Title :
Forecasting aggregate ARMA(1,1) demands: Theoretical analysis of top-down versus bottom-up
Author :
Rostami-Tabar, B. ; Babai, M. Zied ; Syntetos, A.A. ; Ducq, Y.
Author_Institution :
IMS, Univ. Bordeaux, Talence, France
Abstract :
In this paper the relative effectiveness of top-down (TD) versus bottom-up (BU) strategies is compared for forecasting the aggregate demand. We assume that the subaggregate demand follows an Autoregressive Moving Average process of order one and a Single Exponential Smoothing (SES) procedure is used to forecast demand. This demand process is often encountered in practice and SES is one of the standard estimators used in industry. Theoretical Mean Squared Error expressions are derived for the BU and TD strategies in order to contrast the relevant forecasting performances. The results indicate that there is no difference in the relative performance of TD and BU forecasting strategies when the process parameters are identical for all items and smoothing constant is equal for both strategies. The paper closes with an agenda for further research in this area.
Keywords :
autoregressive moving average processes; demand forecasting; mean square error methods; smoothing methods; BU forecasting strategy; SES procedure; TD forecasting strategy; aggregate ARMA(1,1) demand forecasting; autoregressive moving average process; bottom-up strategy; mean squared error method; process parameter; single exponential smoothing; standard estimator; subaggregate demand; top-down strategy; Aggregates; Correlation; Estimation; Forecasting; Smoothing methods; Time series analysis; Uncertainty; Cross-Sectional Aggregation; Demand Forecasting; Single Exponential Smoothing; Stationary Processes;
Conference_Titel :
Industrial Engineering and Systems Management (IESM), Proceedings of 2013 International Conference on
Conference_Location :
Rabat
