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Statistical inference of partially linear panel data regression models with fixed individual and time effects

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  • Tian Liu

Abstract

This article considers a partially linear panel data model with fixed individual and time effects in a setting where both N and T are large. Based on the within transformation and profile likelihood method, we propose an approach to estimating the parametric and non parametric components of the partially linear model. The resultant estimators are shown to be consistent and asymptotically normal. Monte Carlo simulations are also conducted to illustrate the finite-sample performance of the proposed estimators.

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  • Tian Liu, 2017. "Statistical inference of partially linear panel data regression models with fixed individual and time effects," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(15), pages 7267-7288, August.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:15:p:7267-7288
    DOI: 10.1080/03610926.2015.1116577
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