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
Authors:	Schlicht, Ekkehart
Publisher:	München : Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät
Subject:	Trend \| Zeitreihenanalyse \| Statistische Methodenlehre \| Trend extraction \| missing observations \| gaps \| Hodrick-Prescott filter \| Leser filter \| spline \| time-series \| smoothing \| interpolation.

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Series:	Munich Discussion Paper ; 2007-18
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.5282/ubm/epub.1927 [DOI] 530983192 [GVK] hdl:10419/104229 [Handle] RePEc:lmu:muenec:1927 [RePEc]
Classification:	C22 - Time-Series Models ; C32 - Time-Series Models ; C63 - Computational Techniques ; C14 - Semiparametric and Nonparametric Methods
Source:	EconStor

Persistent link: https://www.econbiz.de/10010427491