Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applicationsby Michel Regenwetter, Bernard Grofman, A. A. J. Marley, Ilia Tsetlin
Pub. Date: 01/31/2006
Publisher: Cambridge University Press
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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Table of ContentsPart 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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