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Semiparametric estimation of fixed-effects panel data varying coefficient models

In: Nonparametric Econometric Methods

Author

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  • Yiguo Sun
  • Raymond J. Carroll
  • Dingding Li

Abstract

We consider the problem of estimating a varying coefficient panel data model with fixed-effects (FE) using a local linear regression approach. Unlike first-differenced estimator, our proposed estimator removes FE using kernel-based weights. This results a one-step estimator without using the backfitting technique. The computed estimator is shown to be asymptotically normally distributed. A modified least-squared cross-validatory method is used to select the optimal bandwidth automatically. Moreover, we propose a test statistic for testing the null hypothesis of a random-effects varying coefficient panel data model against an FE one. Monte Carlo simulations show that our proposed estimator and test statistic have satisfactory finite sample performance.

Suggested Citation

  • Yiguo Sun & Raymond J. Carroll & Dingding Li, 2009. "Semiparametric estimation of fixed-effects panel data varying coefficient models," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 101-129, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2009)0000025006
    DOI: 10.1108/S0731-9053(2009)0000025006
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    Cited by:

    1. Sun, Xianming & Xiao, Shiyi & Ren, Xiaohang & Xu, Bing, 2023. "Time-varying impact of information and communication technology on carbon emissions," Energy Economics, Elsevier, vol. 118(C).
    2. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    3. Zhang, Shangfeng & Zhang, Chaojie & Su, Zitian & Zhu, Mengyue & Ren, Huiru, 2023. "New structural economic growth model and labor income share," Journal of Business Research, Elsevier, vol. 160(C).

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