Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models |
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Authors: | Sigelman, Lee Zeng, Langche |
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Affiliation: | The George Washington University |
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Abstract: | Political scientists are making increasing use of the Tobitand Heckit models. This paper addresses some common problemsin the application and interpretation of these models. Throughnumerical experiments and reanalysis of data from a study byRomer and Snyder (1994), we illustrate the consequences of usingthe standard Tobit model, which assumes a censoring point atzero, when the zeros are not due to censoring mechanisms orwhen actual censoring is not at zero. In the latter case, wealso show that Greene's (1981) well-known results on the directionand size of the bias of the OLS estimator in the standard Tobitmodel do not necessarily hold. Because the Heckit model is oftenused as an alternative to Tobit, we examine its assumptionsand discuss the proper interpretation of the Heckit/Tobit estimationresults using Grier and co-workers' (1994) Heckit model of campaigncontribution data. Sensitivity analyses of the Heckit estimationresults suggest some conclusions rather different from thosereached by Grier et al. |
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