The Accuracy and Informativeness of Management Earnings Forecasts: A Review and Unifying Framework*

This paper synthesizes the literature on management earnings forecasts (MFs) and adaption mechanisms, combines existing theories into a unifying framework, and discusses the primary determinants of MF accuracy and informativeness. The proposed model refines existing theories by emphasizing the dynamics and multiperiod interactions among firm management, financial analysts, and investors, thereby simplifying the assessment of the complex relations within the forecast cycle. Furthermore, we analyze when and to what extent financial analysts and investors anticipate bias and misleading information. Overall, the literature review provides strong support for a positive correlation between the extent and credibility of MFs, on the one hand, and stock returns, share liquidity, and analyst coverage, on the other hand. Earnings forecasts tend to be optimistically biased, with a positive correlation with forecast uncertainty, earnings flexibility, financial distress, investor sentiment, and the share price dependency of managers' remuneration. Firm growth, legal liability, and litigation risk are significantly associated with forecast pessimism. We also find that MF accuracy increases with previous forecast accuracy, firm size, analyst coverage, analyst agreement, management qualifications, and corporate governance level. Moreover, investors do not anticipate the full extent of predictable forecast bias, leading to systematic share price drifts after the announcement of earnings forecasts and actual earnings. The study's results have substantial implications for researchers, firm managers, investors, financial analysts, and regulators. Although managers may enhance their forecasts' credibility by providing precise, bundled, and disaggregated forecasts, external stakeholders should carefully analyze forecast antecedents and characteristics to assess the direction and magnitude of expected MF bias.