Arbeitspapier
Forecasting with a noncausal VAR model
We propose simulation-based forecasting methods for the noncausal vector autoregressive model proposed by Lanne and Saikkonen (2012). Simulation or numerical methods are required because the prediction problem is generally nonlinear and, therefore, its analytical solution is not available. It turns out that different special cases of the model call for different simulation procedures. Simulation experiments demonstrate that gains in forecasting accuracy are achieved by using the correct noncausal VAR model instead of its conventional causal counterpart. In an empirical application, a noncausal VAR model comprised of U.S. inflation and marginal cost turns out superior to the bestfitting conventional causal VAR model in forecasting inflation.
- ISBN
-
978-952-462-828-0
- Sprache
-
Englisch
- Erschienen in
-
Series: Bank of Finland Research Discussion Papers ; No. 33/2012
- Klassifikation
-
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
- Thema
-
Noncausal vector autoregression
forecasting
simulation
importance sampling
inflation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Nyberg, Henri
Saikkonen, Pentti
- Ereignis
-
Veröffentlichung
- (wer)
-
Bank of Finland
- (wo)
-
Helsinki
- (wann)
-
2012
- 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
- Nyberg, Henri
- Saikkonen, Pentti
- Bank of Finland
Entstanden
- 2012
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