Quantile regression techniques help understand how different factors affect the distribution of outcomes. The Generalized Quantile Regression (GQR) estimator introduced by Powell in 2013 allows for more flexible estimation of treatment effects without changing the interpretation of the results. It can handle additional variables and instrumental variables, making it useful for various types of data. The GQR estimator is implemented in Stata through the gqr command, which offers options for controlling for endogeneity and estimating standard errors of parameters.