Combining Economic Forecasts
测试了多种组合预测方法，包括考虑预测误差相关性和精度的模型，以及简单平均和贝叶斯方法，发现简单平均、独立正态模型和贝叶斯模型在组合四个主要计量经济模型的GNP预测时表现更好。
A method for combining forecasts may or may not account for dependence and differing precision among forecasts. In this article we test a variety of such methods in the context of combining forecasts of GNP from four major econometric models. The methods include one in which forecasting errors are jointly normally distributed and several variants of this model as well as some simpler procedures and a Bayesian approach with a prior distribution based on exchangeability of forecasters. The results indicate that a simple average, the normal model with an independence assumption, and the Bayesian model perform better than the other approaches that are studied here.