Trend Extraction From Time Series With 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. A practical problem arises, however, when some data points are missing. This note proposes a method for coping with this problem.

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Year of publication:	2007-05
Authors:	Schlicht, Ekkehart
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Trend extraction \| missing observations \| gaps \| Hodrick-Prescott filter \| Leser filter \| spline \| time-series \| smoothing \| interpolation

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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://www.econbiz.de/10005187274