A Bayesian Method of Forecast Averaging: An Application to the Expectations Survey of BCRA
The BCRA publishes monthly an expectations survey (REM) that summaries the forecasts and projections of a group of economic analysts and consultants. The BCRA publishes only the mean, the median, and the standard deviation of the sample received. The logic for using these statistics is that all participants are to be treated equally. Under the assumption that some forecasters have better underlying models than others, one might be able to improve the accuracy of the aggregate forecast by giving greater priority to those who have historically predicted better. The BCRA does not have access to the models used to make the predictions, only the forecasts are provided. An averaging method that puts higher weights on the predictions of those forecasters who have done best in the past should be able to produce a better aggregate forecast. The problem is how to determine these weights. In this paper, we develop a Bayesian averaging method that can estimate those weights. The aggregate forecasts that come from our Bayesian averaging provides statistically better forecasts than the mean, the median, and other methods traditionally used. In particular, the method developed in this paper is much better at detecting changes in the trends of the variables. The aggregate predictions published from the REM provide information that is useful, not only for monetary and economic policy decisions, but also for the consumption and business decisions of private economic agents. Improving these forecasts is of benefit to all members of the economy.
Volume (Year): 1 (2006)
Issue (Month): 45 (October)
|Contact details of provider:|| Postal: |
Phone: (54-11) 4348-3582
Fax: (54-11) 4000-1257
Web page: http://www.bcra.gov.ar
More information through EDIRC
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.:
- Sune Karlsson & Tor Jacobson, 2004.
"Finding good predictors for inflation: a Bayesian model averaging approach,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 23(7), pages 479-496.
- Jacobson, Tor & Karlsson, Sune, 2002. "Finding Good Predictors for Inflation: A Bayesian Model Averaging Approach," Working Paper Series 138, Sveriges Riksbank (Central Bank of Sweden).
When requesting a correction, please mention this item's handle: RePEc:bcr:ensayo:v:1:y:2006:i:45:p:95-119. 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: (Federico Grillo)
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.