Two studies were conducted to examine expert opinions of criteria used to select forecasting techniques. In Study One, while "accuracy" was a dominant criterion, the ratings of five of thirteen criteria varied by the role of the forecaster. Researchers rated accuracy relatively higher than did...

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...

Members of professional groups were much more likely to respond to a mail survey than nonmembers who were also experts in the area (43.7% versus 13.7%). A one-dollar (U.S.)prepaid monetary incentive increased the response rates, and it was as effective for members as for nonmembers (gains of...

We used 59 biographical variables to create a “bio-index” for forecasting U.S. presidential elections. The bio-index method counts the number of variables for which a candidate rates favourably, and the forecast is that the candidate with the highest score would win the popular vote. The...

Policymakers need to know whether prediction is possible and if so whether any proposed forecasting method will provide forecasts that are substantively more accurate than those from the relevant benchmark method. Inspection of global temperature data suggests that it is subject to irregular...

I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods....

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,...

We assessed three important criteria of forecastability—simplicity, certainty, and variability. Climate is complex due to many causal variables and their variable interactions. There is uncertainty about causes, effects, and data. Using evidence-based (scientific) forecasting principles, we...

Those making environmental decisions must not only characterize the present, they must also forecast the future. They must do so for at least two reasons. First, if a no-action alternative is pursued, they must consider whether current trends will be favorable or unfavorable in the future....

We consider how judgment and statistical methods should be integrated for time-series forecasting. Our review of published empirical research identified 47 studies, all but four published since 1985. Five procedures were identified: revising judgment; combining forecasts; revising...