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Replication data for: Estimating Party Positions across Countries and Time - A Dynamic Latent Variable Model for Manifesto Data

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Title Replication data for: Estimating Party Positions across Countries and Time - A Dynamic Latent Variable Model for Manifesto Data
 
Identifier https://doi.org/10.7910/DVN/669Z5L
 
Creator Konig, Thomas
Marbach, Moritz
Osnabrugge, Moritz
 
Publisher Harvard Dataverse
 
Description This article presents a new method for estimating positions of political par- ties across country- and time-specific contexts by introducing a latent variable model for manifesto data. We estimate latent positions and exploit bridge ob- servations to make the scales comparable. We also incorporate expert survey data as prior information in the estimation process to avoid ex post facto in- terpretation of the latent space. To illustrate the empirical contribution of our method we estimate the left-right positions of more than 388 European parties competing in 238 elections across 25 countries and over 60 years. Compared to the puzzling volatility of existing estimates, we find that parties more mod- estly 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.
 
Subject Latent issue positions
Bayesian estimation
Preference measurement
Manifesto data
Bridge observations
 
Date 2013-02