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Unpublished Paper
Candidate Competition and Voter Learning in Sequential Primary Elections: Theory and Evidence
  • Mattias K Polborn
  • George Deltas, University of Illinois at Urbana-Champaign
We develop a model of sequential presidential primaries in which several horizontally and vertically differentiated candidates compete against each other. Voters are incompletely informed about candidate valence and learn over time from election results in previous districts. We analyze the effects of learning about candidate quality, and the effects of candidate withdrawal on the vote shares. An empirical analysis of the 2000-2008 US presidential primaries shows that the evolution of vote shares over the sequence of contests is consistent with the predictions of the theoretical model. The withdrawal of a candidate has a bigger effect on the vote shares of candidates in the same political position, vote variability declines over time in a pattern consistent with learning, and a tilt of the electorate towards a particular political position disproportionately increases the vote shares of the weak candidates espousing that position (relative to the strong candidates in that position). We also use the empirical results to simulate a primary that takes place simultaneously in all states.
  • Voting,
  • primary elections,
  • simultaneous versus sequential elections.
Publication Date
Citation Information
Mattias K Polborn and George Deltas. "Candidate Competition and Voter Learning in Sequential Primary Elections: Theory and Evidence" (2009)
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