Replication data for: Analyzing Censored and Sample-Selected Data with 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) wellknown 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.