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Forecasting economic aggregates by disaggregates Author info | Abstract | Publisher info | Download info | Related research | Statistics David F. Hendry () (Department of Economics, Oxford University, Manor Road Building, Manor Road, Oxford, OX1 3UQ, United Kingdom )
Kirstin Hubrich () (European Central Bank, Kaiserstrasse 29, Postfach 16 03 19, 60066 Frankfurt am Main, Germany. )
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We suggest an alternative use of disaggregate information to forecast the aggregate variable of interest, that is to include disaggregate information or disaggregate variables in the aggregate model as opposed to first forecasting the disaggregate variables separately and then aggregating those forecasts or, alternatively, using only lagged aggregate information in forecasting the aggregate. We show theoretically that the first method of forecasting the aggregate should outperform the alternative methods in population. We investigate whether this theoretical prediction can explain our empirical findings and analyse why forecasting the aggregate using information on its disaggregate components improves forecast accuracy of the aggregate forecast of euro area and US inflation in some situations, but not in others. JEL Classification: C51; C53; E31.
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Paper provided by European Central Bank in its series Working Paper Series with number
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Length: 51 pages
Date of creation: Feb 2006Date of revision:
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Keywords: Disaggregate information ; predictability ; forecast model selection ; VAR ; factor models. ; Other versions of this item:
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