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Hierarchical estimation as basis for hierarchical forecasting

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Author Info
Strijbosch, L.W.G.
Heuts, R.M.J.
Moors, J.J.A. (Tilburg University, Center for Economic Research)

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Abstract

In inventory management, hierarchical forecasting (HF) is a hot issue : families of items are formed for which total demand is forecasted; total forecast then is broken up to produce forecasts for the individual items. Since HF is a complicated procedure, analytical results are hard to obtain; consequently, most literature is based on simulations and case studies. This paper succeeds in following a more theoretical approach by simplifying the problem : we consider estimation instead of forecasting. So, from a random sample we estimate both total demand and the fraction of this total that individual items take; multiplying these two quantities gives a new estimate of individual demand. Then our research question is: can aggregation of items, followed by fractioning, lead to more accurate estimates of individual demand? Thirdly, a more practical situation is investigated by means of simulation.

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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 86.

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Date of creation: 2006
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Handle: RePEc:dgr:kubcen:200686

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Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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