How to Predict the Frequency of Voting Events in Actual Elections

36 Pages Posted: 17 Aug 2011 Last revised: 20 Mar 2012

See all articles by Florenz Plassmann

Florenz Plassmann

SUNY at Binghamton, Department of Economics

T. Nicolaus Tideman

Virginia Polytechnic Institute & State University - Department of Economics

Date Written: March 19, 2012

Abstract

Two commonly-used criteria for evaluating voting rules are how infrequently the rules provide opportunities for strategic voting and how infrequently they encounter voting paradoxes. The lack of ranking data from enough actual elections to determine these frequencies with reasonable accuracy makes it attractive to investigate ranking data simulated with Monte Carlo methods. But such simulations permit inferences about actual frequencies only if they are conducted through statistical models that generate ranking data with the same statistical properties as ranking data from actual elections. We offer statistical evidence that ranking data simulated with a spatial model of vote-casting are extremely similar to ranking data from actual elections.

Keywords: spatial model of voting, ordinal ranking data, urn models, Kullback-Leibler

JEL Classification: C4, C15, D72

Suggested Citation

Plassmann, Florenz and Tideman, T. Nicolaus, How to Predict the Frequency of Voting Events in Actual Elections (March 19, 2012). Available at SSRN: https://ssrn.com/abstract=1911286 or http://dx.doi.org/10.2139/ssrn.1911286

Florenz Plassmann (Contact Author)

SUNY at Binghamton, Department of Economics ( email )

Binghamton, NY 13902-6000
United States
607-777-4304 (Phone)

T. Nicolaus Tideman

Virginia Polytechnic Institute & State University - Department of Economics ( email )

3021 Pamplin Hall
Blacksburg, VA 24061
United States

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