Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications
Michel Regenwetter (University of Illinois, Urbana-Champaign),Bernard Grofman (University of California, Irvine),A. A. J. Marley (University of Victoria, British Columbia),Ilia Tsetlin (Duke University, North Carolina)
Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications
Michel Regenwetter (University of Illinois, Urbana-Champaign),Bernard Grofman (University of California, Irvine),A. A. J. Marley (University of Victoria, British Columbia),Ilia Tsetlin (Duke University, North Carolina)
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.
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