When we want to study the effects of covariates on different quantiles of the outcome, not just on the mean, we use quantile regression. For instance, we might be interested in modeling the grade distribution of students and how it is affected by changes in covariates. The existing qreg command fits quantile regression models, but what if we suspect that one of our covariates is endogenous? This endogeneity might arise for reasons such as self-selection of study participants, omission of a relevant variable from the model, or measurement error. The new ivqregress command allows us to model quantiles of the outcome and, at the same time, control for problems that arise from endogeneity using IV.
After fiting an IV quantile regression model, you can plot the coefficients across quantiles with the estat coefplot command. You can test for endogeneity using the estat endogeffects command. And you can estimate dual confidence intervals that are robust to weak instruments using estat dualci.