Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper investigates the estimation of binary response panel data models with endogenous regressors using semiparametric least squares. The endogeneity arises from an unobserved time-invariant effect and a nonzero correlation between the idiosyncratic error and one or more explanatory variables. Our proposed estimator addresses endogeneity by the correlated random effects and control function approaches. The estimator is shown to be asymptotically normally distributed and to have satisfactory finite sample properties in Monte Carlo experiments. The method’s utility is demonstrated through an empirical application that examines the effect of a husband’s income on the labor force participation of married women.