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Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models

Published online by Cambridge University Press:  04 January 2017

Lee Sigelman  and
Langche Zeng
Lee Sigelman
Affiliation:
The George Washington University
Langche Zeng
Affiliation:
The George Washington University
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Abstract

Political scientists are making increasing use of the Tobit and Heckit models. This paper addresses some common problems in the application and interpretation of these models. Through numerical experiments and reanalysis of data from a study by Romer and Snyder (1994), we illustrate the consequences of using the standard Tobit model, which assumes a censoring point at zero, when the zeros are not due to censoring mechanisms or when actual censoring is not at zero. In the latter case, we also show that Greene's (1981) well-known results on the direction and size of the bias of the OLS estimator in the standard Tobit model do not necessarily hold. Because the Heckit model is often used as an alternative to Tobit, we examine its assumptions and discuss the proper interpretation of the Heckit/Tobit estimation results using Grier and co-workers' (1994) Heckit model of campaign contribution data. Sensitivity analyses of the Heckit estimation results suggest some conclusions rather different from those reached by Grier et al.

Information

Type
Research Article
Information
Political Analysis , Volume 8 , Issue 2 , 16 December 1999 , pp. 167 - 182
Copyright
Copyright © 1999 by the Society for Political Methodology 

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