We propose a new methodology for estimating semiparametric panel data models, with a primary focus on the nonparametric component. We eliminate individual effects using first differencing transformation and estimate the unknown function by marginal integration. We extend our methodology to treat...

We propose an alternative method for estimating the nonlinear component in semiparametric panel data models. Our method is based on marginal integration that allows us to recover the nonlinear component from an additive regression structure that results from the first differencing...

In this article, we consider the estimation of semiparametric panel data smooth coefficient models. We propose a class of local generalized method of moments (LGMM) estimators that are simple and easy to implement in practice. We show that the proposed LGMM estimators are consistent and...