2023/09/11 by Sandra G. Schafhäutle, David Veenman · 14 citations
Business, Management and Accounting · Economics, Econometrics and Finance · #Accrual #Auditing, Earnings Management, Governance #Benchmark (surveying) #Business #Corporate Finance and Governance #Earnings #Economics #Equity (law) #Finance #Financial Markets and Investment Strategies #Financial economics #Revenue
paper · open access · doi:10.2308/tar-2021-0055
published in The Accounting Review 99(2), 421-456 (American Accounting Association)
openalex publication_date 2023/09/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
ABSTRACT This study examines whether crowdsourced forecasts of earnings and revenues help investors unravel bias in earnings announcement news, which is commonly derived from analyst forecasts. Our results suggest that investors, on average, understand and price the predictive signals reflected in crowdsourced forecasts about the bias in analyst-based earnings and revenue surprises. Using the staggered addition of firms to the Estimize platform, we find that crowdsourced coverage is associated with reductions in the mispricing of forecast bias and declines in earnings announcement premia. We further find some evidence that managers use income-increasing accruals to meet the crowdsourced forecast benchmark and that they respond to crowdsourced coverage through increased downward earnings and revenue guidance. Overall, we conclude that user-generated content on crowdsourced financial information platforms helps investors discount biases in traditional equity research and thereby better process the news in earnings announcements. JEL Classifications: G14; G20; M41.