Trend Extraction From Time Series With Structural Breaks and Missing Observations

Trend extraction from time series is often performed by using the filter proposed by Leser (1961), also known as the Hodrick-Prescott filter. Practical problems arise, however, if the time series contains structural breaks (as produced by German unification for German time series, for instance), or if some data are missing. This note proposes a method for coping with these problems.

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Year of publication:	2008-02-25
Authors:	Schlicht, Ekkehart
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	dummies \| gaps \| Hodrick-Prescott filter \| interpolation \| Leser filter \| missing observations \| smoothing \| spline \| structural breaks \| time-series \| trend \| break point \| break point location

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Extent:	application/pdf
Series:	Discussion Papers in Economics.
Type of publication:	Book / Working Paper
Language:	English
Classification:	C22 - Time-Series Models ; C32 - Time-Series Models ; C63 - Computational Techniques ; C14 - Semiparametric and Nonparametric Methods
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005649812