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

Jia Chen, Jiti Gao, Degui Li

Research output: Contribution to journalArticlepeer-review


In this article, 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 behavior of the proposed estimation method.
Original languageEnglish
Pages (from-to)928-955
JournalEconometric Reviews
Issue number8
Early online date13 Mar 2013
Publication statusPublished - Apr 2013


  • Asymptotic distribution
  • Local linear smoother
  • Minimum average variance estimation
  • Panel data
  • semiparametric estimation

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