Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications

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Looking at the probabilistic foundations of collective decision-making rules, the authors challenge much of the existing theoretical wisdom about social choice processes, and seek to restore faith in the possibility of democratic decision-making. In particular, they argue that worries about the supposed prevalence of majority rule cycles, that would preclude groups from reaching a final decision about what alternative they prefer, have been greatly overstated. In practice, majority rule can be expected to work well in most real-world settings. They provide new insights into how alternative model specifications can change our estimates of social orderings.
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Editorial Reviews

From the Publisher
"The juxtaposition of 'behavioral' and 'social choice' is unusual, to say the least, because the former suggests an empirical and the latter a theoretical orientation. In Behavioral Social Choice, the authors succeed remarkably in merging these different orientations and rigorously demonstrating how care and subtlety are required in aggregating individual preferences into the vaunted 'will of the majority'." Steven J. Brams, New York University

"Regenwetter and his colleagues are founding a new field. Behavioral Social Choice will take its place next to Camerer's Behavioral Game Theory, Thaler's Behavioral Finance Theory, and Tversky & Kahneman's Behavioral Decision Theory as another beachhead of psychologically realistic analyses of behavioral phenomena on an intellectual terrain that has long been controlled by descriptively implausible rational choice models. Independent of its path-breaking, field-founding merits, the book presents a beautifully crafted combination of descriptive probabilistic choice models with discrete social choice strategies supported by innovative data analysis. This will be a classic model for behavioral researchers for many years to come. Anyone interested in normative or descriptive models of social choice should read it." Reid Hastie, University of Chicago

"Every now and then—the instances are rare—one reads a piece of research and knows immediately that he or she has read something extraordinary. Such is the case with Behavioral Social Choice. It is the first truly convincing response to Arrow's Impossibility Theorem and its implication that representative democracies, especially those using majority rule procedures, cannot effectively aggregate and interpret their citizens' preferences. The book serves as a model for social scientific research. The authors first develop a probabilistic behavioral social choice theory that generalizes deterministic social choice theory, which has dominated thinking in the field. This alone represents a major contribution. Regenwetter et al. then creatively use survey data to test their theory. No single statement can adequately convey the quality, ingenuity, and subtlety of the empirical analyses. Behavioral Social Choice will appeal to a wide range of social scientists. . . . A must for students of social choice. . . Indispensable for economists and psychologists who study decision making . . . A staple for political scientists who study political representation and elections and voting behavior. . . . It will be a classic." James H. Kuklinski, University of Illinois at Urbana-Champaign

"Starting with Arrow's famous impossibility result for social choice, the subsequent theoretical literature has shown, among other things, that majority rule procedures should be plagued with intransitive cycles. Yet, real world survey data are mostly free of them. Why? This monograph pulls together exceedingly original published results on a probabilistic behavioral social choice theory that simultaneously generalizes classical deterministic social choice theory and individual probabilistic choice models. Data sets are analyzed and Bayesian inference procedures are created, and it is shown that the expectation of cycles is very dependent upon a worst case scenario. The volume, which is a beautiful mix of probabilistic modeling, data analysis, and inference, is very elegant and impressively scholarly." Duncan Luce, University of California, Irvine

"This readable and pioneering book develops an interesting approach toward voting theory that moves the thrust from the classical approach of 'axioms,' which speculate what might happen, to place a behavioral emphasis on the way people might and do behave. By doing so, their work will force us to question and re-examine many of the accepted conclusions that come from classical theory. As such, I expect this book to be influential and controversial; I expect it will alter the way many of us will think about classic issues such as cycles from majority voting, the negative conclusions associated Arrow's and Sen's theorems, and how theory should guide us in analyzing actual political institutions." Donald G. Saari, University of California, Irvine

"This multidisciplinary research team has produced one of the most original books on social choice theory in the past 10 years." -- Choice

2007 Outstanding Academic Title -- Choice Magazine

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Product Details

  • ISBN-13: 9780521829687
  • Publisher: Cambridge University Press
  • Publication date: 1/31/2006
  • Pages: 256
  • Product dimensions: 5.98 (w) x 8.98 (h) x 0.71 (d)

Meet the Author

Michel Regenwetter is Associate Professor of Psychology and Political Science at the University of Illinois at Urbana-Champaign (UIUC). In 1999, Dr Regenwetter was awarded the Young Investigator Award of the Society for Mathematical Psychology. He has been principal investigator on multiple grants from the National Science Foundation and the Research Board of the University of Illinois. Dr. Regenwetter has published over 20 scholarly articles in leading academic journals in his field, including in the Journal of Experimental Psychology: Learning, Memory and Cognition, the Journal of Mathematical Psychology, Management Science, Mathematical Social Sciences, Psychological Review, Psychometrika, Social Choice and Welfare, and Theory and Decision. Dr Regenwetter has served as guest associate editor for Management Science, and since 2003, he has been a permanent member of the editorial board of the Journal of Mathematical Psychology.

Bernard Grofman is a Professor of Political Science at the University of California, Irvine, where he has been teaching since 1980. He received his B.S. in Mathematics at the University of Chicago in 1966 and his Ph.D. in Political Science at the University of Chicago in 1972. He is co-author of 3 previous books published by Cambridge University Press, and co-editor of 16 other books. He has also published over 200 research articles and book chapters, including work in leading journals such as the American Political Science Review, the American Journal of Political Science, the Journal of Politics, the British Journal of Political Science, Electoral Studies, Social Choice and Welfare, and Public Choice.

A. A. J. Marley, a Fellow of the American Psychological Society, was Chair of the Department of Psychology at McGill University from 1992 to 2001 (with a one-year sabbatical break in 1997), and is now Adjunct Professor at the University of Victoria and Professor Emeritus of McGill University. He has been editor of the Journal of Mathematical Psychology and President of the Society for Mathematical Psychology.

Ilia M. Tsetlin is an Assistant Professor of Decision Sciences at INSEAD. His teaching and research interests are in modeling decisions under uncertainty, with particular focus on competitive decision making and social choice. His research has appeared in academic journals such as Operations Research, the Journal of Risk and Uncertainty, and Social Choice and Welfare.

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Table of Contents

Part I. Probabilistic Models of Social Choice Behavior: 1. The lack of theoretical and practical support for majority cycles; 2. A general concept of majority rule; Part II. Applications of Probabilistic Models to Empirical Data: 3. On the model dependence versus robustness of social choice results; 4. Constructing majority preferences from subset choice data; Part III. A General Statistical Sampling and Bayesian Inference Framework: 5. Majority rule in a statistical sampling and Bayesian inference framework; 6. Conclusions and directions for future behavioral social choice research.
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