Panel data quantile regression with grouped fixed effects

By Jiaying Gu, Stanislav Volgushev. Journal of Econometrics, 2018

55 citations recorded by the source corpus.

This paper introduces grouped latent heterogeneity in panel data quantile regression. More precisely, we assume that the observed individuals come from a heterogeneous population with an unknown, 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.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5c42b2a28120004a3476399fb2b75f83ab4f60e4