This paper studies an analyst's forecasting strategy and a manager's earnings management policy. When reporting earnings, the manager trades off the disutility he obtains from falling short of the analyst's forecast against the costs of manipulating earnings. The model predicts that: (i) the analyst's forecast exceeds median reported earnings; (ii) the analyst is more likely to revise his forecast downward than upward; (iii) mean and median forecast errors are larger in magnitude when the analyst has less precise information; and (iv) the stock market is, on average, more sensitive to reported earnings than to the analyst's forecasts.

We discuss Feng et al. (2024), which studies a dynamic model of delegated investment. The paper provides novel insights into the optimal contract between a principal and an agent who obtains private information about both the timing and profitability of investment opportunities. While the analytical analysis provides interesting findings, we have concerns about the validity of the paper’s empirical predictions. We extend the “conceptual” and “operational” levels of Libby boxes by adding an “analytical” level to offer a tool for assessing and developing the link between theoretical models and empirical tests.

I analyze a manager's optimal earnings forecasting strategy and optimal earnings management policy in a setting where both the mean and the variance of the distribution generating the firm's cash flows are unknown. The analysis shows that the equilibrium price of the firm is a function of the manager's forecast, the firm's reported earnings, and the squared error in the manager's earnings forecast. The model contains several predictions, including: (1) the manager manipulates earnings to reduce his forecast error at the earnings announcement date; (2) the firm's stock price is more sensitive to the firm's actual earnings announcement than to the manager's forecast; and (3) controlling for the level of reported earnings and the magnitude of the earnings surprise, the firm's price is higher when it has a positive surprise at the earnings announcement date than when it has a negative surprise.

We study a model in which managers’ disclosure and investment decisions are both endogenous and managers can manipulate their voluntary reports through (suboptimal) investment, financing, or operating decisions. Managers are privately informed about the value of their firm and have incentives to voluntarily disclose information and manipulate their reports in order to obtain more favorable terms when issuing equity to finance a new profitable investment opportunity. The model shows that treating managers’ disclosure and investment decisions both as endogenous and allowing managers to manipulate their voluntary reports yields qualitatively different predictions from when the disclosure and investment decisions are considered separately and managers cannot engage in manipulation. The model predicts that managers’ disclosure strategy is sometimes characterized by two distinct nondisclosure intervals (contrary to traditional threshold equilibria of voluntary disclosure models) and that managers with intermediate news sometimes forego the new profitable investment opportunity. As such, the paper highlights the importance of considering the interdependencies between firms’ disclosure and investment decisions and provides new empirical predictions.

This study models the interaction between a sell-side analyst and risk-averse investors. It derives an analyst’s optimal earnings forecast and investors’ optimal trading decisions in a setting where the analyst’s payoff depends on the trading volume the forecast generates as well as on the forecast error. In the fully separating equilibrium, we find that the analyst biases the forecast upward (downward) if his private signal reveals relatively good (bad) news. The model predicts that: (1) the analyst biases the forecast upward more often than downward and the forecast is on average optimistic; (2) the magnitude of the analyst’s bias is increasing in the per-share benefit from trading volume he receives; and (3) the analyst’s expected squared forecast error may increase in the precision of his private information. Finally, we characterize the circumstances under which the (rational) analyst acts as if he overweights or underweights his private information.

When valuing a firm, investors must assess not only its expected future cash flows but also the systematic risk inherent in these cash flows. In this paper, we model the process by which investors may learn about firms' betas from earnings and how this learning process affects the relationship between earnings, announcement returns, and expected future returns. The model's main predictions are: (i) earnings response coefficients vary with macroeconomic conditions and are lower in upswings than downturns; (ii) earnings positively and negatively predict future returns in economic upswings and downturns, respectively, leading to return autocorrelation; and (iii) real earnings management rises in economic downturns and contributes to systematic risk in the economy. These predictions are directly attributable to investors' uncertainty regarding firms' exposures to systematic risk.

This paper demonstrates the existence of two different kinds of externalities induced by an auditor servicing multiple clients at the same time. First, we show that the capital market price for a client can increase in the number of qualified reports that his auditor issues to his other clients, thus producing a stock price externality. Second, when the audit firm has limited wealth, an additional client can actually decrease the audit quality and increase the average likelihood of audit failure relative to a single-client setting because of reporting externalities. Our analysis also demonstrates how requiring a more effective audit oversight mechanism can actually produce unintended consequences such as an increased likelihood of audit failures.

We study optimal compensation contracts that (1) are designed to address a joint moral hazard and adverse selection problem and that (2) are based on performance measures, which may be manipulated by the agent at a cost. In the model, a manager is privately informed about his productivity prior to being hired by a firm. In order to incentivize the manager to exert productive effort, the firm designs a compensation contract that is based on reported earnings, which can be manipulated by the manager. Our model predicts that (1) the optimal compensation contract is convex in reported earnings; (2) the optimal contract is less sensitive to reported earnings than it would be absent the manager's ability to manipulate earnings; and (3) higher costs of manipulating reported earnings (e.g., due to higher governance quality) are associated with higher firm value, lower expected level of earnings management, and higher output.

This paper studies equilibrium voluntary disclosures for a company financed with both debt and equity, where the firm's manager is compensated based on a linear combination of the market prices of the firm's equity and enterprise values (i.e., the sum of its values of equity and debt). Such compensation policies span “all equity” contracts, “all debt” contracts, and “all enterprise value” contracts. We show: (1) under both “all equity” and “all debt” contracts, increased debt always leads to reduced voluntary disclosure; (2) under “all enterprise value” contracts, increased debt has no effect on voluntary disclosure; (3) for all contracts that place positive weight on both equity and enterprise values, more debt leads to less (respectively, more) disclosure if the initial debt level is low (respectively, high); (4) increasing the weight on equity prices always induces less disclosure, so: (5) “all equity” contracts minimize disclosures, and “all debt” contracts maximize disclosures.