Year: 2013
Type: article
Abstract: This article presents a new method of reconstructing actors' political positions from coded political texts. It is based on a model that combines a dynamic perspective on actors' political positions with a probabilistic account of how these positions are translated into emphases of policy topics in political texts. In the article it is shown how model parameters can be estimated based on a maximum marginal likelihood principle and how political actors' positions can be reconstructed using empirical Bayes techniques. For this purpose, a Monte Carlo Expectation Maximization algorithm is used that employs independent sample techniques with automatic Monte Carlo sample size adjustment. An example application is given by estimating a model of an economic policy space and a noneconomic policy space based on the data from the Comparative Manifesto Project. Parties' positions in policy spaces reconstructed using these models are made publicly available for download.
Source: Political Analysis
DOI: 10.1093/pan/mps042
Author: Martin Elff
Institution: University of Konstanz
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: bronze
Funder: University of Cambridge
OpenAlex ID: W2045790366