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Nonparametric estimation of the marginal effect in fixed-effect panel data models

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  • Lee, Yoonseok
  • Mukherjee, Debasri
  • Ullah, Aman

Abstract

This paper considers multivariate local linear least squares estimation of panel data models when fixed effects are present. One-step estimation of the local marginal effect is of prime interest. A within-group nonparametric estimator is developed, where the fixed effects are eliminated by subtracting individual-specific locally weighted time average, i.e., the local-within-transformation. It is shown that the local-within-transformation-based estimator satisfies the standard properties of the local linear estimator. In comparison, nonparametric estimators based on the conventional (global) within-transformation or first difference result in estimators which are biased, even in large samples. The new estimator is used to examine the nonlinear relationship between income and nitrogen-oxide level (i.e., the environmental Kuznets curve) based on US state-level panel data.

Suggested Citation

  • Lee, Yoonseok & Mukherjee, Debasri & Ullah, Aman, 2019. "Nonparametric estimation of the marginal effect in fixed-effect panel data models," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 53-67.
    • Handle: RePEc:eee:jmvana:v:171:y:2019:i:c:p:53-67
    DOI: 10.1016/j.jmva.2018.11.013
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    2. Qian, Junhui & Wang, Le, 2012. "Estimating semiparametric panel data models by marginal integration," Journal of Econometrics, Elsevier, vol. 167(2), pages 483-493.
    3. Yoonseok Lee & Donggyu Sul, 2022. "Trimmed Mean Group Estimation," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 177-202, Emerald Group Publishing Limited.
    4. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    5. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
    6. Almeida, Alexandre N. & Santos, Augusto S. & Halmenschlager, Vinícius & Gilio, Leandro & Diniz, Tiago B. & Ferreira, Alexandre A. S., 2016. "Flexible-fuel automobiles and CO2 emissions in Brazil: a semiparametric analysis using panel data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235733, Agricultural and Applied Economics Association.
    7. Tomasz Czekaj & Arne Henningsen, 2013. "Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions," IFRO Working Paper 2013/5, University of Copenhagen, Department of Food and Resource Economics.
    8. Huijun Ji & Arber Hoti, 2022. "Green economy based perspective of low-carbon agriculture growth for total factor energy efficiency improvement," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 353-363, March.
    9. Lee, Yoonseok & Sul, Donggyu, 2023. "Depth-weighted means of noisy data: An application to estimating the average effect in heterogeneous panels," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    10. Kota Ogasawara & Yukitoshi Matsushita, 2019. "Heterogeneous treatment effects of safe water on infectious disease: Do meteorological factors matter?," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 13(1), pages 55-82, January.
    11. De Monte Enrico, 2024. "Nonparametric Instrumental Regression with Two-Way Fixed Effects," Journal of Econometric Methods, De Gruyter, vol. 13(1), pages 49-66, January.

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    More about this item

    Keywords

    Environmental Kuznets curve; Fixed effects; Local-within-transformation; Multivariate local linear least squares; Nonparametric estimation; Panel data;
    All these keywords.

    JEL classification:

    • 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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