Practical Considerations for Choosing Between Tobit and SCLS or CLAD Estimators for Censored Regression Models with an Application to Charitable Giving*
نویسنده
چکیده
Practical considerations for choosing between Tobit, symmetrically censored least squares (SCLS) and censored least absolute deviations (CLAD) estimators are offered. Practical considerations deal with when a Hausman test is better than a conditional moment test for judging the severity of a misspecification, the need to bootstrap the sampling distributions of theHausman tests, what to look for in a graphical examination of the residuals and the limited value of SCLS. The practical considerations are applied to a model of the intergenerational transmission of charitable giving using new data from the Panel Study of Income Dynamics (PSID). The paper shows how to use relative distribution methods to calculate CLAD-based marginal effects on the observable dependent variable.
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