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

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journal contribution
posted on 2022-11-08, 05:13 authored by Jia Chen, Degui Li, Jiti Gao
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".

History

Classification-JEL

C13, C14,C23

Creation date

2013-08-01

Working Paper Series Number

18/13

Length

18 pp

File-Format

application/pdf

Handle

RePEc:msh:ebswps:2013-18

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