Distribution-Free Estimation of Heteroskedastic Binary Response Models in Stata

Jason R. Blevins and Shakeeb Khan
Stata Journal 13 (2013), 588–602.

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.

Keywords: dfbr, binary response, heteroskedasticity, nonlinear least squares, semiparametric estimation, sieve estimation.

JEL Classification: C13, C14, C25, C87.

Stata Package Installation

To install the dfbr Stata package you first need to install a prerequisite package called moremata:

ssc install moremata

Next, install dfbr as follows:

net install dfbr, from(https://jblevins.org/)

Suggested Citation

When using dfbr in published work, please cite either the Stata Journal paper or the relevant paper for the specific estimator used (or both):

Citation for the Stata program:

Citations for the sieve and local nonlinear least squares estimators, respectively:

BibTeX Record

  author       = {Jason R. Blevins and Shakeeb Khan},
  title        = {Distribution-Free Estimation of Heteroskedastic Binary
                  Response Models in {Stata}},
  journal      = {Stata Journal},
  volume       = {13},
  year         = {2013},
  pages        = {588--602}