Vector quantile regression beyond the specified case
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1-s2.0-S0047259X17304232-main.pdf
Description
Published version
Size
420.58 KB
Format
Adobe PDF
Checksum (MD5)
be2b8a73ee9672abd2aca5b6988f512e
Author(s)
Carlier, Guillaume
Chernozhukov, Victor V
Galichon, Alfred
Date Issued
September 2017
Journal
Journal of Multivariate Analysis
Publisher
Elsevier BV
Citation
Carlier, Guillaume et al. "Vector quantile regression beyond the specified case." Journal of Multivariate Analysis, 161, (July 2017): 96-102 © 2017 The Authors.
Version
Final published version
Abstract
This paper studies vector quantile regression (VQR), which models the dependence of a random vector with respect to a vector of explanatory variables with enough flexibility to capture the whole conditional distribution, and not only the conditional mean. The problem of vector quantile regression is formulated as an optimal transport problem subject to an additional mean-independence condition. This paper provides results on VQR beyond the specified case which had been the focus of previous work. We show that even beyond the specified case, the VQR problem still has a solution which provides a general representation of the conditional dependence between random vectors. Keywords: Duality; Optimal transport; Vector quantile regression
MIT Department
Massachusetts Institute of Technology. Department of Economics
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.jmva.2017.07.003
