On the Equivalence of Simultaneous and Sequential Binary Elections
AbstractWe explore sequential voting in symmetric two-option environments. We show that the (informative) symmetric equilibria of the simultaneous voting game are also equilibria in any sequential voting structure. In unanimity games, (essentially) the whole set of equilibria is the same in all sequential structures. We also explore the relationship between simultaneous and sequential voting in other contexts. We illustrate several instances where sequential voting does no better at aggregating information than simultaneous voting. The inability of the sequential structure to use additional information in voting models is distinct from that in the herd-cascade literature.
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Bibliographic InfoPaper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number 1206.
Date of creation: Dec 1997
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Postal: Center for Mathematical Studies in Economics and Management Science, Northwestern University, 580 Jacobs Center, 2001 Sheridan Road, Evanston, IL 60208-2014
Web page: http://www.kellogg.northwestern.edu/research/math/
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Other versions of this item:
- Dekel, E. & Piccione, M., 1998. "On the equivalence of simulteneous and sequential binary elections," Discussion Paper Series In Economics And Econometrics 9801, Economics Division, School of Social Sciences, University of Southampton.
- Dekel, E. & Piccione, M., 1999. "Sequential Voting Procedures in Symmetric Binary Elections," Papers 3-99, Tel Aviv.
- C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
- D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
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- Hillier, G. & Armstrong, M., 1996. "On the density of the maximum likelihood estimator," Discussion Paper Series In Economics And Econometrics 9645, Economics Division, School of Social Sciences, University of Southampton.
- Shephard, Neil, 1993. "Distribution of the ML Estimator of an MA(1) and a local level model," Econometric Theory, Cambridge University Press, vol. 9(03), pages 377-401, June.
- Grant Hillier & Mark Armstrong, 1999. "The Density of the Maximum Likelihood Estimator," Econometrica, Econometric Society, vol. 67(6), pages 1459-1470, November.
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