Behavioral Social Choice
Probabilistic Models, Statistical Inference, and Applications
- Authors:
- Michel Regenwetter, University of Illinois, Urbana-Champaign
- Bernard Grofman, University of California, Irvine
- A. A. J. Marley, University of Victoria
- Ilia Tsetlin, INSEAD, Fontainebleau and Singapore
- Date Published: May 2006
- availability: Available
- format: Paperback
- isbn: 9780521536660
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Behavioral Social Choice looks 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. Furthermore, if there is a problem, they show that the problem is more likely to be one of sample estimates missing the majority winner in a close contest (e.g., Bush-Gore) than a problem about cycling. The authors also provide new mathematical tools to estimate the prevalence of cycles as a function of sample size and insights into how alternative model specifications can change our estimates of social orderings.
Read more- Challenges existing wisdom (stemming from Arrow's Impossibility Theorem) that democratic decision-making is inherently flawed
- Close link between theory and empirical applications, including data on real-world elections in US and Europe
- New mathematical tools to estimate majority rule relationship from sample data
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×Product details
- Date Published: May 2006
- format: Paperback
- isbn: 9780521536660
- length: 258 pages
- dimensions: 229 x 152 x 14 mm
- weight: 0.38kg
- contains: 8 tables
- availability: Available
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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