Quantiles, expectiles and splines

Giuliano De Rossi and Andrew Harvey

Journal of Econometrics, 2009, vol. 152, issue 2, 179-185

Abstract: A time-varying quantile can be fitted by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modified state space signal extraction algorithm. It is shown that such quantiles satisfy the defining property of fixed quantiles in having the appropriate number of observations above and below. Like quantiles, time-varying expectiles can be estimated by a state space signal extraction algorithm and they satisfy properties that generalize the moment conditions associated with fixed expectiles. Because the state space form can handle irregularly spaced observations, the proposed algorithms can be adapted to provide a viable means of computing spline-based non-parametric quantile and expectile regressions.

Keywords: Asymmetric; least; squares; Cubic; splines; Quantile; regression; Signal; extraction; State; space; smoother (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (54)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(09)00015-3
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Quantiles, Expectiles and Splines (2007)
Working Paper: Quantiles, Expectiles and Splines (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:152:y:2009:i:2:p:179-185

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().