Statistical Papers

, Volume 53, Issue 2, pp 255–263

Comparing aggregate and disaggregate forecasts of first order moving average models

Regular Article

DOI: 10.1007/s00362-010-0333-6

Cite this article as:
Sbrana, G. & Silvestrini, A. Stat Papers (2012) 53: 255. doi:10.1007/s00362-010-0333-6
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Abstract

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.

Keywords

Contemporaneous aggregation Forecasting Vector moving average models 

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Université de Strasbourg, Bureau d’Économie Théorique et Appliquée (BETA)Strasbourg CedexFrance
  2. 2.Bank of Italy, Economics, Research and International Relations AreaRomeItaly
  3. 3.Université catholique de Louvain, CORELouvain-la-NeuveBelgium

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