CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS

Wagner Gaglianone and Luiz Lima ()

Journal of Applied Econometrics, 2014, vol. 29, issue 5, 736-757

Abstract: SUMMARY Decision makers often observe point forecasts of the same variable computed, for instance, by commercial banks, IMF and the World Bank, but the econometric models used by such institutions are frequently unknown. This paper shows how to use the information available on point forecasts to compute optimal density forecasts. Our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions. We use real‐time data to forecast the density of US inflation. The results indicate that the proposed method materially improves the real‐time accuracy of density forecasts vis‐à‐vis those from the (unknown) individual econometric models. Copyright © 2013 John Wiley & Sons, Ltd.

Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://hdl.handle.net/

Related works:
Working Paper: Constructing Optimal Density Forecasts from Point Forecast Combinations (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:japmet:v:29:y:2014:i:5:p:736-757

Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252

Access Statistics for this article

Journal of Applied Econometrics is currently edited by M. Hashem Pesaran

More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().