分组分位数回归QUANTILE REGRESSION FOR GROUP-LEVEL TREATMENTS




   A methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group-level unobservables,a quantile extension of Hausman and Taylor（1981）。Because of the presence of group-level unobservables,standard quantile regression techniques are inconsistent in our setting even if the treatment is independent of unobservables.In contrast,our estimation technique is consistent as well as computationally simple,consisting of group-by-group
quantile regression followed by two-stage least squares.Using the Bahadur representation of quantile estimators,we derive weak conditions on the growth of the number of observations per group that are sufficient for consistency and asymptotic zero-mean normality of our estimator。