Forecasting key macroeconomic variables from a large number of predictors: A state space approach
We use state space methods to estimate a large dynamic factor model for the Norwegian economy involving 93 variables for 1978Q2–2005Q4. The model is used to obtain forecasts for 22 key variables that can be derived from the original variables by aggregation. To investigate the potential gain in using such a large information set, we compare the forecasting properties of the dynamic factor model with those of univariate benchmark models. We find that there is an overall gain in using the dynamic factor model, but that the gain is notable only for a few of the key variables.
|Date of creation:||May 2007|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (+47) 21 09 00 00
Fax: (+47) 21 09 49 73
Web page: http://www.ssb.no/en/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ssb:dispap:504. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (J Bruusgaard)
If references are entirely missing, you can add them using this form.