Estimating Binary choice models from cohort data

Abstract

In this paper we discuss the estimation of binary choice models with individual effects, when the data available are time series of independent cross-sections. We specify a random effects model assuming that the conditional expectation of the individual effects is a linear function of the explanatory variables, and we show how to obtain a consistent estimator of the reduced form parameters. Then, we consider a minimum distance estimator and a within-groups estimator of the structural parameters, and we derive their asymptotic distributions. Finally, we carry out some Monte Carlo simulations to analyze the small sample performance of our estimators