Forecasting Italian inflation with large datasets and many models
The aim of this paper is to propose a new method for forecasting Italian inflation. We expand on a standard factor model framework (see Stock and Watson (1998)) along several dimensions. To start with we pay special attention to the modeling of the autoregressive component of the inflation. Second, we apply forecast combination (Granger (2000) and Pesaran and Timmermann (2001)) and generate our forecast by averaging the predictions of a large number of models. Third, we allow for time variation in parameters by applying rolling regression techniques, with a window of three-years of monthly data. Backtesting shows that our strategy outrperforms both the benchmark model (i.e. a factor model which does not allow for model uncertainty) and additional univariate (ARMA) and multivariate (VAR) models. Our strategy proves to improve on alternative models also when applied to turning point prediction.
|Date of creation:||2004|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.igier.unibocconi.it/
|Order Information:|| Web: http://www.igier.unibocconi.it/en/papers/index.htm Email: |
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, May.
When requesting a correction, please mention this item's handle: RePEc:igi:igierp:269. 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: ()
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.