Social Choice, Optimal Inference and Figure Skating
We approach the social choice problem as one of optimal statistical inference. If individual voters or judges observe the true order ona set of alternatives with error, then it is possible to use the set of individual rankings to make probability statements about the correct social order. Given the posterior distribution for orders and a suitably chosen loss function, an optimal order is one that minimises expected posterior loss. The paper develops a statistical model describing the behaviour of judges, and discusses Markov Chain Monte Carlo estimation. We also discuss criteria for choosing the appropriate loss functions. We apply our methods to a well-known problem: determining the correct ranking for figure skaters competing at the Olympic Games.
|Date of creation:||2006|
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- Truchon, Michel & Gordon, Stephen, 2009.
"Statistical comparison of aggregation rules for votes,"
Mathematical Social Sciences,
Elsevier, vol. 57(2), pages 199-212, March.
- Michel Truchon & Stephen Gordon, 2006. "Statistical Comparison of Aggregation Rules for Votes," Cahiers de recherche 0625, CIRPEE.
- Michel Truchon, 2004.
"Aggregation of Rankings in Figure Skating,"
Cahiers de recherche
- Peyton Young, 1995. "Optimal Voting Rules," Journal of Economic Perspectives, American Economic Association, vol. 9(1), pages 51-64, Winter.
- Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, June.
- Michel Truchon, 2005. "Aggregation of Rankings: a Brief Review of Distance-Based Rules," Cahiers de recherche 0534, CIRPEE.
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