running. Voters, for their part, react to the choices before them in the ways politicians anticipate: they support the candidate closer to their ideological preferences and stronger in valence over the less desirable candidate on these dimensions. This circularity resulting from politicians deciding whether and how to run based on their expectations about how voters decide makes it difficult to determine the effects of candidate quality on election outcomes. One manifestation of this problem is in estimating the effects of incumbency or challenger experience (Cox and Katz 2002). If incumbents run for reelection when they think they can win and retire when they expect to lose and if their expectations are grounded in reality, comparing districts in which incumbents run with those where they do not to estimate the effect of incumbency gives a biased estimate of the impact of incumbency on elections. Incumbents who run may do better in elections because they are good at anticipating favorable conditions, not because of any inherent benefit of being an incumbent. The same problem troubles estimates of the effects of “high-quality” challengers, defined as those who have held a prior elective office. If these politicians are good at estimating their chances and if they enter when they think their prospects are good and refrain from running when they see their chances as poor, part of the boost experienced challengers receive in the vote share compared with inexperienced challengers may be due to their ability to forecast the election, rather than their campaign prowess. This question of strategic politicians anticipating the reactions of electorates presents a challenge because electoral politics is laced with strategic behavior by politicians. The investments required to run for a House seat are enormous, so it makes sense that politicians and their close supporters would think carefully about their chances of success when they consider whether to run in any given election. However difficult it is to sort out the effects of anticipated reactions, they are more than just an analytical confound in political scientists’ equations estimating the effects of incumbents’ and experienced challengers’ campaigns. They are also a critically important mechanism of electoral accountability. If politicians are good at anticipating voters’ reactions and refrain from running when voters would reject them, they do the voters’ work for them. This is especially true if, as I contend, politicians anticipate the fundamental interests of voters when they decide whether and how to run. Spatial models of candidate competition are based on politicians anticipating the ideological interests of voters: politicians in these models know

Electoral Outcomes

47

that they need the median voter’s support because voters choose candidates based on the Proximity Rule, and the median voters’ support is sufficient to win the election. The circularity these models imply is nicely captured by Barry Burden (2004, 211): “there is a striking irony in a spatial model that is based strictly on proximity. Because ideology is all that matters, candidates converge, leading to an election where ideology [apparently] does not matter.” Because politicians anticipate that voters care about ideology, their behavior makes it difficult or impossible to vote on the basis of their ideological preferences.16 In such a world, in other words, we would not be able to observe an effect of the Proximity Rule because politicians perfectly anticipate the ideological interests of voters. Of course, we could not conclude that voters’ ideology did not affect elections or produce ideological representation. Instead, ideology could affect the election by influencing the positions taken by candidates and produce ideological representation because of anticipated reactions by politicians, not the actual behavior of voters on Election Day. Exactly the same process could be at work on the valence side. Politicians know that voters care about leadership valence, so they enter races when they think their valence reputations are strong enough to help them win. The result could be elections in which low-valence candidates weed themselves out (or are weeded out in primary elections), both candidates are relatively high on these skills and qualities, and the effects we would see on voters’ choices are weak or nonexistent. I deal with this problem of circularity in observing processes that involve anticipated reactions in two ways: first, I assume that in a complex process such as elections with uncertainty on all sides, there are breakdowns of various sorts. Politicians cannot perfectly anticipate the needs and interests of voters; voters cannot determine with certainty the relative benefits associated with competing candidates; errors are made whereby the “wrong” candidate wins; some incumbent officeholders shirk and scandals occur, signaling voters and prospective candidates that an ideological or valence error was made in previous elections. Over time gross errors should become evident to potential challengers looking for career opportunities and therefore to voters on Election Day.17 The

16 17

Downs called this a rationality “crisis” in the theory. Mondak (1995a) suggests a process such as this in a dynamic model of incumbent reelection as a critique of the effects of term limits, which short-circuit this process. This dynamic is also fundamental to Buchler’s (2012) model of elections as hiring processes.

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Candidates, Voting Choice, and Election Outcomes

process will always be noisy, but this logic is at the heart of democratic politics, just as Downs suggested. Second, I measure politicians’ expectations about their prospects for success in the upcoming election by using expert observers’ estimates of these prospects as proxies for what local politicians are thinking before they decide whether to enter a race (see Chapters 2 and 6). I collected these estimates well before the 2010 election cycle began, some sixteen months before Election Day, which means they were expectations untutored by events such as which challenger enters the race or how the candidates conduct their campaigns. Knowing something about how local politicians estimated their prospects for success as they decided whether and how to run is helpful because it allows us to evaluate the hypothesis not only that they anticipated their success, but that their success was linked to the fundamental interests of voters as specified by the Proximity and Valence Rules. Having these measures also gives us new leverage to isolate the effects of voters’ Election Day responses to the choices candidates offer them, and the prior decisions candidates make about whether and how to run (see Chapter 7).

summarizing the argument Everything in this chapter flows from two organizing propositions about voter interests and choice: the Proximity Rule rests on the assumption that voters have an interest in policy; the Valence Rule asserts that voters respond to differences in opposing candidates’ personal suitability to hold high elective office. Spatial models assume that voters’ ideological ideal points can be compared with the ideological positions candidates adopt in campaigns, resulting in a model of choice in which voters support the candidate whose positions are closer to their ideological preferences. But voters’ interests are also in candidates with the traits of character, skill, and commitment they value in elective office holders. It is important to separate these skills and traits from those that are merely instrumental to getting elected, although if the Valence Rule has any force in elections, candidates’ campaign skills and resources should be rooted in the qualities that characterize the Rule. Thus, in the ideal, the “quality” of a candidate reflects his or her proximity and valence advantage over the opposing candidate. The Proximity and Valence Rules emphasize the importance of choice first and foremost as a response to the quality on each dimension of the candidates vying for support in an election. The premise is that we

Summarizing the Argument

49

cannot understand the choices voters make unless we understand the choices they are offered. From this perspective it is possible to assess whether voters choose correctly (that is, consistent with the Proximity and Valence Rules) and to examine the personal and political forces that enhance or undercut voters’ ability to choose correctly. This emphasis on choice can motivate a reassessment of the democratic “capacity” of voters. If voters and electorates choose candidates better aligned with their interests, they meet a critical standard of democratic performance, no matter how disengaged, inattentive, disorganized, or ignorant they may seem when queried by academic surveys. The choice standard may also provide a very different basis of evaluating voters and elections than one that focuses only on officeholders’ relationships to their constituents. The problem of choice is complicated by the fact that many voters are cross-pressured between their ideological and their valence interests because the candidate closer to their policy preferences is weaker than her opponent on valence. This is one reason that voters closest to being indifferent between competing candidates on ideological grounds will be most likely to vote for the stronger candidate on valence when the two dimensions are in conflict. In sum, four propositions guide the analysis of voting choice: r The Proximity Rule: voters choose the candidate closer to their ideological preferences when they vote; r The Valence Rule: voters choose the candidate stronger on leadership qualities when they vote; r The closer voters are to the ideological cut point between the candidates, the more likely they are to vote consistent with the Valence Rule when the proximity and valence dimensions are in conflict. r Proxies and facilitators such as party identification and incumbency increase correct voting on proximity and valence. The elements of ideological proximity and valence differences between candidates bear on more than voting choice; they enable a richer understanding of political representation than one grounded only on the ideological preferences of electorates. The Proximity and Valence Rules apply to electorates as well as individual voters, and as such should drive electoral outcomes. Moreover, analysis of electoral outcomes, including answers to questions about whether electorates enforce their interests in elections, must recognize the two-dimensional nature of political representation. This means that electoral representation can be defined as the distance between candidates’ ideological positions and the preferences

50

Candidates, Voting Choice, and Election Outcomes

of their electorates, and their personal suitability for the office to which they aspire. Representation can be assessed on both dimensions by the degree to which electorates choose the higher quality candidate, and by evaluating winning candidates’ (i.e., incumbents’) quality on each dimension. Representation, like voter choice, is properly understood as involving the behavior of candidates and voters. As if the examination of representation is not complex enough, we must contend with difficulties resulting from the fact that politicians anticipate the reactions of their electorates when they decide whether and how to run. While anticipated reactions is an important mechanism for assuring politicians’ accountability to the interests of their electorates, they make it difficult or impossible to observe the influence of electorates over their behavior. These difficulties can be addressed in this study, although I do not claim they can be completely resolved. Eight propositions inform the analysis of electoral outcomes and representation: r By the Proximity Rule, candidates closer than their opponent to district ideological preferences win more votes than candidates whose ideological positions are more distant from district preferences; r By the Valence Rule, candidates stronger than their opponent on leadership valence win more votes; r Electoral representation is a two-dimensional concept whereby the closer candidates are to district preferences and the higher their leadership valence, the better the representation they provide; r Candidates anticipate the reactions of district electorates in their strategic calculations about their prospects for victory. The greater their prospects, the closer they are to district preferences and the higher in leadership quality they tend to be; r The expected ideological representation that district electorates receive fits a hybrid model that combines the effects of party and district preferences; r Electoral representation can be assessed by the ability of electorates to choose the higher quality candidate competing in an election, or by the quality of the winning candidate or incumbent; r Ideological and valence representation can be explained by a combination of the characteristics of electorates and candidates; r By the Alignment Hypothesis, there is a positive relationship between the proximity and valence differentials of opposing candidates.

Summarizing the Argument

51

The propositions and generalizations about voting choice and electoral outcomes and representation highlight the major contributions of this book. The complications and difficulties facing this sort of investigation are daunting, but they should not deter us from the effort to make headway against them with a new approach, new measures, and new questions that can now be addressed. As with any effort of this sort, questions about the approach and the results it generates can be raised. The next chapter spells out the basis for the new measures on which much of the analysis in this book rests.

2 Design and Data District Informants and the Study of Congressional Elections

This chapter provides a non-technical description of the design and measures used in this study. More detailed information can be found in supplementary materials,1 in the appendix to this book, and in several publications that have discussed this method as used in the 2006 pilot study (Stone and Simas 2010; Buttice and Stone 2012) and in the 2010 study (Maestas et al. 2012). Expert informants or raters (or observers – I use the terms interchangeably) have been widely used in other disciplines (Andersson et al. 2005; Boyer and Rohit 2000; Budge 2000; Cooke and Goossens 2004; Javaras et al. 2011 Kitschelt and Kselman 2011; Phillips 1981), but they have not been employed in congressional election studies.2 Students of comparative politics have used expert-informant surveys to place the ideological and issue positions of political parties in western democracies, among other observations (Budge 2000; Castles and Mair 1984; Hooghe et al. 2010; Steenbergen and Gary Marks 2007). All of the data 1 2

www.cambridge.org/candidates_and_voters If we stretch the concept of expert rater to include documentary sources, it is worth noting Jeffrey Mondak’s (1995; McCurley and Mondak 1995b) innovative study of House incumbents’ integrity and competence that relies on summary accounts of House members in The Almanac of American Politics. Kahn and Kenney (1999) interviewed Senate campaign managers about various aspects of the campaigns in their study, although they did not rely on them for data about candidate positions or valence characteristics. Adams, Bishin, and Dow (2004) is an example of a study that used aggregated mass survey respondents to place opposing candidates (for the Senate) on a liberal-conservative scale. The 2010 study on which this book is based follows a pilot study, conducted in the 2006 elections, which also used expert raters to measure candidates’ ideological positions and valence characteristics. Both the 2006 and 2010 studies followed the Candidate Emergence Study in the use of district informants to study aspects of US House elections (http://ces.iga.ucdavis.edu/).

52

Summary of Design and Measures

53

used in this study are available for other scholars and interested parties to access.3

summary of design and measures For readers uninterested in the details of the design and measures that produced the data employed in this book, a brief summary will aid in understanding the basis of the evidence presented. The use of district expert informants was designed to solve two problems that have limited the ability of scholars to address fundamental questions about elections and representation: (1) how to develop comparable measures of the ideological positions and leadership qualities of opposing candidates vying for electoral support in an election. A related difficulty is how to measure candidates’ ideological positions in the same way that individual voters’ and electorates’ preferences are measured so they can be directly compared. And, (2) these measures must be separate from voters’ perceptions of candidate positions and leadership qualities to avoid the biases that inevitably affect voter perceptions and to allow for the possibility that voter perceptions are but one possible mechanism for explaining voter behavior and electoral outcomes. Soliciting the ratings and judgments of groups of expert observers in each House district included in the study provides a solution to these measurement requirements. Expert raters were identified by the highly visible positions they held (delegates to one of the major party’s national convention or state legislators resident in the district), or as a result of screening individuals who had previously agreed to participate as part of an extensive online panel of ordinary citizens to answer surveys for an internet survey company. The screening of individuals to serve as informants for this study focused on respondents’ information about and engagement in politics. By aggregating informants’ ratings and judgments, a “wisdomof-crowds” effect tends to drive out noise from individual respondents’ errors and uncertainties to produce a measure that closely approximates the attribute I seek to measure. The study also requires information about ordinary voters and constituents, so two extensive surveys were conducted in a national sample of House districts to ascertain information about constituents. Of 3

Data are archived on the project website, http://electionstudy.ucdavis.edu/; and the Harvard Dataverse: UC Davis 2010 Election Study, https://dataverse.harvard.edu/dataset .xhtml?persistentId=doi:10.7910/DVN/JLNWJI.

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Design and Data

particular importance to this study are measures of constituents’ ideological preferences, which can be compared with the ideological positions of the candidates vying for their support. By surveying constituents and informants in 155 district races, we have not only a large number of individual constituent-voters to study, but also enough district electorates and candidates to support reasonable inferences about how well elections work. Identically formatted questions were asked about candidate positions of informants and of voters about their own issue and ideological preferences. This is the basis for treating candidates’ ideological positions and voters’ ideological preferences as directly comparable.

study details My approach to the substantive questions motivating this book is based on several assumptions that shaped the research design: (1) voters seek ideological/policy and valence returns from their electoral participation; (2) voters act on the basis of the differences between the candidates competing for their support – they react, in other words, to the choices presented in the election; and (3) measures of candidate positioning and valence attributes must be independent of voter perceptions. The assumption that voters have fundamental interests in policy and valence returns in elections cannot be directly tested, although we can evaluate hypotheses about the effects of expressions based on the Proximity and Valence Rules. These expressions are candidate proximity and valence differentials, or the observed differences between the candidates based on the empirical measures derived from expert raters’ perceptions and judgments. Candidate proximity differentials are impossible to observe without measures of opposing candidates’ ideological positions that are comparable to one another and to voter preferences. Valence differentials are employed assuming that voters and electorates prefer candidates stronger on leadership-valence characteristics to those weaker on this dimension of choice. Analysis of both differentials rests on the second assumption as well: we cannot adequately evaluate hypotheses about voting choice and representation without incorporating the differences between opposing candidates on the dimension of choice under scrutiny. Studies of voting choice that rely on incumbents’ roll-call record, for instance, fail to meet the condition that comparable measures of both candidates’ positions are necessary, since most challengers in House races do not have roll-call records comparable to those of the incumbents they seek to unseat.

Study Details

55

A number of scholars have attempted to measure candidate ideology and valence characteristics by relying on voter perceptions, on the argument that perceptions govern how voters act. Thus, if a voter sees Candidate A as stronger in character than Candidate B, this perception affects his voting choice, whatever the actual difference between the candidates. A similar argument may be applied to voter’s perceptions of candidate positions. This approach has three significant problems: it assumes that perceptions are the primary (even a necessary) mechanism shaping voters’ reactions to candidates; it ignores the strong biases that affect voter perceptions of candidate positions and valence characteristics; and it excludes as “missing data” respondents unable to report on candidates’ positions and characteristics. Measures of candidate positions and leadership characteristics that are independent of voter perceptions avoid these problems while allowing for investigation of the effects of perceptions alongside other possible mechanisms to account for voter behavior.

Study Design As noted, a pilot study of the 2006 elections employed panels of district expert raters to measure candidate differentials identical to those developed in the 2010 elections. Because competitive elections are not the norm in House races, I augmented the 2006 random sample of 100 House districts with a supplemental sample of districts expected to be competitive in 2006 that were not already in the randomly selected sample of districts.4 This supplemental sample added another fifty-five districts to the base of the study, for a total of 155 districts. The races in these districts were in fact more competitive in 2006 than the average district in the random sample.5 In order to preserve the possibility of district-level panel 4

5

If a district was rated as a “tossup” or “leaning competitive” in the summer of 2006 by any of the following sources, it was included in the supplement: Congressional Quarterly, Cook Report, Sabato Crystal Ball, and National Journal. There was substantial agreement among these sources in which districts would be competitive in the 2006 elections (mean correlation > .70). This method identified a total of eighty-three districts expected to be open or competitive in 2006, of which fifty-five were not included in the random sample and constitute the competitive sample supplement. In 2006, the mean incumbent-party vote share in the competitive supplement was 52.9 percent, compared with a mean of 69.4 percent in the random sample. In 2010, the competitive supplement was slightly less competitive (mean incumbent-party vote share in supplement of 53.7 percent), while the districts in the random sample were more competitive (62.6 percent).

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Design and Data

analysis, the same 155 districts were included in the 2010 study.6 As a result, the 2010 study is based on a random sample of 100 districts plus a supplemental sample of districts expected to be competitive in the preceding mid-term election. I include all districts in the analysis to maximize the number of districts included.7 Because most of the concern in this book is with districts in which two opposing candidates faced one another in the election, five districts in the study in which the incumbent ran unopposed in 2010 are dropped, leaving 150 districts for much of the analysis. In the 2006 pilot study, district expert raters were identified by their positions as 2004 Democratic or Republican delegates to their party’s national convention, or state legislators who lived in the district. Informants were surveyed by mail, with the initial contact by letter in late September 2006, followed by a survey packet in early October 2006. The goal was to contact raters after the campaign was sufficiently underway for them to provide informed judgments about the candidates and their campaigns, while completing the survey data collection before Election Day so that the results of the election would not affect their ratings and judgments. Several problems resulted from this strategy: the numbers of Democratic and Republican delegates and state legislators varied substantially, with the majority party in the district better represented among potential expert respondents, sometimes by a substantial margin. As a result, the number of informants in each district varied, resulting in about 9 percent of districts in which only one expert informant responded to the survey, and 21 percent in which only two responded.8 Overall, the response rate was just over 30 percent, in part because it was difficult to send sufficient reminders within the limited period that the survey was open. In the 2010 study, I sought to remedy these problems while preserving the benefits of employing expert informants that were evident from the pilot by developing two distinct pools of district experts in each of the sample districts. The first pool was identical to the pool defined in the 2006 study: national convention delegates and state legislators in each 6

7

8

The panel aspect to the study is not exploited in this book because of the additional complexity it would involve, and because of key differences in the designs of the 2006 and 2010 studies. All analyses include a “design” control for the supplemental sample. Extensive replication of the results indicate that the core findings reported are not substantially different when the analysis is restricted to the randomly selected districts. The number of responses varied between a low of one to a high of twenty-seven with a mean of 6.0 (standard deviation = 4.2).

Study Details

57

party resident in the districts. Individuals identified in this pool were again contacted by mail with a letter explaining the purposes of the study. In the 2010 study respondents were invited to respond online, although they also received a survey packet by mail if they did not respond or if they requested one. The second pool of potential informants was identified from among all online panelists in the YouGov-Polimetrix panel of potential respondents who lived in a sample district and could pass a battery of screening questions designed to elicit their level of information and interest in the politics of their district.9 The goals of the second strategy for identifying district informants were to find individuals who were sufficiently well informed, to increase the number of informant respondents in each district, to increase the numbers of respondents in each party available in each district’s pool of informants, and to conduct the informant survey efficiently in a narrow time window at the end of the campaign (but before Election Day). The survey window for the panelists in the 2010 campaign-wave survey was the last two weeks in October 2010. The strategy of expanding district pools of potential raters worked well: the mean number of respondents from the YouGov-Polimetrix survey increased to 26.7, with substantially reduced variation in cross-district sample sizes compared with 2006.10 The level of expertise among individual online panelists was lower than among delegate and state-legislator informant respondents, but because the online pools of respondents were so much larger than the delegate pools, the reliability and validity of the online pools are higher. In our detailed comparisons of the informant pools generated from the two sources, it is clear that size matters: a greater number of individually less expert informants is better than a smaller number of individually more expert raters (see Maestas, Buttice, and Stone 2014 for comparisons of the two pools of informants). In fact, by combining informant respondents from both surveys in each district, we realize the greatest benefit owing to the larger number of informants 9

10

Screening questions are available on the project website: http://electionstudy.ucdavis .edu/2010-study/2010_ucd_ces_readme.pdf/view. Because the screened raters from the YouGov-Polimetrix panel were drawn from the same pool of potential respondents as Common Content respondents, 6 percent of Common Content respondents also fell into the informant pools from that source. I have replicated key results based on the Common Content survey dropping from the analysis individuals included in the expert rater pools. I report the results based on the full complement of Common Content respondents because the overlap is small and the weighting algorithm is based on the full sample. Weighting the sample slightly reduces the overlap to 5.5 percent. The standard deviations of the 2006 and 2010 numbers of respondents per district dropped from 4.2 to 1.8.

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Design and Data

included in each district.11 Except as noted, I used combined pools of raters to measure the informant-based variables of interest. A second difference between the pilot and 2010 studies was the inclusion of a “baseline” survey of district informants conducted in July 2009, almost a year and a half before Election Day 2010. The primary purpose of the baseline survey was to solicit informants’ perceptions of the strategic environment in the district before the 2010 cycle began. These perceptions are especially useful in estimating the effects of strategic calculations by politicians and their activist supporters about whether to enter a race (see Chapters 6 and 7). A secondary purpose was to solicit informants’ perceptions of characteristics of their districts that could be used as a check on the validity of informant ratings and perceptions, and potentially to weight the ratings of individual informants by the accuracy of these perceptions.12

assumptions and indicator construction Aside from the usual assumptions about the comparability of survey responses across individual respondents, I make the assumption in constructing the candidate proximities to individual voters and electorates (and the corresponding proximity differentials) that the aggregated informant placements of candidates on the liberal-conservative scale and on individual issue items are on scales equivalent to constitutents’ selfplacements. The assumption is based on the fact that raters were asked to place the candidates using exactly the same items and placement categories as constituents responded to in placing their own preferences. This equivalence assumption is always necessary whenever spatial terms are measured, no matter what method is used to measure candidates’ and voters’ ideological positions. Two other methods as alternatives to the use of district informants have been developed, both of which are based on assumptions at least as heroic as the equivalence assumption here. One asks ordinary survey respondents to indicate their preferences on 11

12

In the campaign wave of the survey, the mean number of informants is 31.4, with smallest and largest district pools of twenty-three and forty-one respectively (standard deviation = 3.19). Weighting individual informant responses by the accuracy of other ratings turns out not to improve the quality of informant-based measures (Maestas, Buttice, and Stone 2014). The “wisdom-of-crowds” logic appears to work through the aggregation of individual ratings under the assumption that individuals’ errors in one rating do not increase the probability of error on another (except in the case of systematic bias, see below).

Assumptions and Indicator Construction

59

issues framed in a manner that closely resembles the way the issue was voted on in Congress, and then compares constituent responses to representatives’ roll-call votes on the same issue (Bafumi and Herron 2010; Ansolabehere and Jones 2010). A similar approach compares constituent survey responses with candidates’ responses on publicly available survey items produced by good-government groups designed to make the public aware of candidates’ positions on a variety of current issues (Shor and Rogowski 2012). In both cases, the assumption is that ordinary citizens respond to survey items on issues in a way that is equivalent to officeholders voting on roll-call items in Congress or responding to survey items about their positions in a campaign. Needless to say, questions can be raised about the assumption that ordinary citizens’ responses to an academic survey in which their anonymity is guaranteed are equivalent to roll-call votes or questionnaire responses that may affect a politician’s career. The good news is that results between studies using the different methods that can be directly compared are remarkably similar (Buttice 2011; Shor and Rogowski 2012; Simas 2013). Still, in all of these studies (including this one) the equivalence assumption, necessary though it is, is almost surely violated to some degree (Jessee 2016). District expert observers surveyed in this study were selected for their expertise about and interest in politics. Ordinary constituents are not as engaged as online panelists selected for their political engagement, to say nothing of national party convention delegates and state legislators. Although informants and constituents were presented with identical survey items – informants to rate the positions of candidates running in their district and constituents to report their own preferences – there can be little doubt that informants have thought more deeply than the average constituent about the meaning of the terms “liberal” and “conservative” or the pros and cons of immigration or tax policy. As a result, informant placements are less likely to have error linked to the question wording or response categories. Questioning the equivalence assumption does not mean we should not make it. In the absence of this assumption, we forgo the opportunity to address critical questions of voting behavior and electoral representation. Moreover, if there is heterogeneity in the meaning of survey responses between informants and ordinary citizens, there is heterogeneity among constituents as well and scholars routinely make comparisons across levels of engagement among citizen respondents. Indeed, there is a literature comparing activists similar to the informants in this study and ordinary

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Design and Data

citizens that attempts to gauge the degree to which party leaders are representative of ordinary citizens (McClosky et al. 1960; Miller and Jennings 1986). As with many assumptions that enable us to address interesting questions empirically, we are better off making them explicit and proceeding with caution than not proceeding at all. With the equivalence assumption in hand, estimating individual voter ideological proximities and other measures based on the informants’ ratings, perceptions, and judgments is straightforward. All informant-based measures are based on aggregated (mean) responses of individual informants who live in each district included in the study. These responses are susceptible to partisan bias, as we would expect of individuals who are highly engaged in the political process. These biases are especially pronounced in measures of candidates’ leadership-valence qualities. Because of the number of informants in each district, partisan bias tends to cancel out when aggregated (Maestas, Buttice, and Stone 2014), although I take several additional precautions. Prior to aggregation, each individual informant’s rating or judgment on all items included in this study is corrected for partisan bias on the assumption that independent raters are not subject to partisan bias.13 I discuss an additional precaution against partisan bias in the section of this chapter dealing with the “measurementendogeneity” problem. Five informant-based measures are the basis of the analysis in this book: (1) the positions of opposing candidates in each district on the “symbolic” liberal-conservative ideology item; (2) the positions of candidates on a “latent” ideology measure composed of candidates’ positions on six issue items; (3) the leadership-valence qualities of each candidate; (4) the campaign-valence skills and resources of each candidate; and (5) candidate prospects for electoral success. A brief explanation of each of the five measures follows: (1) Candidate and constituent positions on “symbolic” ideology: The liberal-conservative item used in multiple surveys and studies of voting behavior as the basis of self-reported ideology is sometimes referred to as measuring “symbolic” ideology because it is based 13

The correction is based on scoring individual informants as in the party opposite to the candidate being rated (−1), strict independent (0), and in the same party as the candidate being rated (1). The characteristic being rated is regressed on this measure of partisanship, and the slope is subtracted from the uncorrected rating to yield an estimate (intercept) equivalent to the predicted rating by an independent informant (Maestas, Buttice, and Stone 2014).

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on asking respondents to indicate their ideology by placing themselves on a scale defined by categories of “liberal” and “conservative.” In this study, constituents were asked to place themselves and informants were asked to place each candidate running in their district on a seven-point scale ranging from “very liberal” (coded −3) through “middle of the road” (coded 0) to “very conservative” (coded 3). Critics have pointed out that this measure may differ from “latent” measures based on respondents’ positions on specific issues because some may identify with the symbolic label “conservative” or “liberal” without much knowledge of how these terms relate to policy debates in American politics (Converse 1964; Ellis and Stimson 2012). I address this problem of potential bias in the symbolic ideology measure compared with an issue-based measure below. I rely primarily on the symbolic measure because it was available in the 2010 Cooperative Congressional Election Study’s Common Content survey that includes a large number of respondents in each district, whereas the issue items employed in the common-content survey were not identical to those posed in the informant survey.14 (2) Candidate and constituent positions on “latent” ideology: I construct a second ideology measure based on constituent selfplacements and informant placements of each candidate on six issue items: gay marriage, health care reform, immigration, the war in Afghanistan, taxes, and increasing regulations to protect the environment. Each was anchored by policy options, such as outlaw/legalize gay marriage, repeal health care reform/universal government insurance, and provide path to citizenship/force to return 14

The mean number of non-missing responses per district on the liberal-conservative item is 125.9. The 2010 Common Content survey is the basis of much of the individual voterlevel analysis (especially in Chapters 4 and 5) in this book. To increase the stability of estimates at the district level (Chapters 6–9), I estimated district ideological preferences by combining the 2010 and 2006 Common Content surveys. The 2006 survey asked the symbolic ideology question in two formats not on the seven-point scale (a five-point and a 100-point scale). Therefore, I impute the 2006 responses on the seven-point scale based on responses in all three formats in the 2006 UC Davis survey module (see Stone and Simas 2010, 383–85) for details. This increases the mean district N to 220.1. Pooling the 2006 and 2010 surveys assumes no meaningful change in district ideological preferences. This assumption is supported by the fact that the pooled district ideology measure correlates more highly with 2004 and 2008 district presidential vote shares than estimates from either year’s survey. In addition, the correlation between change in district ideological preferences between 2006 and 2010 is uncorrelated with the change in district presidential vote share between 2004 and 2008.

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Design and Data home.15 Consistent with the scoring of the symbolic items, issue items are coded on seven-point scales from most liberal response (−3) to most conservative (+3). Principal components analysis confirms that the issue items load strongly on a single left-right dimension.16 As noted, some scholars have raised questions about the validity of the symbolic ideology item, and multi-item measures are generally preferred over single-item measures. It is also true, of course, that a great many scholars rely on the symbolic item because it is widely available and has high face validity. Moreover, the validity of the informant-based symbolic ideology candidate placements is as good as or better than the validity of the latent ideology measures. The two measures are strongly correlated (the correlations for Democratic and Republican candidates are, respectively, .91 and .73). Among individual constituent-respondents, the two measures are also highly correlated (r = .74). There is a modest difference in the means of the two measures, which reflects the tendency of mass respondents to overstate their conservatism on the symbolic measure compared with an issue-based measure.17 This is often attributed to a positivity bias toward the term “conservative” and negativity toward “liberal.” Ideally, of course, I would conduct all analysis using both “symbolic” and “latent” ideology measures. As noted, however, the issue items in the Common Content survey do not match those in the informant survey, nor are they consistent between the 2006 and 2010 surveys.18 Analysis with measures bridging the different data sources finds consistent results with those reported in this book (Buttice 2011, 2012), and in the appendix to Chapter 4 I report replications based on latent measures for comparison with results based on the symbolic measure.

15 16

17

18

The survey instruments with complete question wording are available on the project website: http://electionstudy.ucdavis.edu/. The issue indexes are simple averages of responses on the issue items. Scoring the items by the factor loadings, which relax the assumption that each issue item is equally weighted produces measures extremely similar to the mean index scores (r > .99; .98 for Democratic and Republican candidate placements; .97 for self-placements in the mass sample). The mean on the symbolic liberal-conservative item in the UC Davis module is +.29, while the mean on the issue-based ideology measure is +.01 (the mean symbolic score in the Common Content survey is +.31). The shared issue items are only available on the UC Davis module survey, which was based on a much smaller sample size (N = 2000) than the full Common Content survey in the 2010 CCES study (N = 20,253 respondents in the sample districts).

Assumptions and Indicator Construction

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(3) Candidate leadership-valence qualities: Candidate leadershipvalence scores are based on a seven-item index tapping qualifications, skills, and character traits associated with leadership qualities among officeholders valued by all voters: personal integrity, ability to work well with other leaders, competence, grasp of the issues, ability to find solutions to problems, qualifications to hold office, and overall strength as a public servant. Each item is scored on a seven-point scale ranging from “extremely weak” (−3) to “extremely strong” (+3). I construct a simple mean score across all seven items rather than differentially weighting the items, although weighting the individual items by their factor loading produces virtually identical relative scores (r > .99). In general, scale reliabilities are very high for the valence items and cross-district reliabilities are acceptable if somewhat lower than the ideology measures (Jones and Norrander 1996). Validating the leadership-valence measure is more difficult than the ideology measures because of the absence of well-validated measures of leadership valence. In addition to validation analysis reported in the supplementary materials, I explore the relationship between constituent perceptions of candidates’ valence and the informant measures. This is possible because the Common Content survey included two of the candidate valence items in the informant battery: personal integrity and competence ratings. This analysis serves two purposes: it is at least partially validating to demonstrate a positive association between ordinary constituents’ perceptions of candidates’ valence qualities and those of district expert informants; and it demonstrates that massconstituent perceptions of candidates’ leadership valence qualities are not merely rationalizations.19 Table 2.1 presents an analysis of constituent-respondent valence ratings of Democratic and Republican candidates running in their districts.20 There is a strong and highly significant relationship between the informant-based measures of candidates’ leadership-valence qualities and the ratings provided by mass-constituent respondents. If we assume that informants’ valence ratings capture the true valence quality of the candidates, constituent respondents are remarkably responsive in their perceptions of candidates’ valence qualities. To be sure, there are strong 19 20

See the appendix to Chapter 4 for a parallel analysis of constituents’ perceptions of candidates’ ideological positions. Each respondent’s leadership valence rating is the mean of that respondent’s rating of the candidate’s competence and integrity.

Design and Data

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table 2.1 Explaining Constituent Perceptions of Candidates’ Valence Qualities

Informant-based valence rating Party identification Democratic candidate spending (logged) Republican candidate spending (logged) Incumbent in party ran Open seat Constant Adjusted R-square N

Democratic Candidates

Republican Candidates

0.486∗∗∗ (0.08) −0.457∗∗∗ (0.01) 0.003 (0.02) −0.027 (0.02) 0.117 (0.08) −0.139 (0.10) 0.013 (0.32) 0.312 13428

0.549∗∗∗ (0.09) 0.442∗∗∗ (0.01) −0.027 (0.02) −0.099∗∗∗ (0.03) 0.115 (0.10) 0.000 (0.10) 1.781∗∗∗ (0.37) 0.319 12793

∗∗∗ p < 0.001 Note: Cell entries are OLS regression coefficients with robust standard errors clustered by district in parentheses below each coefficient. District subsample included as a control not shown.

partisan-bias effects among constituents. The negative effect of party identification for Democratic candidates is expected, since party identification ranges from strong Democrat (−3) to strong Republican (+3). Thus, as mass-constituent respondents are more Republican, their valence ratings of Democratic candidates go down. The partisan effect in the opposite direction for Republican candidates indicates that valence ratings increase as constituents were more Republican in their identification. The primary conclusion from Table 2.1 is that constituent- and informant-based assessments of candidate valence are related, independent of partisan bias, candidate spending, and incumbency.21 (4) Candidates’ campaign valence: A number of scholars define a valence advantage of one candidate over the other as any non-policy advantage. This conception includes the leadership 21

District-level analysis shows very similar results, with a strong independent effect of informants’ ratings on mean constituent ratings of candidates in each party.

Assumptions and Indicator Construction

65

qualities of interest in this study, in addition to other advantages rooted in incumbency, fundraising, or other resources that may enhance a candidate’s or party’s election prospects (Groseclose 2001; Londregan and Romer 1993). For reasons spelled out in Chapter 1, I limit the concept of valence to leadership traits and skills intrinsically valued by voters, and I treat resources and skills that are purely instrumental to candidates’ running a successful campaign as separate. In much of the analysis to come these resources can be represented quite well by candidates’ spending, incumbency, and, in the case of challengers, prior elective-office holding experience. However, the informant survey included a battery of items designed to measure candidates’ “campaign valence,” by which I mean the skills and resources not of intrinsic interest to voters, but that are related to the ability to conduct a viable campaign: ability to attract attention, ability to fund own campaign, ability to raise funds from others, current name recognition, ability to be persuasive in public, ability to run a professional campaign, and overall strength as a campaigner. Like the leadershipvalence items, these were asked on seven-point scales ranging from extremely weak (−3) to extremely strong (+3), and are combined in an index based on the mean rating of each candidate in the district.22 Leadership and campaign valence scores are positively correlated, which fits with the idea that the ability of candidates to attract campaign resources and conduct an effective campaign is related to their leadership skills.23 (5) Incumbent reelection prospects: As noted, a goal of the baseline survey conducted in the summer of 2009 was to solicit informants’ judgments about the strategic environment in the district prior to the entry of challengers or other indicators of the shape of the campaign in 2010. The best way to do this was to ask informants to judge the chances the incumbent would win reelection if he or she were to run again in the next election and win his party’s nomination. Responses were on a seven-point scale ranging from extremely unlikely (coded .01) to extremely likely (coded .99) with a “toss up” midpoint (coded .5). Chapter 6 provides evidence about the

22 23

Principal components analysis indicates that the campaign-valence items load on a separate dimension than the leadership-valence items. The correlation between campaign and leadership valence scores for Democrats and Republicans is .56 and .55, respectively.

66

Design and Data predictive power of this measure. In general, the informant assessments were highly predictive, providing additional evidence in support of the use of expert raters to measure the political context in House campaigns.

a measurement-endogeneity problem? While there are significant benefits to the informant-based measures, it is important to assess their potential weaknesses. Because informants’ judgments and ratings are subjective, there will be error associated with measures based on these perceptions. Because expert raters in each district individually provide ratings independent of other experts in the same district, there is good reason to believe that much of the error in individual measures is reduced in the aggregation process. In the case of error associated with partisan bias, it is possible to correct individual ratings to further reduce that source of distortion in aggregated ratings. The problem discussed in this section, however, is potentially more troubling because there is no easy fix. When we ask expert observers to rate candidates’ ideological positions and leadership skills and character traits, we do so in the context of a political campaign, the point of which, from the candidates’ point of view, is to persuade people in the district (including our expert informants) that the ideological positions they take are reasonable and in line with district interests, and that they are qualified as excellent actual or potential office holders. At the same time, of course, candidates are busy attempting to convince everyone in their district that their opponents’ policy positions are hare-brained schemes totally out of touch with district interests and preferences, and that they are scoundrels unsuitable as neighbors much less as high office holders. Into this mix of claims and counter claims, the perpetrators of the UC Davis Election study enter with their questionnaires directed to individuals they have identified as expert informants who are – whatever their suitability as expert observers and reporters – residents of their district and targets of the very same campaign efforts at persuasion aimed at all other members of the district electorate. What we would like to have as a result of the informant-based measures is reasonably objective indicators of candidate differentials on policy and leadership valence. What we have, inevitably, is reputational data based on observations and reports by individuals immersed in and targeted by the candidates we are asking them to rate. Thus, the measures taken in the campaign wave of the study are

A Measurement-Endogeneity Problem?

67

endogenous to the subjects (the candidates and their campaigns) under study. The fact that the measures were taken in the midst of the campaign during which we ask informants to rate the candidates may not be a problem. After all, the intent of the campaign wave of the survey was to go into the field after the campaign was well underway so that informants were in a position to report on the candidates. Moreover, selecting as raters individuals who are well informed is based on the hope that their expertise buffers their susceptibility to campaign blandishments. However, a possible problem is that some campaigns have more resources to make their case than their opponent. This may mean, as the resource-asymmetry hypothesis expects, that candidates rich in resources are able to persuade voters that they are better suited to serve in Congress than their opponent. We know, for example, that incumbents tend to have more resources than their challengers. So, if we find that incumbents are generally rated higher in their leadership valence qualities than challengers, is it safe to assume that the scores reflect real differences between the candidates? This problem is worrisome because a purpose of the study is to evaluate the Valence Rule against the resource-asymmetry hypothesis. If informant valence ratings are driven by resource asymmetries between candidates, an answer to this question based on informant ratings of candidates’ leadership qualities will not be convincing. The problem is made more severe by the expectation that incumbents and well-financed non-incumbents have won elections in the past and may actually be higher-valence candidates because voters and financial backers of candidates in previous elections care about valence as much as current voters do. If we lack a silver bullet to kill off this problem, we are not bereft of any strategy for dealing with it. In fact, we can use the known biases associated with partisanship as a bulwark against its consequences. The argument is as follows: while it is true that campaigns are designed to influence people in the electorate about the relative quality of the candidates running, it is not realistic to suppose that the campaign’s influence is the same for all individuals in the electorate. It should generally be the case that individuals with greater political expertise, although they may be more biased in their perceptions than ordinary citizens, are also less likely to be influenced by campaigns. Those who are well informed and active in politics (as our informants were) are more likely to be partisan – and strongly partisan – than ordinary voters. Informants who identify strongly with their party rate the candidate from their party higher on

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valence attributes and ideologically less extreme than the candidate from the opposing party, and that would be true in the absence of the campaign. Individual informants from the opposing party should be especially impervious to resource-based effects of the opposing candidate’s campaign. This means that when Democratic informants rate the Republican candidate in District A higher than Democratic informants in District B rate the GOP candidate, two conclusions are likely: first, in both districts, Republican candidates will be rated much lower on leadership valence than by the full panel of informants in each district; and, second, it is quite likely that the Republican running in District A is stronger in leadership qualities than her counterpart in District B. To use an example from presidential politics, most Republicans rated Presidents Clinton and Obama negatively on a variety of traits related to leadership valence. A conventional understanding of the two presidents suggests that most objective observers thought one of Clinton’s strengths as a leader was his empathy for ordinary people, while many questioned his personal morality. Republican identifiers in 1996 rated Clinton negatively on both traits, but rated him less negatively on empathy than on morality. President Obama, running for reelection in 2012, presented opposite strengths and weaknesses: he was seen by most observers as somewhat distant, even aloof, while there were no questions about his personal probity. Again, Republicans rated him negatively on both traits, but rated him stronger than Clinton on morality and lower than Clinton on empathy (ANES Cumulative File). The point is that opposing partisans may be impervious to a candidate’s efforts to persuade them of his or her virtue and qualifications, especially compared with the candidate in their own party, but cross-candidate variation in quality should still be detectable. Thus, it is not surprising that opposite-party informants rated winning candidates’ leadership valence much lower than the full complement of district informants (−.82 and +.39, respectively). What matters most, however, is the relative rating of candidates, rather than the absolute ratings. Throughout this book, the emphasis is on candidate differentials – candidate differentials based on ideological proximity to individual voters or to district electorates, and candidate differentials based on valence. If the intuition behind the Clinton and Obama example is correct, these differentials should be reasonably sound even when they are based on informants from the party opposite the candidate being rated. Based on this reasoning, the strategy I use as a robustness check on critical findings most subject to the measurementendogeneity problem is to rely only on opposite-party informants to construct indicators of candidate differentials.

A Measurement-Endogeneity Problem?

69

This strategy of using only opposite-party informants to rate the candidates’ positions and valence characteristics should minimize or eliminate the measurement-endogeneity problem, but it comes with a price. As opposed to an average of over thirty per district when we use all informants as raters, when limited to partisans in one party or the other, we lose over half of all informants per district: there are an average of 11.9 Democrats and 14.4 Republicans per district, with wider variation in the number of informants available (one district, NC03, had no Democratic informant respondents). As a result, estimates based on opposite-party informants are inevitably more unstable. An indication is provided by the rather modest correlations between opposite- and same-party candidate valence differentials and ideological cut points. Valence differentials are measures of direct concern throughout this study. When they are estimated twice in each district, once using opposite-party informants to rate each candidate’s valence quality and once using same-party informants,24 the correlation between the opposite-party and same-party measures is .40. The candidate-based driver in the proximity differential may be captured by estimating the ideological cut point between the candidates. The correlation between opposite- and same-party measures of candidate cut points is .59.25 Although these correlations are a long way from perfect, it is not clear they should be stronger even if using opposite-party measures avoids the measurement-endogeneity problem altogether. As noted, the informant pools are much smaller when broken apart by party. Moreover, using opposite-party informants may present other problems since informants from the opposing party are less aware of the candidate in their district from the opposite party. “Don’t know” responses are typically two to three times higher for informants from the opposite than the same party.26

24

25

26

That is, in the opposite-party measure, valence ratings of the Democratic candidate are based on the ratings only by Republican informants in the district and Republican candidate ratings are based on ratings by Democratic informants. In the same-party measure, valence ratings are based on the ratings of each candidate by informants in his or her party. Both correlations are based on weighting the data by the size of the party informant pool in the district. The unweighted correlations are .36 and .58 for the valence differential and cut point measures, respectively. Although they are not especially high in an absolute sense. For example, 11.2 percent of Republican raters are missing on Democratic candidates’ leadership-valence scores, while 16.9 percent of Democratic raters are missing on Republican candidates’ valence scores. The percentage of missing Democrats rating Democrats and Republicans rating Republicans drops to 5.8 and 4.1 percent, respectively.

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It is also possible that, if informants from the opposing party are less susceptible to persuasive messages from the opposing campaign, they are also less responsive to variation in the true signal from the campaign about the quality or ideological position of the candidate. The upshot is that examining the key substantive results in this book using the opposite-party informants is a useful robustness check to guard against the potentially pernicious effects of measurement endogeneity. For the most part, the results reported in this book are upheld when this is done, as explained in the Appendix and in greater detail in the supplementary materials. Where there are differences, they are highlighted and discussed. In general, I regard substantive analysis based on opposite-party measures as conservative estimates of the effects in question.

conclusion The use of expert ratings in congressional House races has significant advantages over common alternative approaches. Studies of policy representation and voting typically rely on the ideological positions of incumbents without comparable data on challengers, and measure valence with such indicators as incumbency, spending levels, and office-holding experience. In addition to lacking measures of the choices voters face in House races, relying on incumbents’ roll-call voting to measure ideology typically does not result in measures on the same scale for voters. Valence measures based on candidate resources do not measure a concept of candidate valence rooted in voters’ intrinsic interests, nor do they permit scholars to distinguish between the possible distorting effects of candidate resources and their ability to serve as proxies for the leadership qualities voters fundamentally care about. While the use of expert informants permits us to measure candidate differentials on ideology and leadership valence that are otherwise unobservable, the question of the reliability and validity of these measures is vital. Evidence in this chapter and elsewhere provides support, as does analysis reported in Chapter 6, about the ability of groups of district raters to forecast election outcomes in their districts sixteen months before Election Day. Scale and cross-district reliabilities for informant-based measures are consistently good to excellent. The most compelling evidence for their validity is available for measures of incumbents’ ideological positions and reelection prospects. These validity assessments are possible because there are clear criterion variables available – in the case of incumbent prospects, the outcomes of district elections, and in the

Conclusion

71

case of ideological positions, roll-call indicators of incumbents’ voting patterns. The case for the validity of the valence indicators used in this study is necessarily weaker because of the absence of comparable criterion variables. In this chapter, we have evidence that informant valence ratings have significant and strong effects on constituents’ valence ratings, independent of candidate spending, incumbency, and constituents’ partisan bias. This is reassuring evidence that voters can assess candidates’ leadership valence qualities, a question to be pursued in greater depth in future research. In addition, alternative measures of incumbents’ valence qualities culled from other studies and the public record are significant in explaining expert informants’ ratings of incumbents’ leadership valence (see supplementary materials). I doubt this evidence will settle in every scholar’s mind the value of employing expert observers to rate candidates’ ideological positions, valence qualities, and electoral prospects. There is always appropriate skepticism when new methods are applied to old problems. Their subjectivity is an inescapable aspect, as is the fact that their ratings were collected in the midst of campaigns designed to persuade them of each candidates’ suitability for high office. To the skeptics, I suggest holding open the question of whether the analysis that follows has merit based on two conditions: (1) the evidence thus far presented of the measures’ reliability and validity; and (2) the coherence, consistency, and plausibility of the substantive results to follow. I recognize that there will always be competing explanations for any observational finding. I hope those who are to this point unpersuaded will assess the results I present in this book against the standard of whether a substantive advance on questions related to voting, elections, and representation is better than not making the attempt for the lack of better measures.

3 Polarization in Congressional Elections Since 1952

Partisan polarization is a dominant characteristic of contemporary American politics. Polarization is seen as the root cause of gridlock in government and of a general breakdown in civic discourse; it is both cause and consequence of partisan differences in national policy debates. This chapter presents an overview of polarization in congressional elections in the period between 1952 and 2010. For purposes of this analysis, I define polarization as ideological divergence between the parties, as reflected in the ideological positions taken by elites such as members of Congress, or between party identifiers in the public. The trends evident in the analysis show a more or less steady progression in polarization in House voting patterns, with a somewhat more irregular pattern of change in the electorate. First and foremost, the purpose is to show that 2010 was at the apex of partisan polarization in the electorate and in Congress over this period. This sets the context for the study of voting choice and district representation in 2010. Several implications of partisan polarization are relevant for the analysis in this book. First, as some of the indicators make clear, partisan polarization bears directly on the ideological positions of members of Congress, all of whom are partisans, and among voters, most of whom express an affiliation with one of the major parties. Polarization is associated with ideological extremism, a phenomenon with direct implications for spatial models of candidate positioning. Extreme candidates are unrepresentative in spatial models because such models focus on the median voter as pivotal in determining who wins the election. Median voters in most electorates are relatively moderate, and in spatial models of candidate position-taking, candidates gravitate toward the position of the median 72

Polarization in Congressional Elections Since 1952

73

voter (Black 1948; Downs 1957). Candidates who take positions close to the median voter are seen as more representative since their positions are close to the optimal location to best represent the preferences of the entire electorate (Achen 1978; Page 1979). In contrast, polarization implies that candidates from each party are significantly out of line with their electorates’ ideological preferences. As Jessee (2012, 9) points out, candidate divergence or polarization is not evidence against spatial voting, although it does suggest that candidates are not pure office-seeking actors. The Proximity Rule is agnostic on the location of candidates, asserting only that voters support the closer of the two candidates. However, as will be clear in the next section of this chapter, partisan polarization is consistent with a model of district representation that stands in contrast to the median-voter model. A second implication of partisan polarization is that it may enable voters to cast votes consistent with the Proximity Rule more frequently than when party differences are less pronounced. As voters and candidates sort themselves into ideologically consistent parties, Democratic voters and candidates are more consistently liberal, Republican voters and candidates are conservative, and fewer voters and candidates take ideological positions at odds with the dominant ideological commitments of their party. This implies that voters who act on the basis of their party identification are more likely to vote consistent with the Proximity Rule (Joesten and Stone 2014). Democrats who vote for Democratic candidates based on their shared partisanship tend also to vote for the more liberal candidate, even if they are unaware of the ideological position of the Democratic candidate running in their district. The same can be said for Republican voters whose party-based vote leads them to vote for the more conservative candidate. To the extent that the Proximity Rule is based on correct perceptions of candidate and party positioning, polarization should reduce perceptual errors among voters, as when voters see the Republican Party and its local candidate to the left of the Democratic Party and its candidates (Hetherington 2001; Sniderman 2016). A third implication of increased partisan polarization is that it should reduce the effect of individual candidate characteristics and resources such as incumbency (Jacobson 2015). As the parties diverge, voters are more likely to emphasize national party differences in their voting choice because parties are more obviously the vehicles of national policy-making than individual candidates (Jones 2010; Jones and McDermott 2009). Voters unhappy with the direction of the national party, then, should be more likely to see their local candidates as linked to national party

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Polarization in Congressional Elections Since 1952

differences and vote accordingly. At the same time, candidates’ valence and resource differentials should be less important with increased polarization. A moderately conservative voter dissatisfied with the Iraq War in 2006 might choose to vote against the Republican in her district, even if the Republican was ideologically closer to the voter, or had the advantage on valence over his opponent, or was the better financed candidate. In the same way, a moderate Democrat with doubts about the national Democratic Party’s commitment to health care reform might vote Republican in 2010, despite advantages the local Democratic candidate may have enjoyed on ideological proximity or valence.

median-voter vs. party-centered models of district representation Two ideal-type models of district representation inform our discussion: a district median-voter model and a partisan model (Figure 3.1). Under the median-voter model, representatives are more conservative as their districts are more conservative, resulting in a linear relationship between district and representative ideology. The extent to which candidates diverge from the position of the median voter can vary, depending on the assumptions of the model, including how voter abstention and candidate goals other than winning the election are treated. Partisanship among voters and candidates is consistent with the median-voter model of district representation if liberals and conservatives tend to affiliate with the appropriate party. Conservative districts elect Republicans to Congress; liberal districts send Democrats to Washington. However, the ideological makeup of the district is reflected in the position-taking by candidates in each party. Thus, moderately liberal districts elect moderately liberal Democrats who are less liberal than their fellow Democrats elected from more liberal districts. A similar pattern obtains under the median-voter model for conservative Republicans elected from very conservative districts, compared with more moderate Republicans elected from less conservative districts. In the partisan model the key explanatory variable for representatives’ ideological positions is their party rather than the median voter’s ideology in their district. In this model, liberal districts elect Democrats and conservative districts elect Republicans, but there is no distinction between moderate and extreme districts in the ideological flavor of the partisans that represent them. While individual candidates and office holders do not necessarily agree with every position taken by their party, variation in district ideology does not explain candidate position-taking.

Median-Voter Model

Party Model Republicans

Democrats

Republicans

Representative’s Position

Representative’s Position

Conservative

Democrats Liberal Liberal

District Preferences

Conservative

figure 3.1 Median-Voter and Party Models of District Representation

Liberal

District Preferences

Conservative

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Polarization in Congressional Elections Since 1952

Geographical or district variation does not matter in the partisan model: a district from Mississippi that elects a Democrat is as likely to get a representative committed to the party’s liberal policies as a district that sends a Democrat to Washington from Massachusetts, even if the Mississippi district is more conservative. Within each district, the national partisan divide is replicated in the ideological positions opposing candidates take and the primary determinant of the ideology of the district is the proportion of voters in each party. If we assume that the incumbent Representative’s ideological position and that of the district are on the same scale in Figure 3.1, most incumbents in the party model are more extreme than their districts. This is not strictly a consequence of the party model. If, for example, we imagine shifting the Democratic incumbents’ positions in a more conservative direction, a more moderate national Democratic Party would have candidates placed closer to the average district preferences. However, the representation of the party model in Figure 3.1 is more consistent with research on the positioning of candidates and activists in each party relative to voters, with both parties characterized by roughly symmetric extremism (Ansolabehere et al. 2001; Burden 2004; Clinton 2006; McClosky et al. 1960; Miller and Jennings 1986; Stone and Simas 2010).

indicators of partisan polarization The study of polarization is well-trod ground in the literature on Congress and the electorate during the post-WW II period (Abramowitz and Saunders 1998a; Fiorina 2006; Hetherington 2009; Theriault 2008; McCarty et al. 2006). Although there are debates about how deeply polarization penetrates the electorate and what the sources of polarization are, simple measures indicate significant change in US national politics relevant to partisan polarization. Table 3.1 illustrates changes that all scholars agree have characterized this period. Consider first the change evident on the congressional side of the table. There is a regular increase in the divergence in first-dimension DW-Nominate scores by decade. Nominate scores measure the liberalconservative dimension of roll-call votes, with negative scores indicating liberal positions, and positive scores indicating conservative positions. It is apparent that between the 1950s and the 2000s, Democrats in the House moved to the left and Republicans shifted to the right, which produced a regular increase in the ideological divergence between the parties over the period. The divide between the parties stood at .56 in the 1950s, increased regularly to .83 in the 2000s, and was even higher at the end of the 2000s

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table 3.1 Partisan Polarization in the Electorate and in Congress by Decade, 1952–2010 Indicators of Polarization in Congress

Dems Repubs Diff

Correlation between Presidential Correlation Vote Share in between Party District and and Party Holding DW-Nominate Seat

Correlation between Party Identification and Vote for House

−.27 −.29 −.32 −.32 −.37 −.39 −.42

.84 .83 .84 .88 .92 .94 .95

.73 .66 .56 .53 .59 .65 .66

Mean DW-Nominate Scores

1950s 1960s 1970s 1980s 1990s 2000sa 2010 a

Indicators of Polarization in Electorate

.29 .27 .28 .33 .39 .44 .49

.56 .56 .60 .65 .76 .83 .91

.65 .40 .37 .48 .54 .67 .75

Excluding 2010. DW-Nominate scores are available for download at http://voteview.com/. Data on district presidential vote share were provided by Gary Jacobson. Data on party identification and vote for House candidates are from the ANES cumulative file except for 2010, based on the CCES Common Content file.

in 2010, at .91. The correlation between the party of the representative and the ideological positions taken on roll calls also increased regularly from .84 to a peak of .95 in 2010. The indicators of partisan polarization in the electorate are not comparable to the measures reported for Congress because there is no directly comparable measure of ideology in the electorate over the entire period. One measure of the ideological makeup of districts that is often employed is the partisan division of the presidential vote in the district on the assumption that the more conservative the district, the larger the vote share for the Republican candidate for president. This measure also reflects the partisan makeup of the district, a problem if the goal is to link ideological position to partisanship. However, it is serviceable for the analysis here. The pattern in the electorate is different from the regularly increasing trend in polarization in Congress, in that polarization as measured in the table declines into the middle of the period before rebounding from the 1980s to 2010. The decline in the district-level and the individual-level correlations into the middle of the period fits with an extensive literature

78

Polarization in Congressional Elections Since 1952

on “dealignment” in the American electorate (Wattenberg 1996; Dalton et al. 1984). Dealignment helps explain the declining correlation between party identification and voting choice in House elections because voters less anchored by their party identification were more influenced by variables such as incumbency and candidate spending differentials (Mann and Wolfinger 1980; Ferejohn 1977). Since the 1980s the correlation between party identification and voting choice in House elections has rebounded to roughly the levels in the 1950s.

shifting patterns of district ideological representation With greater partisan polarization in Congress and in the public, we can expect to see a shift in patterns of district ideological representation from one approximating the median-voter ideal to one closer to the party model of district representation. This shift should occur for a number of reasons linked to the changing ideological makeup of the parties in government and in the public and has been commented on by a number of scholars (Ansolabehere, Snyder, and Stewart 2001; Jones and McDermott 2009). As parties in Congress diverge, they develop more distinct brands associated with clear differences in policy commitments, and greater potential for collective accountability for outcomes. In response to ideological divergence among candidates and officeholders, the public’s awareness of how individual issues relate to ideological labels increases, as does knowledge of the differences in the parties’ ideological positions (Hetherington 2001; Sniderman 2016). Polarization and its effects on party brands and awareness should increase the link in voters’ minds between individual candidates and their parties, such that voters are more likely to recognize that voting for a Democrat is a vote for more liberal national policy, and a vote for the Republican candidate running in a particular district is a vote for more conservative policy. Scholars have also recognized that greater divergence between the parties and increased agreement within each party are conditions favorable to more party discipline in Congress, which helps advance polarization, as ideological mavericks are weeded out in primaries, disciplined within Congress, or change parties. As a result of these developments, we should observe an increasing effect of national party affiliation on the ideological position-taking of members of Congress. To the extent that district influence declines as the system moves toward the partisan model, we should see a declining effect

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of district ideology on incumbent position-taking. Figure 3.2 illustrates the change in district ideological representation by comparing scatterplots depicting the relationship between incumbent Nominate scores and district ideology as measured by presidential vote shares in two midterm elections: 1954, when polarization was at or near its lowest point in the House; and 2010, when polarization was at its peak. In 1954, conservative districts tended to elect Republicans and liberal districts tended to elect Democrats and the scatterplot is roughly linear, with a smooth transition from predominantly Democratic seats to Republican seats as districts were more conservative. In contrast, a pronounced gap between the parties is present in the 2010 plot that is closely associated with Republican presidential vote share. It appears that district ideological representation reflects a combination of district preferences and the party of the representative, with increasing polarization reflected in the growing effect of party on incumbent ideological position-taking.1

implications of polarization for the arguments in this book The analysis in this book is limited almost entirely to 150 districts in the 2010 elections in which complete data from district informants on opposing candidates were available.2 The study of a single year’s election presents the danger that something unique about the particular year affects the results and conclusions drawn. Thus, although the number of district elections for this study provides ample quantitative leverage on a host of interesting questions about the relationships between competing candidates, voters, and electorates, from another perspective the N for this study is just one year. The foregoing analysis shows that 2010 was not typical of preceding years, although it is part of a clear trend toward increased partisan polarization. Whether the polarization in 2010 will characterize future years is, of course, 1

2

Detailed analysis shows that the most important development over time is in the increasing ideological divergence between the parties. District preferences also have an effect, though the increasingly strong party effect exceeds by a fair margin the effect of district preferences. More attention will be devoted to disentangling the effects of district ideological preferences and party in Chapter 8. For a similar analysis that shows a reduced effect of district opinion with polarization, see Jacobson and Carson (2016). The sample of districts in 2010 includes five districts in which no Democratic candidate challenged the Republican. These districts are usually dropped from the analysis, except when the focus is exclusively on incumbents without reference to the opposing candidate.

1

2010

1

1954

R R RR R R R R R RR R RRR R RR RR R RR R R RRRRR RR R RRR RRR R RR RR R RRR R R RR RR R R R RR RR R R RR RR R R RR RR R R R R R R R RR R R R R R R RR D R R RR R RR R RR RRR RR R R RRR R R R R R R R R R RDR R R R R RR R R RR RRR RR RR R D R R R R R R RR R DRR RR R RR D DDD D R R DD RR R RR R D R D D R D R R R RDD D D D D D DR R D DD D D DDD DDD D DD D D DD D DD DD D D D D DD D D D D D DD DD DDD D D D D D DD D D D D DDD D D DDDD D DD D D D DD D D D D D D D D D DD D DDD D D D DD D D D D DDDD D D D D D D DD DDD D D D DDDDD DD DD DD D D D D D D D D D DD DDD D DD D D DDDD D D DD D D D DD D D D D D D D D D DDD D D D D D D D D D DD D D D D R

D

D D

R R RR R R R R RR RRR R R R R R R R R R R R R RR R RRRRR RR RRRRR R RR RR R RR R RR R R RR R RR RR R R RR R R RR RR RR RR R RR R RR RR RRRR R R R RRR R RR R R R RR RRR R R R R R R R R R R R R RRR R R RRR R RR R RRR R R R RRRRR RRR R RR R R RRRRR R RR RR RRRR RR R RR R R R RRR R RR R R RRRRRR RRRR R R R R R R R R R R RRR RR RR R R R R R R RR R R

Incumbent 1st dim. dw-nominate −.5 0 .5

Incumbent 1st dim. dw-nominate −.5 0 .5

R

D

D DD DDD DD DD D D DD D DD DD D

D D D D D D D D DD DD D D DDDD D DD DDD D D D D D D D D D D D D D D DDDDD DD D DD D DD DD DD D D DD D DD DDDD D DDD D D D DD D D DD D DDDD DD D DD D DD D D DD D D DDD DD DD DDD D DD D D DDD D DDD DD D D D D D D D D D DD D D DD D DD D D D D DD D

D

D

0

20 40 60 80 Republican Presidential Vote Share in District

−1

−1

D

100

0

figure 3.2 Representative by District Ideology in Selected Midterm Elections

20 40 60 80 Republican Presidential Vote Share in District

100

Implications of Polarization for the Arguments in This Book

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unclear.3 Despite uncertainty about the future, it behooves us to speculate on how questions fundamental to the arguments in this book might have been affected if we had data comparable to the informant-based indicators of candidate ideological positions and valence from election years less characterized by partisan polarization than 2010. As noted, increasing agreement between party and ideology suggests that partisan and proximity-based explanations of behavior should overlap to a greater degree in 2010 than in the 1970s and 1980s, when polarization in the electorate was in a relative trough. With comparable data on candidate positioning and voter/district preferences from the 1970s and 1980s, we would see less agreement between party identification and ideology, and more individuals (and districts) caught between their ideological and partisan predispositions. As we will see in Chapter 5, party tends to dominate proximity in explaining voting choice when proximity and party identification predict different votes, so with less partisan/ideological polarization, we would probably see lower levels of proximity voting. By the same argument, the greater polarization in 2010 should produce unusually high levels of agreement between party and ideological preferences. This, in turn, should increase voters’ proximity voting on the basis of their party identification. In the extreme, of course, where every voter has both an ideology and a party identification in perfect agreement (all Democrats adopt the same liberal positions and all Republicans adopt the same conservative positions), it would be impossible to separate proximity voting from partisan voting. Fortunately for the analysis in this book this level of association between party and ideology was not present in 2010, even though the correlation was at an historic high level.4 As Cain et al. (1987) pointed out, the “personal vote” may be depressed when parties are strong because congruence between party and ideology may increase the priority citizens give to national policy concerns over valence differences between local candidates. Other work has suggested similar effects on proxies for valence such as incumbency, where stronger, more unified parties depress the effects of personal differences between 3

4

My view is that polarization is probably the normal state of affairs in the American party system, and the extended period of relatively low levels of partisan divergence between the 1920s and the 1970s was an aberration due especially to racial politics within the Democratic Party. The correlation between party identification and self-identified ideology averaged .26 in the 1970s, increasing to .52 in the 2000s (based on ANES data). The correlation in the 2010 CCES was higher still at .71.

Polarization in Congressional Elections Since 1952

0

.05

.1

.15

82

1952

1962

1972

1982 year

1992

2002

2012

figure 3.3 Partial Coefficients on Incumbency Estimating Effects on Incumbent Vote Share, 1952–2010

candidates based on resources such as incumbency (Jones and McDermott 2009; Snyder and Ting 2002; Jacobson 2015). As Kim and Leveck (2013, 492) put it: “Greater intraparty homogeneity in legislative behavior makes party labels more informative and provides voters with stronger priors about their candidates. Consequently, the individual actions of legislators have less influence in changing voters’ minds.” The intuition that valence effects weaken with polarization may be observed in the data over the period since 1952, provided we are willing to rely on an ambiguous measure of valence: incumbency. Incumbency status may serve as a rough proxy for leadership valence to the extent that prior electorates value leadership valence in the candidates they support. With these qualifications in mind, Figure 3.3 shows the effects of incumbency on the incumbent party vote share over the period 1952– 2010 (cf. Jacobson 2015). The expectation is that the effect of incumbency should be strongest when polarization is weakest. The effects displayed in Figure 3.3 were estimated in equations explaining incumbent vote share as a function of the vote received by the incumbent party’s candidate in the previous election, the presidential vote share in the district coded to

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match the party of the incumbent, and the party holding the seat (Gelman and King 1990). The results in Figure 3.3 are consistent with the expectation that valence effects are strongest when partisan polarization is relatively low. The impact of incumbency peaks in the early 1980s when party effects were weaker and polarization, especially in the electorate, was less pronounced. In parallel analysis not shown, challenger spending and challenger office-holding experience took their largest bites out of incumbents’ vote share in the 1970s, with a regularly declining effect as the polarization in Congress and in the electorate proceeded from the 1970s to 2010.5 Because polarization peaked in 2010, these results suggest that year was inhospitable to the observation of valence effects on voting choice. Of course, 2010 was not a unique election year solely because of the high level of partisan polarization that characterized national politics. It was also a year in which the Republican Party enjoyed a tidal swing in its favor, in part as a correction to previous pro-Democratic tides in 2006 and 2008, and in part due to the opposition generated most prominently by the Tea Party movement against President Obama’s policies. Some of these unique aspects of the 2010 elections can be taken into account in the analysis to come, as when we control for party effects that register the swing toward the Republicans, or by including support for the Tea Party or attitudes toward President Obama’s health care reforms under the Affordable Care Act of 2010. Vigilance in interpreting results that may be affected by the unique characteristics of the 2010 elections is certainly appropriate, but it appears that 2010 was a challenging year to test claims that candidate differences, especially on valence, affect voting choice. 5

Candidate spending data were first available in 1972. Gary Jacobson generously provided data on spending and challenger experience.

4 Ideological Proximity, Valence, and Voter Choice

Can voters see their way to vote their fundamental interests as specified by the Proximity and Valence Rules? Answering that question is the purpose of this chapter. Much is riding on the answer. If the Proximity and Valence Rules describe voter behavior, politicians have incentives to anticipate voters’ interests in policy and valence when they decide whether and how to run for office. Furthermore, the outcomes of the electoral process should be more or less representative, depending on how well the Proximity and Valence Rules describe voters’ choices. While the evidence presented in this chapter supports the relevance of ideological proximity and valence differentials to voters’ choices in the 2010 elections, we will see other factors at work. Voters are capable of enforcing their interests on Election Day conditioned on the choices they are offered between competing candidates, although a number of potential impediments stand in the way of voters’ ability to act on their interests. Voters may lack the information or sophistication to choose on the basis of the Proximity and Valence Rules; partisan polarization may squeeze out local candidate differences as voters rely on party identification or presidential approval as heuristics when choosing between local candidates; candidate resource differentials may obfuscate candidate differences of fundamental concern to voters. Of course, some of these are “impediments” only from the perspective of the Proximity and Valence Rules and are otherwise perfectly reasonable decision rules for voters to employ. Others may be seen as distorting voter behavior away from choosing on the basis of fundamental interests. Analysis of potential impediments (and facilitators) continues into Chapter 5. 84

Candidate Differences Within Districts

85

The analysis proceeds first by providing a descriptive summary of the choices facing voters in the sample districts. I then conduct tests of implications of the Proximity and Valence Rules to demonstrate the relevance of these rules for voting choice. The empirical assessment includes a “Fundamentals” model based only on the effects of demographic variables and candidate proximity and valence differentials. I compare the Fundamentals model with a “Standard” model of voting choice that does not include measures of the candidate differentials, and a “Combined” model that includes the covariates from the Fundamentals and Standard models. As the analysis proceeds, we will attend to how awareness of candidate positions, and partisanship, facilitate or distort the effects of candidate proximity and valence differentials. For purposes of continuity with the rest of the book, the proximity differential will be based on the “symbolic” self-identified liberal-conservative item. However, I replicate in the appendix to this chapter some of the central findings using an issues-based measure of voter and candidate “latent” ideological positions (Ellis and Stimson 2012; Jessee 2012).1

candidate differences within districts Because the Proximity and Valence Rules posit the nature and quality of voter response to candidate differences, we begin the investigation of voting choice by providing more detail about the structure of preferences in the public and the ideological and valence differences between candidates. Figures 4.1 and 4.2 and Table 4.1 summarize the nature, extent, and implications of party polarization among candidates and in the electorate. Figure 4.1 indicates that the ideological divergence between Democratic and Republican candidates greatly exceeds the partisan polarization within the electorate. Democratic candidates were just over 1.5 units to the left on the liberal-conservative scale, while Republican candidates were 2 units to the right of center. In the electorate, Democratic identifiers were less extreme in their liberalism than candidates in their party, as were Republican identifiers relative to their party’s candidates. The overlap between the parties in the electorate suggests the possibility that minorities of identifiers in each party may have been closer to the opposite party’s candidates running in their districts. 1

As noted in Chapter 2, I rely on the symbolic item because it is available in the large-sample Common Content survey, whereas issue items identical to those asked of informants were asked of constituents only in the UC Davis modules (N = 2000). The module survey is adequate to test individual voter-choice models, but not to estimate district preferences.

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.6

Republican Candidates (mean = 2.09; sd = .34)

.4

Democratic Candidates (mean = −1.53; sd = .56)

Independents (mean = .33; sd = 1.28) Republican Identifiers (mean = 1.55; sd = 1.14)

0

.2

Democratic Identifiers (mean = −.85; sd = 1.38)

−3

−2

−1 0 1 Liberal-Conservative Scale

Very Liberal

2

3

Very Conservative

figure 4.1 Candidate and Party Identifier Ideological Distributions

PA02 CO01 MN05 NC11 FL22 OH15 TX18 TX29 MD02 CO03 MO02 IL13 MN03 VA03 CO07 IL17 OH06 WA08 FL09 UT03 PA04 NY29 IN08 TX17 TX06 ID01 TN06 LA01 TX14 GA03

Dem Identifiers District Median

Repub Candidates Dem Candidates

Repub Identifiers

−3

Very Liberal

−2

−1 0 1 Liberal-Conservative Scale

2

3 Very Conservative

figure 4.2 District and Candidate Ideological Positions for Random Subset of Districts (N = 30)

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table 4.1 Breakdown of Ideological Distances Between Party Identifiers and Candidates in Each Party Democrats

Independents

Republicans

Mean Mean Mean Percent Distance Percent Distance Percent Distance Closer to Democrat 80.2 .90 Closer to Republican 19.3 1.14 100% N (8,335)

52.7 1.21 47.3 1.03 100% (2,480)

15.8 1.22 84.2 .67 100% (7,668)

Note: District N = 150; contested races only.

Table 4.1 illustrates the implications of polarization between opposing candidates by showing the percentages of partisan constituents closer to the candidate from each party running in their district, along with the mean distances between partisans and the closer candidate. A large majority of identifiers in each party were ideologically closer to the candidate in their district from their own party, but there was nonetheless a substantial gap on average within districts between candidates and their partisan supporters. Moreover, 19 percent of Democrats and 16 percent of Republicans were ideologically closer to the candidate from the opposing party in their district. For partisans caught between their party loyalty and their ideological interests, the mean distance from the closer candidate was greater than for partisans closer to their party’s candidate. Independents, not surprisingly, were in between, with a slight majority closer to the Democratic candidate than the Republican. Figure 4.2 illustrates ideological distances between candidates, partisans in the districts, and district medians in a randomly selected subset of thirty districts. Districts in the graph are ordered from the most liberal district in the sub-sample (PA02) to the most conservative (GA03). Candidate positions (represented by light grey triangles on the left for Democratic candidates and dark grey triangles on the right for Republican candidates) are substantially more extreme than their district medians and, in most districts, more extreme than partisan identifiers within the district (indicated light and dark grey boxes). In coming chapters, there will be more to say about candidates’ ideological positioning and its implications for district representation. There is almost no evidence of partisan polarization on valence: the mean valence score of Democratic candidates is .29 and the mean

Ideological Proximity, Valence, and Voter Choice

1

88

.2

.4

.6

.8

Candidates' Ideological Cut Points (mean = .28; standard deviation = .36)

0

Candidates' Valence Differentials (mean = −.01; standard deviation = .70)

−2

−1 0 1 Candidates Ideological Cut Points and Valence Differentials

2

figure 4.3 Distributions of Candidate Valence Differentials and Ideological Cut Points

Republican scored just .03 higher at .32. That said, the difference between candidates, whether it favors Democratic or Republican opponents, can be substantial. The absence of systematic polarization on valence alongside sharp ideological polarization is not surprising, as there is no reason to anticipate Republicans would be systematically higher or lower on valence than Democrats, but there is every reason to expect the two parties’ candidates to be sharply divergent in their ideological positions. Given this dissimilarity between ideological and valence partisan differences, it may come as a surprise to compare the distributions of the cut points between the ideological positions of opposing candidates and the valence differentials in Figure 4.3.2 Although there is a large gap between the ideological positions of candidates and no such polarization on valence, the distribution of the ideological cut points between the candidates has a substantially lower variance than the candidate differentials on valence. 2

Negative cut-point scores indicate that the mid-point between opposing candidates in a district was left of center; negative valence-differential scores indicate the Democratic candidate was stronger; positive scores mean the Republican was advantaged on valence.

Candidate Differences Within Districts

ID01 TX29 NY29 MN05 TX17 PA04 CO07 MD02 CO01 TN06 IN08 PA02 CO03 GA03 VA03 WA08 UT03 MN03 IL13 IL17 TX06 LA01 FL22 NC11 TX14 FL09 TX18 MO02 OH06 OH15

89

Republican Candidates

Valence Differentials

Democratic Candidates

−1

Democratic Candidate Stronger

0 Leadership Valence Scale

1

Republican Candidate Stronger

figure 4.4 Valence Differentials and Candidate Valence Scores for Random Subset of Districts (N = 30)

The ideological cut-point distribution in Figure 4.3 does not reflect the partisan polarization so evident between the opposing parties’ candidates because candidate extremism is approximately symmetric between parties and across districts. It is not the case that districts are characterized by one or the other of the parties’ candidates adopting a position dramatically closer to district preferences, while the opposing (presumably losing) candidate takes an extreme position. Both candidates are relatively extreme, which reduces the variation in the cut points compared with what we would observe if moderate candidates consistently faced extremists. As was apparent from Table 4.1, even partisan supporters are distant from the closer candidate in their district. Candidate polarization within districts does not negate the possibility that voters choose consistent with the Proximity Rule, although it does have implications for the ideological representation districts realize, even if all voters slavishly followed the Proximity Rule. Figure 4.4 illustrates within-district configurations that give rise to variation in the valence differentials on the same random subset of districts depicted in Figure 4.2. Districts in Figure 4.4 are sorted from the most to least favorable valence differential to the Democratic candidate

90

Ideological Proximity, Valence, and Voter Choice

running in the district (valence differentials indicated by black dots). In ID01, for instance, the Democratic incumbent running for reelection (Representative Walt Minnick) was rated very strong on valence (+.92) while his Republican challenger (Raul Labrador) had a low valence rating (−.52). Thus, the Democrat was much the stronger candidate on valence. As the difference between the light grey (Democratic candidates) triangles and dark grey (Republican candidates) triangles reduces and flips to indicate the Republican is advantaged, the valence differential drifts in a Republican direction. Thus, OH15 is the district in the subset with the largest pro-Republican valence differential of +.90 (the Republican candidate’s (challenger Steve Stivers) valence score was +.89, and the Democrat’s (incumbent Mary Jo Kilroy) was −.01). Other configurations, of course, are possible as in VA03 where the valence differential barely favors the Republican because both candidates were rated high on valence and the Republican edged the Democrat by being slightly stronger.3 Keep in mind that voters may be cross-pressured between their ideological and valence interests, as when they are ideologically closer to the Democratic candidate, but the Republican candidate in their district is stronger on valence. The district with the strongest pro-Democratic valence score in Figure 4.4 illustrates this point. Although Representative Minnick had a large valence advantage, the ideological leanings of the district were distinctly conservative. The mean Republican presidential vote share in 2004 and 2008 in the district was 66.3 percent Republican, and the average voter in 2010 was .26 units closer to Labrador than to Minnick on the seven-point liberal-conservative scale. Predictably, with Minnick’s large valence advantage combined with Labrador’s ideological advantage among voters, the race was close as Labrador won with only 51 percent of the two-party vote.4

3

4

It is possible for both candidates to be rated negatively on valence (as in IN08, not included in the random subset in Figure 4.4). In that district, the valence differential favored the Democrat because the Democratic candidate was rated somewhat less negatively than the Republican. Although on average 2010 voters in ID01 were cross-pressured between their ideological and valence interests, the district, by the measure used in this study, was not crosspressured. This is because the average constituent in ID01 was less conservative than the average voter (+.74 vs. +1.25), while Minnick was the most conservative Democrat in the sample. Given Labrador’s conservative position (+2.12), he was ideologically more distant from his future constituents, but closer to those who voted. Questions related to cross-pressured voters and districts are addressed in Chapters 5 and 9, respectively.

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explaining voting choice in 2010 The Fundamentals model of voting choice rests primarily on candidate proximity and valence differentials. The question is whether there is evidence that candidate proximity and valence differentials affect voting choice, as the Proximity and Valence Rules expect. The Fundamentals model also includes demographic characteristics assumed to be exogenous to candidate differentials: dummy variables indicating selfidentification as African American, Hispanic, female, college graduate, owning a home, married, urban dweller, and union member. There is also a control for whether the respondent resided in a district in the 2006 supplemental sample. Because the primary focus of the analysis is on the effects of the candidate differentials, I do not report the demographic and design effects. The “Standard” model is based on covariates widely recognized as relevant to explaining voting choice in mid-term House elections excluding the candidate differentials, which are not available in other studies of voting choice. In addition to the demographic and design controls in the Fundamentals model, the Standard model includes as covariates predicting voting choice party identification, presidential approval, support of the Affordable Care Act (Obamacare), support for the Tea Party movement, candidates’ experience and spending differentials,5 the party holding the seat before the election, and whether the race was open with no incumbent running for reelection. I do not mean to imply that the Standard model precisely describes other scholars’ approaches to explaining voting choice in House elections. Rather, the Standard model is meant to capture something like a consensus model of voting choice in the 2010 elections that reflects commonly included covariates such as party identification and candidate resource differentials, as well as factors that capture unique aspects of the 2010 elections, such as attitudes toward health care reform and the Tea Party movement. Finally, I present results based on a Combined model that includes the candidate proximity and valence differentials and the covariates in the Standard model in a single model explaining voting choice. Table 4.2 presents the logistic regressions of each of the three models. 5

The experience differential ranges from Democratic incumbent faces inexperienced Republican challenger (−2), to Democratic incumbent faces experienced Republican challenger (−1), to Republican incumbent faces inexperienced Democratic challenger (+2). The spending differential is logged Republican candidate’s spending minus logged Democratic candidate’s spending.

92

Ideological Proximity, Valence, and Voter Choice table 4.2 Logit Models of Voting Choice, 2010 Fundamentals Standard Model Effect Model

Valence 0.293∗∗ differential (0.10) Proximity 0.835∗∗∗ differential (0.02) Party identification Presidential approval Obamacare opposition Tea Party support Candidates’ experience differential Candidates’ spending differential Democratic-held seat Open seat Constant Pseudo R-square N Log likelihood

Combined Effect Model Effect

+.04 +.73 0.694∗∗∗ (0.04) −2.010∗∗∗ (0.15) 1.088∗∗∗ (0.17) 1.251∗∗∗ (0.16) 0.244∗ (0.11)

+.32

0.153∗∗ (0.05)

+.03

−.18 +.08 +.09 +.04

0.369∗∗∗ (0.11) 0.296∗∗∗ (0.03) 0.585∗∗∗ (0.05) −1.796∗∗∗ (0.15) 1.060∗∗∗ (0.16) 0.876∗∗∗ (0.17) 0.184 (0.10)

+.03

0.129∗ (0.05)

+.01

0.192 (0.18) 0.512

0.257 (0.34) 0.149 (0.19) −0.203 (0.29) 0.712

0.163 (0.33) 0.400∗ (0.18) −0.054 (0.29) 0.728

11920 −3497.4

11920 −2061.9

11920 −1952.4

+.11 +.22 −.15 +.07 +.05

+.02

∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Note: Demographic and design effects estimated but not reported. Cell entries are logit coefficients with robust standard errors clustered by district in parentheses below each coefficient. Effect estimates on continuous and ordinal variables estimated comparing the 75th and 25th percentiles. Presidential approval, Obamacare opposition, and Tea Party support coded as dummy variables.

Column 1 in Table 4.2 reports estimates based on the Fundamentals model, which employs candidate proximity and valence differentials plus design and demographic controls (not shown). Both candidate differentials affect voting choice consistent with the Proximity and Valence Rules. It is clear from the effect estimates reported that candidate proximity

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93

differentials in the Fundamentals model have a much stronger effect than candidate valence differentials. An important reason for the strong effect of proximity differentials in the Fundamentals model is the absence of party identification in that model, and the overlap between party identification and the proximity differential. As noted in previous discussions, partisan polarization strengthens the link between partisanship and ideology for voters and candidates. When party identification is added to the Fundamentals equation as the only additional covariate, the effect of the proximity differential remains strong and highly significant, but it is obvious that it is heavily mediated by party identification (the effect estimate for proximity differentials drops from .73 to .28). In contrast, the effect of the candidate valence differential is not reduced when party identification is included in the Fundamentals equation. Figure 4.5 displays the effects of the proximity and valence differentials by party identification.6 Figure 4.5(a) is similar to graphs produced by other scholars estimating the effects of candidate proximity differentials in American elections by party identification (Buttice 2011; Jessee 2009; Shor and Rogowski 2012; Simas 2013). It is apparent that party identification and proximity differentials affect voting choice, with party identification shifting the intercept upward for Republicans and downward among Democrats. The pattern of relationships in Figure 4.5(a) has led some to conclude that party identification is a “distorting” influence on spatial voting, a position that I challenge in Chapter 5. It is clear that there is some distortion in the effect of party identification, especially when party identification and the proximity differential predict votes for different candidates. The impact of party identification on voting choice is also apparent in Figure 4.5(b), alongside the effects of candidate valence differentials among all three partisan groups. While party identification is the dominant explanation of voting choice in contemporary analyses of congressional elections and obviously overlaps with the proximity differential to an important degree in this analysis, a second conditioning factor in spatial voting is the effect of awareness of opposing candidates’ ideological positions. A related factor is the general sophistication of voters, defined here by level of education, information about politics other than the ideological location of the local House candidates, and engagement in political discourse by following politics in the 6

Partisan effects are estimated for Democratic and Republican identifiers who identify as “not strong,” and strict independents that do not “lean” toward one of the parties.

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1

(a) Proximity Effect by Party

Pr(Republican Vote) .4 .6

.8

Republicans

.2

Strict Independents

0

Democrats

−5

−4

−3

−2

−1 0 1 Proximity Differential

Voters Closer to Democrat

3

2

4

5

Voters Closer to Republican

1

(b) Valence Effect by Party

Pr(Republican Vote) .4 .6

.8

Republicans

.2

Strict Independents

0

Democrats

−2 Democrat Stronger

−1

0 Valence Differential

1

2 Republican Stronger

figure 4.5 Effects of Proximity and Valence Differentials on Voting Choice by Party Identification Note: Effects estimated from Fundamentals model, including party identification.

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media.7 Awareness of candidate positioning has been asserted as a necessary condition for spatial voting to occur (Erikson and Tedin 2011). Placing both candidates’ ideological positions in low-information elections is a difficult task for voters, as evidenced by the fact that only 30.8 percent of the sample and 43.8 percent of voters in the sample met this test.8 Low awareness among voters is one reason many scholars are skeptical of the spatial model of choice in House elections. Awareness of candidate positions has not been included in recent analyses of spatial voting in House elections because of the reliance on measures of latent ideology, which do not permit readily measured indicators of voter awareness of candidates’ positions on the many issues included in such measures. These studies have instead included indicators of general sophistication (Shor and Rogowski 2012). In this study, the effects of each factor can be assessed separately – awareness of candidate positions on the liberalconservative scale and sophistication based on measures distinct from the ability to place the two House candidates’ ideological positions. Figure 4.6 presents the effects of proximity voting by respondents’ ability to place both candidates with reasonable accuracy on the liberalconservative scale. It is clear that although ability to place the candidates increases the effect of proximity differentials on voting choice, it is not a necessary condition for proximity differentials to have an effect since there is a clear effect of proximity differentials on voting choice among voters unable to place the ideological positions of the candidates. Sophistication levels also interact with proximity differentials consistent with other studies of this effect (Jessee 2012; Shor and Rogowski 2012). Voters who are low in sophistication and unable to place both candidates are still strongly affected by proximity differentials in their voting (the effect of proximity drops from .73 in the Fundamentals model to .51 among those low in sophistication and unable to place the candidates). In a polarized party system, many voters may infer individual candidates’ ideological positions on the basis of the positions of the political 7

8

The measure of sophistication is an index composed of three equally weighted variables: the number of years of formal education, the level of information about government and politics as indicated by a battery of factual questions other than the ideological positions of the House candidates, and the level of engagement with various media for political content, including newspaper, television, radio, and the Internet. Respondents were asked to place the Democratic and Republican candidates running in their districts on the seven-point liberal-conservative scale. Respondents who said they did not know one or both candidates’ positions, who placed both candidates at the same ideological position, or who placed the Republican to the left of the Democrat were classified as “unaware” of the candidates’ positions.

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96

Pr(Republican Vote) .6 .4

.8

Able to Place Both Candidates

0

.2

Unable to Place Both Candidates

−5

0 Proximity Differential

5

figure 4.6 Effect of Proximity Differential by Awareness of Candidates’ Ideological Positions Note: Effects estimated from Fundamentals model. “Unaware” voters were unable to place the ideological positions of both candidates running in their district.

parties. A much larger percentage of the sample can accurately place the two political parties on the liberal-conservative scale (73.4 percent of the sample and 88.7 percent of voters).9 This makes sense given the visible place of the parties in national political discourse. As the parties have become more polarized, awareness of their ideological positions has grown (Hetherington 2001). Thus, it is reasonable that voters infer the positions of local candidates on the basis of the ideological positions of their parties (Koch 2002; Franklin 1991; Conover and Feldman 1983). Figure 4.7 shows that the ability to place the ideological positions of the parties does appear to be a necessary condition for voters to 9

The standard is the same as placing the candidates: respondents must place both parties on the liberal-conservative scale with the Democratic Party to the left of the Republican Party.

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Pr(Republican Vote) .4 .6

.8

Able to Place Both Parties

0

.2

Unable to Place Both Parties

−5

0 Proximity Differential

5

figure 4.7 Effect of Proximity Differential by Awareness of Party Ideological Positions Note: Effects estimated on Fundamentals model including party identification.

respond to local candidate proximity differentials.10 Voters able to place both parties’ ideological positions with reasonable accuracy are strongly responsive to the proximity differential between candidates running in their districts; voters unable to place the ideological positions of the parties are not responsive to the relative proximity of candidates in their voting. As the foregoing discussion suggests, further analysis supports the importance of the party’s ideological positions on perceptions of local candidates’ positions, but party is by no means the entire story in explaining constituents’ placements of the candidates running in their district. This question is explored in greater depth in the appendix to this chapter. The Standard model in Table 4.2 (column 2) includes national partisan effects linked to respondents’ party identification and approval of President Obama. In addition, the national debate in 2010 turned heavily on reactions to the Affordable Care Act (or “Obamacare”) and the Tea 10

I am grateful to Jim Adams for suggesting this test and to Larry Bartels for saving me from an interpretation error.

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Party movement that was deeply critical of President Obama’s two major legislative initiatives during the first two years of his term: health care reform and the response to the financial crisis that took hold in the fall of 2008. Most explanations of voting choice also incorporate important aspects of the political environment in district campaigns, most notably resource advantages one candidate may have over the other. The candidate experience differential reflects whether the incumbent ran for reelection combined with the office-holding experience (or lack thereof) of the challenger. The spending differential registers the advantage one candidate has over the other in spending, coded in the usual way with Democratic spending advantages registered by negative scores and Republican advantages indicated by positive differentials.11 The standard model does a good job of explaining voting choice. In fact, it substantially outperforms the Fundamentals model, as indicated by the smaller log likelihood and higher pseudo R2 . All of the individual attitudinal measures – party identification, presidential approval, health care opinion, and Tea Party support – are significantly related to voting choice. In addition to voters’ attitudes, the Standard model indicates that as Republican candidates gain resource advantages over their Democratic opponents in the form of incumbency/experience and spending, voters’ probability of supporting them increases. In the Combined model (column 3, Table 4.2), both the proximity and valence candidate differentials are highly significant. There is no question that adding the proximity and valence differentials to the Standard model adds significant predictive power to the model.12 It is also clear that the partial effect of the proximity differential is substantially reduced compared with the Fundamentals model. As noted, much of this reduction is due to the addition of party identification to the model. Indeed, adding only party identification and presidential approval to the Fundamentals model reduces the effect of the proximity differential to nearly the magnitude observed in the Combined model. This indicates that much of the Fundamentals model proximity effect overlaps with these national partisan covariates. In the Combined model, the increase in the probability of a Republican vote over the same range of the proximity differential is reduced from .73 to .11. The effect of the valence differential is modestly reduced in the Combined model – its magnitude 11 12

The spending measure is the difference in logged spending by the two candidates. A likelihood ratio test supports rejecting the null hypothesis (p < .000).

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in the Fundamentals model is much less than proximity, and its reduction in the Combined model is also much less. The resource-asymmetry hypothesis is a prominent rival to the claim that voters choose candidates based on their interests. In the Combined model, the candidate spending differential is the covariate that picks up the resource advantage of one candidate over the other that significantly affects voting choice. Negative scores on the spending differential indicate that logged Democratic candidate spending is greater than the Republican’s spending; positive scores indicate a Republican spending advantage. While the spending differential is significant, it is quite small – smaller even than the magnitude of the valence differential on voting choice. Thus, while we cannot conclude that candidate spending has no effect in the Combined model, neither should we overstate the effect of spending on voting choice. Its magnitude is dwarfed by the effect of the proximity differential, a factor directly linked to voters’ interests as I define them. Thus, candidate spending has the potential to distort voting choice at the margin, but it is hardly the overwhelming (and overbearing) driver of voting choice that some critics appear to suggest.

conclusion What can we make of these results? One possible conclusion is that the Proximity and Valence Rules are indeed fundamental to voting choice in House elections. In this view, ideological proximity is especially powerful. Models that assign independent effects of alternative rules such as party identification and presidential approval underestimate the effects of spatial voting because there is substantial overlap between party and ideology in the system. In this perspective, too, valence effects are easily missed when resource differentials are the only valence-related variables included, either because resource differentials mediate some of the effect of valence differences or because their effects are allocated entirely to resource asymmetries. A second interpretation emphasizes the Proximity and Valence Rules as independent forces in voting choice, providing value added to standard explanations of voting choice in congressional elections, but not otherwise disturbing party- and candidate resource-centric explanations of voting choice in congressional elections. In this view, the analysis in this chapter provides a useful perspective that enhances our understanding of voting choice and may cause us to elevate our appreciation of the reasonable

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nature of voting based on local candidate differences, but does not fundamentally alter our understanding of voters in these elections. My perspective will ultimately land between these interpretations. The question of how to interpret the difference between the Fundamentals and Combined models of choice is a theme pursued in the chapters to come. Much depends on how we understand the effect of party identification on ideology and voting choice, and the effect of party on election outcomes and representation. While these questions are addressed in chapters to come, the analysis of voting choice in this chapter provides a framework for studying the implications of these factors on candidate behavior and election outcomes.

appendix to chapter 4: latent and symbolic ideology and perceptions of candidate positions The results in this chapter rely on the “symbolic” self-identification question to estimate candidate and voter ideological positions, and the proximity differential. I rely on this item primarily because of its availability in the Common Content survey supports analysis at the district as well as the individual level. However, the UC Davis module included six issue items that can be used to construct “latent” ideology measures to provide parallel tests to those reported in this chapter. This appendix replicates the core results in the chapter using the latent issues-based measure.13 In addition, this appendix explores the basis of constituents’ perceptions of local candidates’ ideological positions since these perceptions are often seen as necessary or important conditions for spatial voting. Scholars have raised concerns about the symbolic ideology measure for two reasons (see Jessee 2012; Ellis and Stimson 2012): it is a single item rather than based on multiple items, which is a preferable measurement strategy (Ansolabehere et al. 2008); and because there is evidence of bias in responses to the symbolic item. Respondents were asked to identify as “liberal” or “conservative” without any indication (other than their willingness to answer the question) that they grasp what these terms mean. Perhaps of greater concern, the terms “liberal,” “conservative,” and “moderate” have taken on political meaning that may not fully map onto individuals’ policy beliefs and opinions when measured by their 13

In-depth replication of the results in this chapter, based on a latent measure such as the interaction between sophistication and the proximity differential, is fully consistent with those reported in this chapter (Buttice 2012).

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preferences on specific policy issues. For example, some respondents identify as “conservative” even though they tend to express liberal opinions when asked about specific issues. This may reflect a generally positive attraction to the word “conservative” and/or negativity toward the word “liberal.” In response to these problems, some scholars have argued that using latent measures of ideology based on responses to specific issue items is preferable to using the symbolic item. While reservations about the symbolic ideology measure may have merit, there are good reasons to use the symbolic item. Many scholars use the symbolic item because it is widely available (including in the ANES time series) and because it is strongly related to behavior and attitudes as one would expect of a valid measure of ideology. Symbolic attachments to ideological labels may be a perfectly legitimate way to measure ideological predispositions, even if measures based on specific issue responses arrive at somewhat different results. Fortunately for purposes of this book, this appendix will show that key results in this chapter replicate using a latent measure. Among the advantages of the symbolic item to this study is the ability to aggregate individual ideological positions to estimate the district median preference, which is critical to the study of district outcomes and representation in Chapters 6–9. However, the UC Davis module in the 2010 study (N = 2000) included a battery of six issue items that can be used to measure voters’ and candidates’ latent ideology. The six items were asked of informants when placing candidates and of voters when giving their own issue opinions in identical formats.14 Thus, it is possible to construct constituent, candidate, and proximity differential measures from these items that can be compared with the analysis reported in this chapter based on the symbolic ideology item.

Replication with Latent Proximity Differential Measure The symbolic and latent ideology measures are strongly, but not perfectly, correlated. Among voters, the correlation is .81; the correlation between Democratic candidate placements by informants on the two measures is .91; the correlation for Republican candidates is .73.15 Consistent with other studies, there is a conservative tilt to constituents’ responses to the 14 15

The items asked about gay marriage, environmental regulation, the war in Afghanistan, health care reform, immigration, and tax reform. The higher correlation for Democratic candidates may be due to the substantially higher standard deviation on both measures for Democratic than for Republican candidates.

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table a.4.1 Logit Models of Voting Choice Based on the Latent Ideology Measure of the Proximity Differential, 2010 Fundamentals Standard Model Effect Model Valence 0.471∗ differential (0.20) Proximity 1.525∗∗∗ differential (0.11) Party identification Presidential approval Tea Party support Candidates’ experience differential Candidates’ spending differential Democratic-held seat Open seat Constant Pseudo R-square N Log likelihood

Combined Effect Model Effect

+.04 +.81 1.091∗∗∗ (0.13) −0.793∗∗∗ (0.14) 0.775∗∗∗ (0.14) 0.178 (0.12)

+.54 −.20 +.08

−0.107 (0.14)

0.239 (0.69) 0.666

−0.885 (0.48) 1.787∗∗∗ (0.36) −0.988 (0.63) 0.799

1227 −235.7

1227 −141.7

0.686∗ (0.34) 0.707∗∗∗ (0.13) 0.980∗∗∗ (0.14) −0.550∗∗∗ (0.15) 0.435∗∗ (0.16) 0.223 (0.13)

+.03 +.22 +.35 −.08 +.02

0.029 (0.16)

+.06

−0.845 (0.53) 1.930∗∗∗ +.06 (0.42) −0.053 (0.56) 0.822 1227 −125.8

∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Note: Demographic and design effects estimated but not reported. Cell entries are logit coefficients with robust standard errors clustered by district in parentheses below each coefficient.

symbolic item compared with their responses on the issue items. The distributions of the two measures for candidates closely overlap with a slight tendency for candidates to be more extreme on the symbolic than the issue item. Table A.4.1 presents a close replication of the Fundamentals, Standard, and Combined models in the chapter based on the symbolic ideology measure. One difference between the tests is the omission of opinion on health care reform, which is one of the issues in the battery of items included in

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the latent measure. On two key points, the replication is reassuring: first, in the Fundamentals model, both the proximity and valence differentials are significant. Second, the effects of the proximity and valence differentials hold up well in the Combined model. As in Table 4.2, the Standard model provides a better fit than the Fundamentals model, but the Combined model improves on the Standard model (p < .000). Thus, whether we use the symbolic or the latent measure, the core finding that proximity and valence differentials affect voting choice holds up. Constituents’ Perceptions of Candidates’ Ideological Positions Voters’ perceptions are not a central focus of this book. My approach is to measure candidate positions and valence characteristics independent of voter perceptions, and observe their effects on voter response, among other questions. To be blunt, I think voter perceptions are overrated as a mechanism explaining behavior. Voters may react to the choices offered to them without being able to report candidate positions (as we have seen) for any number of reasons, including because they are responsive to cues from opinion leaders or the candidates themselves without fully absorbing the ideological reasoning or information levels of opinion leaders (Sniderman and Stiglitz 2012). The over-emphasis on the importance of voters’ perceptions and their ability to report information about the choices they face has led scholars to underestimate the capacity of voters to function reasonably and effectively in elections. Despite my reservations about perceptions, especially as necessary conditions for voters’ behavior, it is clear from the analysis in this chapter that perceptions can have an impact – even a decisive impact – on behavior. While awareness of candidates’ ideological positions had only a marginal effect increasing the impact of proximity differentials on voting choice, awareness of the parties’ ideological positions appears to be a necessary condition for proximity voting to occur. This raises the question of whether constituents’ perceptions of candidates’ positions depend wholly on their perceptions of the party’s location, or whether voters are aware of candidate positions as they differ from their party. Examining the basis of voters’ candidate placement requires a measure of candidates’ positions that is independent of voters’ perceptions, which we have in the district informant placements. It also requires a model that accommodates citizens’ tendency to rationalize their perceptions of candidate positions, depending on their partisanship.

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table a.4.2 Regression Models of Constituents’ Perceptions of Candidates’ Ideological Positions (Symbolic Ideology Item)

Perceived party position Informants’ placement of candidate Party identification Respondent ideology Party identification X ideology Democratic-held seat Candidate was incumbent Constant Adjusted R-square N

Democratic Candidates

Republican Candidates

0.436∗∗∗ (0.02) 0.625∗∗∗ (0.06) −0.067∗∗∗ (0.02) −0.034 (0.02) −0.040∗∗∗ (0.01) −0.199∗ (0.09) −0.137 (0.08) 1.030∗∗∗ (0.12) 0.359 11895

0.423∗∗∗ (0.02) 0.575∗∗∗ (0.05) −0.079∗∗∗ (0.01) 0.109∗∗∗ (0.02) 0.059∗∗∗ (0.01) −0.083 (0.06) −0.045 (0.06) −0.687∗∗∗ (0.16) 0.311 12192

∗

p < 0.05, ∗∗∗ p < 0.001. Note: Demographic and design effects estimated but not reported. Cell entries are OLS regression coefficients with robust standard errors clustered by district in parentheses below each coefficient.

Table A.4.2 shows that constituents’ ideological placements of the local candidates running in their districts are affected by their perceptions of their political party’s ideological position. At the same time, however, there is a strong, independent effect of candidate positions based on the informant measure. This indicates that voters are picking up local variation in candidates’ positions over and above the effects of their understanding of the parties.16 The models also include interactions between party identification and the constituent’s ideology to capture projection effects linked to party identification. The interaction for Democratic placements indicates positive projection among Democratic identifiers who see Democratic candidates as more liberal as they identify 16

An alternative specification is to use Nominate scores to predict constituents’ placement of incumbents in each party. Otherwise identical models support the same substantive conclusions as the analysis based on the informant placement measures.

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as more liberal; and negative projection among Republican identifiers who see Democratic candidates as more liberal as they are more conservative. The same parallel effects exist in the regression of Republican candidate placements, with Democrats’ placements subject to negative projection and Republicans’ placements affected by positive projection. These analyses by no means exhaust the questions that might be addressed about constituent perceptions in the data. However, they do suggest that voters are able to discern the positions local candidates take beyond what they infer from party ideologies. Two conclusions seem to follow: first, voters are attentive to candidate positioning in House elections. Undoubtedly there is variation in voters’ ability to perceive candidate positioning linked to candidate visibility and attributes of voters themselves, such as sophistication,17 but the overall pattern is reassuring. Second, whereas we have seen that placing the candidates’ ideological stands is not a necessary condition for spatial voting, awareness of the parties’ positions looks much closer to a necessary condition, perhaps for voters who report ignorance about candidate positions. It is also true, of course, that a great many more voters are able to place the parties with tolerable accuracy than are able to place both candidates running in their district. 17

There is no loss in alignment with informant placements when respondents placed challengers compared with incumbents (analysis not shown).

5 Correct Voting on Proximity and Valence

An extensive literature addresses the question of voter sophistication, or the capacity of voters to meet putative standards of democratic politics. Among other questions, this has led to research on levels of information about politics and government in the public, investigation into the degree of ideological organization of opinion on issues of the day, and the extent to which policy issues motivate voting choice. Each of these approaches is based on assumptions about how much information voters in a democracy should have, how well their opinions should map onto the ideological debates among political elites, or the effect of policy opinions on voting choice relative to other factors seen as less central to democratic ideals. A protracted debate has ensued about how much information is necessary for voters to act on their interests and what exactly the criteria for effective democratic citizenship should be (Alvarez 1998; Converse 1964; Delli Carpini and Keeter 1996; Schattschneider 1975; Sniderman et al. 1991). The debate about citizen capacity is characterized by a focus on the process of voter decision-making, especially on the amount of information voters bring to the voting decision, and the criteria that appear to shape voting choice. In response to this focus, Larry Bartels (2008) offered this spot-on critique: The political consequences of “public ignorance” must be demonstrated, not assumed. And that requires focusing not just on what voters don’t know, but on how what they know actually affects how they vote. Do they manage to make sensible choices despite being hazy about the details of politics and government? (Okay, really hazy.) If they do, that’s not stupid – it’s efficient. 106

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In other words, it is easy to show that most voters lack information that informed observers might consider “essential” (what is the term of a US Senator? Which party controls the majority in the House of Representatives? What is the name of the Chief Justice?), but the question remains, how is this information useful to the voter? One compelling answer is found in the literature on “correct voting” (Lau and Redlawsk 1997; Lau et al. 2008). This approach to the problem of citizen capacity does not just address the question of how people vote, but how well they vote. A “correct” vote is one that meets some criteria of voting “well,” while an “incorrect” vote falls short of these criteria in some way. This approach is capable of investigating whether and how information is critical to making correct choices, but it is tied to the criteria specified as defining correct voting, rather than to conditions (such as the amount of information) that are presumed to be required for citizens to meet their democratic responsibilities. This chapter brings to bear the framework of this book on the question of correct voting. The Proximity and Valence Rules imply standards of correct voting that extend the literature on this question. Lau and Redlawsk (1998) assumed that voting correctly meant voting consistent with choices made on the basis of full information. Their experimental approach allowed them to inform voters about candidate differences and to compare the choices they made before and after they were informed about the candidates on the dimensions of choice included in the study. In a later paper (Lau, Anderson, and Redlawsk 2008), they investigate correct voting using survey data from presidential elections. They determine correct choices on issues and valence items by comparing the ratings and perceptions of respondents who are above the median level of political knowledge with choices ordinary voters make. The considerations voters use to determine their choices in the Lau et al. model include issues and leadership-valence items, so in that respect, their study is similar to this one.1

a framework for analyzing correct voting The claim that voters pursue ideological and valence returns from their participation in elections sets the standard I employ in this chapter: a “correct” vote is one cast consistent with the ideological and/or valence 1

Lau et al. include additional factors, most notably party identification, among the considerations voters use to vote correctly, and they do not separate policy from valence components in their analysis.

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interests of the voter. As with other studies of correct voting, the point is not merely to assess the amount of correct voting. It is impossible to say what amount of correct voting is necessary or desirable for the functioning of democracy, but armed with a workable concept we can address the conditions that enable or impede correct voting. These conditions may reflect differences among voters (such as how much information they have) and the political context to which voters react such as the ideological divergence between the candidates or the presence of an incumbent running for reelection. I define a correct vote for purposes of this analysis as one that is consistent with the Proximity or Valence Rule, or both. Voters cast a “proximity vote” by voting for the closer candidate as measured by the proximity differential (Boatright 2008; Joesten and Stone 2014). Likewise, a voter who votes for the valence-advantaged House candidate as measured by the candidate valence differential in her district casts a correct “valence vote.” For both differentials, of course, the ideological positions of candidates and their valence characteristics are measured by the aggregated judgments and ratings of expert informants in each district, not by the perceptions of the voters themselves. Following Joesten and Stone (2014), I suggest two types of variables that explain voting correctly: facilitators enhance the probability of a correct vote, but are not themselves decision rules. For example, awareness of the candidates’ ideological positions is frequently thought to be a necessary condition for proximity voting. While awareness of candidates’ positions may strengthen the effect of proximity differentials, it is not an alternative decision rule. Thus, knowing where opposing candidates stand on the liberal-conservative scale is a facilitator of spatially correct voting, but does not predispose the voter to support the more liberal or conservative candidate. Facilitators may be characteristics of individual voters (such as awareness of the candidates’ ideological positions or sophistication), or they may be characteristics of the campaign, such as its visibility or the nature of the office being contested.2 A second type of explanation is offered by proxies or alternative decision rules that predispose voters toward the same choice as the Proximity or Valence Rule, even if the voter is unaware of or indifferent to the cognitive implications of the rule. An example of a proxy for spatial voting is party identification, since a vote cast in response to party, especially in 2

Lau et al. (2008) and Bartels (2008) both speculate that the level of correct voting in presidential elections should be higher than in congressional elections because of the higher visibility of presidential contests.

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a polarized system, frequently results in a spatially correct vote, even if the voter is unaware of the candidates’ ideological positions. This occurs if most Democratic identifiers are liberal and most Republican identifiers are conservative, and candidates in the two parties adopt liberal and conservative positions, respectively. Under these conditions, a Democrat who votes for the Democratic candidate in her district because of party identification (or vice versa for a Republican identifier) would often cast a vote for the more liberal (conservative) candidate because of the alignment of ideology and party in the system. In this example, the proxy decision rule (party identification) produces a voting decision as if the voter were following the Proximity Rule. In the literature on voter decision-making, a heuristic is similar to a proxy because heuristics serve as decision shortcuts that allow voters to approximate the decision they would make if they had more information. Heuristics, in other words, are shortcuts for voters seeking to advance their interests without requiring them to make unrealistic investments in collecting, organizing, and retaining information about the candidates. In the example of party identification as a proxy for spatially correct voting, party identification is a heuristic that voters employ in lieu of bearing the costs associated with gathering and retaining information about candidates’ ideological positions. Although proxy rules and heuristics are similar concepts, I prefer to use “proxy” to avoid an implication of intentionality – voters are not necessarily actively seeking to vote consistent with the Proximity Rule by relying on party identification, although that is one possibility. Voters may decide to identify as Democrats because they are liberal on most policy questions, and they see the Democratic Party as most likely to nominate liberal candidates and pursue liberal policies when in office. It is also possible, however, that voters identify as Democrats for other reasons, including familial socialization and group identification that are not primarily ideological (Green et al. 2002). They may also identify with the party and vote for its candidates because they agree with national party objectives. In such cases, a correct proximity vote may be a byproduct of employing a decision rule like party identification. We are not able to discern whether party identification (or other proxies) are intentional shortcuts to correct voting on proximity or valence, although we will examine the degree to which proxy rules overlap with correct voting on the policy or valence dimensions of choice. Proxies, like heuristics, may also lead voters astray (Kuklinski and Hurley 1994). Because people identify with a political party for myriad reasons, party identification may cause some voters to vote against

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the Proximity or Valence Rules. One well-demonstrated consequence of party identification is that it can act as a “perceptual screen” motivating voters to perceive the political world in ways consistent with their partisan predispositions (Campbell et al. 1960). This may mean that partisans project onto their party’s candidate policy positions or valence characteristics and cause them to vote incorrectly. Other proxies such as incumbency or candidate visibility associated with spending are often seen as distorting voters’ ability to vote consistent with their interests. In sum, the Proximity and Valence Rules are standards that can be used to indicate when voters choose consistent with their fundamental interests. Facilitators and proxy decision rules can help identify the conditions under which voters are likely to vote consistent with their interests, although they cannot resolve the question of intentionality. However, just as the analysis will allow us to see when proxies advance correct voting, we will also be able to observe when they impair correct voting on one dimension or the other. One final point: the analysis of correct voting confronts the problem of cross-pressured voters who cannot vote correctly on both dimensions and who must vote correctly on one. As explained in Chapter 1, aligned voters are in the fortunate position of choosing between candidates, one of which is favored on both valence and ideological proximity. Such voters, of course, may vote correctly or incorrectly, but they are not forced to choose between their interests in policy and valence. Cross-pressured voters, in contrast, face a choice between one candidate who is ideologically closer to their preferences than the other but who is weaker on valence, or vice versa. Cross-pressured voters, therefore, may vote for the candidate who is ideologically more satisfying or who is stronger on valence, but they cannot do both. And, because there are two candidates and two dimensions, cross-pressured voters must vote incorrectly on one dimension and correctly on the other. The only question of interest for such voters is which dimension they choose.

a first look at correct voting In the entire sample, 83.2 percent of voters cast spatially correct votes, whereas 54.6 percent cast correct valence votes.3 Table 5.1 shows that 3

This includes some voters on valence who are missing on the test of proximity voting because they did not respond to the ideological self-identification item (N = 12,591). All voters in contested districts are included in the accounting of correct valence voting (N = 12,817).

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table 5.1 Type of Correct Voting by Whether Voters were Cross-Pressured Full Sample Cross-Pressured Not Cross-Pressured (N = 12,591) (N = 5,966; 47.4%) (N = 6,625; 52.6%) Voted correctly 44.8% Proximity voters only 38.4 Valence voters only 9.9 Voted incorrectly 6.9 100%

NA 79.5% 20.5 NA 100%

86.6% NA NA 13.4 100%

a substantial plurality of the sample voted correctly on both the proximity and valence dimensions; and only about 7 percent of the sample voted incorrectly. In the second column, the sample is restricted to crosspressured voters, which made up 47 percent of the full sample, and among whom proximity voting dominated valence voting by about 4:1. The large margin favoring proximity over valence is consistent with the idea, advanced in Chapter 1, that voters do not weight these two dimensions equally when they vote, although there are other possible explanations.4 The third column shows that among voters not cross-pressured, 87 percent voted correctly and 13 percent voted against their proximity and valence interests. Ideally we might hope that the electoral process would minimize crosspressures, although large percentages of voters are inevitably caught in this way. All voters in a district have the same interest in supporting the valence-advantaged candidate, but substantial proportions of voters in every district will find themselves closer ideologically to the weaker candidate on valence than to the stronger candidate. Candidate incentives may help us understand conditions that increase or mitigate cross pressures. If, consistent with the leeway hypothesis, candidates with valence advantages shirk on policy by taking ideological positions more in keeping with their own preferences or those of select constituencies such as financial contributors, the effect would be to increase the percentage of voters caught between their policy and valence interests. If, in contrast, the alignment hypothesis is correct and in most districts the valence-advantaged candidate is also ideologically closer to the district (i.e., does not shirk on policy relative to the opposition candidate), that would reduce but not eliminate the number of cross-pressured voters. 4

Voters’ choices are likely to reflect candidate differences; thus, since candidates differ much more sharply on ideology than on valence, that may affect how voters respond to being cross-pressured.

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The potential for conflict between proximity and valence interests means that interest-based voting is only partially a matter of the capacity of voters to pursue their interests effectively. No matter how sophisticated, attentive, and engaged in politics an individual is, she cannot vote correctly on both dimensions if she is cross-pressured between her interest in policy and valence. Certainly it is too simple to say that cross-pressured voters who do not make a spatially correct choice are acting against their interests. If we equate correct voting with proximity voting (Boatright 2008; Joesten and Stone 2014) or some other form of issue voting, we assume that voters casting spatially incorrect votes are less sophisticated, when they may be casting correct votes on valence.

facilitators and proxies A facilitator enhances the individual’s chances of casting a proximity or valence vote without prescribing a choice. “Distorting” variables are the flip side of facilitators since they impede the chances of casting a correct vote. Sophistication and awareness of the candidates’ ideological positions condition the effect of the Proximity Rule on voting choice, such that more sophisticated voters and those who correctly perceived the ideological placements of the opposing candidates in their districts were more likely to vote consistent with the Proximity Rule than unsophisticated voters who were unaware of the candidates’ ideological positions. We also saw, however, that even among the unsophisticated and unaware, the Proximity Rule had a powerful impact on voting. Thus, awareness and sophistication appear to be a long way from necessary conditions for proximity voting, even if these variables facilitate higher levels of voting consistent with the spatial model. The distance of the voter from the ideological cut point between the candidates running in her district is a facilitator of proximity and valence voting of particular interest because it can help integrate valence voting with a standard spatial model of voting choice. As discussed in Chapter 1, voters close to the ideological cut point between the candidates should be more prone to casting a valence vote when they are cross-pressured between their valence and policy interests, whereas voters further from the indifference point between the candidates may see their ideological interest in the closer candidate as more compelling. Voters close to the ideological cut point between the opposing candidates running in their district are potential “Stokes voters” in Groseclose’s (2001) model: the return they receive from voting based on the candidate valence differential

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Proportion of Correct Votes .2 .6 .8 .4

Correct Proximity Vote, All Voters

0

Correct Valence Vote, Cross-Pressured Voters

Incorrect Vote, All Voters

0

1 2 3 4 Distance of Voter from Opposing Candidates' Ideological Cut Point

figure 5.1 Correct and Incorrect Voting by Voter Distance from Ideological Cut Point

has the potential to be strong enough to offset the modest policy loss they receive by not supporting the candidate who is (barely) closer to their ideological preferences. Figure 5.1 plots the occurrence of several types of correct voting by the distance of voters from the ideological cut point between the candidates in their district. Among voters cross-pressured between their policy and valence interests, the proportion voting for the stronger candidate on valence drops sharply with distance from the ideological indifference point between the candidates in the district. This is consistent with the idea that voters with a relatively low stake in the ideological difference between the candidates are most likely to cast a valence vote. These are voters who choose the candidate stronger on valence even though, because they are cross-pressured, that means supporting the candidate who is more distant from their ideological preferences. As the distance of the voter from the cut point increases, the rate of valence voting declines markedly because the ideological stakes increase enough to offset an interest in electing the candidate stronger on valence characteristics. Also as expected, proximity voting for the entire sample increases with voters’ distance from the cut point. Cross-pressured voters increase their

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Correct Voting on Proximity and Valence table 5.2 Examples of Proxy Overlap and Correct Voting Party Identification and Proximity Voting Percent of Sample

Proxy and rule overlap 78.5 Absent proxy 9.1 Proxy and rule in conflict 12.3 N 12,477

Incumbency and Valence Voting

Percent Casting Percent of Proximity Vote Sample

Percent Casting Valence Vote

95.4 65.4 19.7 12,477

59.4 43.9 47.7 12,817

62.4 11.8 25.8 12,817

proximity voting as their distance from the candidate cut point increases, but since among cross-pressured individuals the proximity curve is the exact complement of the valence curve, that relationship is not presented in the figure. Notice as well that incorrect voting drops as distance from the cut point declines. Errors occur among non-cross-pressured voters who vote for the candidate who is neither closer to them on ideology nor strongest on valence. Because of the importance of the Proximity Rule in voting choice, it is not surprising that proximity to the cut point is associated with a higher rate of “incorrect” voting. In contrast to facilitators, proxies are alternative decision rules that, if followed, produce a correct vote. Table 5.2 illustrates with two proxy variables: party identification as a proxy for the Proximity Rule, and incumbency as a proxy for valence voting. Party identification is a proxy for spatially correct voting because most Democratic candidates and voters are liberal and most Republicans are conservative. Incumbency is a proxy for valence voting if valence-advantaged candidates tend to win elections. If so, when an incumbent runs for reelection, voters can use incumbency as a proxy for casting a valence vote. In the absence of an incumbent, no such proxy is available and voters must look elsewhere for a cue about the valence differential between the candidates.5 Column 1 of Table 5.2 shows that 78.5 percent of the sample was in a position of “overlap” between party identification and a correct proximity vote in their district. This means that for 78.5 percent of the entire sample their party identification predisposed them to vote in the same direction as the proximity differential in their district. If these voters voted their party identification, they would cast a spatially correct vote. About 5

Experienced challengers may signal weakness in the incumbent (Gordon et al. 2007; Lupia and McCubbins 1998).

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9 percent of the sample were strict independents and thus without party identification as a guide to proximity voting, while 12.3 percent were in conflict between their party identification and proximity differential. Party identification serves as a powerful proxy for the Proximity Rule, as indicated by the second column in Table 5.2. When overlap between party identification and the proximity differential occurs, voters who rely on party identification tend with great regularity to cast proximity votes. As shown in the table, 95 percent of voters in this situation cast spatially correct votes. The rate of proximity voting drops to about 65 percent among strict independents, for whom the party identification proxy is absent. Among voters whose party identification and candidate proximity are in conflict, the rate of voting consistent with the spatial logic plummets to 19.7 percent. By comparison, incumbency is a less reliable proxy for valence voting than party identification is for proximity voting for two reasons. First, there is less overlap between incumbency and valence differentials. Only 62.4 percent of the sample is in the “overlap” cell in which a vote for the incumbent is a vote for the valence-advantaged candidate, while a quarter of the sample is in districts in which a vote for the incumbent is a vote for the weaker candidate on valence. Second, only 59 percent of voters in districts where the incumbent running for reelection was also the stronger candidate on valence voted for the valence-advantaged candidate. In addition, the rate of valence voting among voters for whom the proxy and Valence Rule were in conflict is substantially higher than the rate of proximity voting among voters conflicted between their party identification and ideological proximity.

multivariate analysis of correct voting The analysis of correct voting can be extended to include both facilitators and proxies, while recognizing that a significant proportion of the electorate is cross-pressured between supporting the candidate closer ideologically or stronger on valence. Table 5.3 presents an analysis of spatially correct or proximity voting and combines facilitators and proxies for both correct proximity and valence voting. It is important to see that it is possible to assess correct voting on both dimensions with the dependent variable as correct voting on only one (ideological proximity) because for individuals whose choice is “aligned,” a spatially correct vote is also a correct valence vote. Thus, among aligned voters, a facilitator or proxy variable that increases the probability of a correct vote consistent with the

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table 5.3 Logit Analysis of Proximity Voting among Aligned and Cross-Pressured Voters Cast a Correct Proximity Vote Aligned voters: Sophistication Aware of candidate placements Aware of party placements Distance from candidate cut point Ideological divergence of candidates Voted with party identification Voted with incumbency Cross-pressured voters: Sophistication Aware of candidate placements Aware of party placements Distance from candidate cut point Ideological divergence of candidates Voted with party identification Voted with incumbency Constant Pseudo R-square N Log likelihood ∗

a

0.261∗ (0.12) 0.133 (0.17) 1.584∗∗∗ (0.29) 1.023∗∗∗ (0.13) 0.381∗ (0.17) 0.923∗∗∗ (0.21) 1.514∗∗∗ (0.41) 1.282 (1.06) −0.048 (0.19) 0.457∗ (0.23) −0.838∗ (0.38) 0.171 (0.17) −0.102 (0.26) 1.055∗∗ (0.32) −3.586∗∗∗ (0.75) −3.461∗∗∗ (0.70) 0.341 12207 −3115.9

Effecta +.05 NS +.20 +.17 +.03 +.10 +.14 NS +.03 +.06 +.08 +.23 +.02 +.27 −.21

p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Cell entries are logit coefficients with robust standard errors clustered by district in parentheses below each coefficient. Effects estimated for continuous variables between the 75th and 25th percentiles holding all other covariates at their mean or mode values; design effect included but not shown.

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Proximity Rule has exactly the same effect on correct voting on valence. For voters in this position, to vote correctly on ideological proximity is also to vote correctly on valence, so anything that encourages or discourages correct voting on one has the same effect on the other. The effect among cross-pressured voters is the opposite: a correct proximity vote necessarily implies an incorrect valence vote, and vice versa. Because of this reverse isomorphism, it is possible to observe the effects of the facilitators and proxies in the analysis on correct proximity voting and valence voting, even though the dependent variable is correct proximity voting.6 An example from Table 5.3 will help to illustrate how this is possible. Consider the examples of sophistication and awareness of the candidates’ and parties’ ideological positions. Each of these variables can be considered a facilitator of proximity voting. The more sophisticated an individual voter is, the reasoning goes, the more likely the voter is to understand the stakes involved in ideological conflict and to think ideologically. Awareness of the opposing candidates’ and the parties’ ideological positions facilitates proximity voting by enabling voters to understand the nature of the ideological choices they face. The positive effect of sophistication under the section of the table headed “Aligned voters” indicates that more sophisticated voters are more likely to vote correctly on ideological proximity. The coefficient on sophistication is statistically significant, and the effect estimate indicates a gain in the probability of a correct proximity vote among aligned voters of .05, comparing voters high and low on sophistication. And, because a correct proximity vote among aligned voters also implies a correct valence vote, it is just as true to say that sophistication is associated with higher levels of correct valence voting. Now consider the effects of the same covariates among cross-pressured voters. Notice first that the coefficient on sophistication is negative but not statistically significant. This does not mean that sophistication has no effect on proximity voting among cross-pressured voters. Because the statistical model estimates the effects of each covariate among crosspressured voters with interaction terms, the lack of statistical significance means the slightly weaker effect of sophistication is not significantly different from the positive effect among aligned voters. In fact, sophistication has about the same effect (+.03), increasing proximity voting among cross-pressured voters as it has on aligned voters, under the conditions 6

I am grateful to Matt Buttice for suggesting this approach to the analysis.

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specified in the logit model. The only difference is that among crosspressured voters, sophistication increases the probability of casting a correct proximity vote by .03, while decreasing the probability of casting a correct valence vote by the same amount. The effect of awareness of the ideological placements of parties for aligned and cross-pressured voters is also instructive in interpreting the results in Table 5.3. The effect is strongly positive among aligned voters and significantly less strongly positive among cross-pressured voters (which is why the coefficient among cross-pressured voters is negative). So, whereas awareness of party positions is associated with a .20 increase in casting a spatially correct vote among aligned voters, the significant negative coefficient among cross-pressured voters does not mean the effect is negative. Rather, the effect is positive (+.08) among cross-pressured voters but significantly weaker. In addition to the covariates just discussed, the effects of voting consistent with party identification and incumbency present interesting examples of how proxy variables work differently for aligned and crosspressured voters. Party identification is a proxy for spatially correct voting, and has a stronger effect among cross-pressured voters (+.27) than aligned voters (+.10). The effect of voting consistent with party identification (Figure 5.2(a)) helps explain why party identification as a proxy for spatially correct voting is stronger for cross-pressured than aligned voters. Among aligned voters, the probability of casting a proximity vote is high even for voters whose vote was not consistent with their party identification. This is true because aligned voters who cast a valence vote also vote correctly on proximity. Cross-pressured voters must choose between casting a valence and a proximity vote. As a result, the baseline condition indicates lower levels of proximity voting. The probability of casting a correct proximity vote among cross-pressured voters who voted with their party identification is a bit lower than among aligned voters (.84 vs. .87), although the difference is not statistically significant. The probability of casting a proximity vote among those who did not vote consistent with their party identification is much lower among cross-pressured than aligned voters (.57 vs. .77). Of course, this means the probability of casting a correct valence vote among cross-pressured voters was higher when their vote was not consistent with their party identification (.43) than when their vote reflected their party identification (.16). As is evident in Figure 5.2(b), incumbency works quite differently, depending on whether voters were aligned or cross-pressured. Among aligned voters, voting for the incumbent increased correct voting on both dimensions. If we assume that incumbency is a proxy for valence voting,

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Probability of Correct Proximity Vote .7 .6 .8

.9

(a) Effect of Voting with Party ID

Aligned Voters

.5

Cross-Pressured Voters

0 No

1 Vote Consistent with Party Identification

Yes

Probability of Correct Proximity Vote .7 .6 .8 .9

1

(b) Effect of Voting for Incumbent

Aligned voters

.5

Cross-Pressured Voters

0 No

1

Voted for Incumbent

Yes

figure 5.2 Effects of Party Identification and Incumbency as Proxies on Proximity Voting Note: Estimated from logit equation in Table 5.3.

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this reflects the fact that for aligned voters a correct valence vote also means a correct proximity vote. Since the effect of voting for the incumbent among cross-pressured voters has a negative effect on proximity voting, there is a corresponding increase in correct valence voting. This is an example of an alternative decision rule that is often seen as a distorting factor in congressional election studies, as incumbent visibility and resources appear to cause voters to deviate from their fundamental interests.7 This is a correct inference if we assume that voters are only concerned about policy. Incumbency depresses proximity voting among the large segment of the electorate that is cross-pressured between choosing the better candidate on policy or valence. However, if we see valence as a fundamental interest of voters, incumbency not only loses its status as a distorting factor; it is actually associated with voting on those interests among voters who are aligned as well as among those who are cross-pressured.

conclusion While we cannot specify the absolute level of correct voting that is sufficient to say electoral democracy is working or failing, we can say from the foregoing analysis that voters are not systematically going astray. Indeed, the results suggest that when analysts impose strict information requirements on voters, they probably emphasize the wrong criterion. Awareness of local candidates’ ideological positions in the national electorate is relatively low, but the effect of such awareness is only significant among cross-pressured voters. Awareness of party positions is much higher in the electorate, and the results show that this information has a much greater effect. It is true that awareness of party and candidate positions is linked. When the equation in Table 5.3 is estimated without the party-awareness effect, candidate awareness is associated with modestly higher levels of correct proximity voting (effects of + .03 and an additional + .08 among aligned and cross-pressured voters, respectively). The point here is that the importance of information about individual candidates’ positions is overstated in the literature, while ideological polarization between the parties probably feeds awareness of party positions, which is an important facilitator of spatially correct voting. Various proxies appear to be at work that advance correct voting. When people vote with their party identification in a House race, are 7

Voting with the candidate who spent more on the election has no effect on correct voting, so it does not appear that spending has an independent facilitating or distorting effect on correct voting.

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they seeking to support the candidate closer to them on ideology? When they back the incumbent, are they consciously pursuing their interest in valence returns from the election? Again, we would be remiss to dismiss these possibilities out of hand. Party polarization obviously affects candidate positioning and has had less dramatic but still profound effects on voters’ party identification and awareness of the policy stakes in partisan conflict. As the relationship between ideology and party identification has strengthened, the overlap between partisan and ideological interests in any given election has doubtless increased. Many voters are aware of that overlap. Likewise, incumbency can serve as a proxy for valence, especially if potential challengers refrain from running against incumbents high in leadership valence (Adams et al. 2011; Stone et al. 2004). Challengers who do run may have difficulty attracting support from financial donors and other activists and be lower in visibility as a result. Voters can take a reasonable cue from these patterns that the incumbent is doing a good job and deserves another term. So the evidence in this and the previous chapter supports the working of the Proximity and Valence Rules in voters’ choices. Partisan polarization tends to reinforce proximity voting – there is a modest positive effect of local candidate ideological divergence, in addition to its larger effects on awareness of party positions – but it may undermine valence voting among those who must choose between their interests in policy and valence. When voters’ ideological and valence interests conflict, proximity dominates valence by about 4:1. However, it is a mistake to overlook the importance of valence. As the analysis of incumbency as a proxy for valence voting indicates, we should not assume that the only interest voters have is in candidates who agree with their policy goals. What voters do on Election Day – how their voting choice fits with the fundamental decision rules I have suggested – is but one of the mechanisms by which politicians may be held accountable and representative outcomes are produced from the electoral process. That voters respond to the ideological and valence differences between candidates by pursuing their interests raises the question of whether politicians’ behavior reflects their anticipation of these voter reactions. It also points us toward questions about the relationship between voters’ and politicians’ behavior as it is manifest in the outcomes of elections. These concerns motivate the remaining chapters of this book.

6 Anticipated Reactions and Challenger Entry

Because voters care about valence and policy, politicians must also care. Politicians’ prospects for electoral victory are affected by their fit with the ideological preferences of the electorate and their reputations for leadership valence qualities. Politicians (potential and actual candidates and their activist supporters, including financial contributors) are sensitive to their prospects for success when considering whether to enter a race for a congressional seat. The better their prospects for success, the more likely experienced and skilled politicians are to enter. Politicians anticipate the reactions of their electorates to their candidacies before they decide whether and how to run. Strategic Politician Theory (SPT), developed by Jacobson and Kernell (Jacobson 1989; Jacobson and Kernell 1983), is closely related to the idea of anticipated reactions. SPT emphasizes that politicians are guided by their expectations about how voters are likely to react to their candidacy if they decide to run. If they judge their prospects for winning the election as strong, they run; if they estimate their prospects as not good, they refrain from running. The “quality” of potential candidates is related to their prospects; high-quality candidates generally have stronger prospects than low-quality candidates. Jacobson and Kernell defined “high-quality” candidates as those with previous electoral experience. By this definition, incumbents are high quality because they have won the seat in a prior election. Challengers, which were the focus of SPT, are high quality if they have held elective office prior to running for a seat in Congress. Jacobson and Kernell used SPT to explain how macro-economic patterns of growth and decline could affect congressional elections when 122

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123

there is little evidence that voters react to their perceptions of the state of the national economy when they vote in these elections. Their answer was that politicians, especially potential candidates and their activist supporters, read the tea leaves of the upcoming elections based on the state of the economy during the period when they decide whether or not to enter a race. If the economy is doing well and they are in the president’s party, their party’s prospects are good; if the economy is doing poorly, they anticipate that voters will blame the president with negative repercussions for candidates in his party. As a result, experienced candidates in the president’s party judge their prospects to be poorer, and would hold off running for Congress or pursue other offices or ambitions. Jacobson and Kernell noted a regular aggregate pattern that fits this expectation: when the economy does poorly, experienced, well-funded politicians in the party opposite the president’s disproportionately emerge to run for Congress; when the economy is doing well, the president’s party finds it much easier to recruit a strong cohort of candidates. Because voters are more likely to back challengers who have the resources to mount visible campaigns, the tendency of strong candidates to react to the expected state of the economy creates a link between economic conditions and party fortunes in congressional elections, without voters explicitly choosing between local candidates on the basis of macro-economic performance. There have been refinements and extensions to Jacobson and Kernell’s theory, but out of the box it was built on the idea that in making choices about their political careers, politicians anticipated their electorates’ reactions to factors that would affect their candidacies. One immediate refinement evident in Jacobson’s (1989) own work as well as others (Bianco 1984; Bond et al. 1985) is that strategic politicians estimate their prospects based on district characteristics such as the partisan makeup of the district, as well as national tides. Thus, a strong Democratic potential candidate would think twice about running in a majority-Republican district, anticipating that most voters would be predisposed against his candidacy on partisan and ideological grounds. There is a kind of circularity in SPT. High-quality candidates are more likely to win because of their quality; they enter races where their prospects are good; the data show that high-quality candidates in fact do better in elections than challengers without previous electoral experience. The problem is that it is difficult to know whether they do better in the elections in which they run because of their quality or because they are good at anticipating elections in which they would do well.

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applying strategic politicians theory The argument in this chapter adds another extension to SPT by refining what is meant by a “high-quality” candidate. Jacobson and Kernell were explicit in arguing that the office-holding experience measure captured “high-quality” in the sense that politicians with elected office experience had demonstrated their ability to mount winning campaigns (Jacobson and Kernell 1983, 31): Intuitively, we assume that people who previously managed to get elected to public office at least once should be more effective campaigners than those who have not. They have some experience of (successful) campaigning and wider opportunities for developing skills, contacts, and insights.

Four issues arise in the application of SPT in this chapter: (1) I define “high-quality” candidates as those who are best positioned to appeal to voters’ fundamental interests in policy and leadership valence, rather than prior office-holding experience; (2) why should high-quality candidates as I define them be selective about when to run? (3) How should we measure candidate prospects? And (4) how does the measure employed here help mitigate the circularity problem in SPT? Equating candidate quality with campaign ability is an ambiguous standard because it is unclear how campaign ability relates to the policy and valence interests of voters. Politicians (including House incumbents running for reelection) may have won because they had stronger reputations for leadership valence than their previous opponent, and/or they may have won because they were the candidate closer to their electorate’s policy preferences. Or, they may have won office because they were good fundraisers, had a strong PR firm on their side, or had other resources such as name recognition that their opponent lacked. To be clear, “ambiguous” does not mean “wrong.” Jacobson and Kernell stated that their measure linked quality to campaign ability, but it is possible – even likely – that the ability to attract campaign resources and win elections is related to policy agreement with district electorates and leadership valence. After all, if financial contributors and other activists care about a candidate’s prospects, they should monitor possible candidates’ ability to appeal to their electorates on policy grounds. Moreover, contributors and other activist supporters value leadership valence in the candidates they support for the same reason, and because they have

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an interest themselves in candidates with these characteristics and skills (Stone et al. 2004; Adams et al. 2011).1 So, it is possible that campaign skills, resources, and success are related to policy fit and leadership valence and that prior elective office-holding is a proxy for the qualities that voters intrinsically value in candidates and office-holders. But, because campaign skills and resources are not in themselves of intrinsic interest to voters, we must separate the concepts of leadership and campaign valence. This is all the more essential because of the possibility that campaign resources and skills distort the electoral process in favor of candidates with more resources over those with fewer such resources. This, of course, is the resource-asymmetry hypothesis, which asserts that candidates with more campaign-related resources are able to win elections because of their visibility and capacity to make their case to the voters, even when they are undeserving by more fundamental criteria. In sum, our concept of candidate quality must include leadership valence because, by the Valence Rule, voters seek candidates with these qualities and skills. The definition of a high-quality candidate also depends on the Proximity Rule, since voters seek candidates whose policy commitments are in accord with their own. This is no more than saying that voters seek representation. Since I have defined representation as two-dimensional, a high-quality candidate is one capable of delivering on voters’ interests in policy and valence. The question now is whether in altering the definition of candidate quality we have disturbed the logic of SPT and the hypothesis that high-quality candidates will emerge to run when their prospects for election are good. To answer that question, it helps to review the logic of Jacobson and Kernell’s argument, which is based on a calculus of candidate entry based on Gordon Black’s formulation (Black 1972; Jacobson and Kernell 1983; Rohde 1979): U(O) = p(B) – C. In words, this equation means that the utility of holding an office for a politician is equal to the benefits B associated with the office (status, power, salary, and other perquisites) discounted by the probability of winning the office p, or the politician’s electoral prospects. However, in addition to prospects and benefits, the 1

I do not assume that activists and financial contributors share the policy preferences of the district electorate. Therefore, their concern with the ability of potential candidates to make successful policy appeals rests solely on their interest in backing likely winners. In contrast, their interest in valence rests not only on its effect on a candidate’s prospects, but also on their interest in candidates high in leadership valence, which they share with other constituents.

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equation also includes C, the costs of attaining the office. These costs are primarily associated with overcoming the barriers to mounting a successful campaign, including most especially the ability to attract the necessary financial and other resources (Fulton et al. 2006; Maestas et al. 2006). From this perspective, the Jacobson–Kernell definition of a quality candidate makes perfect sense, since the ability to bear the costs of mounting a campaign is what they were measuring with their officeholding experience measure. It therefore follows that strategic politicians would be selective about bearing those costs, taking them on when their prospects were good and forgoing them when their prospects were poor. The argument in the previous paragraph extends to quality candidates as I define them. Candidates high in leadership valence and ideologically aligned with their electoral constituencies should be in a better position to attract the resources necessary to run a campaign. This is an important reason for believing that the Jacobson–Kernell measure of quality is, in fact, a proxy for quality based on leadership valence and ideological proximity. In addition, we saw evidence in Chapter 5 that voters can reasonably use incumbency as a proxy for correct voting on valence. The conclusion is the same: voters can infer from prior election victories something about a candidate’s quality because prior electorates operated in response to the Proximity and Valence Rules of choice.

measuring candidate prospects Before proceeding to a test of the link between candidate quality and candidates’ strategic anticipation of voters’ reactions, we must consider the question of how to measure candidates’ prospects for electoral success. Ideally, we would like to get into politicians’ heads to understand their perceptions of their electoral prospects and how it is likely to affect their behavior. Doing this was the point of the Candidate Emergence Study (CES), which identified strong potential House candidates well in advance of their decision-making about whether to run for a seat in the House and surveyed them about their perceptions of their chances of winning along with their perceptions of the costs and barriers they would face were they to run for Congress (Stone et al. 2004; Stone and Maisel 2003; Maestas et al. 2006). The advantage of that study was that it was able to identify strong potential House candidates whether or not they eventually decided to run, an advantage I do not have in the current study. Nonetheless, we can follow the CES by relying on district experts

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0

pr(Incumbent Party Wins Election) .6 .2 .4 .8

1

Measuring Candidate Prospects

.5

.6 .7 .8 .9 Informant-Based Measure of Incumbent Reelection Prospects

1

figure 6.1 Informant-Based Estimates of Incumbent Prospects as Predictor of Incumbents’ Party Winning Note: All districts included (N = 155) regardless of whether incumbent actually ran for reelection.

to estimate their incumbents’ electoral prospects well in advance of the 2010 election campaign (Stone et al. 2010a). An advantage of using district informants’ perceptions of incumbent prospects is that it allows us to treat them as proxies for what potential candidates in the district see as their own electoral prospects. To be sure, this is an assumption, because we do not have comparable data about how potential candidates see their prospects, but it is reasonable because district expert informants themselves are well versed in the politics of their district and how well positioned the incumbent is to succeed in getting reelected, if he or she decides to run again. The informant-based measure of incumbent prospects is from the baseline study conducted in July 2009, more than sixteen months before Election Day 2010. As with other informant-based measures, the mean informant rating was calculated after correcting individual informant judgments for partisan bias (see Chapter 2). Figure 6.1 presents the relationship between the informant incumbent-prospects measure and

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table 6.1 Explaining District Informants’ Judgments of Incumbent Prospects Incumbent Prospects Presidential vote share in districta Democratic seat Incumbent party vote 2006 in district Constant Adjusted R-square N ∗∗∗

0.003∗∗∗ (0.00) −0.055∗∗∗ (0.01) 0.002∗∗∗ (0.00) 0.551∗∗∗ (0.04) 0.480 155

p < 0.001.

Cell entries are OLS regression coefficients with standard errors in parentheses below each coefficient. a

Coded to match party of incumbent.

2010 election outcomes, showing a strong relationship between informants’ ratings of incumbent prospects on a pseudo-probability scale as a predictor of the incumbent (or the candidate in the incumbent’s party) winning the election.2 In analysis not shown, there are also strong relationships between incumbent prospects and the vote share incumbents received in 2010, and between expert observers’ judgments of the chances of a strong challenger emerging (in the party opposite the incumbent), and the appearance of an experienced challenger. The strength of these relationships suggests that expert informants understand the strategic environment of their district. Table 6.1 provides additional evidence supporting the incumbentprospects measure by explaining informant ratings using three standard indicators of incumbent reelection chances: the mean presidential vote share in the district (coded to reflect the party of the incumbent) to capture 2

The questionnaire item is a seven-point scale ranging from “extremely unlikely” (coded .01) through “tossup” (.50) to “extremely likely” (.99). I do not treat these scores as actual probabilities, but as indicators of the comparative prospects of incumbents across districts. I include all districts in the sample because of uncertainty about whether the incumbent would actually run. The mean prospects score was .814, indicating a high degree of confidence in the incumbent’s reelection prospects (s.d. = .096). The incumbent with the highest prospects had a score of .985 (Mike Simpson, R ID02); the lowest prospects rating was .537 (Glenn Nye, D VA02).

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the partisan makeup of the district; the party holding the seat to indicate possible effects of a partisan tide; and the incumbent’s party vote in the district in the previous midterm elections. It is apparent that informants were responsive to the partisan makeup in the district and to the electoral performance of the incumbent-party candidate in the previous midterm election when they estimated incumbent prospects. In addition, district informants anticipated the “shellacking” of House Democrats that President Obama lamented the day after the election, as the electoral prospects of incumbents in Democratic seats were expected to drop by about .05, independent of past performance and the partisan makeup of the district. Although the prospects measure is targeted at incumbents, the class of politicians of greatest interest in this chapter is challengers. This means what we really need is a measure of challengers’ prospects, rather than incumbents’ reelection chances. This is not as severe a problem as it may first appear. In a two-party system, a serviceable measure of potential challengers’ election prospects is 1-(incumbent prospects). This is admittedly not a precise measure of each individual potential challenger’s election prospects, since the popular mayor of the major city in the district probably has better chances than a city councilperson from a smaller city in the district no matter what the incumbent does. Thus, any individual potential candidates’ prospect of election is not the exact complement of the incumbent’s chances of winning, since informants were not asked to compare the incumbent with every possible challenger. That would have been impossible, since neither I as the designer of the informant survey nor the informants themselves knew who the challengers were at the time of the baseline survey. Indeed, the point of the baseline survey was to measure incumbent prospects in the district before possible challengers announced their intentions about running. Despite these issues, the complement of incumbent prospects is a serviceable measure of the challenger’s chances because it measures the electoral strength of the most formidable obstacle facing most potential challengers. It certainly is true that the stronger the incumbent’s chances of reelection, the weaker any given potential challenger’s chances.3

3

As we have seen, incumbent prospects are not necessarily only or primarily a result of characteristics of the individual incumbent. For example, the partisan makeup of the district and the prospect of a national partisan tide come heavily into play, affecting both incumbent and potential challenger prospects.

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table 6.2 Strategic Behavior in the 2010 House Elections (mean prospects ratings by district experts) Incumbent Reelection Prospects

Percent experienced challengersa Challenger spending ($100,000)a Incumbent spending ($100,000)a Percent incumbents ran for reelectionc a b c

Low (.70)

Medium High (.83) (.91)

Correlationb

53.5 $1778 $2847 84.6

23.8 $709 $1420 84.6

−.48 −.59 −.58 .10(NS)

2.1 $140 $1033 96.1

Limited to districts where incumbent was challenged and ran for reelection (N = 132). Correlation based on ungrouped incumbent prospects measure. Includes all districts (N = 155).

exploring the relationship between prospects and candidate quality Table 6.2 presents evidence relating to standard indicators used to test SPT in House elections by examining districts grouped on incumbent prospects. Except as noted, the districts included in this analysis are limited to those in which an incumbent ran for reelection and a candidate emerged to challenge the incumbent. Challengers with office-holding experience were more likely to run in districts where the incumbent’s prospects were estimated to be relatively low just as they were able to raise more money in districts where the incumbent was more vulnerable. These two findings are consistent with the literature showing that experienced challengers capable of attracting the resources necessary to run a campaign are strategic in their behavior. They are more likely to run when their prospects are good, and they are better able to raise money from various sources, all of whom are strategic in desiring to support candidates with good prospects. On the incumbent side, the pattern of fundraising is also familiar: vulnerable incumbents have powerful incentives to raise more money than incumbents who expect to win reelection easily (Jacobson 1980). There is only a slight (insignificant) relationship between prospects and incumbents choosing to run for reelection, indicating little or no evidence of strategic retirement in 2010. Table 6.3 presents valence indicators measured in the campaignwave informant survey conducted in October 2010. These measures are designed to distinguish between skills related to fundraising and running

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table 6.3 Campaign and Leadership Valence by Incumbent Prospectsa Incumbent Prospects Low

Medium High

Correlationb

Campaign Valence: Challenger mean campaign valence Incumbent-challenger campaign valence differential

.47 .37

−.26 1.31

−.77 1.95

−.70 .69

Leadership Valence: Challenger mean leadership valence Incumbent-challenger leadership valence differential

.27 .11

.16 .32

.06 .46

−.24 .22

a b

Restricted to districts in which incumbent ran for reelection and was challenged (N = 132). Incumbent prospects grouping identical to Table 6.2. Correlation based on ungrouped prospects measure.

a campaign, and skills and traits that are intrinsically valued by voters (“campaign” vs. “leadership” valence). Because identical batteries of questions were asked of informants about both candidates running in each district, incumbent and challenger valence measures are comparable, and candidate differentials can be calculated. The campaign-valence results mirror the standard indicators in Table 6.2. Strong candidates run in districts where the opportunity is relatively good, while the challengers who eventually run in districts expected to be easily held by the incumbent tend to be much weaker in campaign skills and resources. The differential strength of incumbents relative to challengers reflects the tendency of safe incumbents to be opposed by weak challengers. The effects of prospects on challengers’ leadership valence and on the differential between incumbents and challengers are also apparent though weaker than campaign-valence effects. This is the first evidence of strategic behavior by candidates linked to the skills and character of candidates that are intrinsically valued by voters, as opposed to skills and resources that help them get elected.4 It is preliminary evidence that anticipated reactions by strategic politicians help explain a pattern of valence representation in the US House. 4

Several studies have found patterns consistent with these results. Mondak (1995) showed that incumbents rated high on descriptors in the Almanac of American Politics linked to incumbents’ reputations for competence and integrity were less likely to be challenged by experienced, well-funded challengers. Stone, Maisel, and Maestas (2004) found that strong challengers were deterred from running against incumbents strong in leadership valence, over and above their reluctance based purely on electoral grounds.

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The effects of prospects on valence also mean that the choice on valence grounds between incumbents and challengers is clearer for voters in districts where the incumbent’s prospects are strong than in districts where the incumbent is more vulnerable. As we have seen in Chapter 5, incumbency is a proxy for correct voting on valence. The results here suggest an anticipated-reactions mechanism at work: because challengers strong on valence refrain from running when incumbent prospects are good (and their own prospects are poor), the valence differential between incumbents and challengers is greatest in districts safe for the incumbent. We turn next to a parallel analysis of candidate positioning. Most of the literature on candidate positioning examines only the positioning of the incumbent because roll-call based measures are available for incumbents but not challengers (cf. Ansolabehere et al. 2001). Examining only the ideological positions of incumbents fails to address fundamental questions about district representation for three reasons: it compares the positioning of incumbents relative to other incumbents rather than to the positions of the districts that elected them, it does not compare the positioning of the incumbent to the positioning of the challenger, and it does not entertain the possible relationship between candidate valence and positioning.5 Because of this confusion in the literature, I present incumbent as well as challenger extremism and proximity scores. Table 6.4 compares the ideological extremism and ideological distance of incumbents and challengers from their districts and partisan constituencies within their districts. Inferences based on measures of ideological extremism can lead to inappropriate conclusions. The extremism results in Table 6.4 support skeptics who argue that electoral safety encourages incumbents to shirk in their position-taking (Burden 2004). Since most incumbents are not in electoral jeopardy, it is disturbing to see that incumbents are more ideologically extreme as their prospects for reelection improve. The correlation summarizing this relationship is quite strong and highly significant. In contrast, challengers become less extreme in their ideological position-taking as incumbent’s prospects improve (and therefore as theirs decline). If we stop here, trusting that extremism on the ideological scale is the correct measure, we could conclude that incumbents are less representative as they are electorally more secure, and the challengers who would replace them are more representative as their 5

There are exceptions and work-arounds to the first two problems; there are virtually no examples of work that directly compare the effects of valence and positioning relative to the district (Stone and Simas 2010; Adams et al. 2011; Buttice and Stone 2012).

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table 6.4 Candidate Extremism and Proximity to District by Incumbent Prospectsa Incumbent Prospects

Ideological Extremism: Incumbent mean extremism Challenger mean extremism

Low

Medium High

Correlationb

1.38 2.09

1.81 1.78

2.09 1.67

.46 −.36

1.70 1.89 −.19

1.72 2.03 −.31

.06 (NS) .22 −.07 (NS)

Ideological Distance from District Preference: Incumbent distance from district 1.60 Challenger distance from district 1.86 Incumbent-challenger distance −.26 differentialc a b c

Restricted to districts in which incumbent ran for reelection and was challenged (N = 132). Incumbent prospects grouping identical to Table 6.1. Correlation based on ungrouped prospects measure. Negative scores indicate that the incumbent is closer than the challenger to the district’s preferences.

chances decline. This could support cynicism about politicians who are experienced and relatively viable, since incumbents fall into that category as do experienced challengers. Judging from the challenger-extremism results, it is “citizen politicians” who lack experience and do not play the “money game” who are hopelessly outgunned by incumbents but who would be more representative in the unlikely event they could get elected. The problem with extremism measures is that they are disconnected from district preferences. They assume that candidates more extreme than other candidates, or more extreme than a neutral or moderate position (such as zero on the Nominate or the mid-point of the liberalconservative scale), are, by virtue of their extremism, out of step with their districts. Alternatively, they assume that all districts are at the moderate/zero point on the scale. Neither assumption is warranted. Districts vary substantially in where they fall on the liberal-conservative scale. This means that candidates who are more extreme in an absolute sense are not necessarily more extreme relative to district preferences than candidates who are more moderate (i.e., closer to the mid-point of the ideological scale). With measures of candidates’ and districts’ positions on the same ideological scale, it is possible to compute distances between each candidate running in the district and the mean ideological preferences of citizens in the district. Thus, although there is a relationship between prospects

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Anticipated Reactions and Challenger Entry

and extremity, there is no relationship between incumbents’ reelection prospects and their mean distance from their districts’ ideological preferences. Among challengers, in contrast, there is a relationship consistent with SPT: as challenger’s prospects of election decline (as incumbents’ prospects improve), challengers are on average more distant from their districts’ opinion. This is in marked contrast to the extremism finding, which went in the opposite direction. Thus, although challengers are less extreme ideologically as incumbents’ prospects improve, they are actually more distant from their districts as incumbent prospects increase. What might explain these patterns? Candidates’ prospects are sensitive to the partisan makeup of their district, such that candidates whose chances are excellent (or poor) tend to be in districts that are strongly predisposed for (or against) their candidacy. Such districts also tend to be relatively extreme in their ideological preferences. Thus, incumbents from districts dominated by one party have better election prospects and incentives to be more extreme in response to district opinion. Challengers, in response to this logic, are more moderate as incumbent prospects improve because they are running in districts that are increasingly dominated by the opposite party. As a result, they have incentives to moderate their position. However, the data in Table 6.4 show that although challengers moderate as their prospects decline, they are actually more distant from their districts’ preferences. This is consistent with SPT because challengers are closest to their districts’ ideological preferences when their prospects are best (when incumbents are most vulnerable).

conclusion In this chapter we have seen preliminary evidence consistent with the idea that the strategic calculations politicians make anticipating the reactions of their electorates to their candidacy affect the quality of the candidates who run. In contrast to SPT, I use the term “candidate quality” to refer to traits, characteristics, skills, and ideological positions that align with electorates’ interests, rather than the narrower definition of quality as the skills and resources to win elections. While there is clear evidence consistent with SPT that campaign skills and resources relate to candidates’ election prospects, there is also a tendency for quality in the deeper sense to be associated with prospects. Challengers’ leadership valence improves as their prospects improve (as incumbents’ prospects decline). Although it is true as others have observed that incumbents are more extreme and challengers more moderate as incumbents’ prospects improve, it is not

Conclusion

135

appropriate to conclude that incumbents shirk on policy as their prospects improve, or that challengers in districts where incumbents are less vulnerable would be more representative of their districts’ ideological positions. Instead, challengers are less representative of districts’ interests as their prospects decline, while incumbents are not significantly different in their ideological representation as their reelection prospects improve. A question addressed in the next chapter is how anticipated reactions affect election outcomes. The strategic calculations that politicians respond to are one important way that electorates may exert control; a second is what voters do on Election Day. The circularity at work in democratic politics means that these mechanisms may be difficult to tease out of the data. This chapter provides a start, but the analysis is extended in the next to estimate the weight of these mechanisms in explaining election vote shares.

7 The Proximity and Valence Rules in District Voting

While it may be interesting to think about how voters choose between competing candidates, it will not add up to much if there is no connection between how voters decide and important political outcomes such as who wins elections, whether the “better” candidate tends to win, and how well candidates reflect their electorates’ interests. These outcomes of interest fall under the broad rubric of political representation, a complex, multidimensional concept. In keeping with the theme of this book, I limit the concept to outcomes of elections consistent with the Proximity and Valence Rules. This chapter focuses on demonstrating that proximity and valence differentials affect the vote shares candidates attract in elections. The chapter begins with analysis in close parallel to the discussion of voting choice in Chapter 4, which dealt with the impact of candidate differentials on individual voting choice. The discussion then moves to assessing two mechanisms that may account for the effects of proximity and valence differentials: anticipated reactions by strategic politicians concerned that they must respond to voters’ ideological and valence interests in order to win votes, and the reactions of voters on Election Day to the candidate differences on each dimension. Chapters 8 and 9 assess representative outcomes by evaluating the degree to which ideological and valence outcomes from elections reflect the fundamental interests of the electorates to which candidates appeal. The Proximity Rule at the district level is based on the Median Voter Theorem: district support for a candidate increases as the candidate’s proximity advantage relative to the median voter in the electorate over her opponent increases. If we substitute the preferences of the median 136

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137

voter in the district (Xj ) for the preferences of the individual voter in the Proximity Rule defined in Chapter 1 (xij ), we have the expression for the Proximity Rule at the level of the district electorate: |Xj − Lj | − | Xj − Cj |. The empirical referent for the Proximity Rule is the district proximity differential, where comparisons between candidates are relative to their district electorate’s ideology (as measured by the mean ideological preference of the district electorate). Thus, in parallel to expectations at the individual level, when the liberal candidate is closer to district preferences than the conservative candidate, the expression is negative and the liberal should win more votes. As the relative distance increasingly favors the liberal (the expression becomes increasingly negative), the liberal candidate’s vote share increases. Of course, as the expression is more positive, this means the conservative candidate is closer than the liberal, and the conservative candidate’s vote share increases. The Valence Rule is a district-level variable in individual voter choice as well as vote-share analysis, so the Valence Rule is represented in the district analysis as the valence differential. As in the analysis of individual voting choice in Chapter 4, we examine a “Fundamentals” model predicting the Republican candidates’ district vote share based only on proximity and valence and district demographic characteristics;1 a “Standard” model using a conventional set of predictors that do not include the candidate differentials in the Fundamentals model; and a “Combined” model. The Standard and Combined models include the mean Republican presidential two-party vote share in the district in the two presidential elections previous to 2010, and the Republican vote share in the previous mid-term election (2006). In addition, both models include experience and spending differentials. Three conclusions are apparent from comparing the regression equations in Table 7.1: first, the effects of the proximity and valence differentials are significant both in the Fundamentals model and in the Combined analysis that also includes the standard covariates; second, the effects of the proximity and valence differentials are substantially attenuated in the Combined compared with the Fundamentals model; and third, the explanatory power of the models (as evidenced by the adjusted Rsquares) increases from the Fundamental to the Standard model, with a small increase in the Combined compared with the Standard model. 1

District demographic variables are all based on 2009 census estimates: percent Black, percent Latino, median household income, and percent of district population that graduated from high school.

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138

table 7.1 Regressions of District Republican Vote Share, 2010 Fundamentals Model District proximity differential Valence differential

3.082$ (1.58) 6.432∗∗∗ (1.41)

Republican district presidential vote Republican district vote 2006 Democratic seat Experience differential Spending differential Open seat Constant Adjusted R-square N

86.508∗∗∗ (23.17) 0.475 150

Standard Model

Combined Model

0.625∗∗∗ (0.05) 0.051 (0.03) 1.930 (1.88) 2.186∗∗∗ (0.57) 1.698∗∗∗ (0.32) −1.631 (1.15) 16.336 (9.57) 0.932 150

1.378∗∗ (0.52) 2.555∗∗∗ (0.53) 0.704∗∗∗ (0.05) 0.044 (0.03) 0.627 (1.69) 1.313∗ (0.53) 1.253∗∗∗ (0.30) −0.229 (1.05) 12.243 (8.56) 0.946 150

$ p = 0.05, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Cell entries are OLS regression coefficients with standard errors in parentheses below each coefficient. Note: District demographic and design variables included but not reported.

As noted, the effects of the proximity and valence differentials, while significant, are attenuated in the Combined model. In the Fundamentals model, for instance, the effect of variation in proximity from districts in which the Democratic candidate was much closer to the district median than the Republican (−1.5 on the proximity differential scale) to districts in which the Republican was much the closer candidate (+1.5) amounted to about a 10 percentage point gain in expected vote for the Republican candidate. In the Combined model, the effect over the same range is reduced to a 4 percentage point gain in Republican vote share. The magnitude of the valence effect is also reduced from 19 points in the Fundamentals model over the −1.5 to +1.5 range in valence differentials to an 8 percentage point Republican gain in the Combined model. These comparisons suggest that the proximity and valence differentials have robust

Explaining Proximity and Valence Effects

139

effects, but that their simple effects on vote share are mediated by covariates included in the Standard model.

explaining proximity and valence effects The differences among the three models in Table 7.1 provide an opportunity to explore two mechanisms critical to how the electoral process works. In the previous chapter we saw evidence that anticipated reactions could encourage high-quality challengers to run. That analysis can be extended to address the degree to which the proximity and valence effects on vote share can be explained by anticipated reactions, and how much results from voters’ responses to the candidates on Election Day. The logic behind a test of anticipated reactions by strategic politicians as the mechanism explaining the proximity and valence differentials in the Fundamentals model is straightforward. If candidates react to cues from district electorates in ways that reflect fundamental voter interests, the effects of the proximity and valence differentials in the Fundamentals model should be reduced when we include in the analysis variables that account for politicians’ estimates of their electoral prospects. We know from Chapter 6 that politicians’ electoral prospects are affected by the party makeup of the district and the party holding the seat. These are readily apparent indicators of the structure of opportunity in the district. We also have the informant-based estimates of incumbent prospects, which can serve as proxies for candidates’ own perceptions of their electoral chances. If these variables, when added to the Fundamentals model, reduce the effect of the proximity and valence differentials, a possible reason is anticipated reactions. These three variables – district partisan makeup, the party holding the seat, and incumbent prospects measured in the summer of 2009 – predate the campaign, and they are apparent to politicians as they consider whether to run and how to shape their campaigns. If the entire effect of valence differentials is accounted for by the factors structuring politicians’ estimates of their chances (the effect of the valence differential goes to zero when partisan makeup, party holding the seat, and prospects are added to the Fundamentals model), we would conclude that anticipated reactions explain all of the observed effect of the valence differential. If these variables have no effect on the magnitude of the coefficient on the valence differential when they are added to the Fundamentals model, we would conclude that anticipated reactions do not explain the effect. The same logic applies to the proximity differential.

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The Proximity and Valence Rules in District Voting

table 7.2 Explaining the Effects of Proximity and Valence on Republican Vote Share Fundamentals Model Model 2 District proximity differential Reduction in Effecta Valence differential Reduction in Effecta Repub. district presidential vote share Republican incumbent

3.960∗ (1.70) – 7.001∗∗∗ (1.50) –

Republican candidate’s prospects Experience differential

Model 3

1.802∗∗ 1.853∗∗ (0.57) (0.55) 54% 53% 3.096∗∗∗ 2.463∗∗∗ (0.56) (0.58) 56% 65% 0.757∗∗∗ 0.850∗∗∗ (0.04) (0.05) 7.226∗∗∗ −1.153 (1.05) (2.83) 15.761∗∗ (4.97)

Spending differential Constant Adjusted R-square N

78.093∗∗ (25.23) 0.512 132

−0.721 (9.01) 0.946 132

0.755 (8.70) 0.949 132

Model 4 1.836∗∗∗ (0.52) 54% 2.039∗∗∗ (0.55) 71% 0.665∗∗∗ (0.05) −3.544 (3.30) 10.586∗ (4.90) 0.591 (0.80) 1.364∗∗∗ (0.31) 10.130 (8.52) 0.956 132

∗

p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Compared with Fundamentals model. Note: District demographic and design variables included but not reported. Analysis restricted to districts in which incumbents ran for reelection. Cell entries are OLS regression coefficients with standard errors in parentheses below each coefficient. a

Table 7.2 presents the necessary comparisons with the Fundamentals model to assess the effects of anticipated reactions, as just described.2 The effects of the proximity and valence differentials are slightly stronger in the Fundamentals model when the analysis is restricted to incumbents running for reelection. Equation [2] adds two covariates from the Standard model of vote share that describe the partisan structure of opportunity in the district: the vote for Republican presidents in the district and the party holding the seat.3 The greater the support was for 2 3

This analysis is limited to districts in which incumbents ran for reelection in 2010, so the sample is a subset of the cases included in Table 7.1. I exclude 2006 Republican vote share (which was included in Table 7.1) because it is a mix of partisanship and factors linked to the incumbent, especially in districts where the same incumbent ran in 2006 and 2010.

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141

Republican presidential candidates in the district, the more favorable the partisan makeup of the district to Republican candidates and the higher the vote share ultimately realized by Republican candidates. Republican incumbents running for reelection also had a partisan structural advantage based on the pro-Republican tide in 2010. Including the district partisan structure variables has dramatic effects compared with the Fundamentals model: their presence reduces the magnitude of the proximity and valence differentials effects by 54 percent and 56 percent, respectively, and the R2 increases substantially. I delay most of the discussion of the implications of the increased variance explained when party variables are included in vote share analysis to an in-depth treatment of party effects in the next chapter. District partisan structure, when added to the Fundamentals model, hints at how anticipated reactions may explain much of the effect of proximity and valence differentials. When there is partisan imbalance in the district, challengers and would-be challengers from the opposing party face poor prospects of unseating the incumbent. The district partisan structure also conveys information about district ideological preferences, especially in a polarized party system. Thus, a majority-Republican district is likely to be conservative, whereas a majority-Democratic district is typically more liberal. Thus, candidates and potential candidates may reasonably draw conclusions about district ideological preferences and base their decisions about whether and how to run based on these inferences. Liberal potential candidates in a strongly Republican district know they face an uphill battle if they enter, just as surely as conservative potential candidates in a majority-Republican district know their ideology is closely aligned with district preferences. However, it is also possible that partisan affinity between candidates and districts produces ideological proximity without any conscious process of anticipation or assessment by candidates. Candidates and constituents may affiliate with parties for their own reasons and act in ways (such as voting or taking issue stands) that are consistent with others in the same party. Rather than providing candidates with an important basis for anticipated reactions by strategic politicians seeking to align themselves with district preferences, the overlap between party and ideology may facilitate a connection between the ideological preferences of districts and candidates without the agency of anticipated reactions. An important reason for doubting that the mediating effect of partisan structure is due to simple overlap between district and candidates’

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ideological positions is how strongly district partisan structure mediates the effect of the valence differential as well. The reduction in the coefficient on valence differentials is as great as it is for the proximity differentials, yet candidate valence advantage is not explained by overlap between valence and partisanship. Strategic politicians respond to their prospects when they decide to run; candidates with strong reputations for leadership valence are more likely to run when their prospects are good. A favorable partisan context thus encourages high-valence candidates to run. The equation in column (3) adds Republican candidates’ prospects.4 This model takes account of anticipated reactions by candidates, not only in response to the partisan structure of the district, but to any other factors exogenous to the campaign that affected informants’ (and, by assumption, candidates’) perceptions of prospects sixteen months before Election Day. The coefficient on the proximity differential is unaffected when the prospects variable is included, but the effect of the valence differential is further reduced. This is additional evidence that anticipated reactions help explain the entry of candidates highly rated for their leadership valence. Finally, Equation [4] presents a version of the combined model that adds two candidate resource measures relevant to the conduct of the campaign: spending and experience differentials. When one candidate has an advantage in spending, that should relate to higher visibility and name recognition; candidates with more elective-office experience should be better able to conduct effective campaigns. Of course, these differentials are also the result of anticipated reactions, as experienced challengers enter races and receive more financial support when their prospects are good. Adding these variables to Equation [3] further reduces the impact of the candidate valence differential, with no additional reduction in the impact of relative proximity. It is obvious by the decline in both effects when district partisan structure is included in the analysis that the partisan makeup of the district and the Republican tide in 2010 mediate the effects of proximity and valence. For reasons explored below, almost all of the reduction in proximity and valence in Equation [3] relative to the Fundamental model can be attributed to anticipated reactions. Looking still at Equation [4], this leaves about 47 percent of the original effect of proximity and 35 percent of the valence effect unexplained by anticipated reactions. Candidate spending is endogenous to the campaign and, as will be clear, is affected by partisan structure and prospects. It may have an 4

Republican prospects = incumbent prospects when the seat was held in 2009 by a Republican and (1-incumbent prospects) when the seat was held by a Democrat.

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143

independent effect on vote share for two reasons: it may be a proxy for the Valence Rule since candidates with a valence advantage should attract support from contributors for the same reason they attract voters’ backing; and it may give advantaged candidates the edge in visibility that increases their support because of the resource advantage financial backing confers. The fact that the spending differential has a significant impact on vote share independent of partisan structure, prospects, and the proximity and valence differentials suggests it imparts additional advantages in visibility, vigor, and other consequences for advantaged candidates’ campaigns. However, the additional reduction in the impact of valence (to 71 percent relative to its effect in the fundamentals model) suggests that spending differentials also overlap with – or serve as proxies for – candidate valence differentials. Because the Combined model (Model 4) accounts for 54 percent of the original effect of proximity in the Fundamentals model and 71 percent of the effect of valence, 46 percent and 29 percent of the original effects of proximity and valence, respectively, are unaccounted for by party, prospects, and candidate spending. Subject to the assumption that there are no omitted variables of consequence in the analysis, the remaining effects of proximity and valence on vote share can be attributed to voters’ choices on Election Day. This assumption, of course, is probably not strictly accurate, although Equation [4] explains almost 96 percent of the variance in vote share, and we have seen ample evidence that voters’ Election Day choices are affected by the proximity and valence differentials. The results are consistent with the claim that while party, candidate, and campaign effects are important, voters actively enforce their fundamental interests in the electoral process over and above the effects of anticipated reactions by strategic politicians. Table 7.3 provides additional support for the importance of anticipated reactions. This conclusion hinges on the assumption that candidates, potential candidates, and financial contributors shared district informants’ perceptions of Republican candidate prospects. Based on this assumption, it is striking how much politicians saw candidate prospects in districts where incumbents ran for reelection as driven by partisan factors. The second equation in Table 7.3 shows that candidate spending differentials are also responsive to anticipated reactions, as both partisan structure and prospects affect which candidate attracts more financial support. In short, prospects are highly sensitive to the partisan structure of opportunity in the district, and candidate spending is sensitive to prospects. Anticipated reactions in the form of strategic calculations by candidates and activists strongly shape prospects and resources, which in

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The Proximity and Valence Rules in District Voting table 7.3 Prospects and Anticipated Reactions in 2010 Republican Candidate Prospects

Republican presidential vote in district Republican incumbent Republican candidate prospects Constant Adjusted R-square N

.006∗∗∗ (.001) .567∗∗∗ (.017) – −.112 (.166) .950 132

Candidate Spending Differential .056∗∗∗ (.012) .451 (.758) 4.105∗∗∗ (1.268) −5.792∗∗∗ (2.340) .816 132

Note: Restricted to districts in which incumbents ran for reelection. Design and district demographic variables included but not reported. Cell entries are OLS regression coefficients with standard errors in parentheses below each coefficient.

turn affect outcomes. That these variables also heavily mediate the effects of proximity and valence differentials is evidence for the effects of anticipated reactions as a mechanism for advancing the electorate’s fundamental interests.

the effect of candidate spending Candidate spending differentials, along with incumbency and the associated experience differential, are indicators of resource asymmetries that may distort voting and election outcomes. The analysis in Table 7.2 focuses on incumbents running for reelection, and reports (Model 4) a significant effect of spending differentials. This effect, while it may be partially understood as a proxy for valence, certainly raises the possibility that spending differentials have a distortionary effect. Simple differences between incumbents’ and challengers’ spending levels, and between winners’ and losers’ spending, are often cited in popular discussions as evidence that congressional election results are explained by candidates’ asymmetric financial resources. To take one example of this sort of analysis from the districts in this study, incumbents who won reelection in 2010 spent almost nine times more than the challengers they defeated, whereas challengers who managed to unseat incumbents outspent them by about 1.6:1.5 5

Comparisons are based on median spending levels.

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table 7.4 Assessing Effects of Spending Differential on Republican Vote Share

Spending differential Effect on vote sharea Reduction in Effectb Republican candidate prospects Republican presidential vote share in district Republican incumbent Constant Adjusted R-square N

Design Control Only

Demographics and Design Controls

6.137∗∗∗ (0.28) 28% –

5.346∗∗∗ (0.27) 24% 13%

3.428∗∗∗ (0.49) 15% 44% 15.803∗∗∗ (3.51)

47.842∗∗∗ (0.81) 0.794 132

63.289∗∗∗ (14.12) 0.845 132

57.200∗∗∗ (13.21) 0.866 132

Plus Prospects

Plus District Party 1.646∗∗∗ (0.35) 7% 73% 17.626∗∗∗ (5.10) 0.594∗∗∗ (0.05) −3.694 (2.93) 9.373 (9.27) 0.944 132

∗

p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Note: District demographic and design variables included but not reported. Analysis restricted to districts in which incumbents ran for reelection. Cell entries are OLS regression coefficients with standard errors in parentheses below each coefficient. a Effect estimates based on comparing races +/− one standard deviation in logged spending differential. b Compared with Design Control model.

Political scientists reject a simplistic link between spending and votes, mostly on grounds consistent with Strategic Politician Theory: financial backing is more readily available to candidates who have good electoral prospects than it is to candidates whose electoral prospects are poor. Because contributors respond to prospects (as shown in Table 7.3), the correlation between spending advantage and vote share may reflect candidate prospects, including the advantages of a favorable partisan makeup in the district, as much or more than it reflects the effect of spending advantages on electoral outcomes. Table 7.4 provides several regression models of Republican vote share, beginning with the simple relationship between spending advantages and vote share (“Design Control Only”), introducing increasingly complete controls for other variables that may drive the relationship. Note the reduced effect of spending associated with the imposition of controls. Introducing prospects reduces the effect of spending differentials by 44 percent compared with the simple model; including prospects and the

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The Proximity and Valence Rules in District Voting

partisan structure of the district reduces the effect of spending on vote share by almost three-quarters. The analysis in Table 7.4 does not eliminate the possibility that the resource-asymmetry hypothesis is a distorting factor in congressional elections, but it does provide a more realistic estimate of its effect independent of the strategic calculations affecting the behavior of financial contributors. The independent explanatory effect of spending differentials is greatly reduced once these factors are taken into account, although it is not eliminated. This is consistent with the claim that spending in these elections was due to strategic anticipation of the outcome, as opposed to independently determining the outcome. On the evidence so far, the impact of resource advantages in House elections is usually vastly overstated. It remains to be seen what direct evidence can be marshalled to support the effect of spending on representative outcomes as distinct from vote share, a question taken up in Chapter 9.

conclusion The jump in the R-squared when district partisan structure is added to the Fundamentals model in Tables 7.1 and 7.2 is a rather large hint about the importance of party over and above the proximity and valence differentials. Thus, although it is true that partisan structure accounts for much of the effect of the proximity and valence rules, it also accounts for much more: party strongly affects vote share independent of proximity and valence effects. As will be clear in the next chapter, this has profound consequences for the pattern of ideological representation in Congress, which cannot be fully explained by the spatial logic. Despite the obvious importance of party in the system, we have seen consistent evidence of proximity and valence effects on election outcomes, with support for anticipated reactions and voter choices as mechanisms that explain the impact of voters’ fundamental interests on elections. As demonstrated in the next chapter, partisan polarization shifts district ideological representation toward the partisan model, although district median-voter effects persist and must be accommodated in any understanding of ideological position-taking by candidates and office holders. District electoral outcomes, in other words, are affected by partisan factors as well as by the spatial logic captured by the proximity differential.

8 District Ideological Representation

The concept of representation in this book is based on the idea that representative outcomes are consistent with the interests of electorates in policy and in having in office individuals of the highest leadership quality. The policy dimension of representation is captured by the ideological fit between the district and candidates or officeholders. The proximity differential, applied to the explanation of candidates’ vote shares in Chapter 7, expresses a concept of ideological representation: by the spatial logic, the candidate closer to the district electorate’s ideological preferences should win more votes than the candidate more distant from those preferences. The focus of this chapter is on ideological representation; the next chapter extends the discussion of ideology and includes the valence dimension of representation. There is an extensive literature on district ideological representation to which this chapter relates. A good deal of the analysis in this chapter is consistent with that literature, especially with work focusing on the period since the 1990s when ideological polarization between the parties took hold (Ansolabehere et al. 2001; Burden 2004; Clinton 2006). Despite the well-developed character of this literature, three problems have prevented political scientists from developing a more complete picture: first, empirical studies of district representation frequently have not had measures of district opinion and incumbent or candidate positions on the same ideological scale; second, much of the literature focuses only on incumbent legislators rather than on opposing candidates vying for support from district or state electorates; and third, no study has included leadership valence as a dimension of district representation. As noted, I delay 147

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District Ideological Representation

discussion of the valence dimension and its relationship to district ideological representation until the next chapter.

approaches to the study of district ideological representation Comparison is essential to any science. In studying representation, we must decide which comparisons are possible with the available data, and which comparisons are interesting given our substantive understanding of the concept. Clarifying the nature of the comparisons of interest has both substantive and methodological implications for the study of electoral representation. Two approaches based on different comparisons are fundamental: Proximity vs. Responsiveness: One approach to ideological representation compares incumbent representatives across districts (Bartels et al. 2016; Clinton 2006; Erikson and Wright 2000; Miller and Stokes 1963). The most common approach involves investigating covariance-based measures relating the ideological or issue positions of incumbent representatives to some measure of district opinion. Achen (1978) labeled this “responsiveness” because the core hypothesis is that legislators respond to variation in their district positions by taking increasingly conservative positions as their districts are more conservative. This approach does not measure the distance between the legislator’s ideological position and the preferences of the district, and its basis of comparison is usually of legislators rather than opposing candidates vying for support from district electorates. A proximity-based measure of ideological representation calibrates the difference between the legislator and the district on a liberal-conservative scale. Proximity (or distance) measures are consistent with spatial theories of legislator and district preferences, and therefore with the Proximity Rule, but require measures of the ideological preferences of districts and candidates in a common ideological or issue space, whereas covariancebased measures of responsiveness do not. A proximity measure can produce results at odds with responsiveness measures. Office Holders vs. Candidates: By far the most common comparisons made in studies of representation are of officeholders, usually legislators such as members of Congress. The logic behind this approach, whether it is based on responsiveness or proximity models of representation, is unassailable: office holders make policy, so we should investigate how well their behavior in office comports with the interests and preferences

Approaches to the Study of District Representation C1

−3

Very Liberal

−2

C3

C2

I1

D1

D2

D3

−3

0

1

I2

2

149 I3

3 Very Conservative

figure 8.1 Responsiveness vs. Proximity in District Ideological Representation

of the electorates that voted them into office. However, choice-based voter rules based on ideological proximity suggest comparisons between opposing candidates rather than officeholders, as between winning and losing candidates. In this comparison, representation is enhanced when the more desirable of the two candidates is selected. A choice-based concept of representation emphasizes the comparison between the two candidates on offer to the district electorate, rather than comparing legislators from different districts, and it reflects what voters and electorates must do: choose the candidate who better represents their interests. Figure 8.1 illustrates the relevance of comparisons based on responsiveness vs. proximity and officeholders vs. opposing candidates to our understanding of district ideological representation. In the example, there are three districts whose preferences are at the three positions on the liberal-conservative scale indicated by D1 , D2 , and D3 . All three districts are represented by conservative incumbents (I1 , I2 , and I3 ) each of whom is opposed by liberal to moderate challengers (C1 , C2 , and C3 ). A covariance-based measure of incumbent responsiveness to district preferences would show a strong relationship between the positions taken by incumbents and their districts’ preferences because incumbents take more conservative positions exactly as the districts that elected them are more conservative. As noted, this approach does not assume district preferences and representative positions are measured on the same scale. In Figure 8.1 because they are on the same scale, the intercept in a regression of incumbents’ positions on their district preferences indicates the mean ideological bias of incumbents relative to their districts’ ideological preferences.1 1

The regression equation for incumbent positions in Figure 8.1 is 2 + 1X (District Ideology), which indicates perfect responsiveness combined with a two-unit conservative bias on the liberal-conservative scale.

150

District Ideological Representation

A responsiveness approach comparing incumbents and their opponents would show that incumbents are more representative than challengers, whose ideological positions are not as consistently responsive to variation in district preferences. In contrast, a proximity-based measure would show the conservative bias in the representation incumbents provide since each incumbent is two units to the right of his or her district’s preferences. Although challengers are less responsive to variation in district preferences, on average they take positions closer to their districts than incumbents. The choice-based concept recognizes that the electoral process produces representation as a result of the competition between candidates for the district electorate’s support, and implies a standard of representation different from absolute standards such as proximity to the median voter: representation is enhanced when the candidate closer to the district’s preferences defeats the candidate more distant from district preferences. Applying the Proximity Rule to the example in Figure 8.1, C1 and C2 would unseat the incumbents in their districts because they are closer to district opinion than the legislator holding the seat. D3 ’s preference is at the ideological cut point between C3 and I3 and is therefore indifferent on policy grounds between the two candidates and not predictable by the Proximity Rule. As noted, the absence of research designs capable of assessing proximity, and the focus on incumbent legislators rather than opposing candidates as the relevant suppliers of district representation, have hampered empirical work in this field. Not only is there a disconnect possible between responsiveness and proximity, but looking only at incumbents (whether based on responsiveness or proximity) ignores the choices voters face between opposing candidates. Whereas there may be evidence of weak or non-existent representation by incumbent legislators of constituency preferences, limited inferences may be drawn without knowing how incumbents compare with their opponents. For example, if the regression equation indicates a slope of .6 as the effect of district preferences on incumbent positions, it is possible the slope for challengers is larger. Likewise, if incumbents average two units’ distance from their districts, challengers may average 2.5 units. A concern with the functioning of the electoral process in producing representative outcomes should ideally focus on whether electorates are adept at choosing the more representative candidate, as well as assessing the representation offered by incumbent office holders.

Polarization and Ideological Representation

151

Republican Identifiers in Republican Districts (1.60)

All Constituents, Republican Districts (.51)

All Constituents (.31)

All Constituents, Democratic Districts (.21)

Republican Challengers (2.05)

Democratic Identifiers in Democratic Districts (−.85) Democratic Challengers (−1.42)

Democratic Incumbents (−1.60)

−3 Very Liberal

−2

Republican Incumbents (2.18)

−1

0 Ideological Scale

1

2

3 Very Conservative

figure 8.2 Ideological Map before the 2010 Elections (mean ideological positions) Note: Challengers include candidates running in open seats, where the challenger is defined as the candidate from the party that did not hold the seat before the election.

partisan polarization and ideological representation Let us begin with an ideological map of the American electoral system as it existed prior to the 2010 elections (Figure 8.2). Incumbents, challengers, and district and partisan constituencies are located by their mean positions on the 7-point liberal-conservative scale (in parentheses) and their densities. We can observe the distances between parties as represented in Congress by Democratic and Republican incumbents, by challengers running under their party’s banner, or in the electorate as represented by Democrats in districts that elected Democrats and Republicans in districts held by the GOP. These distances between various partisan groups are what many observers mean by partisan polarization. Figure 8.2 can be used to address fundamental questions of ideological representation in 2010. For example, the mean position of Democratic incumbents was considerably to the left of the preferences of districts that elected them, an observation that applies with equal force to

152

District Ideological Representation

Republican incumbent ideological positions vis-à-vis their district preferences. Candidates in both parties were much closer to their fellow partisans in the electorate than they were to the preferences of their district electorates as a whole. Party is obviously an important factor in explaining candidates’ ideological positions, as reflected in the polarization between candidates in the two parties. The distributions in Figure 8.2 illustrate the nature of partisan polarization beyond the comparison of mean positions. Democratic incumbents and challengers are somewhat more dispersed than Republican incumbents and challengers, but there is no overlap between the distributions of candidates in the two parties.2 Likewise, there is no overlap in the mean partisan constituency positions, indicating substantial polarization between partisan constituencies in districts represented by incumbents from their party.3 The degree of polarization in district-wide ideological preferences between districts represented by Democrats and those represented by Republicans amounts to only a faint hint of the divergence between partisan candidates and officeholders. This is not the first study showing challengers as more moderate than incumbents (Burden 2004), but because the figure places district preferences in the same ideological space, we can also observe that challengers were modestly more moderate than incumbents in their party because challengers run in districts held by the opposing party. This observation revisits (see Chapter 6) the distinction between absolute extremism on the liberal-conservative scale (i.e., relative to the mid-point of the scale) and distance from district preferences. Although challengers were more moderate than incumbents in an absolute sense, relative to their district electorates, they were more extreme. Incumbents averaged 1.73 units more extreme than their districts on the seven-point liberal-conservative scale; challengers averaged 1.91 units more distant from their districts’ preferences (difference between incumbents and challengers: p < .001). The national ideological mapping of candidates and districts in Figure 8.2 does not link individual candidates’ ideological positions to the preferences of their districts. Figure 8.3 illustrates the partisan polarization in the system alongside the responsiveness of candidates’ ideological positions to district preferences. And, because districts and candidates 2 3

The standard deviations of Democratic incumbents and challengers are .62 and .38, respectively. Among Republican incumbents and challengers, they are .41 and .31. As was true among candidates, Democratic partisan constituencies within districts represented by Democrats exhibit more variation than Republican partisan constituencies in GOP-held districts (s.d. = .32 vs. .16).

3

Polarization and Ideological Representation

153

Republican Candidate Ideology = 1.98 + .40*District Ideology; R-sq. = .18

Candidate Ideological Positions −2 1 2 −1 0

Very Conserv.

Very Liberal

−3

Democratic Candidate Ideology = −1.78 +.75*District Ideology; R-sq. = .23

−1

Liberal

−.5

0 District Ideology

.5

1

Conservative

figure 8.3 Candidate Positioning and District Preferences, 2010 Triangle = Democratic candidates; square = Republicans; 95% confidence intervals.

are on the same ideological scale, inferences about the mean proximity of candidates to district opinion can also be made. By the criterion of responsiveness, the effect of district opinion is somewhat stronger among Democrats than Republicans, although both slopes are significant (all coefficients, including intercepts are statistically significant (p < .01)). The slope estimate for Democrats is almost twice the magnitude of the slope for Republicans, indicating Democratic candidates were more responsive to variation in their districts’ ideological preferences in their own position-taking than Republicans. A comparison of the intercepts indicates that Democrats were also a bit closer to their districts’ preferences than Republicans. Democratic candidates in moderate districts (located at 0) are predicted to be 1.76 units to the left; Republican candidates running in the same centrist district are predicted to be 1.96 units to the right. Adding the two intercepts provides a convenient measure of polarization: Democratic and Republican candidates running in a moderate district are expected to adopt positions fully 3.72 units apart on the liberal-conservative scale.

154

District Ideological Representation

Still another way of seeing the distance between district opinion and candidate positions is to notice that the district ideological preferences on the X-axis in Figure 8.3 are on a much narrower range than the candidate positions. The most liberal district in the sample (CA28) had a district ideology score of −.81. The Democratic candidate in that district, incumbent Howard Berman, had an ideological score of −1.77, .96 units to the left of his district. Based on the regression equation for Democratic candidates, the predicted score for Representative Berman is −2.28, or 1.47 units more liberal than the district. A similar exercise for the Republican challenger in the district indicates that his ideological position was far to the right of the district’s preference.4 Thus, while the positive effect of district preferences on candidate position-taking in both parties indicates responsiveness to district interests, the partisan polarization between opposing candidates is substantial.5 Another way of investigating the responsiveness of opposing candidates’ positions is by examining the relationship between ideological cut points and district ideology (Ansolabehere et al. 2001). Candidates are responsive to variation in district preferences if the ideological cut point between opposing candidates is more conservative as district preferences are more conservative. This way of looking at candidate responsiveness, of course, hides the partisan polarization between opposing candidates so evident in Figure 8.3, and it ignores partisan differences in candidate responsiveness. The analysis in Figure 8.4, too, provides insights about responsiveness and mean proximity in the candidate district-electorate relationship. The intercept in the cut-point equation indicates a modest but significant conservative bias among opposing candidates vis-à-vis their districts. A moderate district at the center of the liberal-conservative scale is expected to have candidate cut points .09 more conservative than district preferences (p < .01). If the system conformed perfectly to the partisan model, we would expect to observe a slope approximating zero, since candidates running in each district would adopt positions consistent

4

5

The Republican challenger, Merlin Froyd, had an ideology score of +1.76, or 2.57 units to the right of the district. Froyd’s ideological position was relatively moderate for a Republican, and close to the predicted ideological position based on the Republican equation (+1.68). Figure 8.3 replicates a pattern reported in Ansolabehere, Snyder, and Stewart (2001 142, Figure 1) from the 1996 elections, with the key difference that greater partisan polarization was present in 2010 than in 1996. They also found modest district effects commensurate with those present in 2010, including a stronger effect of district preferences on Democratic candidates’ ideological positions than was true for Republican candidates.

Incumbent Representation and Party Change in 2010

3

155

Candidates' Ideological Cut Points −2 1 2 −1 0

Very Conserv.

Candidate Cut Point = .09 + .57*District Ideology; R-sq. = .35

−3

Very Liberal

−1 Liberal

−.5

0 .5 District Ideological Preferences

1 Conservative

figure 8.4 Relationship between Opposing Candidates’ Ideological Cut Points and District Ideology

with their party invariant to district opinion; if the system conformed perfectly to the median-voter model, we would expect to observe a steeper slope, approaching 1.0 in magnitude.

incumbent representation and party change in 2010 As noted, many studies of district ideological representation focus only on incumbent legislators, rather than including opposing candidates running in the same districts. The incumbent-district ideological relationships in Figure 8.5 highlight the selection effect of district preferences on the party that holds or wins the seat. No Republican in the sample held a left-ofcenter district.6 Figure 8.5 shows the relationship between incumbents’ ideological positions and district ideology for Democratic and Republican Representatives after the elections. As in Figure 8.3, the ideological chasm between the parties is evident alongside a weak effect of district preferences within parties. 6

The left-most district held by a Republican in the sample in either the 111th or 112th Congress had a mean ideological preference of .003 (NJ07).

District Ideological Representation

3

156

Republican Incumbent Ideology = 1.98 + .39*District Ideology; R-sq. = .05

Very Conserv.

0 0 0 0 0 1 00 11 00 0 1 0 1 10 1 11000 0 0 0 10 011 1 0101 00 1 1 0 1 0 1 01100 0 1 1 1 1 0 1 001 1 0 1 1 1 1 0 0 1 0 0 0 1 0 0 1 1 1 10 0 0 1 0

Incumbent's Ideology in 112th Congress −1 −2 0 1 2

1

0 0

0

0

0 0

Very Liberal

0 00

00 0 0 00 00 0 00 0 0 0

0

0

0

0

00

0

0 0 00 0 000 0 00 0 0 0 0 00 00 0 0 00 0 0

0

0 0

0

0

−3

Democratic Incumbents' Ideology = −1.80 + .60*District Ideology; R-sq. = .12

−1

Liberal

−.5

0 District Ideology

.5

1

Conservative

figure 8.5 Incumbent and District Ideology after the 2010 Elections Triangle = Democratic candidates; square = Republicans. Indicator variable: 0 = seat did not change parties in election; 1 = seat switched parties in 2010 elections.

The 2010 elections wrought a massive Republican tide – a “shellacking” in President Obama’s morning-after characterization – with the GOP picking up 63 seats and wresting the majority from the Democrats for the first time since the 2006 elections. Republican victories in 2010 were mostly concentrated among the most conservative districts held by the Democrats – another indicator of the selection effect of district ideology on the party of the incumbent Representative. One conclusion from the analysis presented thus far is clear: the system of district representation in Congress more closely approximates the expectations of the partisan, as opposed to the district-median-voter model discussed in Chapter 3. The prominence of party differences is evident in the candidate and incumbent relationships in Figures 8.3 and 8.5, as is the relatively modest effect within each party of district preferences. One way of seeing the effects of partisan polarization in the 2010 elections is to compare the candidate positions in districts that remained in the hands of each party and in swing districts that changed party control

Incumbent Representation and Party Change in 2010

157

table 8.1 District and Candidate Ideology by District Party Outcome, 2010 Party Holding Seat before and after 2010 Elections Continued Swing Continued Democratic (Dem.-Repub.) Republican Mean district ideology Mean Democratic candidate ideology Mean Republican candidate ideology N ∗

.04 (.04) −1.76 (.07) 1.98 (.04) 62

.46 (.04) −1.30 (.10) 2.16 (.04) 42

.54 (.03) −1.42 (.05)∗ 2.20 (.05) 51

Democratic candidates in “continued Republican” column exclude five districts in which no Democratic candidate ran (N = 46). Cell entries are mean scores with standard errors in parentheses.

as a result of the elections. Table 8.1 shows the mean ideological positions of districts and candidates in three types of districts: those that remained in Democratic hands, those that switched from Democratic to Republican hands,7 and districts that were Republican before and after the elections. As we would expect, districts that remained Democratic were to the left of districts that continued Republican. Swing districts, though they were somewhat less conservative than continuing Republican districts, were much closer in their ideological makeup to core Republican than to continuing Democratic districts. Partisan polarization among candidates combined with some evidence of modest district effects is also evident in the table. No matter the type of district, Democratic candidates were identified as liberal and Republicans as even more conservative. This ideological gap between the candidates meant that a pattern of “leapfrog representation” (Bafumi and Herron 2010) occurred in swing districts: Democrats, most of whom were incumbents running in districts that flipped to the GOP, were substantially more moderate in their liberalism than Democratic candidates running in districts that remained in their party’s hands after the election.8 This difference may be attributed to 7

8

All of the swing districts in the study sample switched from Democratic- to Republicanheld seats. Among all districts, three switched from the Republican to the Democratic Party, but none of these districts was in the sample. In thirty-one of the forty-two swing districts in the sample, Democratic incumbents ran and were defeated. Democratic incumbents in these districts were only slightly more liberal than their Democratic counterparts running in open seats that were lost to the GOP.

District Ideological Representation

158

Representative’s Party (b) (c) (a) District Ideology

Representative’s Ideology

figure 8.6 Direct and Selection Effects of District Ideology on Representative Ideology

district preferences because of the more conservative preferences of swing districts. Many of the Republicans running in these districts were affiliated with the Tea Party movement and were more conservative even than incumbents representing core Republican districts.9 Thus, at least for the Tea Party winners, the leapfrog effect was especially pronounced in 2010 swing districts.

probing the effects of district and party The comparisons in Table 8.1 of swing districts with districts that remained consistent in their partisan representation hint at deeper questions about the effects of district and party in the American system of representation. This is a question that has been of interest to students of representation for three generations (Ansolabehere et al. 2001; Fiorina 1974; Turner 1952; Brady 1973). The “leapfrog” pattern suggests a strong partisan effect, but we have also seen clear district effects on both Democratic and Republican candidates’ ideological positions. The arrow diagram in Figure 8.6 suggests that districts affect the representation they receive in two ways (Fiorina 1974). The direct effect (link “a”) of district ideological preferences influences the positions candidates take when they run: less conservative Republicans and more liberal Democrats run in liberal districts; more conservative Republicans and less liberal Democrats oppose each other in more conservative districts. There is also the indirect effect of district preferences on which party’s candidates win (link “b”). 9

Sixty-two percent of Republicans running in districts that flipped to the Republicans in 2010 were affiliated with the Tea Party. Their mean ideology score was 2.27, compared with non-Tea Party Republicans who won in these districts whose mean ideology score was 1.98.

159

.8 .6 .4 .2 0

Probability Republicans Hold Seat after 2010 Elections

1

Probing the Effects of District and Party

−1

−.5

0 District Ideology

.5

1

figure 8.7 District Effect on the Party of the Representative after the 2010 Elections

This selection effect occurs because liberal districts select the Democratic candidate and conservative districts tend to select the Republican candidate. The leapfrog effect by which relatively extreme candidates in one party are replaced by extreme candidates in the other (link “c”) is a party effect, due to the personal preferences of partisans who run for Congress, or to the influence of primary voters, partisan activists, and contributors (Aldrich 1983; Bawn et al. 2012; Kujala 2016).10 Figure 8.7 illustrates the district effect on the party of the representative (link “b” in Figure 8.6). There is a strong relationship between district 10

This raises the question of whether districts would choose more moderate candidates in general-election contests if they ran. It seems reasonable to assign the relatively extreme positions candidates take to a party influence of some sort, but there still is the selection effect associated with districts selecting one partisan extremist over the other. This effectively assigns the leapfrog pattern to a “lesser of two evils” effect, rather than a result of district preferences for extreme candidates. In the absence of more moderate candidates, we cannot be sure whether the leapfrog pattern is due to district preferences for extremists, or is a byproduct of partisan preferences that produces candidates more extreme than their districts. Given the distributions of candidate positions in the observational data, these questions are probably best addressed in experimental designs (Sniderman and Stiglitz 2012; Tomz and Van Houweling 2008).

District Ideological Representation

160

table 8.2 Regression Analysis of Candidate Ideology on Party and District Ideology, 2010a Candidate Conservatism Candidate’s party District ideology District ideology X party Design Constant Adjusted R-square N

3.726∗∗∗ (0.06) 0.748∗∗∗ (0.10) −0.350∗∗ (0.13) −0.034 (0.05) −1.735∗∗∗ (0.06) 0.952 300

∗

p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001.

a

Cell entries are OLS regression coefficients with robust standard errors clustered by district in parentheses below each coefficient.

ideology and the party of the representative holding the seat after the elections. Consistent with the partisan model, districts that select Democrats get consistently liberal representation, with a modest effect of the degree of district liberalism, and districts that select Republicans get conservative representatives with a small effect of how moderate or extreme the district is in its conservatism. One way of summarizing the effects of district and party is to return to Figure 8.3, which shows the effect of district ideology on Democratic and Republican candidates’ ideological positions. The plot shows the familiar pattern: modestly positive slopes representing the effect of variation in district preferences combined with large partisan differences in the ideological positions of candidates. Table 8.2 replicates these relationships in a single equation showing the effects of district ideology on candidate ideology in each party alongside the effect of party. The party effect in Table 8.2 is the gap identified by the two intercepts in Figure 8.3, which indicate respectively the predicted ideology of Democratic and Republican incumbents representing moderate districts (−1.76; +1.96). The party effect in Table 8.2 of 3.73 describes the ideological distance between the two parties on the seven-point liberal-conservative scale (the difference between the two intercepts in Figure 8.3 within rounding error). This estimate of partisan polarization

A Partisan-Hybrid Model of District Representation

161

in Congress is consistent with the picture we have seen in this chapter and in Chapter 3. The main effect of district ideology describes the effect of district ideology on Democratic candidates’ ideological positions. As we saw in Figure 8.3, the slope estimate for Democrats is .75, while the effect of district ideology on Republican candidates is less, estimated to be about .40 (p < .01). Since the range of district ideological preferences spans almost two units on the scale (from −.81 to +1.05), the magnitude of district responsiveness over the full range of district opinion is considerably less than the ideological divergence between the parties: the Democratic candidate from the most liberal district is predicted to be about 1.4 units more liberal than the Democrat running in the most conservative district, while the Republican running in the most conservative district is predicted to be .74 units more conservative than the Republican running in the most liberal district. These intra-party differences linked to district ideology are dwarfed by the inter-party ideological gap of 3.73. This way of assessing the impact of district ideology leaves the district as distinctly inferior to the effect of party, which is two and a half to more than five times greater than the maximum effect of district ideological preferences. As noted, however, this accounting ignores the substantial effect of district ideology on the party that ends up holding the seat (i.e., the party of the incumbent). As Figure 8.7 showed, the confidence intervals at the extremes of district ideology are tight, with districts at the extremes all but certain to elect candidates from the ideologically compatible party. District ideology has a powerful impact on which party’s candidate wins, and therefore on the ideological representation the district receives. At the same time, of course, partisan polarization exerts a strong force on district ideological representation. In the next section, I propose a model to capture the combined effects of party and district on ideological representation in the House.

a partisan-hybrid model of district ideological representation The analysis thus far shows that candidate ideology reflects a direct effect of district ideology; that there is substantial divergence between candidates in the two parties; and that district ideology also has a strong effect on which party’s candidate is likely to win the election. At the very least, this means that “party” is a variable associated with “district,” and not limited to party activities inside Congress or the personal preferences

District Ideological Representation

162

table 8.3 Probability of Republican Victory and Expected Candidate Ideological Positions, 112th Congress

District ideology is: Most liberal in sample (−.81) Moderate (0) At tipping point in 2010 (+.23) Mean district ideology (+.31) Most conservative Dem. seat (+.80) Most conservative in sample (+1.05)

Probability Republican Wins Seat (Link “b”)

Expected Ideology of Democrat (Link “a”)

Expected Ideology of Republican (Link “a”)

E(R) Party Expected Divergence Ideology (Link “c”) of Winner

.00

−2.37

1.64

4.01

−2.36

.19 .503

−1.76 −1.58

1.96 2.05

3.72 3.63

−1.05 +.24

.61

−1.53

2.08

3.61

+.67

.97

−1.22

2.28

3.50

+2.18

.99

−.98

2.38

3.36

+2.35

Note: Estimates are based on the statistical model behind Figure 8.7 and in Table 8.2.

of the candidates, although those are two additional interpretations of what party means in this context. The partisan-hybrid model I propose recognizes that the partisan affiliation of the representative and the ideological position the representative adopts are a function of district ideology. The partisan-hybrid model is based on the concept of the “expected representation” (E(R)), or the expected ideological position the winning candidate adopts. The ideological position of the legislator elected from a district is a function of the district’s ideology, since the impact of district ideology is on both the probability of a Republican winning the district and the ideological positions of the candidates. The expected ideological representation a district receives in an election is a product of each party’s chances of winning the seat and the candidates’ expected ideological positions: E(R) = p(Repub. Win)(Repub. Cand. Exp. Ideology) + (1 − p)(Repub. Win)(Dem. Cand. Exp. Ideology) The analysis in Table 8.3 illustrates how the direct effect of district ideology combines with the probability of the Republican candidate winning the district to produce the expected ideological representation the district

A Partisan-Hybrid Model of District Representation

163

receives. The first three columns of entries in the table are drawn from the analysis of the relationship between district ideology and the probability of the Republican winning (see Figure 8.7), and the predicted ideological positions of the candidates in each party (Table 8.2). Illustrative districts in the table are ordered from the most liberal to the most conservative districts in the sample (district ideologies are reported in parentheses), with several example districts in between these extremes. The impact of district ideology on the probability of a Republican winning the district (link “b” in Figure 8.6) and on the ideological positions of Democratic and Republican candidates (link “a”) is apparent moving from the top to the bottom of the table. Of course, there is also a pronounced divergence between the expected ideological positions of candidates in the two parties consistent with partisan polarization (link “c”). By this formulation, the expected ideological representation for the most liberal district in the sample is −2.36 because the Republican candidate’s chances of winning are estimated to be essentially zero. This means the district is expected to receive the ideological representation predicted of the Democratic candidate (within rounding error). Because of partisan polarization among candidates, the Democrat selected will be more extreme than the district’s ideological preference (of −.81). In the case of a moderate district exactly at the mid-point of the liberal-conservative scale, the probability of a Republican winning is approximately .19. This means the expected value of the ideology of the winning candidate is (.19 × 1.96) + (.81 × −1.76) = −1.05. And so on, with the expected value of the winning candidate’s ideology becoming more conservative as the district is more conservative, along with a corresponding increase in the probability of a Republican victory and progressively more conservative opposing candidates. Again, on the conservative side, Republican candidates overshoot district preferences by being much more extreme in their conservatism than the districts that elect them. The reason the divergence or polarization between the parties is reduced as districts become more conservative is because Democratic candidates are more responsive than Republicans to district ideological preferences. Figure 8.8 depicts thee curves salient to understanding the relationship between district ideology and ideological representation. The solid line depicts the effect of district ideology in the full sample of districts on the expected ideology of the winner based on the partisan-hybrid model of district ideological representation. The partisan-hybrid curve in the figure is estimated in the manner just illustrated in Table 8.3. It indicates the non-linear relationship between district ideology with more modest

District Ideological Representation

3

164

Very Conserv.

2 1 0

Opposing Candidates' Ideological Cut Points

−1

Incumbents' Ideological Positions After Election

Expected Representation, Partisan-Hybrid Model

−2

Expected Representation, Median Voter Model

−3

Very Liberal

−1

Liberal

−.5

0 District Ideology

.5

1 Conservative

figure 8.8 Models of District Ideological Representation, 112th Congress (lowess curves)

responsiveness to variation in district ideology toward the extremes and an accelerated effect of district ideology among moderately conservative districts. The steepest part of the curve reflects the sharply increasing probability of a Republican winning the district over the range of moderate-to-moderately conservative districts. It is important to see that the partisan-hybrid model does not predict that individual candidates from center-right districts are moderates. Although they are more moderate than co-partisans running in more extreme districts, they are nonetheless distant from their districts’ preferences. The partisan-hybrid curve indicates expected moderate representation in these districts because the probabilities of each party winning are relatively even. This is another way of saying they are the most likely swing districts. Thus, over time, we would expect their representation to be more moderate than in extreme districts as party turnover occurs, leapfrogging the seat back and forth between parties, resulting over time in more moderate average representation. Centrist districts moderate their ideological representation not so much by selecting moderate candidates, but by alternating between candidates from relatively extreme partisan camps.

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165

One way of defining the maximum possible influence of district ideology on incumbent ideology is based on the median-voter model: opposing candidates in each district adopt positions close to or at the preference of the median voter in the district. The result of this sort of representation would be a linear relationship between district and incumbent ideology as indicated in the figure.11 In the median-voter model as in the partisan model, the party of the incumbent may be determined by the district, such that relatively liberal districts elect Democrats and relatively conservative districts elect Republicans. In this model, however, incumbent ideological positions are determined by district preferences with no independent effect of party. The difference between the partisan hybrid and median-voter curves is one way of characterizing the “distortion” that results from polarization in the system. That the hybrid curve dips substantially below the median-voter curve among liberal districts reflects the tendency of liberal/Democratic incumbents to be substantially more liberal than their districts’ preferences; that it extends well above the median-voter curve in conservative districts results from a corresponding tendency toward extremism relative to district opinion among conservative/Republican incumbents. A second way of seeing how the system departs from the median-voter model is to compare the median-voter and cut-point curves in Figure 8.8. Under the median-voter model the ideological cut points between candidates should track district preferences such that the median-voter and cut-point curves would be identical. This identity is not necessarily threatened by some degree of partisan divergence between opposing candidates in the same districts, since partisan divergence could coexist with identity between the cut-point and median-voter curves. In this situation of identity between the two curves, we might conclude that district ideology has its maximum effect within the partisan-hybrid model. This could occur if there were substantial partisan divergence between candidates combined with strong responsiveness by both parties’ candidates to district preferences. That the cut-point slope is positive and linear is consistent with our conclusion that district ideology has an important effect on candidate position-taking; that the slope is weaker than the median-voter slope

11

The median-voter model as presented in Figure 8.8 is based on the incumbent winner adopting exactly the same ideological position as the district. Strictly speaking, the median-voter model does not require the winner to adopt the same ideological position as the district, but it does imply that it is an ideal form of district ideological representation.

166

District Ideological Representation

indicates that district ideology has a less than maximum effect within the context of the partisan-hybrid model.

conclusion Ideological polarization between the political parties, often lamented as a central feature of contemporary American politics, is abundantly evident in our investigation of district ideological representation. The two parties as defined by their House candidates are far apart on the ideological scale – substantially more divergent than the districts that elected them. This means that the ideal of representation defined by the median-voter theorem does not match reality. At the same time, however, partisan polarization does not mean that the median-voter logic holds no sway over district representation. Candidates in both parties are responsive to variation in district preferences, with more responsiveness on the Democratic side than among Republican candidates. In this, there is evidence that district preferences matter; the system is not completely dominated by partisan differences. The partisan-hybrid model of district representation recognizes the importance of district preferences both because these preferences affect how extreme candidates are, and because district preferences have a strong effect on each party’s prospects of winning. Against the medianvoter concept of representation, the partisan-hybrid model indicates substantial distortion, even as it grants significant influence to district electorates in determining the ideological representation they receive. Despite the evidence of polarization, candidates closer to their electorates’ ideological preferences receive an electoral payoff consistent with the Proximity Rule. That this payoff fails to produce more moderation among candidates is a significant puzzle from the perspective of the Proximity Rule. I consider possible solutions and responses to this puzzle in the Conclusion of this book. First, it is necessary to accommodate the valence dimension in our conception of district representation.

9 Getting it Right? Valence and Ideology in District Representation

The fit between district ideological preferences and representative or candidate ideological position-taking examined in the previous chapter does not fully address the concept of electoral representation because it fails to consider the leadership valence dimension. Electorates seek ideological outcomes consistent with their policy preferences, but they also seek office-holders strong in leadership skills and traits. This chapter examines outcomes on each dimension, attempts to explain these outcomes, and evaluates the leeway and alignment hypotheses in an exploration of the relationship between the two dimensions of representation. This is the first empirical investigation into these questions of which I am aware. Armed with the concepts and findings developed throughout this book, we are in a position to advance our understanding of the nature and sources of electoral representation. In Chapter 7, we saw evidence that congressional electorates enforced their interests on these dimensions by their effects on candidates’ vote shares. The questions here are the extent to which electorates choose the “correct” candidate on each dimension, and the degree of representation achieved. We have seen that incumbents are typically much more extreme ideologically than their district electorates. We have also seen, however, that electorates tend to be influenced by the relative proximity of candidates, with an electoral benefit accruing to the closer candidate. Thus, it is possible that the better of the two candidates is usually selected, but that district electorates routinely do rather poorly when the quality of representation afforded by representatives is assessed as the distance between members of Congress and their districts’ ideological preferences. 167

168 Getting it Right? Valence and Ideology in District Representation table 9.1 Breaking Down the Sample by Outcome on Proximity and Valence Dimensions Outcome on Valence Outcome on Proximity

Incorrect

Correct

Incorrect Correct

20.7% 18.7%

18.7% 42.0%

Note: Includes all districts in which candidates in both parties ran (N = 150).

do congressional electorates choose the correct candidate? The first question is simple: How often did congressional electorates get it right in the 2010 elections? Table 9.1 provides a preliminary answer to this question by classifying the outcome in each district as correct on valence (the district electorate chose the candidate stronger on valence over the weaker candidate), correct on proximity (the candidate closer to district preferences won), or correct on neither. By the accounting in Table 9.1, 42 percent of districts made the correct choice on both dimensions by selecting the more desirable candidate on valence and ideological proximity. One-fifth of all districts made an incorrect choice by voting into Congress the less desirable candidate on these two criteria. Because districts in these two cells could select the correct (or incorrect) candidates on both dimensions with a single choice, these districts were aligned going into the election. Adding the two percentages together indicates that 62.7 percent of all districts were aligned. Of these, correct outcomes trumped incorrect results 2:1, with 67 percent electing the correct candidate and 33 percent electing the incorrect candidate. The remaining 37 percent of districts were cross-pressured such that the stronger candidate on one dimension was weaker on the other. Those districts split exactly with 50 percent voting in the stronger candidate on valence who was more distant from the district electorate on ideology, and 50 percent electing the ideologically more representative but valence-disadvantaged candidate. The results in Table 9.2 present the mean valence and proximity scores in aligned and cross-pressured districts rather than classifying them as “correct” or “incorrect.” The relative scores presented in the table are calculated by comparing the winner in each district with the losing candidate; the winners’ scores present the scores for the winning candidates

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169

table 9.2 Mean Valence and Proximity Scores by Outcome Relative Score (Winner–Loser) Valence Outcome, Aligned Districts (N = 94): Correct on proximity and valence .64 (.05) Incorrect −.58 (.08) Net score .24 (.07)

Proximity

Winners’ Scores Valence

Proximity

.54 (.05) −.51 (.06) .20 (.06)

.64 (.03) .07 (.06) .46 (.04)

−1.56 (.05) −1.98 (.07) −1.70 (.05)

Outcomes, Cross-Pressured Districts (N = 56): Correct on valence only .55 −.32 (.08) (.05) Correct on proximity only −.43 .58 (.07) (.10) Net score .06 .13 (.08) (.08)

.55 (.04) .03 (.07) .29 (.06)

−2.03 (.05) −1.49 (.07) −1.76 (.06)

Note: Cell entries are mean scores with standard errors in parentheses.

only. Relative scores address the question of how well electorates chose, given the two candidates on offer. Positive scores indicate the winner was stronger on the dimension; negative scores indicate the winner was weaker. Among districts that selected the correct candidate on both proximity and valence, the mean valence advantage of the winner over the loser was .64. Since the maximum valence advantage of winners over losers in the data set was 1.7 (standard deviation = .68), this amounts to a substantial valence gain in representation for aligned districts that selected the stronger candidate. Likewise, winning candidates in this category were just over half a unit closer to their districts than the losing candidate. In other words, districts in this category not only made the correct choice; in doing so, they realized a substantial gain on both dimensions over the alternative candidates. If aligned districts that voted correctly realized a gain in valence and ideological representation, aligned districts that voted incorrectly (second row in Table 9.2) suffered nearly commensurate losses, relative to how they would have done had they chosen the stronger candidate. Relative to the winners, losing candidates in these districts were almost as strong on valence and as close to the district as the winners were in “correct”

170 Getting it Right? Valence and Ideology in District Representation

districts. Just as there were benefits to a correct choice, real costs resulted from an incorrect choice on these dimensions. The “winners’ scores” reported in Table 9.2 ignore the scores of the losing candidate in each district to report the mean valence scores and proximities of the winning candidates. This way of thinking about electoral representation shifts the focus from the quality of the choices electorates make to the quality of representation provided on each dimension by office holders. Focusing on incumbent office holders is also by far the more common approach mostly because equivalent data on opposing candidates are typically not available. Comparing the two approaches can yield different conclusions about the quality of representation electorates receive.1 Comparing the ideological proximity of winners to the relative proximity scores shows that, while winning candidates in aligned districts were closer to their district preferences than losing candidates, they were nonetheless more than 1.5 units from those preferences. Thus, from a choice perspective, electorates did well in aligned districts when they selected the correct candidate because they chose candidates who were about half a unit closer to their preferences. However, winning candidates – even when they were the correct choice in their districts – became members of Congress who were quite unrepresentative of their district preferences. Of course, this is consistent with the pattern we saw in Chapter 8, which showed that incumbent members of Congress from both parties before and after the elections were considerably more extreme than their districts’ ideological preferences. It is no surprise that aligned districts that failed to choose the better candidate suffered worse representation from incumbents on both valence and proximity. Winners’ valence scores were not significantly in positive territory, while their distance from their district was significantly greater than in aligned districts that made correct choices. Net scores reported in Table 9.2 indicate the mean scores for aligned and cross-pressured districts. The net relative valence score (+.24), for instance, reports the mean valence advantage of winners over losers in all aligned districts, whether or not the correct candidate on valence won the election. Comparison of the net scores among aligned and cross-pressured districts suggests that representation on both dimensions improves when 1

Oddly, the mean valence score for winning candidates is identical to the relative valence score. This is because the mean valence score for losing candidates in aligned districts was zero (within rounding).

Explaining Electoral Outcomes

171

choices between candidates are aligned as opposed to when they are crosspressured. Finally, results in Table 9.2 show the cost in representation that districts bear from being cross-pressured in their choice between the valenceadvantaged candidate and the candidate closer to their preferences on ideology. Among cross-pressured districts that selected the stronger candidate on valence, the gain that districts realized in relative valence representation was almost as high as in aligned districts, but they suffered a loss in relative ideological representation. A corresponding tradeoff in the opposite direction is evident among cross-pressured districts that selected the correct candidate on ideology. And, as noted, because cross-pressured districts cannot maximize their return on both dimensions, the net representation scores are lower than in aligned districts. Three conclusions seem warranted from the descriptive patterns we have seen thus far: (1) when districts are aligned, electorates make correct choices more frequently than not, although a significant minority err. The benefit they realize when they do make correct choices is substantial relative to the alternative. However, (2) the ideological extremism of winning candidates relative to their district preferences is evident in these results, even in aligned districts that make correct choices on ideology. Moreover, (3) cross-pressured districts not only face a difficult choice between their interests in valence and policy: on the dimension these districts choose correctly, the gains they realize approach that of aligned districts, but the losses they suffer on the dimension they choose incorrectly approach those of aligned districts that make incorrect choices on both dimensions.

explaining electoral outcomes Since electoral outcomes vary, with some districts advancing their interests on policy and valence while others act inconsistent with these interests, the next step is to attempt an explanation for this variation. Why did some district electorates get it “right,” whereas others did not? This endeavor involves three different ways of assessing how well district electorates did in “getting it right”: analysis of correct outcomes on ideological proximity and valence, the relative strength of winners vs. losers on each dimension, and the ideological fit and valence strength of winning candidates. I employ three types of covariates to explain representative outcomes, plus controls: the structure of district ideological preferences, candidates’ ideological extremity and resources, and the political sophistication of

172 Getting it Right? Valence and Ideology in District Representation

district electorates. I employ the same set of covariates to explain ideological proximity and valence outcomes. The substantive covariates are: r Structure of district ideological makeup: It stands to reason that outcomes, however they are measured, have something to do with the ideological makeup of districts. Two measures capture the structure of ideological preferences in the district: r District ideological extremism: The more distant the district is from the mid-point of the ideological scale, the more ideologically extreme it is. More extreme districts are typically dominated by one party in their makeup and are ideologically more homogeneous. Both factors should increase the ideological agreement between the incumbent and the district. By a similar logic, district ideological extremism should increase the ideological agreement between the winning candidate and the district relative to the loser. Since the partisan divide among candidates is large, ideologically extreme districts are closer to winning candidates who share the partisanship of the dominant party. r Distance of majority partisans in the district from the district median: This variable captures the partisan pressures incumbents face from within the district. As constituents who share the party of the winning candidate (which is how I define majority partisans) diverge ideologically from the district as a whole, there is pressure within the district electorate on representatives to diverge from the district median. The expectation is that the ideological distance between majority partisans and the district will have a negative effect on the ideological representation of the district. r Candidate extremism and resources: r Candidate extremism: Like the district extremism measure, this is extremism relative to the center of the ideological scale, not relative to the ideological preference of the district electorate. We have seen in Chapter 8 that candidates, including those who win the election, are substantially to the left or right (depending on their party) of their district electorates’ preferences. As noted, some of this extremism may result from partisan pressures within the district itself, but some may be due to candidate extremism from other sources, including pressures from partisan activists and financial contributors and from the candidates’ own personal preferences. r Candidate resources: Candidate resource advantages stemming from greater financial backing and incumbency are the basis of

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173

many observers’ skepticism about the capacity of the electoral process to deliver effective representation. Resource advantages create a visibility advantage among voters which, especially in lowinformation elections like those for the House of Representatives, can distort the process from electorates’ fundamental interests in policy and valence outcomes. At the same time, candidate resources may signal an advantage on valence or ideological agreement with the electorate. r Voter sophistication: Much of the extensive literature on the sophistication of the American electorate implies that voter sophistication is a necessary – or at least a helpful – attribute for voters seeking to exert control over election outcomes. The more engaged and the better informed voters – and, by extension, electorates – are, the better the electoral process should function, although that hypothesis has recently been challenged (Ashworth and Mesquita 2014).2 Because many of these studies find that voters are less sophisticated than hoped, skepticism about the capacity of electorates to enforce desirable outcomes is widespread (Achen and Bartels 2016). r Controls: r District is cross-pressured: As with individual voters, districts may be “aligned” or “cross-pressured” in their choice between the stronger candidate on ideological and valence grounds. Because electorates must choose the stronger candidate on proximity or valence in cross-pressured districts, the effects of other covariates may vary by whether the district is aligned or cross-pressured. r Party holding the seat in the election. r District demographics: The 2009 percent ages of African Americans, Latinos, and high school graduates, and median household income in the district. r Design: Dummy variable indicating 2006 competitive subsample of districts. Explaining “Correct” Outcomes Table 9.3 presents a logit analysis of correct proximity outcomes among aligned districts (Equation [1]). Equation [2] presents the results for all districts, aligned and cross-pressured included. The analysis of aligned 2

Debra Leiter (2013) argues that sophistication is more relevant to proximity voting than it is to valence voting, a claim supported in my results by the fact that sophistication among individual voters does not have a conditioning effect on valence voting.

174 Getting it Right? Valence and Ideology in District Representation table 9.3 Logit Analysis of Correct Proximity Outcomes by District Electorates Aligned Districts Coeff. (SE) Structure of district ideology District extremism Majority divergence

4.191∗ (2.10) 0.852 (1.45)

Candidate behavior and resources Winner extremism −4.471∗∗ (1.46) Spending differential 0.242 (0.26) Incumbent ran 3.549∗ (1.49) Mean voter sophistication 8.057∗∗ (2.87) Democratic seat −2.958∗ (1.34) Cross-pressured – Constant Pseudo R-square Log likelihood N

15.710 (10.35) 0.473 −31.416 94

All Districts

Effect

Coeff. (SE)

Effect

.13

2.952∗ (1.19) −1.047 (0.99)

.15

NS

−.23 NS .38 .22 −.28

−3.111∗∗∗ (0.75) 0.050 (0.16) −0.278 (0.63) 3.752∗ (1.51) −1.080 (0.65) −1.027∗ (0.45) 10.376 (6.57) 0.251 −75.318 150

NS

−.27 NS NS .12 NS −.17

∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Note: Design and demographic controls included but not shown. Effect estimates based on comparing 75th and 25th percentiles of continuous variables setting all other covariates at their mean or mode values.

districts explains correct outcomes on both ideology and valence since a correct proximity outcome also means the district selected the valenceadvantaged candidate. Consider first the analysis of aligned districts. As expected, the more extreme the ideological preferences of the district, the greater the chance of a correct outcome. Comparing districts relatively high in extremism (the seventy-fifth percentile) with less extreme districts (the twenty-fifth percentile), the probability of a correct outcome increases by about .13. Ideologically extreme districts tend to be dominated by conservatives in Republican districts or liberals in Democratic districts. Everyone – incumbent Representatives, challengers, potential challengers, and activist

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175

supporters in each party – understands the strategic implications of oneparty districts. A spatially correct outcome is more likely in extreme districts because the majority-dominant district is likely to choose the candidate from the dominant party who, in a polarized party system, is usually closer to the district’s preferences. A correct outcome on valence is also more likely in these districts because the structure of opportunity is clear to candidates and potential candidates, and the disadvantaged party tends to attract candidates relatively weak on valence. The more ideologically extreme the winning candidate was, the lower the probability of a correct outcome in the election. This is not surprising, although it does raise the possibility that not only does the winning candidate’s ideological extremism create distance between the incumbent and the district (a finding explored below), but the winning candidate’s extremism also undermines the ability of electorates to make a correct choice. There is a strong positive effect of the mean level of sophistication in electorates on spatially correct outcomes. The probability of the candidate who is closer on ideology to district preferences will win increases by .22 from districts relatively low to high in the percentage of sophisticates. This supports the interest of scholars in voter capacity and engagement by suggesting a link between the level of sophistication in electorates and desirable electoral outcomes. The precise mechanism for this effect is unclear. A likely possibility is turnout, which is higher in districts with more sophisticated electorates. When turnout is included in the analysis, the effect of sophistication loses its significance while voter turnout is significant (Verba and Nie 1972). This is consistent with turnout as the mechanism, although there are other possibilities.3 When the logit model in Table 9.3 is estimated on the full set of districts, the covariates just discussed remain significant. One additional effect is also evident: cross-pressured districts were less likely to produce correct outcomes on ideological proximity (a reduction of −.17). This is a finding similar to the individual-level analysis reported in Chapter 5 showing that cross-pressured voters were less likely to vote correctly. In crosspressured districts, a correct outcome on proximity necessarily means the candidate weaker on valence was selected, or vice versa. Since the two 3

Proximity voting rates are somewhat higher as sophistication levels increase, although including the rate of proximity voting does not have the same mediating effect as turnout. Aggregate awareness of candidates’ ideological positions likewise has no effect when sophistication levels are included. For an interesting theoretical argument claiming that there is no necessary connection between voter sophistication and democratic performance, see Ashworth and Bueno de Mesquita (2014).

176 Getting it Right? Valence and Ideology in District Representation

dimensions are in conflict in cross-pressured districts, we should observe a reduction in spatially correct outcomes. A reduction in correct proximity outcomes in cross-pressured districts is matched by an increase in correct valence outcomes in such districts. Somewhat to my surprise, unlike the analysis at the individual level, there is little evidence that the covariates explaining spatially correct outcomes are conditioned on whether the district was cross-pressured. In statistical models that examine the differences between cross-pressured and aligned districts, there is, with but one exception, no evidence of significant differences in the covariates included in Table 9.3. Thus, for example, district extremism has a positive effect on correct proximity outcomes in aligned and in cross-pressured districts, with no significant interaction with whether the district was cross-pressured. There is one important exception to the similarity of effects of covariates in aligned and cross-pressured districts. Notice that in aligned districts, the presence of an incumbent running for reelection has a significant positive effect on correct outcomes. Can we conclude from this that incumbency is not a distorting influence in House elections and that it consistently promotes correct outcomes? Figure 9.1 presents the one instance in which there is a clear difference in effects between aligned and crosspressured districts, a difference that speaks to how incumbency does – and does not – distort electoral outcomes. The effect of incumbency is significant and positive in aligned districts (as seen in Equation [1] in Table 9.3), increasing the probability of a correct outcome on proximity and valence by .38. In aligned districts, therefore, incumbency does not distort election outcomes; if anything, it promotes correct outcomes on both dimensions. However, in cross-pressured districts in which it is not possible for electorates to choose the stronger candidate on both valence and ideology, incumbency reduces the probability of a correct outcome on proximity by .38.4 This result in the aggregate parallels the effect of incumbency among individual voters reinforcing the claim that incumbency serves as a proxy for valence voting. In aligned districts where a correct valence outcome also implies a correct proximity outcome, incumbency enhances positive outcomes on both dimensions. But in cross-pressured districts, incumbency “distorts” the process from ideal proximity outcomes because it advances correct outcomes on valence. Thus, the appearance of distortion linked to incumbency occurs when the two dimensions are in conflict, when the loss in ideological representation is matched by a 4

That the probabilities appear to offset exactly is coincidental.

177

Pr(Correct Proximity Outcome) .2 .6 .4 .8

1

Explaining Electoral Outcomes

Cross-Pressured Districts

0

Aligned Districts

0

1 Incumbent Ran in 2010

figure 9.1 Effect of Incumbency on Correct Proximity Outcomes by Whether the District Is Aligned or Cross-Pressured

gain in valence representation. This conditional effect of incumbency on correct outcomes is canceled out among all districts when we ignore the difference between aligned and cross-pressed districts (in Table 9.3, there is no significant effect of incumbency among all districts). Variation in District Ideological and Valence Representation As demonstrated in Table 9.2, proximity and valence scores of winning and losing candidates can be compared to provide a finer grained picture of the quality of representation than is possible by examining whether outcomes are correct or incorrect on each dimension. I analyze four dependent variables using the same covariates as in Table 9.3: relative (winner–loser) ideological representation; the ideological representation of the incumbent in the 112th Congress; and relative and winner-only levels of valence representation (Table 9.4). The first two columns in Table 9.4 present substantively similar explanations of the quality of ideological representation received by districts, whether the quality is assessed as the winning candidates’ ideological representation of the district relative to that offered by the loser, or the

178 Getting it Right? Valence and Ideology in District Representation table 9.4 OLS Analysis of the Quality of District Ideological and Valence Representation Proximity Dimension

Valence Dimension

Winner Winner–Loser Only

Winner Winner–Loser Only

Structure of district ideology District extremism 0.579∗∗ (0.22) Majority divergence −0.726∗∗∗ (0.19)

0.666∗∗∗ −0.103 (0.10) (0.27) −0.459∗∗∗ 0.355 (0.09) (0.23)

−0.080 (0.16) 0.219 (0.14)

Candidate behavior and resources Winner extremism −0.701∗∗∗ (0.10) Spending differential −0.014 (0.03) Incumbent ran −0.071 (0.14) Mean voter sophistication 0.739∗ (0.29) District cross-pressured −0.092 (0.09) Democratic seat −0.305∗ (0.12) Constant 2.909∗ (1.34) Adjusted R-square 0.349 N 150

−0.728∗∗∗ −0.101 (0.04) (0.12) 0.131∗∗ −0.042∗∗ (0.02) (0.04) −0.118 0.593∗∗∗ (0.06) (0.17) 0.127 0.357 (0.13) (0.35) −0.035 −0.139 (0.04) (0.11) −0.249∗∗∗ −0.109 (0.06) (0.15) 1.084 0.471 (0.62) (1.64) 0.715 0.176 150 150

−0.053 (0.07) 0.046+ (0.02) 0.378∗∗∗ (0.11) 0.085 (0.22) −0.118 (0.07) −0.076 (0.09) 1.271 (1.01) 0.130 150

+ p < 0.10, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Note: Cell entries are OLS regression coefficients with standard errors in parentheses below each coefficient.

ideological representation provided by the winner. In both equations, district extremism has a positive effect on district ideological representation, while majority divergence and the district and the winner’s absolute extremism both drive down ideological representation. Because district extremism, majority divergence, and winner extremism are measured on the liberal-conservative scale, their effects can be directly compared. Two of the district-structure measures are linked to winners being in less ideological agreement with their districts: majoritypartisan distance from the district median and the extremism of the winning candidate. Majority divergence from the district median accounts for

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about half (51 percent) of the combined negative effects of majority divergence and winner extremism on the relative ideological representation of the district, and about 39 percent of the distance between winning candidates and their districts. This indicates that within-district partisan pressures explain a good portion of the ideological distance between districts and incumbents, although the leftover effects of winner extremism indicate there is more to the story. The remainder may be due to the influence of partisan activists and contributors (Kujala 2016), or to the personal preferences of incumbents who, after all, emerge from the milieu of active partisans and appear to share their more extreme ideological views.5 This point is revisited in the next chapter. There continues to be an effect of mean levels of sophisticated voters in district electorates on relative ideological proximity, although the effect on winner proximity is not significant. This may suggest that voter sophistication comes most directly into play in the process of choice between competing candidates. Finally, there is evidence of distorted ideological representation consistent with the resource-asymmetry hypothesis in the relative spending effect on winning candidates’ proximity to district preferences: the more winning candidates spent relative to their vanquished opponents, the further they were from their district preferences. While the effect does not appear in analysis of relative proximity or in the correct-outcome analysis, the partial effect here is significant. This effect, like others in the analysis of proximity representation, is not sensitive to whether the district was cross-pressured or aligned. This result reinforces the finding in Chapter 7 that spending has an independent effect on vote share, taking full account of the strategic basis of financial resources. At least with respect to the winner’s distance from district preferences, the spending advantage enjoyed by winning candidates appears to have a modest distorting effect on district ideological representation.6 The covariates that explain valence outcomes are different from those associated with measures of ideological proximity. Spending differentials, and especially the presence of an incumbent running for reelection, are positively related to valence representation, whether measured as the valence strength of the winner relative to the loser, or the valence strength 5 6

In the aggregate, Democratic activists were only .12 units less extreme than Democratic incumbents; Republican activists were .19 units less extreme than Republican incumbents. It is possible the statistical effect results because incumbents who are less representative raise and spend more money to compensate for losses they might otherwise incur because they are out of line with their districts’ preferences.

180 Getting it Right? Valence and Ideology in District Representation

of the winner. When an incumbent ran for reelection, the valence advantage of the winner over the loser was almost .6 of a unit on the scale stronger than in open-seat districts (third column in Table 9.4); the gain in valence of winners was about .38 stronger in districts in which incumbents ran than in districts where no incumbent was on the ballot (fourth column). In addition, of course, the positive effect of spending on relative valence representation and the leadership-valence strength of the winner (p < .10) undermines a simple claim that the evidence for the resourceasymmetry hypothesis as it appears in Equation [2] is the whole story. Whereas spending advantages are associated with lower levels of proximity representation of the winning candidate, they are also associated with higher levels of valence representation. Because the interaction effect of cross-pressured districts, when included in the analysis, is not significant in these equations, a simple story of tradeoffs in the effect of incumbency for aligned and cross-pressured districts (as was true of correct outcomes) is not available.7

leeway? the relationship between ideological proximity and valence If, as I have argued, candidates are aware of voters’ fundamental interests in ideology and valence, they should strive to respond on both dimensions. However, as noted in the discussion of the leeway hypothesis in Chapter 1, this “alignment hypothesis” is not the conventional view in political science. When the relationship between valence and ideological positioning has been considered, especially in the literature on incumbency and the personal vote, the most common argument has been that a strong valence reputation with voters frees representatives to pursue policy objectives at odds with the preferences of their districts. A problem with the literature is that the leeway hypothesis has never been fully tested owing to a lack of appropriate data. As discussed in Chapter 1, data on candidates’ relative proximity to their districts’ preferences and their valence differentials are required. If the leeway hypothesis holds, candidates with a valence advantage should tend to be opposed by candidates closer to district preferences. This is no more than saying that 7

Particular caution is called for in interpreting the effects of incumbency and spending on valence representation because of the “measurement-endogeneity” problem discussed in Chapter 2. As the analysis in supplementary materials shows, the incumbency effect on valence holds up when we employ opposite-party informants to measure candidates’ leadership valence, but spending effects are not significant.

Leeway?

2

181

Aligned, Republican

Candidate Proximity Differential −1 0 1

Cross-Pressured

Cross-Pressured

−2

Aligned, Democratic

−2

−1

0 Candidate Valence Differential

1

2

figure 9.2 Relationship Between Valence and Proximity Candidate Differentials

the leeway hypothesis anticipates that one candidate’s valence advantage is likely to increase the chances of the district being cross-pressured. In contrast, the alignment hypothesis expects a positive relationship between the candidates’ valence and proximity differentials. As I argued in Chapter 1, valence-advantaged candidates have little incentive to grant a strategic opening to their opponent on ideological proximity in a world where voters care about their interests on both dimensions. Candidates should, under this argument, strive to maximize their advantage on both dimensions in order to protect their interest not only in winning the current election, but also to advance their ambitions to win future elections. Figure 9.2 evaluates the leeway hypothesis by examining the relationship between candidate valence and proximity differentials for Republican candidates vs. Democrats in the 2010 elections. There is a moderately strong positive relationship between the valence and proximity dimensions (r = .34; p < .001), against the leeway and for the alignment hypothesis. Thus, there is a tendency for the stronger candidate on valence to be the candidate who is also ideologically closer to the district. Rather than being in tension as the leeway hypothesis would have it, the two dimensions of representation tend to be positively correlated, reflecting the incentives candidates have of responding to voters’ interests

182 Getting it Right? Valence and Ideology in District Representation

in policy and valence. As we have already seen in Table 9.1, the tendency among districts in which the candidates are aligned on both dimensions is to select the correct candidate on both dimensions.8 The evidence in support of the alignment hypothesis – candidates stronger on leadership valence also tend to be ideologically closer to their districts – is a significant finding addressing a debate of some standing in the literature. Ansolabehere and Snyder (2000) and Groseclose (2001) were among the first to propose spatial models of candidate positioning that included valence; both reached conclusions contrary to the leeway hypothesis. That is, for somewhat different reasons, the formal models in both papers concluded that valence-advantaged candidates would not use that advantage to shirk on their ideological positioning vis-à-vis their electorates’ preferences. Both papers anticipated the positive relationship between the valence and ideological dimensions of representation reported in Figure 9.3, but neither offered an empirical test. Neither did these scholars consider the problem of cross-pressured districts that arises when the stronger candidate on valence is not the candidate closer to the district electorate’s preferences. Because the findings in this study supporting alignment between the two dimensions amount to one of the ways the study contributes to the “good news” about the electoral process, it is worth testing the alignment hypothesis in the context of the multivariate analysis of ideological representation. Figure 9.3 shows the partial effect of the winning candidate’s valence advantage over the losing candidate on the same candidates’ relative proximity advantage, estimated from the model in the first column of Table 9.4, except that relative valence advantage is an added covariate. This figure shows that the alignment between the two dimensions survives wholly intact when winning vs. losing candidates are compared in a model that includes the structure of district ideology, the winner’s ideological extremism, and the candidates’ resources. This analysis raises the question of whether it is appropriate to think of the valence advantage of the winning candidate over the loser as an independent variable explaining candidate ideological positioning. The emphasis thus far has been on two independent dimensions of electoral representation: ideological proximity and valence. However, the leeway hypothesis effectively treats a valence advantage as a cause of candidate 8

The positive relationship holds equally when the relationship is compared between winning and losing candidates after the election (see Figure 9.3). That is, winning candidates stronger on valence also tend to be ideologically closer to their district electorates’ ideological preferences than losing candidates. The correlation when the data are organized by comparing winners vs. losers on each dimension is similar (r = .29; p < .001).

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Winner's Proximity Advantage over the Loser −.5 0 .5 1

Conclusion

−2

−1 0 1 Winner's Valence Advantage over the Loser

2

figure 9.3 Additional Evidence for the Alignment Hypothesis: Partial Effect of Valence Advantage on Proximity Advantage of Winning Candidates Compared with Losing Candidates, 2010 Note: Estimated from Equation [1], Table 9.3, including relative winner–loser valence advantage as an additional covariate.

positioning: candidates’ valence advantage frees them to shirk on ideology. The alignment hypothesis, in contrast, does not treat valence advantage as a cause, although it does expect a relationship: there is a positive correlation between valence and proximity not because politicians trade support they gain from their valence advantage to offset losses from shirking on ideology, but because successful candidates must be attentive to voters’ fundamental interests in policy and valence.9

conclusion We gain considerable insight into how candidates and officeholders relate to their electorates by recognizing that electoral representation results from the ideological and valence dimensions of voter interests. For instance, it is clear that different factors affect representation on each 9

This does not resolve the question of whether candidate valence is exogenous and may affect positioning. For examples of empirical analysis that treat valence as exogenous, see Stone and Simas (2010), Adams et al. (2011), and Buttice and Stone (2012).

184 Getting it Right? Valence and Ideology in District Representation

dimension, even though we have seen that the two dimensions are themselves positively correlated. An example is incumbency, often seen as a distorting factor in congressional elections because it relates to strong resource asymmetries between candidates. If we look at all districts, there is actually little evidence that incumbency advances or impedes correct outcomes. When we separate aligned and cross-pressured districts, however, we can see that incumbency serves as a powerful proxy of valence representation. Among aligned districts where there is no conflict between valence and ideological representation, incumbency is among the strongest factors associated with increased representation. In crosspressured districts where district electorates must choose between their interests in valence and ideology, incumbency increases valence representation at the expense of ideological representation. When we examine the effect of incumbency on the degree of valence representation, it has a positive effect, whether we examine the winner relative to the loser or the leadership valence of winning candidates. Elections seem to do a reasonably good job of producing outcomes consistent with electorates’ interests, especially if we focus on the choice dimension of representation. Electorates, more often than not by a fair margin, choose the better of the two candidates. This, of course, is especially clear in aligned districts where electorates can make a correct choice on both dimensions by choosing the stronger candidate on either dimension. When we shift the focus to representation provided by incumbents rather than comparing the quality of the opposing candidates, the ideological extremism of candidates relative to their districts produces patterns of ideological representation seriously at odds with the median-voter model. This was apparent in Chapter 8, and in this chapter we saw that a fair portion of the distance between candidates and their districts cannot be explained by the structure of district preferences. While it is true that district ideological extremism and the extremism of winning candidates’ partisan supporters help account for incumbent extremism, other forces are clearly at work pushing incumbents to greater extremes than district or partisan constituents’ preferences.

Conclusion

The optimistic tone of my argument throughout this book rests primarily on five empirical claims that are supported by the evidence and analysis I have presented. These claims have their greatest force when the focus is on choice, as when voters choose the better qualified candidate and the outcomes that result from elections are assessed as choices of one candidate over the other: (1) Voters act on their interests. Far more commonly than not voters choose the candidate better aligned with their interests by the criteria set forth in the Proximity and Valence Rules. Overall levels of correct voting by these rules outweigh incorrect voting by better than 6:1 when the choices between candidates for voters are aligned. By about 4:1, they vote their ideological interests over their valence interests when voters are cross-pressured between their ideological and valence interests. However, as voters are closer to the indifference point between the candidates on ideology, correct voting on valence increases. (2) Politicians anticipate voter reactions. High-quality politicians are strategic about when they run, and they tend to enter races when their prospects are good and to refrain from entering when their chances are poor. The structure of opportunity, including the partisan makeup of electorates, goes a long way toward explaining why proximity and valence differentials affect election outcomes. (3) Despite the force of anticipated reactions, voters’ reactions on Election Day have observable effects on vote shares. If anticipated 185

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reactions worked perfectly, there would be little or no empirical daylight to observe voters’ ability to choose the stronger candidate. Weaker candidates would anticipate losing, they would take positions less aligned with their electorates’ interests, and they would be weaker in the leadership valence qualities voters value. However, there is leakage in strategic entry and related behaviors reflecting anticipated reactions, so voters’ collective choices are not perfectly anticipated by politicians. As a result, we observe the effects of proximity and valence differentials on Election Day, both in the voting decisions of individual voters and in the voting behavior of electorates. (4) Electorates more often than not select higher quality candidates over their lower quality opponents. When candidates are aligned, district electorates choose the better candidate on ideology and valence by about a 2:1 margin. When district electorates are crosspressured between their ideological and valence interests, they select the stronger candidate on valence at the same rate as they select the candidate closer on ideology.1 (5) Higher quality candidates on valence also tend to be closer to district ideological preferences consistent with the alignment hypothesis. This suggests that candidates are attentive to voters’ interests in policy and valence. In contrast to the leeway hypothesis, there is no evidence that candidates tend to trade support from their strength on valence for the opportunity to shirk on policy. This may be rooted in uncertainty and politicians’ ambition for careers in electoral politics. In an uncertain world, why hand an opponent a strategic advantage on one dimension, no matter how great the advantage on the other? To do so may risk electoral defeat in the short term, but seems especially counterproductive to the long-term interests politicians have in winning elections in a future where the shadow of uncertainty darkens potential pitfalls and vulnerabilities in ways difficult or impossible to predict. 1

Whereas cross-pressured electorates split evenly between correct valence and ideological outcomes, at the individual level (point 1 above) the split is substantially in favor of proximity over valence voting. This difference is because correct proximity votes do not necessarily aggregate to correct aggregate outcomes, since individual voters cast correct votes for the winning and losing candidates. Correct valence voting by individuals, in contrast, does aggregate to correct valence outcomes because more votes for the valence-advantaged candidate directly increases the chances that candidate wins.

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As noted, these conclusions apply most consistently to analysis focusing on the implications of political choice. When the question is whether voters and electorates tend to choose the stronger candidate, the answer is positive. When the question is whether the higher quality candidate on the ideological and valence dimensions tends to win elections, the answer is affirmative. Elections are fundamentally about choice, and the primary reasons for doubt about the capacity of voters and the efficacy of elections tend to lose their significance when the focus is on how voters respond to the choices on ideology and valence they are offered. Indeed, some of the reasons expressed by critics such as partisan polarization and incumbency lend themselves to advancing, rather than distorting, voters’ ability to choose based on their fundamental interests. For example, the contemporary polarization between the parties provides a supportive context for proximity voting. In the current regime of partisan divergence between elites and constituents, voting consistent with party identification sharply increases proximity voting rates. Moreover, awareness of party positions is both common in the electorate and strongly associated with higher levels of proximity voting. By sorting candidates and voters into ideological camps, partisan polarization facilitates proximity voting, although the minority of voters (about 20 percent) whose party identification is contrary to their ideological interests as defined by the Proximity Rule vote 4:1 with their party over their ideological interests. At the same time, of course, polarization increases the distance of winning candidates from their district electorates’ ideological preferences. Voters manage to vote consistent with their interests in supporting the candidate whose ideological positions better align with their own preferences, but only a minority of voters can accurately place the ideological positions of the candidates vying for their support. We can accept the widely supported finding that voters are not aware about nor deeply engaged in politics, without being forced to conclude that they cannot vote their interests (Popkin 1994; Sniderman 2000; Sniderman et al. 1991). In addition to concerns about voter ignorance and distortions based on partisanship, skeptics emphasize the resource asymmetries between opposing candidates in House elections. Incumbents are said to win elections handily because they have huge financial and visibility advantages that make it impossible for all but a handful of challengers to mount competitive campaigns against them. This argument, however, assumes that incumbency and financial backing aside, incumbents and challengers

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start with a more or less level playing field. That is manifestly untrue, as most House districts have distinct partisan predispositions reflecting the dominance of one party or the other. Incumbents win because they are usually elected from the dominant party in the district. They raise more money than their challengers for the same reason, which is to say they raise more money because their prospects for election are strong. They win, in other words, not primarily because they raise more money and have other advantages associated with their office. They win because they are more aligned with their districts’ partisan and ideological interests than their opponents. Indeed, we have seen little evidence of distortion due to financial advantage, and none associated with incumbency. Instead, the consistent finding is that incumbency serves as a useful proxy for voters seeking to advance their valence interests, even if it can mean voting against their ideological interests.

a realist view? By positing the Proximity and Valence Rules, I began this book with what I see as voters’ fundamental interests in elections. The evidence I present supporting and building on these two rules amounts to the reason for my optimistic take on the ability of voters to promote quality control in elections by the twin mechanisms of anticipated reactions by strategic politicians, and voters’ own responses to candidate differences on Election Day. A persistent finding in this book is the power of party. We see it when comparing the model fit between the Fundamentals and Conventional models of individual voting choice and in the parallel models of district electorates’ vote shares, we see it in the relationship between district ideological preferences and the ideological positions of candidates, and we see it in the ideological extremism of incumbent Representatives. How, then, to reconcile the Proximity and Valence Rules with the obvious importance of party to voters’ and electorates’ behavior, and to the nature of ideological representation in the system? A recent “realist” (from my perspective, “skeptical”) take on this question implies that I am wrong about the fundamental effect of ideology on voters’ and electorates’ behavior. According to Achen and Bartels (2016), party and associated group identifications are fundamental, and the ideological positions voters adopt are, by a large margin, driven by these identifications. This perspective renders ideology and the Proximity Rule subservient to party identification in that voters adopt ideological positions in response to their party identification, rather than the other way

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around. It also is a view at home with the strong impact of party on voters’ choices and on the extreme positions candidates adopt. As we would expect of two scholars of Achen’s and Bartels’ caliber, the analysis in their book is broad in scope, subtle, and insightful. In a critical chapter, for example, they present striking evidence in favor of group-identification explanations of the shift toward the Republican Party among white southerners in the decades between 1964 and 1992, and changes in abortion attitudes following Roe v. Wade. As Achen and Bartels summarize their argument (2016, 266): For most people, partisanship is not a carrier of ideology but a reflection of judgments about where ‘people like me’ belong. They do not always get that right, but they have much more success than they would constructing their political loyalties on the basis of ideology and policy convictions. Then, often enough, they let their party tell them what to think about the issues of the day. As a result, selfdescribed liberals mostly wind up with the Democrats and conservatives with the Republicans. But the usual interpretation of that relationship supplied by the folk theory of democracy is quite misleading. If election outcomes have policy content, it comes primarily, not from voters, but from the relationships between parties and social groups.

To clarify the stakes as they apply to the analysis in this book, by Sniderman’s (Sniderman and Stiglitz 2012; Sniderman 2016) categories, 71 percent of voters in the 2010 survey were “programmatic partisans.” That is, they were sorted (their ideological self-identification conformed to the dominant ideological position of their party) and they were aware of the ideological differences between the parties (they placed the Democratic Party to the left of the Republican Party).2 On Achen and Bartels’ telling, this overlap is mostly due to the influence of party identification on ideology (Miller 2000), as a rationalization of long-standing partisan loyalties, with little in the way of substance to the ideological component. This is not the place for a blow-by-blow comparison of my findings and conclusions with those presented by Achen and Bartels. Indeed, if such a comparison were to be undertaken, I suspect I would be inclined to agree with Bartels’ comment that our differences are in important ways a matter of perspective (personal communication). Certainly I do not question any of the empirical analysis they present. Where we differ is in what these results may mean for how well elections work. So, let me briefly suggest how my perspective leads to a different reading of the evidence. 2

I classify moderates as unsorted. Aware moderates are by far the largest group among voters who were not classified as programmatic partisans.

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First, the debate about what is causing what with respect to party identification and ideology says nothing about the Valence Rule. I have found consistent support for the impact of candidate valence differentials on voters’ and electorates’ choices, independent of partisanship. So, at one level, the addition of the Valence Rule to the “folk theory” of democracy remains unchallenged by their discussion. Of course, I have shown that voters’ judgments about candidates’ leadership valence qualities are strongly influenced by their partisanship (Table 2.1). For that matter, so are voters’ perceptions of House candidates’ ideological positions (Table A.4.2). However, it is also true that controlling for partisan bias of this sort, voters’ judgments of candidates’ valence qualities and ideological positions are remarkably consistent with aggregated expert raters’ valence judgments and ideological placements of the candidates. On two critical ingredients of the valence-modified folk theory, therefore, voters appear to be adept at judging candidates’ qualities and ideological positions, even when those candidates are not especially visible and when one candidate typically has a substantial resource advantage over the other. These findings about the quality of voters’ perceptions of candidates’ positions and leadership skills and qualities do not comport with a view of voters as locked into partisan camps with little in the way of independent judgment. Second, much of my analysis emphasizes voters’ responses to the choices they are offered. By that standard, individual voters (and electorates) do quite well in choosing the candidate closer to them on ideology. This emphasis on choice is different from the perspective one gets from looking at incumbents’ ideological position-taking relative to districts or individual voters. On that analysis, both the Achen–Bartels’ analysis (see their ch. 2) and my own analysis (Chapters 3 and 8) agree that elected office holders are extreme relative to their districts (more on this point in the next section). The perspective provided by focusing on choice is important, especially if the question is voter competence in general elections. Voters in this context can do no better than making the most of the choice with which they are faced. If we focus on all the evidence of voter ignorance and disengagement, things do not look good. If instead we focus on how well voters choose between the candidates on offer, a criterion much less studied yet far more relevant to assessing voter competence, voters perform very well. Third, speaking to the overlap between party identification and ideology, I think a fair-minded assessment of the evidence in this book would not equate the strength of the Proximity Rule with the Fundamentals

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model, especially as it is applied to individual voters’ choice. The Fundamentals model was designed to identify the ceiling of the possible effect of the spatial logic (and valence differentials) to voters’ electoral choices. As Chapter 4 showed, that ceiling is very high – almost certainly too high (a shift in the probability of voting Republican of .73 when those much closer to the Democratic candidate are compared with those closer to the Republican – see Table 4.2). As I suggest in Chapter 5, party identification is a strong facilitator of correct proximity voting among those aware and among those unaware of candidate positions. Much of this effect could be due to voters being motivated entirely by party identification, with no thought whatsoever to the policy-based logic behind the spatial model. On that interpretation, the much more modest effect of the proximity differentials found in the Combined model that includes party identification and a host of other covariates suggests a floor of the effect of the Proximity Rule. I suspect that the true effect of the Proximity Rule is somewhere between the estimates found in these two models. Keep in mind that the effect of the Proximity Rule is strong among strict independents, who, by definition, lack any guidance from party identification (see Figure 4.5(a)).3 And, if the effect of candidate proximity differentials is strong among strict independents who are less engaged and informed than partisans, it is reasonable to assume that many voters whose partisanship facilitates correct voting on the ideological difference between candidates are not merely automatons following partisan attachments with no understanding of the policy consequences of party differences. Finally, we must ask what the Proximity Rule expects of voters. Is our expectation that voters come to elections with a fully formed ideology that they have developed based on thinking deeply and independently about the values and policy debates on the public agenda? If so, we will most often be disappointed. I prefer, instead, to think of voters as re-actors rather than actors. The choices they make are reactions to candidate and party differences, not to an open-ended query about their definition of the good society. Are their choices a simple translation of socialized, pre-rational identifications learned, as Morris Fiorina (1981) put it, at “mommy’s knee?” For most voters, it seems preferable to think

3

The effect of the proximity differential in the Fundamentals model that includes party identification comparing strict independent voters on the same categories of the proximity differential as in Table 4.2 is +.48.

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of ideological self-identifications and the overlap between party identification and ideology as reflecting a certain level of comfort on policy and the values behind policy differences between the parties and candidates. That comfort is at least as likely to come from one’s social affiliations as it is from some deeply reasoned ideological perspective. Indeed, we might ask where else it would come from. If voters take cues from their church or work affiliations, or members of other social affiliations to determine that “people like me” are in one or the other party, that seems both reasonable and a fair representation of their political interests. Moreover, if they take the lead from party leaders whom they have come to trust, why is that surprising or unsettling? John Zaller’s (1992) theory of public opinion has a healthy dose of elite leadership and voter ambivalence about complex issues of public policy, and using party identification as a way to organize and think about predispositions toward policy issues is efficient and consistent with fundamental ideas about how democracy works.

the puzzle of incumbent extremism Whatever one makes of the relationship between party identification and ideology, once we step away from an analytic focus on choice, the puzzle of candidate ideological extremism is apparent. It is also a reason to be skeptical about the efficacy of elections, to say nothing of the medianvoter model (Achen and Bartels 2016; Bartels et al. 2016; Bartels 2016). Although we saw in Chapters 8 and 9 that electorates tend to choose the ideologically more representative candidate, the candidate closer to district preferences is decidedly more extreme than district preferences. The fact that both parties’ candidates are extreme relative to their district shows that even when electorates choose the closer candidate, they end up with a Representative who is out of step with their ideological preferences. Why does this occur, and what consequences follow for our understanding of district representation? The Partisan Model of District Representation There can be little doubt that over the recent decades of partisan polarization in US politics, especially since the realignment of the white South in response to the civil rights movement, the system of district representation in Congress has shifted toward a partisan model. Democratic voters in districts throughout the country are in more agreement with the national Democratic Party’s liberal agenda; Republican Party voters

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table c.1 District Groups and Incumbent Ideological Placements (2010 Election Winners)

Mean ideological position of: District electorates Majority partisans Majority party activists Winning candidates Winners’ mean distance from: District electorates Majority partisans Majority party activists N

Democratic Winners

Republican Winners

.04 −.93 −1.71 −1.76

.50 1.61 2.27 2.17

1.80 .89 .49 (62)

1.67 .59 .27 (88)

across districts are similarly in agreement with the conservatism of the Republican Party. Cross-district variance in ideological preferences is due more to the partisan makeup of districts and less to ideological variation in the preferences of partisan voters. As a result, districts in which there is a Democratic plurality of voters tend to elect Democrats; districts with Republican pluralities elect Republicans. As seen in Chapter 8, party is not everything. Variation in Republican and Democratic candidate positions is responsive to district preferences, but the effect of partisan differences and candidate extremism linked to party is clear. The ideological extremism of incumbents relative to different constituency groups is summarized in Table C.1, which makes clear the partisan basis of who gets represented within districts. Majority partisans in both parties are substantially more extreme to the left or right than district electorates, as we have seen. Table C.1 also includes estimates of activists’ ideological preferences within districts, based on the mean ideological preferences of district informants in the winning candidates’ party. Democratic activists by this measure are substantially more extreme in their liberal preferences than Democratic identifiers, just as Republican activists identify as much more conservative than rank-and-file Republican identifiers. Indeed, Democratic activists in the aggregate are only .06 units less liberal than incumbents from districts that sent Democrats to represent them in Washington as a result of the 2010 elections. Republican activists in the aggregate are .10 units more extreme than winning Republican candidates in 2010. Matching up these three groups within districts – the preferences of district electorates, majority partisans, and

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majority-party activists – with the positions of incumbents in the 112th Congress elected in 2010 demonstrates that incumbents were much closer to rank-and-file identifiers within their party than they were to the district electorate as a whole, and they were closer still to their party’s activists in the district. Richard Fenno (1978, 8–27) pointed out that Representatives think of constituencies as “nested” within the geographical district: the reelection constituency, the primary constituency, and the personal constituency composed of “intimates” and other close supporters. In a partisan era, it is not much of a stretch to think of these constituencies as increasingly committed to the ideological program of their party. The primary constituency in most districts is probably a somewhat more committed set of partisans than the rank-and-file identifiers in Table C.1, while the personal constituencies of Representatives is at best roughly approximated by our informant-activists. The simple pattern is this: the more partisan the constituents, the better their ideological preferences are represented. Therefore, it appears that the partisan model of representation, as captured by the partisan breakdown of district constituents, does a fair job of accounting for the ideological extremism of incumbent Representatives.4 Despite this evidence, there are reasons for doubting that the partisan model of district representation is a fully satisfactory explanation of incumbent and candidate extremism. There is nothing in the partisan model of district representation that insists that candidates will be more extreme in their ideological position-taking than their partisan electorates. If candidates count on their partisan supporters to back them in primary and general election campaigns, well and good from the perspective of the partisan model. Why should partisan supporters tolerate candidates whose positions are more extreme than their own preferences, when they can support a primary candidate closer to their own preferences? Incumbents are presumably aware that their partisan electorates may be wooed in a primary by a less extreme alternative – why do they fail to locate closer to their partisans’ preferences to shut off primary challenges of this sort? A related reason for doubting the partisan model explains candidate extremism rests on the logic of the Proximity Rule. If, as I have shown, 4

See Kujala (2016) for a detailed analysis consistent with this conclusion. Kujala has collected ideological-position data on district electorates, partisans within districts, and financial contributors by party and district based on large samples of all constituency subgroups and comparable measures of ideological positions, and finds contributors to be most aligned with incumbents and challengers in House races between 2002 and 2010.

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candidates closer to district preferences tend to attract more support, it would seem that incumbent extremism leaves substantial room for candidates closer to those preferences to mount successful challenges. The effect of party on the system of ideological representation is undeniable, but the median-voter logic is also evident in the data. It is difficult to see how, on the strength of these forces, an equilibrium in which candidates are routinely so extreme occurs. Candidates must raise money and attract other resources controlled by activists in their party, but the ultimate prize in elections is votes, not money or activist supporters. Whether we attribute candidate extremism to pressure from extremist activists or to the preferences of candidates themselves, an equilibrium that locates candidates between primary and general-election constituencies seems plausible (Aronson and Ordeshook 1972; Coleman 1972). On the strength of the partisan model of district representation, that equilibrium could be closer to the preferences of partisan voters than to the district electorate as a whole, but the Proximity Rule seems to militate against excessive polarization where candidates are even more extreme than their partisan supporters. Bawn et al. (2012) stress the importance of extremist “policy demanders” that control the resources (activist volunteers and financial contributions) that candidates need to mount successful campaigns, but asserting that extremists withhold critical resources if candidates stray too far from their ideological preferences begs the question of how these demanders can safely assume that candidate extremism is an equilibrium position for candidates in both parties. Voter Preferences And yet the hybrid model of district ideological representation developed in Chapter 9 and a good deal of other evidence (Bafumi and Herron 2010; Kujala 2016) support the conclusion that candidates routinely take ideological positions more extreme than their partisan supporters’ preferences.5 This pattern can be explained as resulting from candidates being captured by activists or other extremist sub-constituencies (Bishin 5

For an intriguing challenge to the conventional finding that elites are more extreme than voters, see Broockman (2016). Broockman’s argument rests on the idea that the explanation for the apparent extremism of elites is their consistency in taking liberal or conservative positions across a large number of issues, compared with voters who tend to be less consistent in this way. This critique applies to studies based on latent ideology measures composed of multiple items as opposed to this study, which relies primarily on the single symbolic ideology item.

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2009), or because candidates follow their own policy preferences that conform with other activists in their district. One possibility is that voters actually prefer extremists over candidates whose stands are more congruent with their own preferences. In considering two versions of this idea, I enter a frankly speculative mode. One possibility is that the Proximity Rule itself is in need of reformulation. One such reformulation is the directional model that inverts the expectations of the spatial model, conditioned on whether the voter and candidate are on the same side of an issue (Rabinowitz and Macdonald 1989). In this model, voters prefer extremist candidates over moderates because they prefer candidates whose intensity motivates them to pursue shared policy goals over candidates whose commitment to the policy is less intense.6 A number of scholars have attempted to test the directional vs. the spatial model, but it can be difficult in an observational study to find voters whose voting choice is expected to differ under the two models (Lewis and King 2000; Tomz and Houweling 2008). This is especially true in a polarized system where most candidates and voters take sides on issues consistent with their party. In experimental work testing the two models under controlled choices, the weight of evidence seems to support the spatial over the directional model (Claassen 2007; Tomz and Houweling 2008). Although I cannot test the directional against the proximity model, an implication related to its underlying logic may be relevant, especially in the deeply partisan context of the 2010 elections. In a polarized system, partisans may not be sensitive to the positions of candidates in their own party, giving them support regardless of their proximity to the candidate. A failure to respond to extremism by candidates in their own party is consistent with Sniderman and Stiglitz’s (2012) Latitude Prediction. Since we know that proximity differentials affect voting choice, this possibility must allow for responsiveness to relative proximity in the system. This could mean that independents respond to the Proximity Rule in choosing candidates and that opposite-party voters respond to their distance from candidates in the opposing party. This notion of asymmetric response to the distance of voters from candidates borrows from directional theory because most partisans can assume that they are on the same side of the ideological divide as candidates in their party. Independents, who cannot safely make that assumption, should be sensitive to their distance from candidates in both parties. Out-party voters may assume that candidates 6

Oddly, the model includes a penalty for candidates who are too intense.

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are on the opposing ideological side, but if opposing candidates are relatively moderate (or less “intense”) in the positions they adopt, they may reward that reduced distance by increasing their support for such candidates. Figure C.1 presents evidence that this sort of asymmetry is present in voters’ responses to candidates. Rather than estimate the effect of proximity differentials as in Chapter 4, the analysis in Figure C.1 examines the effect of the ideological distance between voters and each party’s candidate separately. In Figure C.1(a), Democratic identifiers are unresponsive in their voting to their ideological distance from Democratic candidates: their probability of voting for the Democrat does not vary with their ideological distance from the Democrat.7 In contrast, Republican voters are responsive to their distance from the Democratic candidate, in that Republicans who are close to the Democratic candidate are less likely to vote for the Republican than their fellow partisans who are more ideologically distant from the Democrat running in their district. Independents are more responsive than Republicans to the distance between their ideological positions and the positions of Democratic candidates, with independents close to the Democrat in their district more likely to vote Democratic than independents whose preferences are distant from the Democratic candidate. Figure C.1(b) shows that the asymmetric response works similarly with Republican candidates. Republican voters were unresponsive to variation in their distance from GOP candidates, while Democratic and independent voters closer to the Republican candidate were responsive as indicated by an increased probability of voting Republican. Thus, in both parties, partisans do not react to the distance between themselves and their party’s candidate, while independents and opposite-party identifiers are responsive to the distance between themselves and candidates.8 Asymmetry in voters’ perceptual bias is a possible mechanism for the asymmetric response of partisans to their ideological distance from candidates. Analysis of voters’ ideological distances from candidates reveals 7

8

The statistical model estimates the effects for voters whose ideological distances from the other candidate (in Figure C.1(a), distance from Republican candidates) is at the mean. The effects reported in Figure C.1 are estimated on a modified Fundamentals model that includes ideological distance from each candidate as separate covariates, party identification, demographic variables, and the sample design control. The asymmetric response to distance from candidates’ ideological positions conditioned on party replicates when I substitute the latent, issues-based measures of candidates’ and voters’ ideologies and estimate the model on the UC Davis module survey.

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1

(a) Distance from Democratic Candidates

Pr(Republican Vote) .6 .4

.8

Republicans

.2

Independents

0

Democrats

0

2 4 Respondent Ideological Distance from Democratic Candidate

6

1

(b) Distance from Republican Candidates

Pr(Republican Vote) .6 .4

.8

Republicans

.2

Independents

0

Democrats

0

2 4 Respondent Ideological Distance from Republican Candidate

6

figure c.1 Ideological Distance Effects for Republican and Democratic Candidates by Party Identification

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that partisans’ perceptions of their distance from candidates in their own party are only weakly related to their actual distance as measured by district informants’ placements of the candidates. In contrast, the perceived distances by independents and voters in the opposing party are much more strongly related to the distances calculated based on informant placements. The pattern holds for Republicans perceiving Republican candidates. In the case of each party’s candidates, then, the effect of the informant-based measure on voters’ perceptions of the distance between their preferences and candidates’ positions is weakest among the partisans of the candidates; the strongest effect is among the opposite party’s voters. In sum, there is reason to speculate that partisan constituents are less responsive to their ideological distance from candidates in their own party than they are to their distance from opposing party’s candidates. This sort of heterogeneity in voter response to candidate proximity is masked by proximity differentials that assume symmetric responses. The relevance of this exercise to the puzzle of candidate extremism is that partisans forgive extreme positions taken by candidates in their own party. If voters in a polarized system are unresponsive to candidate extremism by candidates in their party while being more aware of and responsive to their ideological proximity to candidates in the opposing party, there may be incentives for candidates who rely on their partisan voters to get elected to adopt ideological positions more extreme than those voters’ preferences. Still another possibility is consistent with these findings if partisans actually want candidates from their party to adopt extreme positions in campaigns. In electing individuals to a legislature, voters may conclude that extreme candidates will be more likely to push policy in their desired direction than moderate (more proximate) candidates. This reasoning roughly coincides with a discounting model of choice, another alternative to the Proximity Rule. In discounting models, voters are more concerned with policy outcomes than they are with the policy stands candidates or parties take. For example, voters may compare the policy status quo with the policy likely to result if their preferred candidate wins the election. Because of the inertia in a complex legislature like the US House of Representatives (to say nothing of the constitutionally interdependent institutions that must coordinate to change policy), voters may estimate that extremist candidates are more likely to shift policy in their preferred direction than candidates who adopt positions congruent with their interests (Grofman 1985; Lacy and Paolino 1998).

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Orit Kedar (2005) suggests a discounting model in which moderate voters, concerned with policy results rather than party platform positions, support extremist parties whose platforms are at odds with their own preferences: Perhaps voters, predicting their vote to be watered down along the path, prefer parties to hold positions more extreme than their own opinions …If voters are concerned with platforms, ideological incongruence between voters and parties raises a potential concern of deficient representation. If, however, voters are concerned with policy outcomes, they might prefer parties’ positions on issues to differ from their own views, and therefore this discrepancy is of less concern. (Kedar 2005)

Kedar’s model and analysis apply most directly to comparisons between two-party systems in which voters’ policy choices have a direct path to policy (elect a party that controls Parliament and that party will implement its policy proposals) and multi-party systems in which post-election coalition building interferes with the link between the vote and a “direct path” to policy. However, as Kedar suggests, a similar logic may apply to legislative elections in systems of separated powers that also interfere with simple majority-building links to policy (Adams et al. 2004; Alesina and Rosenthal 1995).

The Relevance of Valence in Extremist Models The relevance of valence to voting choice, election outcomes, and representation is a reason for treating the foregoing as speculative. Why should voters who see the election as an opening bid in a game to alter the status quo in an institutional environment organized to resist change also value the valence qualities in the candidates they support? It is possible, of course, that some valence qualities such as personal integrity are associated with extreme positions and unbending opposition to the opposing party’s positions. Other skills and traits such as the ability to work effectively with other leaders and to solve pressing problems of public policy suggest the willingness to compromise as a desired leadership quality. The most compelling reason for the leadership-valence dimension of representation is that officeholders with these qualities can be trusted to handle the many tasks and responsibilities of a Member of Congress, even if their behavior cannot always be directly observed. Critical among these tasks is the business of negotiating policy compromises necessary to build successful coalitions across the many power centers in American national

Toward a Defense of the Partisan-Hybrid Model

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government. Members of Congress high in leadership qualities and skills may be more extreme in their policy positions than their constituents, but they will also be more effective legislators, more honest brokers, and more skilled in navigating the policy process on behalf of their constituents. If voters prefer extreme legislators who are able to shift policy in a positive direction, their preference for legislators high in valence qualities should make the process capable of addressing widely perceived problems (Adler and Wilkerson 2012). The result may be a policy process less gridlocked and less dysfunctional than would be the case based on the ideological positions of legislators and parties.

toward a normative defense of the partisan-hybrid model Whatever the explanation is for candidates adopting extreme ideological positions relative to their constituents, partisan polarization is more or less a permanent part of the representation landscape. The partisanhybrid model is meant to describe a system characterized by partisanship alongside one that also responds to district median-voters. Another way of stating this is that representation in House elections reflects a component linked to the national partisan policy debate combined with a local effect reflecting district preferences. A normative defense of this pattern of representation would first and foremost have to reconcile itself to a relatively modest median-voter effect. This is not an easy lift. The appeal of the median-voter logic is based on voter equality in the electoral process: the place of the median voter occurs in a two-candidate race because each voter has equal weight in determining the outcome and, under the assumptions of the standard spatial model, the median voter is pivotal in making the majority. A departure from the median voter’s preferences indicates some form of inequality in the electorate such that activists, contributors, or partisans have disproportionate weight in determining the election outcome and, therefore, the ideological positioning of the winning candidate. In a word, a significant departure from median voters’ preferences in election outcomes indicates distortion in the process of representation. What additional considerations should weigh when assessing processes of district ideological representation? One implication of the medianvoter logic is that the representatives in Congress are motivated by local concerns. Congress, however, is a national policy-making institution. Critics of a Congress full of locally motivated members point out that as

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Conclusion

national policy-making becomes particularized, its members search for ways to convert national policy-making to locally advantageous policy moves. To be clear, the median-voter logic does not directly imply universalism and particularism in Congress (Mayhew 1974; Weingast 1979), but the implications of the median-voter model of representation are undeniably local or district-centered. A defense of the partisan-hybrid model, then, might recognize its potential for balancing local electoral interests with the national policy-making role of Congress. As advocates of strong parties remind us, the parties are uniquely able to focus attention on the national implications of policy debates and promote collective responsibility in an institution composed of individuals accountable to local electorates. A pattern of representation that incorporates interests linked to national policy debates and unique district interests may not be a bad solution to a problem in thinking about representation that has been with us at least since Edmund Burke. Polarization is a political environment supportive of party government in Congress (Rohde 1991), but we have seen that it does not preclude significant district electoral influence on ideological position-taking by members of Congress. Moreover, the emphasis on partisan polarization can lead to over-emphasis on partisan conflict as a zero-sum game, with concomitant underappreciation of the incentive and ability of members to cooperate across party lines (Adler and Wilkerson 2014).

elections and institutional effectiveness Although the analysis in this book offers an optimistic reading of how well elections work, it is by no means clear that this implies Congress as an institution will meet popular expectations for effectiveness, even granting that the electoral process selects for valence-advantaged candidates. David Mayhew’s (1974) classic assessment of the electoral connection in Congress is that there is a fundamental tension between the individual reelection incentives of members and the functioning of Congress as an institution. It is possible to imagine a Congress in which the process resulting in the election of its members meets standards such as implied by the Proximity and Valence Rules, while failing to meet expectations as an institution. Valence aside, citizens tend to react negatively to congressional inaction, gridlock, and obstructionism. The constitutional system of mid-term elections and interdependence among the national policy-making institutions manufactures multiple opportunities for frustration. In this context, primary elections encourage candidates to attend

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to more extreme interests in their district because the nomination campaign comes first and candidates must attract primary voters and others with the resources needed to run in the general election (Hill 2015). It is tempting to conclude that any system of democratic governance is a breeding ground for discontent. Consider the median-voter vs. partisan models of representation. In the current regime of partisan polarization, voters are more aware of the national policy stakes in elections consistent with responsible party models, and high levels of proximity voting are one consequence. We have seen that when party identification and ideological proximity are at odds, voters vote substantially more with their party identification, a clear indication that reduced polarization would produce more “spatial errors” in voting. Although the same connection between party and spatially correct outcomes is more difficult to draw for district electorates, it seems reasonable to suppose that ideological representation of electorates’ preferences would be reduced as well, at least by the criteria of correct outcomes. If the median-voter model prevails, electorates should make more spatially incorrect votes, but errors would be less consequential because the candidates would be closer together. At the limit, candidates would position themselves at the median voter’s preferences, and both candidates would be “spatially correct.” If it is possible for elections to work well while the institutions to which elected leaders are sent are highly dysfunctional, it must also be said that ideological polarization need not impair the functioning of government institutions. The evidence on this question is mixed and ripe for further research. Bartels et al. (2016) present an interesting analysis linking local responsiveness to divergence of the House median from the national electorate’s preferences. On the other hand, others have found that voters respond to party polarization by subordinating local candidate differences to the performance of the partisan majority (Jones 2010; Jones and McDermott 2009). This sort of collective responsibility is most likely to be enforced when the parties are unified and divergent. Under these conditions, as well, voters comprehend the policy differences between the parties. National institutions may succeed in making significant policy changes even with polarization when one party controls the presidency and Congress. The Affordable Care Act of 2010 is but one recent example. The problem lies more in the intersection of polarization and a constitutional order that imposes a short time-frame on presidential majorities as mid-term elections carry the threat of undoing a partisan mandate two years into a presidency.

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Whatever the larger institutional consequences may be, the question of how voters and electorates choose and the consequences for the representation electorates experience is a fundamental link in our understanding of modern representative democracies. The framework in this book proposes to understand the choices made by comprehending the choices on offer, even if the choices in front of voters are less than ideal. In rethinking the capacity of voters and electorates to produce representative outcomes, this analysis deepens our appreciation of voters and electorates to do reasonably well with the choices they face, and it challenges skeptics of the electoral process who assume voters must meet high standards of information, engagement, and awareness.

Appendix Issues in the Use of Expert Informants

Multiple questions about the reliability and validity of informant-based measures of candidates’ ideological positions and valence characteristics and skills can be raised. These issues as they relate to this study are addressed in several publications, including the appendices to published articles (Maestas et al. 2014; Buttice and Stone 2012; Stone and Simas 2010) and in online appendices to this book.1 The purpose of this brief appendix is to summarize the evidence on these questions. One characteristic of informant ratings is that they are subject to partisan bias. This bias is especially pronounced in the case of candidates’ leadership valence characteristics and skills. Partisan bias is ameliorated in two ways: by correcting for partisan bias in individual informants’ ratings prior to aggregating those ratings to the level of the candidate estimated by the mean informant rating; and by the aggregation of individual ratings and judgments such that uncorrected sources of bias tend to cancel out (Maestas et al. 2014). A variety of tests of the reliability of informant-based measures provide assurance that they meet or exceed acceptable standards, although aggregated informant ratings of candidates’ valence qualities are less reliable than mean placements of candidates’ ideological positions. Testing the validity of informants’ placements of incumbents is easiest because of readily available criterion variables in the form of DW-Nominate and other roll-call based measures. The R-square relationship between informant and a roll-call measure based on DW-Nominate and ADA scores is .94, indicating a very close fit between the informant and criterion variables. The R-square drops but is still strong and highly significant 1

www.cambridge.org/candidates_and_voters

205

Appendix

206

table a.1 Replicating Table 4.2 with Opposite-Party Informants Fundamentals Model Proximity differential Valence differential

0.775∗∗∗ (0.02) 0.023 (0.07)

Party identification Presidential approval Obama care support Tea Party support Experience differential Spending differential Democratic held seat Open seat Constant Pseudo R-square N Log likelihood

−0.050 (0.19) 0.509 11865 −3504.2

Standard Model

Combined Model

0.645∗∗∗ (0.05) −0.659∗∗∗ (0.06) 0.762∗∗∗ (0.17) 0.543∗∗∗ (0.06) 0.241∗ (0.11) 0.157∗∗ (0.05) 0.167 (0.35) 0.136 (0.20) −0.594∗ (0.30) 0.725 11865 −1963.8

0.223∗∗∗ (0.03) 0.260∗∗ (0.08) 0.563∗∗∗ (0.05) −0.610∗∗∗ (0.06) 0.773∗∗∗ (0.16) 0.420∗∗∗ (0.06) 0.215∗ (0.11) 0.133∗ (0.05) 0.081 (0.34) 0.364 (0.19) −0.585∗ (0.29) 0.735 11865 −1888.8

∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Note: Demographic and design effects estimated but not reported. Cell entries are logit coefficients with robust standard errors clustered by district in parentheses below each coefficient.

with the analysis restricted to incumbents in each party (.59 and .40 for Democrats and Republicans, respectively). Thus, it is clear that the strong validity of the informant-based measure is not due simply to informants sorting Democrats and Republicans into liberal and conservative camps (Tausanovitch and Warshaw 2015), although limiting the analysis to within-party comparisons necessarily restricts the variance, especially for Republicans. Validating the informant-based measure of candidates’ leadership valence scores is more difficult for the lack of clear criterion variables. However, the validation analysis shows significant effects of

1

Appendix

207

Proportion of Correct Votes .4 .2 .6 .8

Correct Proximity Vote, All Voters

Correct Valence Vote, Cross-Pressured Voters

0

Incorrect Vote, All Voters

0

1 2 3 Distance of Voter from Candidates' Ideological Cut Point

4

figure a.1 Replicating Figure 5.1 with Opposite-Party Informants Note: All measures in this figure based on opposite-party informant candidate placements or valence ratings.

the legislative performance of incumbents, the presence of a scandal, and the mean constituent ratings on valence. An issue taken up in some detail in the online supplementary materials is the possible “measurement-endogeneity” problem discussed in Chapter 2, which arises because the district expert observes we employed as informants were themselves in the midst of the campaigns we asked them to report on. Along with every other constituent in their district, they were targeted by campaigns attempting to convince them of the quality of their candidate (and the scurrilous nature of their opponent) and the reasonableness of their policy positions (alongside the hare-brained schemes of the opposition). This means that informants may have reported what the campaigns wanted them to know and judge about the candidates, rather than making informed and independent judgments. There is no simple solution to the measurement-endogeneity problem, but the logic of the tests reported here and in the supplementary materials is to use partisan bias as a bulwark against the problem since opposite-party informants ought to be most inured against the campaign appeals of candidates. Candidate differentials, therefore, are estimated

Appendix

208

table a.2 Replicating Table 7.2 with Opposite-Party Informants Fundamentals Model 6.109∗∗ (1.92)

District proximity diff. Reduction in Effecta Valence differential

–

Reduction in Effecta Republican district vote share

–

2.602$ (1.36)

Republican incumbent

Model 2

Model 3

Model 4

1.068 (0.66) 82% 2.214∗∗∗ (0.47) 15% 0.828∗∗∗

1.203 (0.63) 80% 1.552∗∗ (0.48) 40% 0.715∗∗∗

1.328∗∗ (0.58) 78% 1.320∗∗ (0.44) 49% 0.614∗∗∗

(0.04) 8.900∗∗∗ (0.99)

(0.05) 3.856∗ (1.58) 14.150∗∗∗

(0.05) −0.763 (2.75) 10.437∗∗

(3.59)

(3.49) 0.656 (0.80) 1.465∗∗∗ (0.30) 12.303 (8.41) 0.956 131

Republican candidate’s prospects Experience differential Spending differential Constant Adjusted R-square N ∗ a

73.351∗∗ (25.91) 0.480 131

−0.439 (9.25) 0.942 131

2.384 (8.77) 0.948 131

p