We investigate to what extent the market uses information that is predictive of whether earnings will meet or beat the analyst consensus forecast of earnings ( MBE henceforth): measures of a firm's incentives to engage in MBE behavior, measures of constraints on MBE , measures of past MBE practices by firm and industry, and other variables. Using the Mishkin test framework and Bonferroni‐adjusted p ‐values, we document that of a total of 21 variables, the market inefficiently uses information in one difficulty measure and four other predictors, suggesting that strong empirically and theoretically grounded relationships concerning MBE behavior are more likely to be unraveled by the market. We further show that a portfolio based on the difference between the objective MBE probability and the market‐assessed MBE probability generates significant abnormal returns. The documented return anomaly is distinct from other known anomalies and cannot be fully explained by arbitrage risk or transaction costs.

We propose financial statement similarity as a measure of financial reporting comparability. The firm‐pair version of our measure reflects the degree to which two firms report similar relations within their financial statement items; this version can help managers and market participants identify peer firms. The firm‐year version of our measure reflects the degree to which a firm reports financial statement relations that are similar to other members of its industry; this version can help market participants, regulators, and auditors screen firms for further attention. Our measure uses the presence and amounts of almost all financial items reported by a firm. We validate our measure in four sets of analyses to establish concurrent validity and in three sets of analyses to establish predictive validity. In all these tests, we contrast our measure with the comparability measure in De Franco et al. (2011) and a multivariate measure that considers the presence, but not amounts, of financial statement items. Our measure outperforms the alternatives and can be a useful tool for users.

Asymmetric information is a fundamental friction that results in mismatches and efficiency losses in the labor market. In this study, we posit that more disaggregated financial disclosure by a CEO candidate's prior employer can help the hiring firm better assess the possible fit between its operational needs and the candidate's skill set. Using a mandatory segment reporting reform in the United States (SFAS 131) as an exogenous shock to disclosure disaggregation, we find a significant increase in the firm‐CEO match quality when the hiring firm has access to more disaggregated segment information about the external candidate's past employment. Furthermore, the improvement in firm‐CEO matching is greater when segment information is incrementally more useful for evaluation of candidate skills. These findings reveal a novel labor market benefit of disaggregated financial disclosure: alleviating pre‐hiring information deficiencies and facilitating efficient allocation of CEO talent across firms.

We consider an investor's choice of conservative reporting, bonus payments, and investment decisions in the presence of the hidden‐information agency problem of a manager's productivity and the hidden‐action agency problem of a manager's diversion of resources. It is important to consider the hidden‐action and hidden‐information agency problems in isolation and their interaction to gain insights into the drivers of demand for conservatism. We show that the conservative (nonconservative) regime is optimal for the high‐productivity (low‐productivity) manager when both agency problems exist, even though the nonconservative regime is optimal for both the high‐ and low‐productivity managers when only the hidden‐action or the hidden‐information problem exists. Essentially, the low‐productivity manager can misrepresent as the high‐productivity manager to obtain high investment levels and divert resources only in the presence of both agency problems. This added layer of agency problem creates the demand for conservatism and highlights the importance of the interaction between the hidden‐action and hidden‐information agency problems. Furthermore, we show that as the conservatism level increases (i) the optimal investment level conditional on a good report for the high‐productivity manager increases and approaches the first‐best level (i.e., ex‐post investment efficiency increases); (ii) the expected optimal investment level for the high‐productivity manager decreases and diverges from the expected first‐best level (i.e., ex‐ante investment efficiency decreases); and (iii) the expected bonus payment to the high‐ and low‐productivity managers decreases. These findings provide insights into how the demand for conservatism arises in the presence of both hidden‐information and hidden‐action agency problems and provide empirical guidance relating conservatism to investment efficiency.

We synthesize evidence from six papers presented at the 2025 Journal of Accounting Research Conference on how generative artificial intelligence (GenAI) is reshaping capital‐market information flows. Our discussion is organized around an economic framework with three layers: information production by firms and accounting professionals, information dissemination through intermediaries, and information processing by investors. Across these layers, the conference papers show that GenAI can lower preparation costs, improve intermediary productivity, and reduce investors’ processing costs. At the same time, they point to a common constraint: whether GenAI improves the information environment depends critically on information verification costs. We also highlight gaps in current evidence and outline future research opportunities within and across the three layers.

We introduce a firm-specific measure of the technological aspect of competition—technological peer pressure—and examine firm-initiated product development-related press releases. We argue that empirical examinations of the theorized negative relation between competition and disclosure require the type of voluntary disclosure to be relevant to the dimension of competition under examination to ensure that firms incur significant proprietary costs of disclosure. In other words, many types of disclosure do not provide actionable information to competitors and, thus, should not be affected by that dimension of competition. We expect a negative relation between technological peer pressure and product disclosure because the latter reveals firms' strategies, allocations, and progress of technological investments in product development to competitors. In contrast, we do not expect a negative relation between technological peer pressure and management earnings forecasts—the most common type of voluntary disclosure used in accounting research. Our test results are consistent with these expectations. Data Availability: All data are available from public sources. Our TPP Measure is available for download, please see the link in Appendix G.