Using analysts' forecasts to measure properties of analysts' information environment.
提出一个模型，将分析师预测的离散度和误差与分析师的不确定性和共识联系起来，并展示如何用这些可观测变量衡量分析师公共和私人信息的质量。
Abstract This paper presents a model that relates properties of the analysts' information environment of the properties of their forecasts. First, we express forecast dispersion and error in the mean forecast in terms of analyst uncertainty and consensus (that is, the degree to which analysts share a common belief). Second, were reserve the relations to show how uncertainability and consensus cab be measured by combining forecast dispersion, error in the mean forecast, and the number of forecasts. Third, we show that the quality of common and private information available to analysts can be measured using these same observable variables. The relations we present are intuitive and easily applied in empirical studies.