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Estimating Semiparametric Panel Data Models by Marginal Integration

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  • Qian, Junhui
  • Wang, Le

Abstract

We propose a new methodology for estimating semiparametric panel data models, with a primary focus on the nonparametric component. We eliminate individual effects using first differencing transformation and estimate the unknown function by marginal integration. We extend our methodology to treat panel data models with both individual and time effects. And we characterize the asymptotic behavior of our estimators. Monte Carlo simulations show that our estimator behaves well in finite samples in both random effects and fixed effects settings.

Suggested Citation

  • Qian, Junhui & Wang, Le, 2009. "Estimating Semiparametric Panel Data Models by Marginal Integration," MPRA Paper 18850, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:18850
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    References listed on IDEAS

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    1. Daniel L. Millimet & John A. List & Thanasis Stengos, 2003. "The Environmental Kuznets Curve: Real Progress or Misspecified Models?," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1038-1047, November.
    2. Su, Liangjun & Ullah, Aman, 2007. "More efficient estimation of nonparametric panel data models with random effects," Economics Letters, Elsevier, vol. 96(3), pages 375-380, September.
    3. Oliver Linton & David Jacho-Chávez, 2010. "On internally corrected and symmetrized kernel estimators for nonparametric regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 166-186, May.
    4. Mammen, Enno & Støve, Bård & Tjøstheim, Dag, 2009. "Nonparametric Additive Models For Panels Of Time Series," Econometric Theory, Cambridge University Press, vol. 25(2), pages 442-481, April.
    5. Newey, Whitney K., 1994. "Kernel Estimation of Partial Means and a General Variance Estimator," Econometric Theory, Cambridge University Press, vol. 10(2), pages 1-21, June.
    6. Andrews, Donald W. K., 1991. "Asymptotic optimality of generalized CL, cross-validation, and generalized cross-validation in regression with heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 359-377, February.
    7. KNEIP, Alois & SIMAR, Léopold, 1995. "A General Framework for Frontier Estimation with Panel Data," LIDAM Discussion Papers CORE 1995060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Masry, Elias & Tjøstheim, Dag, 1997. "Additive Nonlinear ARX Time Series and Projection Estimates," Econometric Theory, Cambridge University Press, vol. 13(2), pages 214-252, April.
    9. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
    10. Li, Qi, 1996. "On the root-N-consistent semiparametric estimation of partially linear models," Economics Letters, Elsevier, vol. 51(3), pages 277-285, June.
    11. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    12. Li, Qi & Stengos, Thanasis, 1996. "Semiparametric estimation of partially linear panel data models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 389-397.
    13. 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.
    14. Hardle, W. & Marron, J., 1989. "Bootstrap Simultaneous Error Bars For Nonparametric Regression," LIDAM Discussion Papers CORE 1989023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Banerjee, Abhijit V & Duflo, Esther, 2003. "Inequality and Growth: What Can the Data Say?," Journal of Economic Growth, Springer, vol. 8(3), pages 267-299, September.
    16. Su, Liangjun & Ullah, Aman, 2006. "Profile likelihood estimation of partially linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 92(1), pages 75-81, July.
    17. Naisyin Wang, 2003. "Marginal nonparametric kernel regression accounting for within-subject correlation," Biometrika, Biometrika Trust, vol. 90(1), pages 43-52, March.
    18. Hengartner, Nicolas W. & Sperlich, Stefan, 2005. "Rate optimal estimation with the integration method in the presence of many covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 246-272, August.
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    Cited by:

    1. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.
    2. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    3. 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.
    4. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    5. Peter Pütz & Thomas Kneib, 2018. "A penalized spline estimator for fixed effects panel data models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 145-166, April.
    6. Juan Rodriguez-Poo & Alexandra Soberón, 2015. "Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study," Computational Statistics, Springer, vol. 30(3), pages 885-906, September.
    7. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    8. 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.
    9. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Halder, Shaymal C. & Malikov, Emir, 2020. "Smoothed LSDV estimation of functional-coefficient panel data models with two-way fixed effects," Economics Letters, Elsevier, vol. 192(C).
    11. Henderson, Daniel J. & Qian, Junhui & Wang, Le, 2015. "The inequality–growth plateau," Economics Letters, Elsevier, vol. 128(C), pages 17-20.
    12. Huazhen Lin & Hyokyoung G. Hong & Baoying Yang & Wei Liu & Yong Zhang & Gang-Zhi Fan & Yi Li, 2019. "Nonparametric Time-Varying Coefficient Models for Panel Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 548-566, December.
    13. Li, Cong & Liang, Zhongwen, 2015. "Asymptotics for nonparametric and semiparametric fixed effects panel models," Journal of Econometrics, Elsevier, vol. 185(2), pages 420-434.
    14. Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
    15. Chu, Chi-Yang & Henderson, Daniel J. & Parmeter, Christopher F., 2017. "On discrete Epanechnikov kernel functions," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 79-105.
    16. Taining Wang & Jinjing Tian, 2020. "Recasting the trade impact on labor share: a fixed-effect semiparametric estimation study," Empirical Economics, Springer, vol. 58(5), pages 2465-2511, May.
    17. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers CWP06/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.
    19. 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

    Semiparametric Panel Data Model; Partially Linear; First Differencing; Marginal Integration;
    All these keywords.

    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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