This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

  1. Home
  2. Journals
  3. Journal of Economic Perspectives
  4. Fall 2001
  5. Quantile Regression

Journal of Economic Perspectives

ISSN 0895-3309 (Print) | ISSN 1944-7965 (Online)

Quantile Regression

  • Roger Koenker
  • Kevin F. Hallock
Journal of Economic Perspectives
vol. 15, no. 4, Fall 2001
(pp. 143–156)
Download Full Text PDF
(Complimentary)

Abstract

Quantile regression, as introduced by Koenker and Bassett (1978), may be viewed as an extension of classical least squares estimation of conditional mean models to the estimation of an ensemble of models for several conditional quantile functions. The central special case is the median regression estimator which minimizes a sum of absolute errors. Other conditional quantile functions are estimated by minimizing an asymmetrically weighted sum of absolute errors. Quantile regression methods are illustrated with applications to models for CEO pay, food expenditure, and infant birthweight.

Citation

Koenker, Roger, and Kevin F. Hallock. 2001. "Quantile Regression." Journal of Economic Perspectives, 15 (4): 143–156. DOI: 10.1257/jep.15.4.143

JEL Classification

  • C20 Single Equation Models; Single Variables: General
There are no comments for this article.
Login to Comment