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

Jia Chen, Jiti Gao and Degui Li

No 2010-09, Adelaide Economics Working Papers from Adelaide University, School of Economics

Abstract: 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 so-called refined minimum average variance estimation based on a local linear smoothing method to estimate both the parameters in the single-index and the average link function. As the cross-section dimension N and the time series dimension T tend to infinity simultaneously, we establish asymptotic distributions for the proposed parametric and nonparametric estimates. In addition, we provide two real-data examples to illustrate the nite sample behavior of the proposed estimation method.

Keywords: asymptotic distribution; local linear smoother; minimum average variance estimation; panel data; semiparametric estimation; single-index models (search for similar items in EconPapers)
Pages: 31 pages
Date: 2010-05
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions (2013)
Working Paper: Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions (2011)
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