Estimation of quantile treatment effects with Stata

In this article, we discuss the implementation of various estimators proposed to estimate quantile treatment effects. We distinguish four cases involving conditional and unconditional quantile treatment effects with either exogenous or endogenous treatment variables. The introduced ivqte command covers four different estimators: the classical quantile regression estimator of Koenker and Bassett (1978, Econometrica 46: 33-50) extended to heteroskedasticity consistent standard errors; the instrumental-variable quantile regression estimator of Abadie, Angrist, and Imbens (2002, Econometrica 70: 91-117); the estimator for unconditional quantile treatment effects proposed by Firpo (2007, Econometrica, 75: 259-276); and the instrumental-variable estimator for unconditional quantile treatment effects proposed by Frolich and Melly (2008, IZA discussion paper 3288). The implemented instrumental-variable procedures estimate the causal effects for the subpopulation of compliers and are only well suited for binary instruments. ivqte also provides analytical standard errors and various options for nonparametric estimation. As a by-product, the locreg command implements local linear and local logit estimators for mixed data (continuous, ordered discrete, unordered discrete, and binary regressors).