Forecast Uncertainty, Disagreement, and the Linear Pool
分析了线性池方法在组合密度预测时，个体预测方差无偏的情况下，分歧成分会加剧方差预测的高估偏差，提出去除分歧成分的居中线性池，模拟和通胀数据实证显示其更优。
Summary The linear pool is the most popular method for combining density forecasts. We analyze its implications concerning forecast uncertainty, using a new framework that focuses on the means and variances of the individual and combined forecasts. Our results show that, if the variance predictions of the individual forecasts are unbiased, the well‐known “disagreement” component of the linear pool exacerbates the upward bias of its variance prediction. This finding suggests the removal of the disagreement component from the linear pool. The resulting centered linear pool outperforms the linear pool in simulations and an empirical application to inflation.