Panel Data Quantile Regression with Grouped Fixed Effects

01/15/2018

∙

by   Jiaying Gu, et al.

∙

0

∙

share

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.