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Reconsideration of a simple approach to quantile regression for panel data

Author

Listed:
  • Galina Besstremyannaya

    (Centre for Economic and Financial Research at New Economic School)

  • Sergei Golovan

    (New Economic School)

Abstract

The note discusses a fallacy in the approach proposed by Ivan Canay (2011, The Econometrics Journal) for constructing a computationally simple two-step estimator in a quantile regression model with quantile-independent fixed effects. We formally prove that the estimator gives an incorrect inference for the constant term due to violation of the assumption about additive expansion of the first-step estimator, which requires the independence of its terms. Our simulations show that Canay's confidence intervals for the constant term are wrong. Finally, we focus on the fact that finding a sqrt(nT) consistent within estimator, as required by Canay's procedure, may be problematic. We provide an example of a model, for which we formally prove the non-existence of such an estimator.

Suggested Citation

  • Galina Besstremyannaya & Sergei Golovan, 2018. "Reconsideration of a simple approach to quantile regression for panel data," Working Papers w0248, Center for Economic and Financial Research (CEFIR).
    • Handle: RePEc:cfr:cefirw:w0248
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    File URL: http://www.cefir.ru/papers/WP248.pdf
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    References listed on IDEAS

    as
    1. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    2. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
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    Cited by:

    1. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.

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    More about this item

    Keywords

    quantile regression; panel data; fixed effects; inference;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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