This paper studies moral hazard in teams using a model where efforts are promoted via the combination of profit shares and relational contracts. The focus is on how these two forms of incentives interact. According to the degree of effort observability and the importance of future interaction, the optimal allocation of profit shares can range from a wide dispersion across players to a full concentration of shares in the hands of a single player. When shares are sufficiently concentrated, the corresponding residual claimant can also adopt the role of administering all relational contracts, therefore serving as an endogenously chosen principal.

Organizations fail due to incentive problems (agents do not want to act in the organization's interests) and bounded rationality problems (agents do not have the necessary information to do so). This survey uses recent advances in organizational economics to illuminate organizational failures along these two dimensions. We combine reviews of the literature with simple models and case discussions. Specifically, we consider failures related to short-termism and the allocation of authority, both of which are instances of “multitasking problems”; communication failures in the presence of both soft and hard information due to incentive misalignments; resistance to change due to vested interests and rigid cultures; and failures related to the allocation of talent and miscommunication due to bounded rationality. We find that the organizational economics literature provides parsimonious explanations for a large range of economically significant failures. (JEL D21, D23, D82, D83, M10)

We study how relational contracts mitigate Becker's classic problem of providing general human capital when training contracts are incomplete. The firm's profit-maximizing agreement is a multiperiod apprenticeship in which the novice is trained gradually over time and eventually receives all knowledge. The firm adopts a 1/e rule, whereby at the beginning of the relationship the novice is trained, for free, just enough to produce a fraction 1/e of the efficient output. After that, the novice earns all additional knowledge with labor. This rule causes inefficiently lengthy relationships that grow longer the more patient the players. A minimum wage is welfare enhancing. (JEL D82, D86, J24, M53)

The principal motivating factor in our lives is the pursuit of happiness. In most cultures, when seeking this end, individuals place a high priority on income, and spend much of their waking time procuring this intermediate goal. The connection between income and happiness is by no means trivial, however. Two critical factors come into play. First, beyond subsistence level, the positive effect of a permanent change in income tends to be short lived. We rapidly become accustomed to a more expensive lifestyle. A common name for this feature is habit formation. Second, the satisfaction derived from a given level of income is sharply dependent on how it compares to the income of peers. See, for example, Andrew B. Abel (1990), Becker (1996), and William A. Brock and Steven N. Durlauf (2001) for a demonstration of the influence of habits and peer comparisons over behavior, and see Shane Frederick and George Loewenstein (1999) for a review of the underlying psychology. Habits and peer comparisons mean that an individual is not concerned mainly with her absolute level of income, but rather with the difference between her income and a benchmark that changes over time. In recent years, economists have become increasingly interested in this fact. This interest has been both applied (i.e., the study of habits and peer influences over behavior and the analysis of happiness surveys) and theoretical (i.e., a search for biological foundations). But unlike other more developed areas of economics, these two approaches remain fairly separate from each other. In particular, the existing theoretical work is motivated only by the most basic empirical observations. And the existing applied work, for the most part, has not been influenced by theoretical results. In this essay, we seek to reduce the distance between these two literature strands. In particuHabits, Peers, and Happiness: An Evolutionary Perspective

We model happiness as a measurement tool used to rank alternative actions. Evolution favors a happiness function that measures the individual’s success in relative terms. The optimal function is based on a time‐varying reference point—or performance benchmark—that is updated over time in a statistically optimal way in order to match the individual’s potential. Habits and peer comparisons arise as special cases of such an updating process. This updating also results in a volatile level of happiness that continuously reverts to its long‐term mean. Throughout, we draw a parallel with a problem of optimal incentives, which allows us to apply statistical insights from agency theory to the study of happiness.

A principal specifies time paths of effort provision, task allocation, and knowledge transfer for a cash-constrained apprentice, who is free to walk away at any time. In the optimal contract the apprentice pays for training by working for low or no wages and by working inefficiently hard. The apprentice can work on both knowledge-complementary and knowledge-independent tasks. We study the optimal time path of effort distortions and their impact on the knowledge transfer, and analyze the effect of regulatory limits on the length of apprenticeships and on how much effort apprentices are allowed to provide. (JEL D82, D86, J24, J41, M53)

A sender randomly draws a “prospect” characterized by its profitability to the sender and its relevance to a receiver. The receiver observes only a signal provided by the sender and accepts the prospect if his Bayesian inference about the prospect’s relevance exceeds his opportunity cost. The sender’s profits are typically maximized by partial information disclosure, whereby the receiver is induced to accept less relevant but more profitable prospects (“switches”) by pooling them with more relevant but less profitable ones (“baits”). Extensions include maximizing a weighted sum of sender profits and receiver surplus and allowing the sender to use monetary incentives.

We study the joint design of dynamic incentives and performance feedback for an environment with a coarse (all‐or‐nothing) measure of performance, and show that hiding information from the agent can be an optimal way to motivate effort. Using a novel approach to incentive compatibility, we derive a two‐phase solution that begins with a “silent phase” where the agent is given no feedback and is asked to work non‐stop, and ends with a “full‐transparency phase” where the agent stops working as soon as a performance threshold is met. Hiding information leads to greater effort, but an ignorant agent is also more expensive to motivate. The two‐phase solution—where the agent's ignorance is fully frontloaded—stems from a “backward compounding effect” that raises the cost of hiding information as time passes.

We examine legislative policy making in institutions with two empirically relevant features: agenda setting occurs in real time and the default policy evolves. We demonstrate that these institutions select Condorcet winners when they exist, provided a sufficient number of individuals have opportunities to make proposals. In policy spaces with either pork barrel or pure redistributional politics (where a Condorcet winner does not exist), the last proposer is effectively a dictator or near-dictator under relatively weak conditions. Copyright The Econometric Society 2006.

We obtain optimal dynamic contests for environments where the designer monitors effort through coarse, binary signals—Poisson successes—and aims to elicit maximum effort, ideally in the least amount of time possible, given a fixed prize. The designer has a vast set of contests to choose from, featuring termination and prize-allocation rules together with real-time feedback for the contestants. Every effort-maximizing contest (which also maximizes total expected successes) has a history-dependent termination rule, a feedback policy that keeps agents fully apprised of their own success, and a prize-allocation rule that grants them, in expectation, a time-invariant share of the prize if they succeed. Any contest that achieves this effort in the shortest possible time must in addition be what we call second chance: once a pre-specified number of successes arrive, the contest enters a countdown phase where contestants are given one last chance to succeed.