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Strategic Voting and Multinomial Choice In US Presidential Elections

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Author Info
Myoung-jae Lee () (Department of Economics, Korea University, Seoul, South Korea)
Sung-jin Kang () (Department of Economics, Korea University, Seoul, South Korea)
Abstract

Ross Perot was a relatively viable third party candidate in the 1992 US presidential election, but he was not any more in the 1996 election. This provides a good opportunity to analyze strategic voting behavior?voting for a candidate not most preferred by the voter?in the US presidential elections with panel data drawn from NES (National Election Studies). First, the 1992 election is analyzed with multinomial choice estimators. Second, using the estimates, each individual¡¯s choice is predicted for the 1996 election. Third, those who were predicted to vote for Perot in 1996 but did not are identified as strategic voters and their profile is drawn. In addition to the main task of analyzing the strategic voting behavior, this paper does two additional tasks. First, analyzing the 1992 data with multinomial choice estimators, t is found that the following variables mattered significantly for the US presidential election: respondent and candidate ideology, personal finance, age, education, income, sex, abortion stance, health insurance policy, and welfare program policy. Second, critical mistakes in the literature in applying multinomial probit to election data are pointed.

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Paper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 0907.

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Length: 25 pages
Date of creation: 2009
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Handle: RePEc:iek:wpaper:0907

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Related research
Keywords: strategic voting; presidential election; multinomial logit; multinomial probit;

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References listed on IDEAS
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  1. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September. [Downloadable!] (restricted)
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  2. Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
  3. Lee, Myoung-jae & Kim, Young-sook, 2007. "Multinomial choice and nonparametric average derivatives," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 63-81, January. [Downloadable!] (restricted)
  4. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470. [Downloadable!]
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This page was last updated on 2009-11-28.


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