The Library

Combining forecasts : forty years later

Tools

Wallis, Kenneth Frank. (2011) Combining forecasts : forty years later. Applied Financial Economics, Vol.21 (No.1-2). pp. 33-41. ISSN 0960-3107

Preview

PDF
WRAP_Wallis_0170226-ec-020811-combining40_final.pdf - Accepted Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (213Kb)

Official URL: http://dx.doi.org/10.1080/09603107.2011.523179

Abstract

This article is dedicated to the memory of Clive Granger, a founding editor of this journal. Its title echoes the title of his invited review article in a special issue of the Journal of Forecasting in 1989. That issue marked the twentieth anniversary of the publication of his article with John Bates, which is widely regarded as the seminal article in the field of forecast combination. This article returns to two of the topics in ‘Combining forecasts – twenty years later’ that are of much current interest, namely the impact of forecasters’ different information sets on the original point forecast combination result, and properties of different methods of combining density forecasts. A parallel result to his inefficiency-of-mean-forecasts result for point forecasts is seen to apply to density forecasts, where logarithmic combination is shown to have some advantage over linear combination.

Item Type:

Journal Article

Subjects:

H Social Sciences > HB Economic Theory

Divisions:

Faculty of Social Sciences > Economics

Library of Congress Subject Headings (LCSH):

Economic forecasting

Journal or Publication Title:

Applied Financial Economics

Publisher:

Routledge

ISSN:

0960-3107

Official Date:

2011

Dates:

Date	Event
2011	Published

Volume:

Vol.21

Number:

No.1-2

Page Range:

pp. 33-41

Identification Number:

10.1080/09603107.2011.523179

Status:

Peer Reviewed

Access rights to Published version:

Open Access

References:

Barnard, G.A. (1963). New methods of quality control. Journal of the Royal Statistical
Society A, 126, 255-258.
Bates, J.M. and Granger, C.W.J. (1969). The combination of forecasts. Operational
Research Quarterly, 20, 451-468.
Berkowitz, J. (2001). Testing density forecasts, with applications to risk management.
Journal of Business and Economic Statistics, 19, 465-474.
Bjornland, H., Gerdrup, K., Jore, A.S., Smith, C. and Thorsrud, L.A. (2009). There is more
than one weight to skin a cat: combining densities at Norges Bank. Conference on
Forecasting and Monetary Policy, Deutsche Bundesbank, Berlin, March 2009.
Boero, G., Smith, J. and Wallis, K.F. (2008). Uncertainty and disagreement in economic
prediction: the Bank of England Survey of External Forecasters. Economic Journal,
118, 1107-1127.
Box, G.E.P and Jenkins, G.M. (1970). Time Series Analysis: Forecasting and Control. San
Francisco: Holden-Day
Clemen, R.T. (1989). Combining forecasts: a review and annotated bibliography.
International Journal of Forecasting, 5, 559-583.
Crowe, C. (2010). Consensus forecasts and inefficient information aggregation. Working
Paper No.10/178, International Monetary Fund, Washington DC.
Faria, A.E.and Mubwandarikwa, E. (2008). The geometric combination of Bayesian
forecasting models. Journal of Forecasting, 27, 519-535.
Faria, A.E. and Smith, J.Q. (1997). Conditionally externally Bayesian pooling operators in
chain graphs. Annals of Statistics, 25, 1740-1761.
Genest, C. and Zidek, J.V. (1986). Combining probability distributions: a critique and an
annotated bibliography (with discussion). Statistical Science, 1, 114-148.
Geweke, J. and Amisano, G. (2009). Optimal prediction pools. Working Paper No.1017,
European Central Bank, Frankfurt.
Granger, C.W.J. (1969). Prediction with a generalized cost of error function. Operational
Research Quarterly, 20, 199-207.
Granger, C.W.J. (1989). Combining forecasts – twenty years later. Journal of Forecasting,
8, 167-173.
Hall, S.G. and Mitchell, J. (2007). Combining density forecasts. International Journal of
Forecasting, 23, 1-13.
Hora, S.C. (2004). Probability judgements for continuous quantities: linear combinations and
calibration. Management Science, 50, 597-604.
Jore, A.S., Mitchell, J. and Vahey, S.P. (2010). Combining forecast densities from VARs
with uncertain instabilities. Journal of Applied Econometrics, 25, 621-634.
Kascha, C. and Ravazzolo, F. (2010). Combining inflation density forecasts. Journal of
Forecasting, 29, 231-250.
Kim, O., Lim, S.C. and Shaw, K.W. (2001). The inefficiency of the mean analyst forecast as
a summary forecast of earnings. Journal of Accounting Research, 39, 329-336.
Mitchell, J. and Hall, S.G. (2005). Evaluating, comparing and combining density forecasts
using the KLIC with an application to the Bank of England and NIESR ‘fan’ charts of
inflation. Oxford Bulletin of Economics and Statisics, 67, 995-1033.
Mitchell, J. and Wallis, K.F. (2010). Evaluating density forecasts: forecast combinations,
model mixtures, calibration and sharpness. Journal of Applied Econometrics, in press.
Morris, S. and Shin, H.S. (2002). Social value of public information. American Economic
Review, 92, 1521-1534.
Pearson, K. (1894). Contributions to the mathematical theory of evolution. Philosophical
Transactions of the Royal Society of London, A, 185, 71-110.
Ranjan, R. and Gneiting, T. (2010). Combining probability forecasts. Journal of the Royal
Statistical Society B, 72, 71-91.
Rich, R. and Tracy, J. (2010). The relationships among expected inflation, disagreement, and
uncertainty: evidence from matched point and density forecasts. Review of Economics
and Statistics, 92, 200-207.
Smith, J. and Wallis, K.F. (2009). A simple explanation of the forecast combination puzzle.
Oxford Bulletin of Economics and Statistics, 71, 331-355.
Wallis, K.F. (2005). Combining interval and density forecasts: a modest proposal. Oxford
Bulletin of Economics and Statistics, 67, 983-994.
Winkler, R.L. (1968). The consensus of subjective probability distributions. Management
Science, 15, B61-B75.
Zarnowitz, V. (1969). The new ASA-NBER survey of forecasts by economic statisticians.
American Statistician, 23(1), 12-16.