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Ideal Point Estimation with a Small Number of Votes: A Random-Effects Approach

Published online by Cambridge University Press:  04 January 2017

Michael Bailey*
Department of Government, ICC, Suite 681, Georgetown University, Washington, DC 20057. e-mail: baileyma@gunet.georgetown.edu


Many conventional ideal point estimation techniques are inappropriate when only a limited number of votes are available. This paper presents a covariate-based random-effects Bayesian approach that allows scholars to estimate ideal points based on fewer votes than required for fixed-effects models. Using covariates brings more information to bear on the estimation; using a Bayesian random-effects approach avoids incidental parameter problems. Among other things, the method allows us to estimate directly the effect of covariates such as party on preferences and to estimate standard errors for ideal points. Monte Carlo results, an empirical application, and a discussion of further applications demonstrate the usefulness of the method.

Research Article
Copyright © 2001 by the Society for Political Methodology 

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