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Consistent specification test for partially linear models with the k-nearest-neighbor method

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  • Wang, Wenju
  • Wang, Qiao

Abstract

This study proposes a consistent test for the partially linear model based on the k-nearest-neighbor estimation method. The test statistic has an asymptotic normal distribution under the null hypothesis and diverges to positive infinity when the null hypothesis is false. Simulations show that the estimated power of the proposed test is better than that of the kernel method when the data have heavy tails.

Suggested Citation

  • Wang, Wenju & Wang, Qiao, 2019. "Consistent specification test for partially linear models with the k-nearest-neighbor method," Economics Letters, Elsevier, vol. 177(C), pages 89-93.
    • Handle: RePEc:eee:ecolet:v:177:y:2019:i:c:p:89-93
    DOI: 10.1016/j.econlet.2019.02.004
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    References listed on IDEAS

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    Cited by:

    1. Yixiao Jiang, 2020. "A Hausman Test for Partially Linear Models with an Application to Implied Volatility Surface," JRFM, MDPI, vol. 13(11), pages 1-12, November.

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    More about this item

    Keywords

    Partially linear model; k-nearest-neighbor; Consistent test;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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