Is It Better to Average Probabilities or Quantiles?
Is It Better to Average Probabilities or Quantiles?
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DOI：
10.1287/mnsc.1120.1667
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发表时间：
2013-07-01
影响因子：
5.4
通讯作者：
Winkler, Robert L.
中科院分区：
文献类型：
--
作者：
Lichtendahl, Kenneth C., Jr.;Grushka-Cockayne, Yael;Winkler, Robert L.
我们考虑两种方法来聚合专家意见使用简单的平均值：平均概率和平均分位数。我们研究这些预测的分析特性，并比较它们利用群众智慧的能力。就位置而言，两个平均预测的均值相同。平均分位数预测总是更精确：它的方差比平均概率预测低。即使平均概率预测过于自信，平均分位数预测的形状仍然提供了更好预测的可能性。使用概率预测的国内生产总值增长和通货膨胀的专业预测调查，我们提出的证据表明，无论是当平均概率预测是过度自信，当它是信心不足，它是优于平均分位数预测。我们的研究结果表明，平均分位数是一个可行的替代方案，并表明在某些条件下，它可能比平均概率更有用。
We consider two ways to aggregate expert opinions using simple averages: averaging probabilities and averaging quantiles. We examine analytical properties of these forecasts and compare their ability to harness the wisdom of the crowd. In terms of location, the two average forecasts have the same mean. The average quantile forecast is always sharper: it has lower variance than the average probability forecast. Even when the average probability forecast is overconfident, the shape of the average quantile forecast still offers the possibility of a better forecast. Using probability forecasts for gross domestic product growth and inflation from the Survey of Professional Forecasters, we present evidence that both when the average probability forecast is overconfident and when it is underconfident, it is outperformed by the average quantile forecast. Our results show that averaging quantiles is a viable alternative and indicate some conditions under which it is likely to be more useful than averaging probabilities.