We study how the potential for discretionary disclosure affects the way a firm designs its reporting system. In our model, the firm's primary but nonexclusive concern is to induce beliefs that exceed a threshold. Such thresholds arise in numerous contexts, including investing decisions, liquidation/continuation choices, covenants, audits, impairments, listing requirements, index inclusion, credit ratings, analyst recommendations, and stress tests. The optimal reporting system is characterized by informative good reports when the threshold is high and, potentially, uninformative reports when the threshold is low. Under an optimal impairment-type reporting system, the likelihood of reported impairments and the information content of non-impairment reports both increase in the probability of the firm observing private information. We provide a novel motivation for the quiet period around an IPO and empirical predictions relating the probability of discretionary disclosure to the properties of financial reports. In extensions, we consider disclosure mandates, report manipulation, endogenous thresholds, and alternative payoff functions.

We study the optimal dynamic contract that provides incentives for an agent (e.g., SPAC sponsor, VC general partner, CTO) to exploit investment opportunities/targets that arrive randomly over time via a costly search process. The agent is privy to the arrival as well as to the quality of the target and can take advantage of this for rent extraction during the search process and the ensuing production. The optimal contract provides the agent with incentives for timely and truthful reporting via a time-varying threshold for investment and an internal charge for the time spent on search. In the equilibrium, as time elapses, the charge becomes progressively higher while the investment threshold is progressively lower, resulting in overinvestment at a time-varying degree. Our model generates empirically testable predictions regarding investments (such as M&As, hedge fund activism, VC investing, SPACs, and internal innovations), linking the degree of overinvestment to observable firm and industry characteristics. • Optimal dynamic contract for the search and use of investment opportunities/targets. • Adverse selection arises regarding the arrival of targets and their quality. • Optimal contract involves a progressively declining hurdle for investments. • The investments hurdle is always below the first-best, implying overinvestment. • Our results shed light on internal innovation, M&A, SPACs, VC and HFA investments.