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

Author

Listed:
  • Jia Chen

    (School of Economics, University of Adelaide)

  • Jiti Gao

    (School of Economics, University of Adelaide)

  • Degui Li

    (School of Economics, University of Adelaide)

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.

Suggested Citation

  • Jia Chen & Jiti Gao & Degui Li, 2010. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," School of Economics and Public Policy Working Papers 2010-09, University of Adelaide, School of Economics and Public Policy.
    • Handle: RePEc:adl:wpaper:2010-09
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    Cited by:

    1. Dong, Chaohua & Gao, Jiti & Peng, Bin, 2015. "Semiparametric single-index panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 188(1), pages 301-312.
    2. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    3. Huang, Lei & Jiang, Hui & Wang, Huixia, 2019. "A novel partial-linear single-index model for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 110-122.
    4. Kutlu, Levent & Sickles, Robin & Tsionas, Mike G., 2019. "Heterogeneous Decision-Making and Market Power," Working Papers 19-008, Rice University, Department of Economics.
    5. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.
    6. Suigen Yang & Xiujuan Yang & Xuefei Wang, 2024. "Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    7. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    8. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    9. Xiaohui Yuan & Xuefei Xiang & Xinran Zhang, 2023. "Bayesian composite quantile regression for the single-index model," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-17, May.
    10. Yang, Suigen & Xue, Liugen & Li, Gaorong, 2014. "Simultaneous confidence band for single-index random effects models with longitudinal data," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 6-14.
    11. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    12. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    13. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.

    More about this item

    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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