Non- and Semi-Parametric Panel Data Models: A Selective Review

Jia Chen, Degui Li and Jiti Gao

No 18/13, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This article provides a selective review on the recent developments of some nonlinear nonparametric and semiparametric panel data models. In particular, we focus on two types of modelling frameworks: nonparametric and semiparametric panel data models with deterministic trends, and semiparametric single-index panel data models with individual effects. We also review various estimation methodologies which can consistently estimate both the parametric and nonparametric components in these models. The time series length and cross-sectional size in this article are allowed to be very large, under which the panel data are called “large dimensional panels".

Keywords: Deterministic trends; local linear fitting; panel data; semiparametric estimation; single-index models (search for similar items in EconPapers)
Date: 2013
New Economics Papers: this item is included in nep-ecm
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