Forecasting an aggregate of cointegrated disaggregates

This study examines the problem of forecasting an aggregate of cointegrated disaggregates. It first establishes conditions under which forecasts of an aggregate variable obtained from a disaggregate VECM will be equal to thos e from an aggregate, univariate time Series model, and develops a simple pr ocedure for resting those conditions. The paper then uses Monte Carlo simul ations to show, for a finite sample, that the proposed test has good size a nd power properties and that whether a model satisfies the aggregation cond itions is closely related to out-of-sample forecast performance. The paper then shows that ignoring cointegration and specifying the disaggregate mode l as a VAR in differences can significantly affect analyses of aggregation, with the VAR-based test for aggregation possibly leading to faulty inferen ce and the differenced VAR forecasts potentially understating the benefits of disaggregate information. Finally, analysis of an empirical problem conf irms the basic results. Copyright (C) 2000 John Wiley & Sons, Ltd.