%0 Journal Article %A Wheatley, Jonathan %D 2015 %T Identifying Latent Policy Dimensions from Public Opinion Data: An Inductive Approach %U https://tandf.figshare.com/articles/journal_contribution/Identifying_Latent_Policy_Dimensions_from_Public_Opinion_Data_An_Inductive_Approach/1257723 %R 10.6084/m9.figshare.1257723.v2 %2 https://tandf.figshare.com/ndownloader/files/1815535 %K confirmatory factor analysis %K Latent Policy Dimensions %K European territories %K factor analysis %K Public Opinion Data %K European countries %K policy space %K opinion data %K cfa %K voter alignments %K policy spaces %K model %K policy dimensions %K Inductive Approach AbstractA %X

Abstract

A common way of classifying policy dimensions is by means of a two-dimensional model, based on one economic (Left/Right) dimension and one liberal–conservative dimension that Marks et al. (2006) refer to as Tan/Gal. However, as Lipet and Rokkan (1967) note, voter alignments developed in different ways in different European countries, so the dimensions that define the respective policy spaces may vary from country to country. In this paper, I test the two-dimensional model on opinion data from four European territories using confirmatory factor analysis (CFA) and go on to develop alternative “better fit” models using a combination of exploratory factor analysis and CFA. I find that the two-dimensional model is appropriate in some but not all the cases and suggest that a more context-sensitive approach is needed to identify the dimensionality of the policy space.

%I Taylor & Francis