Institute for Economic and Social Research

Nonparametric Estimation of Generalized Transformation Models With Fixed Effects


Econometric Theory

Songnian ChenXun LuXi Wang



This paper considers a generalized panel data transformation model with fixed effects where the structural function is assumed to be additive. In our model, no parametric assumptions are imposed on the transformation function, the structural function, or the distribution of the idiosyncratic error term. The model is widely applicable and includes many popular panel data models as special cases. We propose a kernel-based nonparametric estimator for the structural function. The estimator has a closed-form solution and is easy to implement. We study the asymptotic properties of our estimator and show that it is asymptotically normally distributed. The Monte Carlo simulations demonstrate that our new estimator performs well in finite samples.

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Copyright © 2019 Institute for Economic and Social Research ICP record No.: Yue ICP Bei No. 12087612