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

Overview

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 ...

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Overview

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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Product Details

  • ISBN-13: 9780521536660
  • Publisher: Cambridge University Press
  • Publication date: 1/31/2006
  • Edition description: New Edition
  • Pages: 256
  • Product dimensions: 5.98 (w) x 8.98 (h) x 0.55 (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 Journal of Experimental Psychology: Learning, Memory and Cognition, 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 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, Journal of Risk and Uncertainty, and Social Choice and Welfare.

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Table of Contents

1 The lack of theoretical and practical support for majority cycles 23
2 A general concept of majority rule 52
3 On the model dependence versus robustness of social choice results 109
4 Constructing majority preferences from subset choice data 124
5 Majority rule in a statistical sampling and Bayesian inference framework 155
6 Conclusions and directions for future behavioral social choice research 191
A Definitions of cultures of preference distributions 199
B Definitions and notation for binary relations 202
C Proofs of theorems and observations 204
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