Regular Article

Statistical Papers

, Volume 53, Issue 2, pp 255-263

First online:

Comparing aggregate and disaggregate forecasts of first order moving average models

  • Giacomo SbranaAffiliated withUniversité de Strasbourg, Bureau d’Économie Théorique et Appliquée (BETA) Email author 
  • , Andrea SilvestriniAffiliated withBank of Italy, Economics, Research and International Relations AreaUniversité catholique de Louvain, CORE

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


This paper compares the performance of “aggregate” and “disaggregate” predictors in forecasting contemporaneously aggregated vector MA(1) processes. The necessary and sufficient condition for the equality of mean squared errors associated with the two competing predictors is provided in the bivariate MA(1) case. Furthermore, it is argued that the condition of equality of predictors as stated by Lütkepohl (Forecasting aggregated vector ARMA processes, Springer, Berlin, 1987) is only sufficient (not necessary) for the equality of mean squared errors. Finally, it is shown that the equality of forecasting accuracy for the two predictors can be achieved using specific assumptions on the parameters of the vector MA(1) structure.


Contemporaneous aggregation Forecasting Vector moving average models