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Management Science Vol. 32 No. 3 1986

Forecasting When Pattern Changes Occur Beyond the Historical Data

Robert Carbone1; Spyros Makridakis2

1 Faculty of Management, McGill University, Montreal, Quebec, Canada · 2 INSEAD Fontainebleau France

Abstract

Forecasting methods currently available assume that established patterns or relationships will not change during the post-sample forecasting phase. This, however, is not a realistic assumption for business and economic series. This paper describes a new approach to forecasting which takes into account possible pattern changes beyond the historical data. This approach is based on the development of two models: one short, the other long term. These models are then reconciled to produce the final forecasts by setting certain parameters as a function of the number, extent, and duration of pattern changes that have occurred in the past. The proposed method has been applied to the 111 series used in the M-Competition. Post-sample forecasting accuracy comparisons show the superiority of the proposed approach over the most accurate methods in the M-Competition.

DOI
10.1287/mnsc.32.3.257
Volume
32
Issue
3
Pages
257-271
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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