Estimation of quantile treatment effects with STATA
WARNING: this page is no longer updated. Go to http://www.econ.brown.edu/fac/Blaise_Melly/ to find the current version of the codes. News: This paper will be published by the Stata Journal soon. Therefore, it can nolonger be downloaded from this page. In this paper, we discuss the implementation of various estimators proposed to estimate quantile treatment effects (QTE). We distinguish four cases: conditional and unconditional QTE with exogenous or endogenous treatment variable. Therefore, the ivqte command covers four different estimators: the classical quantile regression estimator of Koenker and Bassett (1978) extended to heteroskedasticity consistent standard errors, the IV quantile regression estimator of Abadie, Angrist, and Imbens (2002), the estimator for unconditional QTE proposed by Firpo (2007), and the IV estimator for unconditional QTE proposed by Frölich and Melly (2007). The implemented IV procedures estimate the causal effects for the sub-population of compliers and are well-suited for binary instruments only. This command also provides analytical standard errors and various options for nonparametric estimation. As a by-product, the command locreg implements local linear and local logit estimators for mixed data (continuous, ordered discrete, unordered discrete and binary regressors).