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Panel data quantile regression with grouped fixed effects

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  • Gu, Jiaying
  • Volgushev, Stanislav

Abstract

This paper introduces estimation methods for grouped latent heterogeneity in panel data quantile regression. We assume that the observed individuals come from a heterogeneous population with a finite number of types. The number of types and group membership is not assumed to be known in advance and is estimated by means of a convex optimization problem. We provide conditions under which group membership is estimated consistently and establish asymptotic normality of the resulting estimators. Simulations show that the method works well in finite samples when T is reasonably large.

Suggested Citation

  • Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    • Handle: RePEc:eee:econom:v:213:y:2019:i:1:p:68-91
    DOI: 10.1016/j.jeconom.2019.04.006
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    References listed on IDEAS

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