Distribution-free estimation of heteroskedastic binary response models in Stata
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.
View all articles by these authors:
Jason R. Blevins, Shakeeb Khan
View all articles with these keywords:
dfbr, binary response, heteroskedasticity, nonlinear least squares, semiparametric estimation, sieve estimation
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