Horowitz, J.;
Lee, S.;
(2004)
Nonparametric estimation of an additive quantile regression model.
(cemmap Working Papers
CWP07/).
Institute for Fiscal Studies: London, UK.
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Abstract
This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n^{-r/(2+10)} when the additive components are r-times continuously differentiable for some r\geq2. This result holds regardless of the dimension of the covariates and, therefore, the new estimator has no curse of dimensionality. In addition, the estimator has an oracle property and is easily extended to a generalized additive quantile regression model with a link function. The numerical performance and usefulness of the estimator are illustrated by Monte Carlo experiments and an empirical example.
| Type: | Working / discussion paper |
|---|---|
| Title: | Nonparametric estimation of an additive quantile regression model |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://www.cemmap.ac.uk/publications.php?publicati... |
| Language: | English |
| Additional information: | Please see http://eprints.ucl.ac.uk/12660/ for the version published in the Journal of the American Statistical Association. The abstract contains LaTex text; please see the PDF for rendered equations |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/14695 |
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