Quantile Regression Methods
Title
Quantile Regression Methods
Author
Fitzenberger, Bernd
Wilke, Ralf Andreas
Research Area
Methods of Research
Topic
Statistical Methods
Abstract
Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even if the mean regression model does not.