A Monte Carlo comparison of parametric and nonparametric quantile regressions

This study compares parametric and nonparametric quantile regression methods using Monte Carlo simulations. Simulation results indicate that the nonparametric quantile regression approach is more appropriate, particularly when the underlying model is nonlinear or the error term follows a non-normal distribution.

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Year of publication:	2004
Authors:	Min, Insik ; Kim, Inchul
Published in:	Applied Economics Letters. - Taylor & Francis Journals, ISSN 1350-4851. - Vol. 11.2004, 2, p. 71-74
Publisher:	Taylor & Francis Journals

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005632596