Ivan Marinovic

Optimal Contracts with Performance Manipulation

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 managers 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.

Internal control system, earnings quality, and the dynamics of financial reporting

Using an earnings management model in which managers manipulate information when the firm’s control system fails, I introduce a measure of earnings quality, based on the notion of integral precision, that has solid theoretical foundations. A trade-off between the frequency and the magnitude of overstatements is shown: overstatements are larger when misreporting is less likely. Overall, the model generates a distribution of earnings announcements similar to its empirical analogue and provides a structural method to identify the likelihood and magnitude of misreporting by exploiting information from the moments of the distribution of reported earnings.

Chapter 12 – Forecasters’ Objectives and Strategies

Abstract This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive literature on analysts, we review the empirical evidence on strategic forecasting and illustrate how our model can be structurally estimated.

Competition for Talent Under Performance Manipulation: CEOs on Steroids

We study how competition for talent affects CEO compensation, taking into consideration that CEO decisions and CEO skills or talent are not observable, and CEOs can manipulate performance as measured by outsiders. Firms compete by offering contracts that generate rents for the CEO. We derive the equilibrium compensation contract, and we describe how competition changes that contract and the outcome. Intuitively, competition increases realized CEO compensation. It also strengthens the incentive power of the contracts. While competition mitigates inefficiencies caused in its absence, it also generates inefficiencies of its own. Competition replaces a downward distortion by an upwards distortion (incentive power is excessively strong), and it switches the focus of equilibrium effort distortions from low-talent CEOs to high-talent CEOs. Competition leads to higher effort but also to more manipulation of measured performance. If the cost of manipulating performance is low, the distortions can outweigh those that are mitigated, and competition for talent may reduce the overall surplus. We discuss possible remedies, including regulatory limits to incentive compensation.

How Often Do Managers Withhold Information

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: (i) managers face disclosure frictions 35% of the time; (ii) conditional on being informed, managers withhold information 17% of the time; and (iii) conditional on being silent, managers possess information 24% of the time. Managers’ strategic withholding motives increase investors’ uncertainty about earnings by 3%. We find that managers’ price motives reduce strategic withholding by one-third, in response to investors’ increased skepticism in the event of non-disclosure.

Dynamic Certification and Reputation for Quality

We study firms incentives to invest and build reputation for quality, when quality can be certified at a cost. We consider two types of equilibria: one in which certification decisions are made based on firms reputation and the second in which they are made based on the time since last certification. We show that reputation-based certification has a very limited effect on incentives to invest in quality, so that in equilibrium the firm invests only its reputation is the lowest. We also show that the firm in this case suffers from an over-certification trap in which the benefits of reputation are dissipated by excessive certification. These problems can be avoided with time-based certification, which can allow first-best investment in quality for sufficiently small certification cost, despite investment being unobservable. We also show that the optimal certification duration results in the firm certifying when its reputation is high.

Random Inspections and Periodic Reviews: Optimal Dynamic Monitoring

This paper studies the design of monitoring/audit policies in dynamic settings. Firm quality is private information and evolves stochastically via a Markov process with transitions depending on the firms unobservable effort. The firm benefits from having a reputation for quality. A principal designs a monitoring policy that allows him to learn the firms quality by conducting costly reviews. Monitoring plays two roles. First, it plays an incentive role, because when the principal discloses the outcome of inspections to the public, it affects the firms reputation. Second, information is directly valuable when the principals payoff is convex in reputation, for example because it allows consumers to make better choices. Our main result is a characterization of the optimal monitoring policy that induces full effort. The policy is surprisingly simple. It is either deterministic, whereby the date of the next inspection is pre-announced, or random, with a constant hazard rate of next inspection. We discuss how the type of optimal monitoring depends on history, the cost of monitoring, the persistence of quality, and the cost of effort. We also consider how the optimal monitoring policy is affected by the presence of exogenous news, showing how the evolution of the hazard of random monitoring depends on whether the absence of news is perceived to be good or bad news about quality.

Cashing-In Credibility

This paper studies a dynamic communication game in which the seller of an asset, whose credibility is unknown to the market, reports changes in the asset value during multiple periods before selling the asset. We characterize the strategy by which the seller exploits his credibility over time to maximize the assets terminal price. Though the asset value is iid across periods, and its distribution is continuous, the equilibrium has a simple Markov structure that depends on a single state variable: the sellers cumulative report. The possibility of misreporting generates reports that are serially dependent, even when the shocks are independent across periods. In equilibrium, prices are relatively insensitive to good news, particularly in the last period. The sellers cumulative report tends to grow over time, while the sellers credibility tends to decrease slowly. The seller is able to maintain inflated prices for as long as necessary. Furthermore, the terminal price explodes as the sellers horizon grows large.