Arbeitspapier
On the Design of Data Sets for Forecasting with Dynamic Factor Models
Forecasts from dynamic factor models potentially benefit from refining the data set by eliminating uninformative series. The paper proposes to use forecast weights as provided by the factor model itself for this purpose. Monte Carlo simulations and an empirical application to forecasting euro area, German, and French GDP growth from unbalanced monthly data suggest that both forecast weights and least angle regressions result in improved forecasts. Overall, forecast weights provide yet more robust results.
- Sprache
-
Englisch
- Erschienen in
-
Series: WIFO Working Papers ; No. 376
- Klassifikation
-
Wirtschaft
- Thema
-
Faktorenanalyse
Prognoseverfahren
Monte-Carlo-Simulation
Schätzung
Nationaleinkommen
Deutschland
Frankreich
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Rünstler, Gerhard
- Ereignis
-
Veröffentlichung
- (wer)
-
Austrian Institute of Economic Research (WIFO)
- (wo)
-
Vienna
- (wann)
-
2010
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
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.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Rünstler, Gerhard
- Austrian Institute of Economic Research (WIFO)
Entstanden
- 2010
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