Non‐parametric models in binary choice fixed effects panel data

In this paper we extend the fixed effects approach to deal with non‐linear panel data with non‐parametric components. Specifically, we propose a non‐parametric procedure that generalizes the conditional logit approach. We develop an estimator based on non‐linear stochastic integral equations and provide the asymptotic property of the estimator and an iterative algorithm to implement the estimator. We analyse the small sample behaviour of the estimator through a Monte Carlo study.