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Linear Quantile Regression and Endogeneity Correction

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  • Christophe Muller

    (AMSE - Aix-Marseille Sciences Economiques - 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

The main two methods of endogeneity correction for linear quantile regressions with their advantages and drawbacks are reviewed and compared. Then, we discuss opportunities of alleviating the constant effect restriction of the fitted-value approach by relaxing identification conditions.

Suggested Citation

  • Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Working Papers halshs-02272874, HAL.
    • Handle: RePEc:hal:wpaper:halshs-02272874
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02272874
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    10. 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.
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    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.

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    More about this item

    Keywords

    Two-Stage Estimation; Quantile Regression; Fitted-Value Approach; Endogeneity;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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    This paper has been announced in the following NEP Reports:

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