文章基本信息

标题：Quantiles, Expectiles and Splines
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作者：Giuliano De Rossi ; Andrew Harvey
期刊名称：Cambridge Working Papers in Economics / Faculty of Economics ; Department of Applied Economics
出版年度：2007
卷号：1
出版社：Cambridge University
摘要：A time-varying quantile can be .tted to a sequence of observations by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modi.ed state space sig- nal extraction algorithm. It is shown that such time-varying quantiles satisfy the de.ning property of .xed quantiles in having the appropri- ate number of observations above and below. Expectiles are similar to quantiles except that they are de.ned by tail expectations. 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 .xed expectiles. Time-varying quantiles and expectiles provide information on various aspects of a time series, such as dispersion and asymmetry, while estimates at the end of the series provide the basis for forecasting. Because the state space form can handle irregularly spaced observations, the proposed algorithms can be easily adapted to provide a viable means of comput- ing spline-based non-parametric quantile and expectile regressions.
关键词：Asymmetric least squares; cubic splines; dispersion; non-parametric regression; quantile regression; signal extraction; state space smoother.