Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T10:30:09.272Z Has data issue: false hasContentIssue false
  • English
  • Français

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: [email protected]
Get access Rights & Permissions [Opens in a new window]

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 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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