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Title: Nonparametric multi-dimensional fixed effect panel data models Authors:  Daniel Henderson - University of Alabama (United States) [presenting]
Juan Manuel Rodriguez-Poo - Universidad de Cantabria (Spain)
Alexandra Soberon - Universidad de Cantabria (Spain)
Abstract: Multi-dimensional panel data sets are becoming increasing popular to identify marginal effects in empirical research. Fixed effects estimators are typically employed in order to deal with potential correlation between unobserved effects and regressors. Nonparametric estimators for one-way fixed effects models exist, but are cumbersome to employ in practice as they typically require iteration, marginal integration or profile estimation. We develop a nonparametric estimator for the gradient of the conditional mean that works for any dimension fixed effect model and has a closed-form solution. The asymptotic properties of our estimator are given and the finite sample properties are shown via simulations, as well as via an empirical application which further extends our estimator to the partially linear setting.