Arbeitspapier
How good are out of sample forecasting Tests on DSGE models?
Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the specification b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of specification will almost definitely also improve on VAR forecasts.
- Sprache
-
Englisch
- Erschienen in
-
Series: Cardiff Economics Working Papers ; No. E2014/11
- Klassifikation
-
Wirtschaft
General Aggregative Models: General
General Aggregative Models: Forecasting and Simulation: Models and Applications
- Thema
-
Out of sample forecasts
DSGE
VAR
specification tests
indirect inference
forecast performance
DSGE-Modell
Prognoseverfahren
Modellierung
Statistischer Test
VAR-Modell
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Minford, Patrick
Xu, Yongdeng
Zhou, Peng
- Ereignis
-
Veröffentlichung
- (wer)
-
Cardiff University, Cardiff Business School
- (wo)
-
Cardiff
- (wann)
-
2014
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Minford, Patrick
- Xu, Yongdeng
- Zhou, Peng
- Cardiff University, Cardiff Business School
Entstanden
- 2014
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