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Testing the Predictions of the Multidimensional Spatial Voting Model with Roll Call Data

Published online by Cambridge University Press:  10 September 2007

Gyung-Ho Jeong
Gyung-Ho Jeong*
Affiliation:
Department of Political Science, Washington University in St. Louis, Campus Box 1063, One Brookings Drive, St. Louis, MO 63130, e-mail: gjeong@artsci.wustl.edu
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Abstract

This paper develops a procedure for locating proposals and legislators in a multidimensional policy space by applying agenda-constrained ideal point estimation. Placing proposals and legislators on the same scale allows an empirical test of the predictions of the spatial voting model. I illustrate this procedure by testing the predictive power of the uncovered set—a solution concept of the multidimensional spatial voting model—using roll call data from the U.S. Senate. Since empirical tests of the predictive power of the uncovered set have been limited to experimental data, this is the first empirical test of the concept's predictive power using real-world data.

Information

Type
Research Article
Information
Political Analysis , Volume 16 , Issue 2 , Spring 2008 , pp. 179 - 196
Copyright
Copyright © The Author 2007. Published by Oxford University Press on behalf of the Society for Political Methodology 

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