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Estimation of Models with Beta-Distributed Dependent Variables: A Replication and Extension of Paolino's Study

Published online by Cambridge University Press:  04 January 2017

Jack Buckley
Jack Buckley*
Affiliation:
Department of Political Science, State University of New York, Stony Brook, NY 11794-4392. e-mail: sbuckley@ic.sunysb.edu
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Abstract

This note replicates and extends Paolino's discussion (2001, Political Analysis 9:325–346) on the estimation of models with beta-distributed dependent variables in two ways. First, it introduces an easy-to-use program for estimating the model using Stata. Second, it presents a Bayesian estimator for beta variables based on Paolino's model. Results are compared to those in the original article.

Type
Replications and Extensions
Information
Political Analysis , Volume 11 , Issue 2 , Spring 2003 , pp. 204 - 205
Copyright
Copyright © Political Methodology Section of the American Political Science Association 2003 

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References

Keiser, Lael R., and Soss, Joe. 1998. “With Good Cause: Bureaucratic Discretion and the Politics of Child Support Enforcement.” American Journal of Political Science 42:1133–1156.Google Scholar
Paolino, Philip. 2001. “Maximum Likelihood Estimation of Models with Beta-Distributed Dependent Variables.” Political Analysis 9:325–346.Google Scholar
Selden Sally, Coleman, Brudney, Jeffrey L., and Edward Kellough, J. 1998. “Bureaucracy as a Representative Institution: Toward a Reconciliation of Bureaucratic Government and Democratic Theory.” American Journal of Political Science 42:717–744.Google Scholar