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Smoothed quantile regression for panel data

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  • Galvao, Antonio F.
  • Kato, Kengo

Abstract

This paper studies fixed effects estimation of quantile regression models for panel data. Under an asymptotic framework where both the numbers of individuals and time periods grow at the same rate, we show that the fixed-effects estimator for the smoothed objective function has a limiting normal distribution with a bias in the mean, and provide the analytic form of the asymptotic bias. We propose a one-step bias correction estimator based on the analytic bias formula obtained from the asymptotic analysis. Importantly, our results cover the case that observations are dependent over time. We illustrate the effects of the bias correction through simulations.

Suggested Citation

  • Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    • Handle: RePEc:eee:econom:v:193:y:2016:i:1:p:92-112
    DOI: 10.1016/j.jeconom.2016.01.008
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    More about this item

    Keywords

    Bias correction; Incidental parameters problem; Panel data; Quantile regression; Smoothing;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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