Identification of quantile regression models with endogeneity

The instrumental variables approach is a standard practice to address endogeneity, while it is often challenging to obtain valid and strong instruments in many empirical studies. This paper considers a linear simultaneous triangular system of quantile regressions in the absence of instruments. We establish identification results for this model by leveraging copula of the latent error terms to characterize their dependence structure.