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Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models

Author

Listed:
  • Aman Ullah

    (Department of Economics, University of California Riverside)

  • Yoonseok Lee

    (Syracuse University)

  • Debasri Mukherjee

    (Western Michigan University)

Abstract

This paper considers multivariate local linear least squares estimation of panel data models when fixed effects present. One step estimation of the local marginal effect is of the main interest. A within-group type nonparametric estimator is developed, where the fixed effects are eliminated by subtracting individual-specific locally weighted time average (i.e., using 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, the nonparametric estimators based on the conventional (i.e., global) within transformation or first difference result in biased estimators, where the bias does not degenerate even with 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 the U.S. state-level panel data.

Suggested Citation

  • Aman Ullah & Yoonseok Lee & Debasri Mukherjee, 2018. "Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models," Working Papers 201901, University of California at Riverside, Department of Economics.
    • Handle: RePEc:ucr:wpaper:201901
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    Cited by:

    1. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    2. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
    3. van den Berg, G. J & Lundborg P & Nystedt P & Rooth D, 2009. "Critical Periods During Childhood and Adolescence: A Study of Adult Height Among Immigrant Siblings," Health, Econometrics and Data Group (HEDG) Working Papers 09/20, HEDG, c/o Department of Economics, University of York.
    4. 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.
    5. 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.
    6. 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.
    7. Qian, Junhui & Wang, Le, 2012. "Estimating semiparametric panel data models by marginal integration," Journal of Econometrics, Elsevier, vol. 167(2), pages 483-493.
    8. Almeida, Alexandre N. & Santos, Augusto S. & Halmenschlager, Vinícius & Gilio, Leandro & Diniz, Tiago B. & Ferreira, Alexandre A. S., "undated". "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.
    9. 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.
    10. 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).
    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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    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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