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A robust test of exogeneity based on quantile regressions

Author

Listed:
  • Tae-Hwan Kim

    (Yonsei University)

  • Christophe Muller

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper, we propose a robust test of exogeneity. The test statistics is constructed from quantile regression estimators, which are robust to heavy tails of errors. We derive the asymptotic distribution of the test statistic under the null hypothesis of exogeneity at a given quantile. The finite sample properties of the test are investigated through Monte Carlo simulations that exhibit not only good size and power properties, but also good robustness to outliers.

Suggested Citation

  • Tae-Hwan Kim & Christophe Muller, 2017. "A robust test of exogeneity based on quantile regressions," Post-Print hal-01647506, HAL.
    • Handle: RePEc:hal:journl:hal-01647506
    DOI: 10.1080/00949655.2017.1319947
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    Cited by:

    1. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(5), pages 123-128, August.
    2. Cristina Bernini & Silvia Emili & Federica Galli, 2021. "Does urbanization matter in the expenditure‐happiness nexus?," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1403-1428, December.

    More about this item

    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    Statistics

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