Ideology and interests : a hierarchical Bayesian approach to spatial party preferences

• Main Author: Mohanty, Peter Cushner
• Format: Others
• Language: en_US
• Published: 2013
• Subjects: Hierarchical models; Generalized linear models; Markov Chain Monte Carlo (MCMC); Public opinion; Political parties; European Union
• Online Access: http://hdl.handle.net/2152/22529

This paper presents a spatial utility model of support for multiple political parties. The model includes a "valence" term, which I reparameterize to include both party competence and the voters' key sociodemographic concerns. The paper shows how this spatial utility model can be interpreted as a hierarchical model using data from the 2009 European Elections Study. I estimate this model via Bayesian Markov Chain Monte Carlo (MCMC) using a block Gibbs sampler and show that the model can capture broad European-wide trends while allowing for significant amounts of heterogeneity. This approach, however, which assumes a normal dependent variable, is only able to partially reproduce the data generating process. I show that the data generating process can be reproduced more accurately with an ordered probit model. Finally, I discuss trade-offs between parsimony and descriptive richness and other practical challenges that may be encountered when v building models of party support and make recommendations for capturing the best of both approaches. === text