IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

A Bayesian Method of Forecast Averaging for Models Known Only by Their Historic Outputs: An Application to the BCRA´s REM

Listed author(s):
  • Pedro Elosegui

    (Central Bank of Argentina)

  • Francisco Lepone

    (Central Bank of Argentina)

  • George McCandless


    (Central Bank of Argentina)

Similar to other Central Banks, the BCRA publishes monthly a REM that summaries the forecasts and projections of a group of economic analysts and consultants who volunteer to participate in the program. The BCRA publishes only 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 do that well. The aggregate forecasts that come from our Bayesian averaging provides statistically better forecasts than the mean, median, best model, five best models 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 are of benefit to all members of the economy.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
File Function: English version
Download Restriction: no

File URL:
File Function: versión en Español
Download Restriction: no

Paper provided by Central Bank of Argentina, Economic Research Department in its series BCRA Working Paper Series with number 200607.

in new window

Length: 20 pages
Date of creation: Aug 2006
Handle: RePEc:bcr:wpaper:200607
Contact details of provider: Postal:
Reconquista 266 - C1003ABF - Buenos Aires

Phone: (54-11) 4348-3582
Fax: (54-11) 4348-3794
Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:bcr:wpaper:200607. 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.