This paper examines the role of conservatism when an agent can manipulate upcoming earnings before all uncertainty is resolved. An increase in conservatism, by reducing the likelihood of favorable earnings, requires steeper performance pay to maintain the same level of incentives, which in turn increases the equilibrium earnings manipulation. Trade‐offs between inducing effort and curbing manipulation predict an interior level of conservatism as optimal. The optimal level of conservatism is positively associated with enforcement, economic profitability and earnings quality, and negatively associated with agency frictions. In particular, we show that more economically profitable firms choose to be more conservative. We also establish that the association between performance pay and manipulation identifies whether conservatism is optimally chosen or exogenously imposed. In an application to debt contracting, we show that optimal conservatism is negatively associated with borrowers’ bargaining power.

We study optimal disclosure via two competing communication channels: hard information whose value has been verified, and soft disclosures such as forecasts, unaudited statements, and press releases. We show that certain soft disclosures may contain as much information as hard disclosures, and we establish that: (1) exclusive reliance on soft disclosures tends to convey bad news, (2) credibility is greater when unfavorable information is reported, and (3) misreporting is more likely when soft information is issued jointly with hard information. We also show that a soft report that is seemingly unbiased in expectation need not indicate truthful reporting. We demonstrate that mandatory disclosure of hard information reduces the transmission of soft information, and that the aggregation of hard with soft information will turn all information soft.

This article develops a theory of standard-setting in which accounting standards emerge endogenously from an institutional bargaining process. It provides a unified framework with investment and voluntary disclosure to examine the links between regulatory institutions and accounting choice. We show that disclosure rules tend to be more comprehensive when controlled by a self-regulated professional organization than when they are under the direct oversight of elected politicians. These institutions may not implement standards desirable to diversified investors and, when voluntary disclosures are possible, allowing choice between competing standards increases market value over a single uniform standard. Several new testable hypotheses are also offered to explain differences in accounting regulations.

Does managing the production of information add value in economic environments where a manager may claim to be uninformed and withhold unfavorable news? We examine this question by nesting an optimal persuasion mechanism, controlling how evidence is organized, within a voluntary disclosure framework. Information has productive consequences because the firm uses it to make a continuous operating decision. The optimal reporting strategy features coarse information at the most unfavorable reported event if and only if the firm bears penalties for nondisclosure or positive disclosure costs. The model demonstrates the optimality of imprecise information over bad news in a voluntary disclosure environment, and that such imprecision increases the quality of public signals after considering strategic disclosure effects.

This paper explores how the emergence of generative artificial intelligence is reshaping the information environment in capital markets. Leveraging an unexpected ban on ChatGPT in Italy, we examine its impact on the information processing capabilities of market participants. We employ metrics for AI-generated text detection to show that the ban coincides with decreased AI usage by domestic financial analysts and fewer earnings forecasts issued relative to foreign analysts covering the same firm. The negative effects are more pronounced among analysts whose pre-ban reports are more consistent with AI use or analysts with a technical background. The ban also diminishes forecast accuracy, increases reliance on industry-specific information, and reduces information efficiency. Furthermore, investor reactions to earnings announcements become more pronounced, and bid–ask spreads widen, reflecting lower market efficiency.

We develop a model in which accounting information and prudential regulation interact to affect banks’ incentives to originate loans. Prudential regulators impose capital requirements to prevent banks from taking excessive risk. However, regulators cannot commit to ex ante efficient intervention and, instead, respond to ex post accounting information. We show that capital requirements and accounting measurement are substitutes when considered separately. By contrast, when considered jointly, accounting measurement and capital requirements are complementary tools that affect the level and efficiency of credit decisions. Comparative statics link capital requirements, quality of accounting information, and regulatory intervention to credit market conditions. An upshot of our analysis is that by appropriately optimizing the information from expected loss models, prudential regulators may design looser capital requirements to spur more bank lending.

Investors have a finite capacity to organize all information they receive from financial disclosures. Under rational inattention, we show that investor processing capacity affects the probability of disclosure. Our main result is that the likelihood of disclosure is inverse-U shaped in investor attention. For low levels of attention, more attention facilitates communication and increases disclosure; for high levels of attention, more attention better identifies, and therefore deters, unfavorable voluntary disclosures. We provide empirical evidence that the relationship between investor attention and management forecast follows the predictions of the theory, using institutional ownership as a proxy for investor attention as well as exogenous shocks to fund manager distraction.

We estimate a dynamic model of voluntary disclosure, using annual management forecasts of earnings, that features a manager with price motives and an uncertain, but persistent, information endowment. Our estimates imply that: (1) managers face disclosure frictions 35 percent of the time; (2) conditional on being informed, managers withhold information 17 percent of the time; and (3) conditional on being silent, managers possess information 24 percent of the time. Managers' strategic withholding motives increase investors' uncertainty about earnings by 3 percent. We find that managers' price motives reduce strategic withholding by one-third in response to investors' increased skepticism in the event of non-disclosure.

Firm managers likely have more information than outsiders. If managers strategically conceal information, market uncertainty will increase. We develop a dynamic corporate disclosure model, estimating the model using the management earnings forecasts of US public companies. The model, based on the buildup of reputations by managers over time, matches key facts about forecast dynamics. We find that 80% of firms strategically manage information, that managers have superior information around half of the time, and that firms conceal information about 40% of the time. Concealment increases market uncertainty by just under 8%, a sizable information loss.