Many people are impatient. We introduce domain-specific discounting to a contracting model and test a strategy for improving incentives when people are impatient over effort: implement time-bundled contracts that make the payment for future effort increase in current effort. Using a randomized evaluation of an exercise incentive program among diabetics in India, we find that time-bundled contracts generate equivalent effort to time-separable contracts at 15 percent lower cost. Moreover, they perform 30 percent better among individuals with above-median effort impatience. Pooled across contracts, incentives increase steps by 20 percent and improve blood sugar relative to a control group. (JEL D86, D91, I12, I18, O12)
A principal hires an agent to learn about the cost of a project (experimentation) and then to execute it (production). The agent is privately informed about the probability that the cost is low, with the high-type agent more optimistic than the low type. Learning is modeled as a series of experiments, where the agent privately chooses his effort in each experiment. Due to the joint presence of adverse selection and moral hazard, even the low type can misrepresent his type, shirk during experimentation and earn a rent. In the optimal contract, the principal uses the length and outcome of experimentation as well as the timing of payments to induce effort and screen the agent. The principal may find it optimal to reward the low type after failure in experimentation. We provide sufficient conditions for both success and failure to be rewarded. We show that over-experimentation can be optimal as it reduces the asymmetric information after a series of failed experiments. We also consider whether it may be optimal to separate experimentation and production between two different agents. When the same agent works on both tasks, the principal can leverage the adverse selection rent to mitigate moral hazard. Therefore, integrating experimentation and production is optimal when adverse selection is severe.
This paper studies a model with wage bargaining, random on-the-job search and renegotiation. Wages are determined by a bargaining process in which the firm and the worker alternate in making offers and there is a probability that this process breaks down. In the model, a given wage contract ends at a Poisson rate, and then the firm and the worker bargain over a new wage. In this setting, a higher wage decreases the firm's markup, but this effect is partly offset by lowering turnover, which increases match surplus. This increase in match surplus enables the worker to capture a higher share of the surplus. This positive effect of a higher wage on match surplus diminishes when they renegotiate more frequently. Eventually, as the contract length tends to zero, the equilibrium of the model converges to the equilibrium payoffs discussed by Pissarides (1994). My model thereby justifies using the Nash bargaining solution with perfectly transferable values in models with on-the-job search. In contrast, when the Poisson rate goes to zero, the equilibrium in the model, which I show to be unique, converges to one of the equilibria found by Shimer (2006).
We analyze optimal procurement contracts when suppliers learn about project costs over time and retain an ex-post right to exit. In the first period, the firm observes a private signal on the likelihood of high costs; in the second, it learns the realized cost type and decides whether to continue or exercise its outside option. We show that when exit opportunities are sufficiently attractive, the optimal mechanism pools all first-period signals and reduces to a cost-plus contract, with payments tied only to realized, verifiable costs. Attempts to elicit cost forecasts ex-ante backfire: firms strategically under-report expectations, triggering exit in high-cost states and generating overruns. This provides a mechanism-based interpretation of cost overruns as failures of incentive design. Finally, we demonstrate that more generous outside options can raise procurement costs and lower firm profits, identifying conditions where limiting exit rights is ex-ante Pareto improving. (JEL D82, D86, H57)
We examine a scenario in which an employee exerts productive effort to achieve a target but can also manipulate a performance measure to falsely claim target achievement. Although manipulation is detrimental from a societal perspective because of its negative externalities, the firm’s shareholders may benefit from undetected manipulation. We analyze the firm’s optimal implementation of internal control and its impact on the employee’s productive effort and manipulative behavior. We demonstrate that a profit-maximizing firm primarily utilizes internal control to enhance the employee’s performance pay contract; however, this does not necessarily reduce manipulation. We identify situations in which internal control reduces or aggravates manipulation and discuss factors that can complement internal control to combat manipulation.
Risk pooling has become an increasingly critical tool for managing risks among corporations, institutions, states, and nations, with examples including multinational pooling, decentralized insurance schemes, catastrophe risk pooling, and burden sharing for nuclear accidents. Although there has been a rich literature on such practices, little is known from a theoretical viewpoint regarding the operational strategies of risk pools and, in particular, on issues about the effect of a pool’s expansion on each existing member’s welfare. This paper is the first to explore these issues by establishing different notions of consensus for the expansion of a risk pool: strong consensus, where both existing members and new candidates improve their risk measures due to the pool’s expansion, and weak consensus, which refers to the willingness of existing members to remain in the pool. Under optimal risk sharing for each pool, we show that its properties regarding expansion’s effects depend strongly on the underlying pricing rule. For instance, only with risk-adjusted equilibrium pricing are existing members willing to accept highly risky new members, whereas simple linear pricing excludes such members from the pool. Additionally, the impact of exogenous reinsurance on consensus is analyzed under both pricing rules. The established framework offers valuable managerial insights and policy implications, which we illustrate through two indicative case studies based on real data.
We address organizations that rely on donors, when those donors are motivated by making a difference. We show that when donors care sufficiently about their marginal impact, firms use practices that would normally be deemed inefficient. These include prioritizing less valuable opportunities over better ones, investing most in their weakest initiatives, and benefiting from not identifying the quality of their projects. These all arise from a distinction between marginal and average returns generated by donor preferences.
Adverse selection famously leads to the crowding out of socially beneficial trades. We show that even more trades may be simultaneously crowded in. The reason is that, in the absence of complete unravelling, “lemons” fetch more under adverse selection. It is demonstrated how these “bad” trades occur in insurance, credit and used-car markets, and some policy implications are discussed.
A principal incentivizes a team of agents to work by privately offering them bonuses contingent on team success. We study the principal’s optimal incentive scheme that implements work as a unique equilibrium. This scheme leverages rank uncertainty to address strategic uncertainty. Each agent is informed only of a ranking distribution and his own bonus, the latter making work dominant provided that higher-rank agents work. If agents are symmetric, their bonuses are identical. Thus, discrimination is strictly suboptimal, in sharp contrast with the case of public contracts (Winter 2004). We characterize how agents’ ranking and compensation vary with asymmetric effort costs. (JEL D23, D62, D81, D82, D86)
We provide general conditions under which principal-agent problems with either one or multiple agents admit mechanisms that are optimal for the principal. Our results cover as special cases pure moral hazard and pure adverse selection. We allow multidimensional types, actions, and signals, as well as both financial and non-financial rewards. Our results extend to situations in which there are ex ante or interim restrictions on the mechanism, and allow the principal to have decisions in addition to choosing the agent's contract. Beyond measurability, we require no a priori restrictions on the space of mechanisms. It is not unusual for randomization to be necessary for optimality and so it (should be and) is permitted. Randomization also plays an essential role in our proof. We also provide conditions under which some forms of randomization are unnecessary.