Benjamin Lauderdale, “Latent Versus Self-Reported Ideology”

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Spatial voting axes are seldom directly measurable. In general, political scientists employ latent variable models that aim to infer the presence and characteristics of axes from their impact on measurable quantities such as voting behavior. Ideology in the electorate is a rare case where researchers regularly attempt to measure a spatial quantity directly, typically by asking people to rank themselves on ordinal scales from liberal to conservative. These self-reported ideology scores have been widely used as a nationally comparable measure of ideological position, but whether different citizens are using consistent criteria for assessing and reporting their ideology is largely unknown. To better understand the relationship between issue positions and ideology in the electorate, I develop a item-response model for self-reported ideology as a function of issue positions. I find that political information is required for voters to self-report ideology consistently with their issue positions. Groups which are less attuned to the terminology of the national political discourse tend to self-report ideology in ways that are less informative about their issue positions on the primary political axis defined by that discourse.

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I am a Professor of Political Science at University College London. From 2011-2018 I was on the faculty at the London School of Economics. I have been a Senior Data Science Advisor to YouGov since 2016 and was previously an Associate Editor of the American Political Science Review (2016-2020). My research is focused on the measurement of political preferences from survey, voting, network and text data. Applications of these methods have included citizens, legislators and judges in the US, UK and EU.

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