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Multivariate Local Polynomial Regression With Autocorrelated Errors

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  • Ke Yang

    (University of Hartford)

Abstract

We propose a three-step local polynomial procedure for a multivariate nonparametric regression in which the errors are autocorrelated. The proposed estimator uses all sample points to estimate m(x), the regression function evaluated at point x, but the contributions from all non-local points are used only through their residuals. Our proposed estimator exhibits good finite sample performance in a Monte Carlo simulation study.

Suggested Citation

  • Ke Yang, 2012. "Multivariate Local Polynomial Regression With Autocorrelated Errors," Economics Bulletin, AccessEcon, vol. 32(4), pages 3298-3305.
    • Handle: RePEc:ebl:ecbull:eb-12-00705
    as

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    File URL: http://www.accessecon.com/Pubs/EB/2012/Volume32/EB-12-V32-I4-P317.pdf
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    References listed on IDEAS

    as
    1. Su, Liangjun & Ullah, Aman, 2006. "More Efficient Estimation In Nonparametric Regression With Nonparametric Autocorrelated Errors," Econometric Theory, Cambridge University Press, vol. 22(1), pages 98-126, February.
    2. 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.
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    More about this item

    Keywords

    local polynomial regression; autocorrelated errors; efficiency;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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