Estimating relative prevalence of competing issue voting rules in multiparty elections using finite mixture modeling

Abstract

How do citizens of democratic polities translate their policy preferences into voting choices? Proximity and directional theories of issue voting offer different answers to this question that have strong implications for parties’ strategies. Controlled scenarios in imaginary two-candidate contests have gained popularity as a method to estimate proportions of proximity and directional voters in the population. However, this method is not always applicable in comparative research where scholars often have to study multiparty elections with observational data. In the present paper, I demonstrate how relative prevalence of different issue voting rules can be estimated using finite mixture modeling. Using both a paradigmatic and a recent case, I demonstrate that the mixture model predicts observed voting choices better than the alternatives. I also show how finite mixture modeling can be used to study individual-level characteristics of proximity and directional voters using education as an example.