Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/212236 
Year of Publication: 
2012
Series/Report no.: 
Bank of Finland Research Discussion Papers No. 33/2012
Publisher: 
Bank of Finland, Helsinki
Abstract: 
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.
Subjects: 
Noncausal vector autoregression
forecasting
simulation
importance sampling
inflation
JEL: 
C32
C53
Persistent Identifier of the first edition: 
ISBN: 
978-952-462-828-0
Document Type: 
Working Paper

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