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| Field |
Value |
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| Title |
Replication data for: Testing Core Predictions of Spatial Models: Platform Moderation and Challenger Success
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| Identifier |
https://doi.org/10.7910/DVN/26681
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| Creator |
Montagnes, B. Pablo, and Jon C. Rogowski
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| Publisher |
Harvard Dataverse
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| Description |
A large class of spatial models of elections converges upon a single prediction: a candidate’s vote share increases in the congruence between her platform and the median voter’s preferences. Though considerable empirical research provides support for this prediction, these studies have not adequately identified the effects of platform positioning net of other factors. In this paper, we study the impact of challenger moderation on vote shares using data from 444 U.S. House elections from 1996-2006 in which successive challengers competed against a common incumbent. Our findings are largely null. We uncover no evidence that challengers increase their vote shares by adopting more moderate platform positions. This finding is robust across a wide range of model specifications and subsets of districts.
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| Date |
2014
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ICAR Research Data Repository for Knowledge Management