Quantile and probability curves without crossing

Victor Chernozhukov, Ivan Fernandez-Val () and Alfred Galichon

No CWP10/07, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract:

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.

Date: 2007-04-30
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Citations: View citations in EconPapers (11)

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Related works:
Working Paper: Quantile and Probability Curves Without Crossing (2014)
Journal Article: Quantile and Probability Curves Without Crossing (2010)
Working Paper: Quantile and Probability Curves without Crossing (2010)
Working Paper: Quantile and Probability Curves without Crossing (2010)
Working Paper: QUANTILE AND PROBABILITY CURVES WITHOUT CROSSING (2007)
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