Unconditional Quantile Regressions
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Abstract
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.
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The record
- Venue
- Econometrica
- Topic
- Statistical Methods and Inference
- Field
- Mathematics
- Canadian institutions
- University of British ColumbiaCanadian Institute for Advanced Research
- Funders
- —
- Keywords
- QuantileQuantile regressionEconometricsMathematicsStatisticsQuantile functionMarginal distributionVariable (mathematics)Distribution (mathematics)Random variableCumulative distribution functionProbability density function
- Has abstract in OpenAlex
- yes