Using analysts' forecasts to measure properties of analysts' information environment

Orie Edwin Barron, Oliver Kim, Steve C. Lim, Douglas E. Stevens

Research output: Contribution to journalArticlepeer-review

366 Scopus citations


This paper presents a model that relates properties of the analysts' information environment to 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, we reverse the relations to show how uncertainty and consensus can 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.

Original languageEnglish (US)
Pages (from-to)421-433
Number of pages13
JournalAccounting Review
Issue number4
StatePublished - Oct 1 1998

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics


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