|Authors:||Victor Chernozhukov , Ivan Fernandez-Val and Alfred Galichon|
|Date:||31 May 2010|
|Type:||Journal article, Econometrica, Vol. 78, No. 3, pp. 1093–1125|
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.