ECOLOGICAL INFERENCE AND AGGREGATE ANALYSIS OF ELECTIONS by Won-ho Park A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Political Science) in The University of Michigan 2008 Doctoral Committee: Professor Christopher H. Achen, Co-Chair, Princeton University Professor Kenneth W. Kollman, Co-Chair Professor John E. Jackson Professor Michael W. Traugott °c Won-ho Park 2008 All Rights Reserved To my parents, Yong-Tae Park and Kyung-ja Lee ii ACKNOWLEDGEMENTS I thank my advisors, Chris Achen, Ken Kollman, John Jackson, and Mike Trau- gott for their support and guidances over the years. I am also indebted to JungHwa Lee, Mike Hanmer, Sang-jung Han, Corrine McConnaughy, Ismail White, Clint Peinhardt, and Kwang-Il Yoon for many insights and lasting friendships. The project was supported by the Institute of International Education (Fulbright Grad- uate Degree Study Awards), the Rotary International (Rotary Ambassadorial Schol- arship), the American National Election Studies (Pre-Doctorate Research Award), the Horrace H. Rackham Graduate School (Dissertation Fellowship), and the De- partment of Political Science at the University of Michigan. iii TABLE OF CONTENTS DEDICATION ............................................. ii ACKNOWLEDGEMENTS ...................................... iii LIST OF FIGURES ........................................... vi LIST OF TABLES ............................................ vii CHAPTER I. Introduction ......................................... 1 1.1 The Study of Elections and Voting . 1 1.2 Limitations of Survey Studies in Studying Electoral Politics . 2 1.3 The Ecological Inference Problem . 6 1.4 The Voter Transition model . 7 1.5 Outline of Chapters . 9 1.5.1 Current Strategies . 9 1.5.2 Extensions to Multiparty Systems . 10 1.5.3 The Covariate Model . 11 II. Voter Transition Rates and Ecological Inference .................... 14 2.1 Introduction . 14 2.2 Voter Transition Rates and the Failure of Generic Ecological Estimators . 16 2.2.1 The Baseline Model: Ecological Regression . 16 2.2.2 King’s Estimation Procedure for Ecological Inference . 18 2.2.3 Empirical Examples . 20 2.3 Aggregation Bias, Non-linearity and Disaggregation Consistency . 23 2.3.1 The Direction of Aggregation Bias in VTR Setup . 23 2.3.2 Non-Linearity Problems . 27 2.3.3 Do “Better” Data Always Help?: Disaggregation Consistency . 29 2.4 Thomsen’s Nonlinear Model . 31 2.4.1 Modeling Partisanship . 31 2.4.2 Bias in the Aggregate Correlation . 34 2.5 Empirical Results . 38 2.6 Conclusion . 41 III. Ecological Inference in Multiparty Systems ....................... 44 3.1 Introduction . 44 3.2 Voter Transition Rates in Multiparty Systems: Current Methods . 45 3.2.1 Multivariate Extension of the Constrained Regression . 46 3.2.2 The King Estimator in A Multiparty Setup: Imputation . 50 iv 3.2.3 The Thomsen Estimator in Multiparty Setup . 53 3.3 Iterative Proportional Fitting (IPF) ......................... 55 3.4 Simulation using Ballot Images The 2000 US Presidential Election in Miami-Dade, FL . 59 3.4.1 Point Estimates of IPF .......................... 60 3.4.2 Standard Errors and MSE . 63 3.5 Empirical Test: Voter Transition in South Korean Presidential Elections 1992– 1997 . 65 3.5.1 Background and Data . 67 3.5.2 Results . 71 3.6 Remarks . 77 IV. Ecological Inference with Covariates ........................... 78 4.1 Introduction . 78 4.2 The Model . 79 4.2.1 The Voter Transition Setup with Covariates . 79 4.2.2 Revisiting the Thomsen Estimator . 81 4.2.3 Extending the Thomsen Estimator . 85 4.2.4 Estimation: The Thomsen Estimator with Covariates . 90 4.3 Application: The Impact of Democratization on Voter Turnout . 95 4.3.1 Introduction . 95 4.3.2 Background: The Dynamics of Voter Turnout in South Korea . 97 4.3.3 Examining Entrances and Exits . 99 4.3.4 Unpacking the Entrances and Exits . 102 4.3.5 Discussion . 111 V. Conclusion ..........................................115 BIBLIOGRAPHY ............................................ 119 v LIST OF FIGURES Figure 2.1 Voter Transition Rates in Two Successive Elections . 16 2.2 Parameter Bounds and Their Density . 19 2.3 An “Overcorrection” by King MLE . 26 2.4 When Things Go Wrong . 27 2.5 Non-Linearity in VTR Models . 29 2.6 Decomposition of Variances . 35 3.1 Coefficients in a Three Party System: King’s Approach . 50 3.2 Coefficients in a Multiparty System: Thomsen’s Approach . 53 3.3 Variables and Parameters of Voter Transition Rates: South Korean Presidential Elections, 1992–1997 . 72 4.1 Voter Transition with a Covariate . 79 4.2 Turnout in South Korean Elections . 98 4.3 Replacement of Voters . 99 4.4 Estimated Turnouts in Legislative Elections, Selected Demographic Groups . 106 4.5 Estimated Entrance and Exit Rates by Education and Age . 110 vi LIST OF TABLES Table 2.1 Voter Transition Estimates in British Parliamentary Elections 1964–1966, Straight- Fight Seats. 21 2.2 Voter Transition Estimates in South Korean Presidential Elections, 1992–1997. 22 2.3 Voter Transition Estimates in British Parliamentary Elections 1964–1966, Straight- Fight Seats. 39 2.4 Voter Transition Estimates in South Korean Presidential Elections, 1992–1997 . 39 2.5 Comparison of Ecological Estimates at Different Levels of Aggregation, South Ko- rean Presidential Elections, 1992–1997 . 41 3.1 Implementing the IPF Algorithm: An Example . 58 3.2 IPF Iterations: Example Continued . 59 3.3 Distribution of Voters in Presidential and Senate Contests, Ballot Image Estimates: 2004 General Election, Miami-Dade, Florida . 61 3.4 Distribution of Voters in Presidential and Senate Contests, Ecological Estimates: 2004 General Election, Miami-Dade, Florida . 61 3.5 Bootstrap Estimates of Coefficients and Their Precision . 64 3.6 Candidates in Presidential Elections, 1987–1997 . 67 3.7 National Support for Candidates: Survey vs Aggregate . 71 3.8 Ecological Estimates from a Three Party System: South Korean Elections 1992–1997 74 4.1 Key Variables in the Extended Thomsen Model with a Covariate . 84 4.2 Estimated Distribution of Voters across Elections in Different Education Groups: South Korean Elections 1981–1985 . 94 4.3 Estimated Transition Rates in Different Education Groups: South Korean Elections 1981–1985 . 95 4.4 Voter Transition Rates Around Democratization . 100 4.5 Entrances and Exits from the Polling Booth . 102 vii 4.6 Entrance and Exit Rates in Urban and Rural Districts . 103 4.7 (Appendix) Estimated Turnout Rates by Different Demographic Groups in South Korean Elections . 113 4.8 (Appendix) Estimated Entrance Rates of Different Demographic Groups in South Korean Elections . 114 4.9 (Appendix) Estimated Exit Rates of Different Demographic Groups in South Ko- rean Elections . 114 viii CHAPTER I Introduction 1.1 The Study of Elections and Voting Elections are aggregation processes, and a majority of electoral analysis is bound to focus upon looking at electoral returns as a starting point at the least. Electoral outcomes are determined when the votes are tallied up in a given electoral unit, and such an outcome of elections constitutes the natural unit of analysis. For ex- ample, it could be either how the electoral fate of an incumbent party is swayed by the economic conditions over time nationwide, or how a given electoral dis- trict’s peculiar configuration explains any electoral outcomes unique to that dis- trict. Strongly embedded in our language are such phrases as “how the country decided ...,” or “how the district has chosen ...,” and studying elections with ag- gregate information makes sense. Voting is also an individual behavior. It is neither the country nor the districts that decide, but the voters that make choices. Analyzing elections and explaining the outcomes would necessarily involve a certain theory of voters. Particularly meaningful in this context are the successes and achievements that survey methodology brought into the study of elections since the end of the Sec- ond World War. Epitomized in the American National Election Studies (ANES) 1 2 and followed by many survey studies in various democracies, this research method addresses questions on the psychological factors and rational calculus that work within voters. Survey research combined with powerful statistical tools has produced per- haps the most enduring successes in quantitative electoral studies. Thanks to the ingenuity in the design and subsequent analyses of the collective body of the ANES, we now know more about the American voter than we did half a century ago. Also, many concepts and methodology developed through the ANES experi- ence provide an excellent benchmark for the study of voters in other democracies as well, as is evidenced in the electoral studies conducted in many countries. For example, the Comparative Study of Electoral Systems (CSES) includes election survey studies from more than thirty countries in the world, with an eye towards unifying the study of voting behavior in the comparative politics context. Survey measures are by no means perfect. Respondents are known to lie, for- get, or misinterpret the questions when they face an interviewer or when they fill in a questionnaire. Yet, the simple virtue of directly measuring the voter’s behavior, intention, and characteristics enables the researcher to examine the di- rect linkage between them. This exactly is the reason why survey studies have dominated electoral studies in the past fifty years with so many successes. 1.2 Limitations of Survey Studies in Studying Electoral Politics Even though survey studies