The Impact of Earnings Management and Expectations Management on the Usefulness of Earnings and Analyst Forecasts in Firm Valuation

In this dissertation, I examine the impact of earnings management and expectations management on the usefulness of earnings and analyst forecasts in firm valuation. Earnings and analyst forecasts are important inputs into accounting valuation models. Their ability to reflect current and predict future firm performance can help valuation models predict intrinsic value. However, increasing earnings management and expectations management activities in recent years may have adversely affected the usefulness of these information items in firm valuation. This study shows that intrinsic value metrics estimated using manipulated earnings or forecasts have less ability to track stock prices and predict future returns through V/P ratios, providing evidence for the joint hypothesis of (i) long-term market efficiency and (ii) the negative impact of earnings management and expectations management on the usefulness of earnings and analyst forecasts in firm valuation. It contributes to the accounting literature in several ways. First, it challenges the conventional view that more accurate and less biased forecasts are necessarily of better quality and proposes to assess the quality of analyst forecasts directly by examining their usefulness. It also introduces an improved measure for expectations management and presents new evidence on (i) the usefulness of earnings and analyst forecasts in firm valuation; (ii) the negative impacts of earnings management and expectations management on this usefulness; and (iii) the overall performance of accounting valuation models in firm valuation