Working Paper

Quantile and probability curves without crossing

Authors

Victor Chernozhukov, Ivan Fernandez-Val, Alfred Galichon

Published Date

30 April 2007

Type

Working Paper (CWP10/07)

The most common approach to estimating conditional quantile curves is to fit a curve, typically linear, pointwise for each quantile. Linear functional forms, coupled with pointwise fitting, are used for a number of reasons including parsimony of the resulting approximations and good computational properties. The resulting fits, however, may not respect a logical monotonicity requirement that the quantile curve be increasing as a function of probability. This paper studies the natural monotonization of these empirical curves induced by sampling from the estimated non-monotone model, and then taking the resulting conditional quantile curves that by construction are monotone in the probability.


Latest version

Quantile and probability curves without crossing
Victor Chernozhukov, Ivan Fernandez-Val, Alfred Galichon
CWP