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- Title
FORECASTING WHEN PATTERN CHANGES OCCUR BEYOND THE HISTORICAL DATA.
- Authors
Carbone, Robert; Makridakis, Spyros
- 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.
- Subjects
TIME series analysis; MATHEMATICAL statistics; PROBABILITY theory; BUSINESS forecasting; ECONOMIC forecasting; BUSINESS cycles; MANAGEMENT science; COMMERCIAL statistics; ECONOMIC statistics
- Publication
Management Science, 1986, Vol 32, Issue 3, p257
- ISSN
0025-1909
- Publication type
Article
- DOI
10.1287/mnsc.32.3.257