Estimating a generalized correlation coefficient for a generalized bivariate probit model. (English) Zbl 1418.62423
Summary: In this paper we consider semiparametric estimation of a generalized correlation coefficient in a generalized bivariate probit model. The generalized correlation coefficient provides a simple summary statistic measuring the relationship between the two binary decision processes in a general framework. Our semiparametric estimation procedure consists of two steps, combining semiparametric estimators for univariate binary choice models with the method of maximum likelihood for the bivariate probit model with nonparametrically generated regressors. The estimator is shown to be consistent and asymptotically normal. The estimator performs well in our simulation study.
MSC:
| 62P20 | Applications of statistics to economics |
| 62G05 | Nonparametric estimation |
| 62F12 | Asymptotic properties of parametric estimators |
| 62E20 | Asymptotic distribution theory in statistics |
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