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Combination forecasts of output growth in a seven-country data set

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Author Info
Mark W. Watson (Woodrow Wilson School and Department of Economics, Princeton University and the National Bureau of Economic Research, USA)
James H. Stock (Department of Economics, Harvard University and the National Bureau of Economic Research, USA)

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Abstract

This paper uses forecast combination methods to forecast output growth in a seven-country quarterly economic data set covering 1959-1999, with up to 73 predictors per country. Although the forecasts based on individual predictors are unstable over time and across countries, and on average perform worse than an autoregressive benchmark, the combination forecasts often improve upon autoregressive forecasts. Despite the unstable performance of the constituent forecasts, the most successful combination forecasts, like the mean, are the least sensitive to the recent performance of the individual forecasts. While consistent with other evidence on the success of simple combination forecasts, this finding is difficult to explain using the theory of combination forecasting in a stationary environment. Copyright © 2004 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.928
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 23 (2004)
Issue (Month): 6 ()
Pages: 405-430
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:jof:jforec:v:23:y:2004:i:6:p:405-430

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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This page was last updated on 2009-11-1.

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