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Trend Extraction From Time Series With Structural Breaks and Missing Observations

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Author Info
Schlicht, Ekkehart

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Abstract

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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File URL: http://epub.ub.uni-muenchen.de/2127/1/JJSS-Missing_Date_and_Breaks_DP.pdf
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Publisher Info
Paper provided by University of Munich, Department of Economics in its series Discussion Papers in Economics with number 2127.

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Date of creation: 25 Feb 2008
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Handle: RePEc:lmu:muenec:2127

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Related research
Keywords: dummies; gaps; Hodrick-Prescott filter; interpolation; Leser filter; missing observations; smoothing; spline; structural breaks; time-series; trend; break point; break point location;

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

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This page was last updated on 2009-11-26.

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