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Encompassing Tests for Nonparametric Regressions

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  • Lapenta, Elia
  • Lavergne, Pascal

Abstract

We set up a formal framework to characterize encompassing of nonparametric mod-els through the L2 distance. We contrast it to previous literature on the comparison of nonparametric regression models. We then develop testing procedures for the encom-passing hypothesis that are fully nonparametric. Our test statistics depend on kernel regression, raising the issue of bandwidth’s choice. We investigate two alternative ap-proaches to obtain a “small bias property” for our test statistics. We show the validity of a wild bootstrap method, and we illustrate the attractive features of our tests for small and moderate samples.

Suggested Citation

  • Lapenta, Elia & Lavergne, Pascal, 2022. "Encompassing Tests for Nonparametric Regressions," TSE Working Papers 22-1332, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:126888
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    References listed on IDEAS

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    More about this item

    Keywords

    Encompassing; Nonparametric Regression; Bootstrap; Bias Correction; Locally Robust Statistic.;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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