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Improving Oil Price Forecasts by Sparse VAR Methods

Krüger, Jens ; Ruths Sion, Sebastian (2019)
Improving Oil Price Forecasts by Sparse VAR Methods.
doi: 10.25534/tuprints-00009643
Report, Erstveröffentlichung

Kurzbeschreibung (Abstract)

In this paper we document the results of a forecast evaluation exercise for the real world price of crude oil using VAR models estimated by sparse (regularization) estimators. These methods have the property to constrain single parameters to zero. We find that estimating VARs with three core variables (real price of oil, index of global real economic activity, change in global crude oil production) by the sparse methods is associated with substantial reductions of forecast errors. The transformation of the variables (taking logs or differences) is also crucial. Extending the VARs by further variables is not associated with additonal gains in forecast performance as is the application of impulse indicator saturation before the estimation.

Typ des Eintrags: Report
Erschienen: 2019
Autor(en): Krüger, Jens ; Ruths Sion, Sebastian
Art des Eintrags: Erstveröffentlichung
Titel: Improving Oil Price Forecasts by Sparse VAR Methods
Sprache: Englisch
Publikationsjahr: Dezember 2019
Reihe: Darmstadt Discussion Papers in Economics
Band einer Reihe: 237
DOI: 10.25534/tuprints-00009643
URL / URN: https://tuprints.ulb.tu-darmstadt.de/9643
Kurzbeschreibung (Abstract):

In this paper we document the results of a forecast evaluation exercise for the real world price of crude oil using VAR models estimated by sparse (regularization) estimators. These methods have the property to constrain single parameters to zero. We find that estimating VARs with three core variables (real price of oil, index of global real economic activity, change in global crude oil production) by the sparse methods is associated with substantial reductions of forecast errors. The transformation of the variables (taking logs or differences) is also crucial. Extending the VARs by further variables is not associated with additonal gains in forecast performance as is the application of impulse indicator saturation before the estimation.

URN: urn:nbn:de:tuda-tuprints-96436
Zusätzliche Informationen:

JEL classification: C32, Q47

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 300 Sozialwissenschaften > 330 Wirtschaft
Fachbereich(e)/-gebiet(e): 01 Fachbereich Rechts- und Wirtschaftswissenschaften
01 Fachbereich Rechts- und Wirtschaftswissenschaften > Volkswirtschaftliche Fachgebiete
01 Fachbereich Rechts- und Wirtschaftswissenschaften > Volkswirtschaftliche Fachgebiete > Fachgebiet Empirische Wirtschaftsforschung
Hinterlegungsdatum: 08 Dez 2019 20:55
Letzte Änderung: 08 Dez 2019 20:55
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