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A Monte Carlo comparison of estimators for a bivariate probit model with selection

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  • Belkar, R.
  • Fiebig, D.G.

Abstract

A Monte Carlo experiment is undertaken to examine the small sample properties of three alternative estimators of a bivariate probit model with selection. The three estimators are the censored probit estimator, single-equation probit applied to the selected sub-sample and single-equation probit applied to the full sample. These estimators are compared in terms of properties of coefficient estimates and predicted probabilities. While no estimator dominates in all possible situations a clear recommendation follows from an overall evaluation of the relative performance of the three estimators. Ignoring the selection problem through use of a single-equation probit can often lead to very poor estimator and predictor performance. Both single-equation probit estimators have properties that can vary dramatically over the different design points. The properties of censored probit vary much less than the two single-equation estimators and this robustness characteristic tends to favour its use.

Suggested Citation

  • Belkar, R. & Fiebig, D.G., 2008. "A Monte Carlo comparison of estimators for a bivariate probit model with selection," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 250-256.
    • Handle: RePEc:eee:matcom:v:78:y:2008:i:2:p:250-256
    DOI: 10.1016/j.matcom.2008.01.016
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    References listed on IDEAS

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