Trend Extraction from Time Series with Structural Breaks and Missing Observations

Ekkehart Schlicht

doi:10.14490/jjss.38.285

Articles

Trend Extraction from Time Series with Structural Breaks and Missing Observations

Author information

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

JOURNAL FREE ACCESS

2008 Volume 38 Issue 2 Pages 285-292

DOI https://doi.org/10.14490/jjss.38.285

Details

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.

Corresponding author

Register with J-STAGE for free!