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Nonparametric regression estimation with general parametric error covariance

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  • Martins-Filho, Carlos
  • Yao, Feng

Abstract

The asymptotic distribution for the local linear estimator in nonparametric regression models is established under a general parametric error covariance with dependent and heterogeneously distributed regressors. A two-step estimation procedure that incorporates the parametric information in the error covariance matrix is proposed. Sufficient conditions for its asymptotic normality are given and its efficiency relative to the local linear estimator is established. We give examples of how our results are useful in some recently studied regression models. A Monte Carlo study confirms the asymptotic theory predictions and compares our estimator with some recently proposed alternative estimation procedures.

Suggested Citation

  • Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
  • Handle: RePEc:eee:jmvana:v:100:y:2009:i:3:p:309-333
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ke Yang, 2012. "Multivariate Local Polynomial Regression With Autocorrelated Errors," Economics Bulletin, AccessEcon, vol. 32(4), pages 3298-3305.
    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. Ke Yang, 2013. "An Improved Local-linear Estimator For Nonparametric Regression With Autoregressive Errors," Economics Bulletin, AccessEcon, vol. 33(1), pages 19-27.
    4. 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.
    5. Shujie Ma & Jeffrey S. Racine & Aman Ullah, 2015. "Nonparametric Regression-Spline Random Effects Models," Department of Economics Working Papers 2015-10, McMaster University.
    6. Rodriguez-Poo, Juan M. & Soberón, Alexandra, 2015. "Nonparametric estimation of fixed effects panel data varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 95-122.
    7. Paul Evans & Ji Uk Kim, 2016. "Convergence analysis as spatial dynamic panel regression and distribution dynamics of $$\hbox {CO}_{2}$$ CO 2 emissions in Asian countries," Empirical Economics, Springer, vol. 50(3), pages 729-751, May.
    8. Charnigo, Richard & Feng, Limin & Srinivasan, Cidambi, 2015. "Nonparametric and semiparametric compound estimation in multiple covariates," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 179-196.
    9. 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.
    10. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, Open Access Journal, vol. 4(3), pages 1-17, September.
    11. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

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