Forecasting When Pattern Changes Occur Beyond the Historical Data

Robert Carbone and Spyros Makridakis
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Robert Carbone: Faculty of Management, McGill University, Montreal, Quebec, Canada
Spyros Makridakis: INSEAD, Fontainebleau, France

Management Science, 1986, vol. 32, issue 3, 257-271

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.

Keywords: forecasting/time; series (search for similar items in EconPapers)
Date: 1986
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:32:y:1986:i:3:p:257-271

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