Estimating Party Positions across Countries and Time—A Dynamic Latent Variable Model for Manifesto Data

Abstract

This article presents a new method for estimating positions of political parties across country- and time-specific contexts by introducing a latent variable model for manifesto data. We estimate latent positions and exploit bridge observations to make the scales comparable. We also incorporate expert survey data as prior information in the estimation process to avoid ex post facto interpretation of the latent space. To illustrate the empirical contribution of our method, we estimate the left-right positions of 388 parties competing in 238 elections across twenty-five countries and over sixty years. Compared to the puzzling volatility of existing estimates, we find that parties more modestly change their left-right positions over time. We also show that estimates without country- and time-specific bias parameters risk serious, systematic bias in about two-thirds of our data. This suggests that researchers should carefully consider the comparability of party positions across countries and/or time.