Causal Forces: Structuring Knowledge for Time-Series Extrapolation

@inproceedings{Armstrong1993CausalFS,
  title={Causal Forces: Structuring Knowledge for Time-Series Extrapolation},
  author={J. Scott Armstrong and Fred L. Collopy},
  year={1993}
}
This paper examines a strategy for structuring one type of domain knowledge for use in extrapolation. It does so by representing information about causality and using this domain knowledge to select and combine forecasts. We use five categories to express causal impacts upon trends: growth, decay, supporting, opposing, and regressing. An identification of causal forces aided in the determination of weights for combining extrapolation forecasts. These weights improved average ex ante forecast… 

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