The Accuracy of extrapolative forecasting methods: additional empirical evidence
Author: Fildes, R. ; Hibon, Michèle ; Makridakis, SpyrosINSEAD Area: Technology and Operations Management Series: Working Paper ; 95/04/TM Publisher: Fontainebleau : INSEAD, 1995.Language: EnglishDescription: 12 p.Type of document: INSEAD Working Paper Online Access: Click here Abstract: Replication is an important aspect of hard sciences in developing and objective knowledge base that the great majority of scientists can accept. In social sciences, however, replication has proved problematic. One of the exceptions has been the M-competition whose calculations and conclusions have been replicated by many researchers. In order to extend the range under which extrapolative methods have been compared we examine a unique set of 263 series. Unlike the M-competition data they come from a single source countaining series of similar characteristics (the same calendar, no seasonality, little randomness, and a downward sloping trend). We show that the conclusions of the M-competition are still valid while at the same time it is found that robust-trend, a new method not used in the M-competition, outperforms all other methods. In addition, the relative performance of exponential smoothing is shown to depend on the ways its parameters are optimized. The implications of these conclusions are discuss| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Digital Library | Available | BC001085 |
Replication is an important aspect of hard sciences in developing and objective knowledge base that the great majority of scientists can accept. In social sciences, however, replication has proved problematic. One of the exceptions has been the M-competition whose calculations and conclusions have been replicated by many researchers. In order to extend the range under which extrapolative methods have been compared we examine a unique set of 263 series. Unlike the M-competition data they come from a single source countaining series of similar characteristics (the same calendar, no seasonality, little randomness, and a downward sloping trend). We show that the conclusions of the M-competition are still valid while at the same time it is found that robust-trend, a new method not used in the M-competition, outperforms all other methods. In addition, the relative performance of exponential smoothing is shown to depend on the ways its parameters are optimized. The implications of these conclusions are discuss
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