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FORECAST CONTENT AND CONTENT HORIZONS FOR SOME IMPORTANT MACROECONOMIC TIME SERIES

John Galbraith and Greg Tkacz ()

Departmental Working Papers from McGill University, Department of Economics

Abstract: For quantities that are approximately stationary, the information content of statistical forecasts tends to decline as the forecast horizon increases, and there exists a maximum horizon beyond which forecasts cannot provide discernibly more information about the variable than is present in the unconditional mean (the content horizon). The pattern of decay of forecast content (or skill) with increasing horizon is well known for many types of meteorological forecasts; by contrast, little generally-accepted information about these patterns or content horizons is available for economic variables. In this paper we attempt to develop more information of this type by estimating content horizons for variety of macroeconomic quantities; more generally, we characterize the pattern of decay of forecast content as we project farther into the future. We find wide variety of results for the different macroeconomic quantities, with models for some quantities providing useful content several years into the future, for other quantities providing negligible content beyond one or two months or quarters.

JEL-codes: C53 E17 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2007
New Economics Papers: this item is included in nep-ets, nep-for and nep-mac
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Related works:
Journal Article: Forecast content and content horizons for some important macroeconomic time series (2007)
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