Author(s):	David F Hendry, Kirstin Hubrich
Publication Date:	January 2006
Keyword(s):	disaggregate information, factor models, forecast model selection, predictability, VAR
JEL(s):	C51, C53, E31
Programme Areas:	International Macroeconomics
Link to this Page:	cepr.org/active/publications/discussion_papers/dp.php?dpno=5485

We explore whether forecasting an aggregate variable using information on its disaggregate components can improve the prediction mean squared error over first forecasting the disaggregates and then aggregating those forecasts, or, alternatively, over 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.