Minimax Regression Quantiles

Stefan Bache ()

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question.

Keywords: Quantile regression; non-linear quantile regression; estimating functions; minimax estimation; empirical process theory (search for similar items in EconPapers)
JEL-codes: C1 C4 C5 C6 (search for similar items in EconPapers)
Pages: 15
Date: 2010-08-01
New Economics Papers: this item is included in nep-ecm and nep-ore
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