Forecasting the Icelandic business cycle using vector autoregressive models
AbstractThis paper considers the modelling and forecasting of the Icelandic business cycle. The method of selecting monthly variables, coincident and leading, that mimic the cyclical behavior of the quarterly GDP is described. The general business cycle is then modelled by a vector autoregressive, VAR, model. The cyclical behavior of the business cycle is summarized by a composite coincident index, which is based on the root mean squared forecast error over a pseudo out of sample. By applying a bootstrap forecasting procedure, using the estimated VAR model, point and interval forecasts of the composite coincident index are estimated.
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Bibliographic InfoPaper provided by Department of Economics, Central bank of Iceland in its series Economics with number wp36.
Date of creation: Sep 2007
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-02-09 (All new papers)
- NEP-ETS-2008-02-09 (Econometric Time Series)
- NEP-FOR-2008-02-09 (Forecasting)
- NEP-MAC-2008-02-09 (Macroeconomics)
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