A conventional contract is a contract that each side of a bargain expects the other side to insist on, because it is standard and customary under the circumstances. The author considers a process of convention formation in which agents expectations evolve through repeated interactions in a large-population setting. Agents choose best replies given their knowledge of the precedents, subject to some inertia and random error in their choice behavior. Over the long run, this adaptive learning process tends to select contracts that are efficient, and egalitarian in the sense that the payoffs are centrally located on the efficiency frontier of the payoff possibility set. When the payoffs form a convex, comprehensive bargaining set, the process selects the Kalai-Smorodinsky solution.

Survey data suggest that cropsharing contracts exhibit a much higher degree of uniformity than is warranted by economic fundamentals. We propose a dynamic model of contract choice to explain this phenomenon. Landowners and tenants recontract periodically, taking into account expected returns as well as conformity with local practice. The resulting stochastic dynamical system is studied using techniques from statistical mechanics. The most likely states consist of patches where contractual terms are nearly uniform, separated by boundaries where the terms shift abruptly. These and other predictions of the model are borne out by survey data on agricultural contracts in Illinois.

The author shows how a group of individuals can learn to play a coordination game without any common knowledge and with only a small amount of rationality. The game is repeated many times by different players. Each player chooses an optimal reply based on incomplete information about what other players have done in the past. Occasionally they make mistakes. When the likelihood of mistakes is very small, typically one coordination equilibrium will be played almost all of the time over the long run. This stochastically stable equilibrium can be computed analytically using a general theorem the author proves on perturbed Markov processes.

New ideas, products, and practices take time to diffuse, a fact that is often attributed to some form of heterogeneity among potential adopters. This paper examines three broad classes of diffusion models—contagion, social influence, and social learning—and shows how to incorporate heterogeneity into each at a high level of generality without losing analytical tractability. Each type of model leaves a characteristic “footprint” on the shape of the adoption curve which provides a basis for discriminating empirically between them. The approach is illustrated using the classic study of Ryan and Gross (1943) on the diffusion of hybrid corn.

Interconnections among financial institutions create potential channels for contagion and amplification of shocks to the financial system. We estimate the extent to which interconnections increase expected losses and defaults under a wide range of shock distributions. In contrast to most work on financial networks, we assume only minimal information about network structure and rely instead on information about the individual institutions that are the nodes of the network. The key node-level quantities are asset size, leverage, and a financial connectivity measure given by the fraction of a financial institution’s liabilities held by other financial institutions. We combine these measures to derive explicit bounds on the potential magnitude of network effects on contagion and loss amplification. Spillover effects are most significant when node sizes are heterogeneous and the originating node is highly leveraged and has high financial connectivity. Our results also highlight the importance of mechanisms that go beyond simple spillover effects to magnify shocks; these include bankruptcy costs, and mark-to-market losses resulting from credit quality deterioration or a loss of confidence. We illustrate the results with data on the European banking system.

We propose a model to study when an intermediate action can serve as a stepping stone that enables the elimination of a harmful norm. While the intermediate action may facilitate the first “step,” it may also become a new norm. We derive intuitive conditions for stepping stones, which depend on the relative size of social penalties and intrinsic utility benefits. We propose an econometric approach to testing whether an intermediate action is a stepping stone, and apply it to original data on female genital cutting in Somalia. The analysis shows that the intermediate action may become the new norm.