Affiliation:
1. Department of Political Science Texas A&M University College Station Texas USA
2. Department of Political Science Louisiana State University Baton Rouge Louisiana USA
Abstract
AbstractObjectiveWe propose a simple approach to dealing with partial contestation in models of multiparty elections.MethodsOur proposed approach is to add a tiny value to the vote share of parties that do not contest a district and then to include dummy variables identifying those districts in which parties do not compete. We can then estimate a single system of equations using a seemingly unrelated regression (SUR) approach and Aitchison's log‐ratio transformation. In our SUR system, we interact the dummy variable for a party that partially contested districts with other predictors in the equation that uses the share of votes of the same party in the log‐ratio outcome. Finally, we estimate robust standard errors for predictors in this equation to address heteroscedasticity.ResultsWe demonstrate the utility of our approach using simulated data and election results from the English parliamentary elections in 2017.ConclusionFrom our simulations, we find that our recommended approach performs as well as that proposed by Tom, Tucker, and Wittenberg. Our strategy is advantageous in that it is easy to estimate, uses information from all districts, and addresses partial contestation in real‐world elections with a single system of seemingly unrelated regressions.
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1 articles.
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