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The Stata Journal
Volume 13 Number 3: pp. 588-602

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Distribution-free estimation of heteroskedastic binary response models in Stata

Jason R. Blevins
Ohio State University
Columbus, OH
[email protected]
Shakeeb Khan
Duke University
Durham, NC
[email protected]
Abstract.  In this article, we consider two recently proposed semiparametric estimators for distribution-free binary response models under a conditional median restriction. We show that these estimators can be implemented in Stata by using the nl command through simple modifications to the nonlinear least-squares probit criterion function. We then introduce dfbr, a new Stata command that implements these estimators, and provide several examples of its usage. Although it is straightforward to carry out the estimation with nl, the dfbr implementation uses Mata for improved performance and robustness.
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View all articles with these keywords: dfbr, binary response, heteroskedasticity, nonlinear least squares, semiparametric estimation, sieve estimation

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