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One for all and all for one: regression checks with many regressors

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  • Lavergne, Pascal
  • Patilea, Valentin

Abstract

We develop a novel approach to build checks of parametric regression models when many regressors are present, based on a class of sufficiently rich semiparametric alternatives, namely single-index models. We propose an omnibus test based on the kernel method that performs against a sequence of directional nonparametric alternatives as if there was one regressor only, whatever the number of regressors. This test can be viewed as a smooth version of the integrated conditional moment (ICM) test of Bierens. Qualitative information can be easily incorporated into the procedure to enhance power. In an extensive comparative simulation study, we find that our test is little sensitive to the smoothing parameter and performs well in multidimensional settings. We then apply it to a cross-country growth regression model.

Suggested Citation

  • Lavergne, Pascal & Patilea, Valentin, 2011. "One for all and all for one: regression checks with many regressors," MPRA Paper 35779, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:35779
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    References listed on IDEAS

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    Cited by:

    1. Maistre, Samuel & Lavergne, Pascal & Patilea, Valentin, 2014. "Powerful nonparametric checks for quantile regression," TSE Working Papers 14-501, Toulouse School of Economics (TSE).

    More about this item

    Keywords

    Dimensionality; Hypothesis testing; Nonparametric methods;

    JEL classification:

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

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