Disagreement as a Measure of Uncertainty
利用利文斯顿调查的通胀预测数据，证明预测者之间的分歧能有效衡量预测不确定性，其对预测误差的条件方差有显著正向影响，且效果优于ARCH模型。
This paper presents evidence from the Livingston survey of inflation forecasts that forecaster disagreement provides a useful measure of forecast uncertainty. The evidence is analogous to the evidence for ARCH effects. Disagreement at the time of the forecast has as large positive effect on the conditional variance of the subsequent forecast error. As a conditioning variable, forecaster disagreement dominates ARCH for both survey errors and the error terms in Robert Engle's quarterly model of inflation. As measured by the resulting conditional variances, disagreement indicates larger and more variable levels of uncertainty for the 1946-94 period. Copyright 1996 by Ohio State University Press.