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Estimating Semiparametric Panel Data Models by Marginal Integration

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  • Qian, Junhui
  • Wang, Le
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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.

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File URL: http://mpra.ub.uni-muenchen.de/18850/
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 18850.

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Date of creation: 10 Nov 2009
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Handle: RePEc:pra:mprapa:18850

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Keywords: Semiparametric Panel Data Model; Partially Linear; First Differencing; Marginal Integration;

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  1. Li, Qi, 1996. "On the root-N-consistent semiparametric estimation of partially linear models," Economics Letters, Elsevier, Elsevier, vol. 51(3), pages 277-285, June.
  2. Su, Liangjun & Ullah, Aman, 2006. "Profile likelihood estimation of partially linear panel data models with fixed effects," Economics Letters, Elsevier, Elsevier, vol. 92(1), pages 75-81, July.
  3. Naisyin Wang, 2003. "Marginal nonparametric kernel regression accounting for within-subject correlation," Biometrika, Biometrika Trust, Biometrika Trust, vol. 90(1), pages 43-52, March.
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  6. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, Econometric Society, vol. 56(4), pages 931-54, July.
  7. Su, Liangjun & Ullah, Aman, 2007. "More efficient estimation of nonparametric panel data models with random effects," Economics Letters, Elsevier, Elsevier, vol. 96(3), pages 375-380, September.
  8. KNEIP, Alois & SIMAR, Léopold, 1995. "A General Framework for Frontier Estimation with Panel Data," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 1995060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, Elsevier, vol. 144(1), pages 257-275, May.
  10. 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.
  11. Newey, Whitney K., 1994. "Kernel Estimation of Partial Means and a General Variance Estimator," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 10(02), pages 1-21, June.
  12. Mammen, Enno & Støve, Bård & Tjøstheim, Dag, 2009. "Nonparametric Additive Models For Panels Of Time Series," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 25(02), pages 442-481, April.
  13. 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, Springer, vol. 19(1), pages 166-186, May.
  14. Li, Qi & Stengos, Thanasis, 1996. "Semiparametric estimation of partially linear panel data models," Journal of Econometrics, Elsevier, Elsevier, vol. 71(1-2), pages 389-397.
  15. Hengartner, Nicolas W. & Sperlich, Stefan, 2005. "Rate optimal estimation with the integration method in the presence of many covariates," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 95(2), pages 246-272, August.
  16. Banerjee, Abhijit V & Duflo, Esther, 2003. " Inequality and Growth: What Can the Data Say?," Journal of Economic Growth, Springer, Springer, vol. 8(3), pages 267-99, September.
  17. 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, Elsevier, vol. 47(2-3), pages 359-377, February.
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Cited by:
  1. Lena Korber & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, Elsevier, vol. 176(2), pages 112-133.

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