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Quantiles, expectiles and splines
[journal article]
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 appr... view more
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.... view less
Classification
Economic Statistics, Econometrics, Business Informatics
Free Keywords
C14; C22; Asymmetric least squares; Cubic splines; Quantile regression; Signal extraction; State space smoother
Document language
English
Publication Year
2009
Page/Pages
p. 179-185
Journal
Journal of Econometrics, 152 (2009) 2
DOI
https://doi.org/10.1016/j.jeconom.2009.01.001
Status
Postprint; peer reviewed
Licence
PEER Licence Agreement (applicable only to documents from PEER project)