Arbeitspapier

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.

Sprache
Englisch

Erschienen in
Series: Munich Discussion Paper ; No. 2008-3

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Computational Techniques; Simulation Modeling
Semiparametric and Nonparametric Methods: General
Thema
dummies
gaps
Hodrick-Prescott filter
interpolation
Leser filter
missing observations
smoothing
spline
structural breaks
time-series
trend
break point
break point location
Trend
Zeitreihenanalyse
Strukturbruch
Statistische Methodenlehre
Theorie

Ereignis
Geistige Schöpfung
(wer)
Schlicht, Ekkehart
Ereignis
Veröffentlichung
(wer)
Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät
(wo)
München
(wann)
2008

DOI
doi:10.5282/ubm/epub.2127
Handle
URN
urn:nbn:de:bvb:19-epub-2127-6
Letzte Aktualisierung
20.09.2024, 08:23 MESZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Schlicht, Ekkehart
  • Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät

Entstanden

  • 2008

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