This paper proposes a quantile regression estimator for a model with interactive effects potentially correlated with covariates. We provide conditions under which the estimator is asymptotically Gaussian and we investigate the finite sample performance of the method. An approach to testing the...

This paper proposes an ℓ1 penalized quantile regression estimator which adapts the Hausman–Taylor instrumental variable approach in order to address the bias resulting from the shrinkage of the individual effects.