Working Paper Series, Department of Economics, University of Zurich 29
The bivariate probit model is frequently used for estimating the effect of an endogenous binary regressor (the treatment) on a binary health outcome variable. This paper discusses simple modifications that maintain the probit assumption for the marginal distributions while introducing non-normal dependence using copulas. In an application of the copula bivariate probit model to the effect of insurance status on the absence of ambulatory health care expenditure, a model based on the Frank copula outperforms the standard bivariate probit model.
bivariate probit binary endogenous regressor Frank copula Clayton copula