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Quantiles, expectiles and splines


DeRossi, Giuliano; Harvey, Andrew


Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):http://nbn-resolving.de/urn:nbn:de:0168-ssoar-212384

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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.
Klassifikation Wirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatik
Freie Schlagwörter C14; C22; Asymmetric least squares; Cubic splines; Quantile regression; Signal extraction; State space smoother
Sprache Dokument Englisch
Publikationsjahr 2009
Seitenangabe S. 179-185
Zeitschriftentitel Journal of Econometrics, 152 (2009) 2
DOI http://dx.doi.org/10.1016/j.jeconom.2009.01.001
Status Postprint; begutachtet (peer reviewed)
Lizenz PEER Licence Agreement (applicable only to documents from PEER project)