Monash University
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Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions

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journal contribution
posted on 2022-11-04, 03:50 authored by Jia Chen, Jiti Gao, Degui Li
In this paper, we study semiparametric estimation for a single-index panel data model where the nonlinear link function varies among the individuals. We propose using the refined minimum average variance estimation method to estimate the parameter in the single-index. As the cross-section dimension N and the time series dimension T tend to infinity simultaneously, we establish asymptotic distributions for the proposed estimator. In addition, we provide a real-data example to illustrate the finite sample behaviour of the proposed estimation method.

History

Classification-JEL

C13, C14, C23

Creation date

2011-09

Working Paper Series Number

12/11

Length

28 pages

File-Format

application/pdf

Handle

RePEc:msh:ebswps:2011-12