Combining Non-Replicable Forecasts

Evaluating Combined Non-Replicable Forecasts*

Macroeconomic forecasts are often based on the interaction between econometric models and experts. A forecast that is based only on an econometric model is replicable and may be unbiased, whereas a forecast that is not based only on an econometric model, but also incorporates an expert's touch, is non-replicable and is typically biased. In this paper we propose a methodology to analyze the qual...

Combining forecasts

To improve forecasting accuracy, combine forecasts derived from methods that differ substantially and draw from different sources of information. When feasible, use five or more methods. Use formal procedures to combine forecasts: An equal-weights rule offers a reasonable starting point, and a trimmed mean is desirable if you combine forecasts resulting from five or more methods. Use different ...

Combining Forecasts using Clustering

Given sales forecasts for a set of items along with the standard deviation associated with each forecast, we propose a new method of combining forecasts using the concepts of clustering. Clusters of items are identified based on similarity in their sales forecasts and then a common forecast (or combined forecast) is computed for each cluster of items. The objective of clustering is to minimize ...

Combining Economic Forecasts

Combining Probability Forecasts

Linear pooling is by the far the most popular method for combining probability forecasts. However, any nontrivial weighted average of two or more distinct, calibrated probability forecasts is necessarily uncalibrated and lacks sharpness. In view of this, linear pooling requires recalibration, even in the ideal case in which the individual forecasts are calibrated. Toward this end, we propose a ...