Unconditional Quantile Regressions
提出一种新回归方法，通过将无条件分位数的影响函数回归到解释变量上，来评估解释变量分布变化对结果变量无条件分位数的影响。
We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics. Copyright 2009 The Econometric Society.