This paper examines the feasibility of rule-based forecasting, a procedure that applies forecasting expertise and domain knowledge to produce forecasts according to features of the data. We developed a rule base to make annual extrapolation forecasts for economic and demographic time series. The...

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,...

Opinion polling procedures allow for reasonable inferences about attitude changes. We examined this contention using surveys about the nomination of Clarence Thomas. In this situation, prior theory allowed us to predict the direction of changes, surveys had been conducted by a number of...

Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining the rules use statistical and domain-based features of time series. RBF was originally developed, tested, and validated only on annual data. For the M3-Competition, three major...

Rule-based forecasting (RBF) is an expert system that uses features of time series to select and weight extrapolation techniques. Thus, it is dependent upon the identification of features of the time series. Judgmental coding of these features is expensive and the reliability of the ratings is...

Causal forces are a way of summarizing forecasters' expectations about what will happen to a time series in the future. Contrary to the common assumption for extrapolation, time series are not always subject to consistent forces that point in the same direction. Some are affected by conflicting...

Sports and war metaphors abound in business today. For example, one management book, 'Thunder in the Sky', by Thomas Cleary, opens with a Chinese saying that translates: The marketplace is a battlefield. The Asian people view success in the business world as tantamount to victory in battle. The...

We report on the opinions of 49 forecasting experts on guidelines for extrapolation methods. They agreed that seasonality, trend, aggregation, and discontinuities were key features to use for selecting extrapolation methods. The strong agreement about the importance of discontinuities was...

This study evaluated measures for making comparisons of errors across time series. We analyzed 90 annual and 101 quarterly economic time series. We judged error measures on reliability, construct validity, sensitivity to small changes, protection against outliers, and their relationship to...

When causal forces are specified, the expected direction of the trend can be compared with the trend based on extrapolation. Series in which the expected trend conflicts with the extrapolated trend are called contrary series. We hypothesized that contrary series would have asymmetric forecast...