Earnings surprises that motivate analysts to reduce average forecast error

• 成果类型: Article
• 署名作者: Barron, Orie E.; Byard, Donal; Yu, Yong
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; City University of New York (CUNY) System; Baruch College (CUNY); University of Texas System; University of Texas Austin
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/accr.2008.83.2.303
• 发表日期: 2008
• 页码: 303-325
• 关键词: biased earnings; INFORMATION; management; volume; price; performance; incentives; disclosure; revisions; matter

摘要

Large earnings surprises and negative earnings surprises represent more egregious errors in analysts' earnings forecasts. We find evidence consistent with our expectation that egregious forecast errors motivate analysts to work harder to develop or acquire relatively more private information in an effort to avoid future forecasting failures. Specifically, we find that after large or negative earnings surprises there is a greater reduction in the error in individual analysts' forecasts of future earnings, and these individual forecasts are based more heavily on individual analysts' private information. This increased reliance on private information reduces the error in the mean forecast of upcoming earnings (even after controlling for the effect of reduced error in individual forecasts). As reliance on private information increases, more of each individual forecast error is idiosyncratic, and thus averaged out in the computation of the mean forecast.