"Income smoothing" is the process of manipulating the time profile of earnings or earnings reports to make the reported income stream less variable. This paper builds a theory of income smoothing based on the managers' concern about keeping their position or avoiding interference, and on the idea that current performance receives more weight than past performance when one is assessing the future. When investment is added to the model, so that income reports and dividends can be set independently, we find that both dividends and income reports may be smoothed and that dividends may convey information not present in the income report.

This paper studies agents who consider the experiences of their neighbors in deciding which of two technologies to use. We analyze two learning environments, one in which the same technology is optimal for all players and another in which each technology is better for some of them. In both environments, players use exogenously specified rules of thumb that ignore historical data but may incorporate a tendency to use the more popular technology. In some cases these naive rules can lead to fairly efficient decisions in the long run, but adjustment can be slow when a superior technology is first introduced.

We examine the rational expectations equilibrium paths of the model of search and barter in Diamond's "Aggregate Demand Management in Search Equilibrium." For some initial positions, there are two equilibrium paths converging to different steady states, with the high-activity path Pareto-dominating the low-activity path. With some parameters there is also a continuum of equilibrium paths converging to another steady state. Moreover, there can be cycles that are equilibrium paths, even though the environment is stationary.

"Income smoothing" is the process of manipulating the time profile of earnings or earnings reports to make the reported income stream less variable. This paper builds a theory of income smoothing based on the managers' concern about keeping their position or avoiding interference, and on the idea that current performance receives more weight than past performance when one is assessing the future. When investment is added to the model, so that income reports and dividends can be set independently, we find that both dividends and income reports may be smoothed and that dividends may convey information not present in the income report.

Presents a correction to an article on rational expectations in business cycles. (This abstract was borrowed from another version of this item.)

We examine the rational expectations equilibrium paths of the model of search and barter in Diamond's "Aggregate Demand Management in Search Equilibrium." For some initial positions, there are two equilibrium paths converging to different steady states, with the high-activity path Pareto-dominating the low-activity path. With some parameters there is also a continuum of equilibrium paths converging to another steady state. Moreover, there can be cycles that are equilibrium paths, even though the environment is stationary.

This paper studies agents who consider the experiences of their neighbors in deciding which of two technologies to use. The authors analyze two learning environments, one in which the same technology is optimal for all players and another in which each technology is better for some of them. In both environments, players use exogenously specified rules of thumb that ignore historical data but may incorporate a tendency to use the more popular technology. In some cases, these naive rules can lead to fairly efficient decisions in the long run but adjustment can be slow when a superior technology is first introduced.

We study agents who are more likely to remember some experiences than others but update beliefs as if the experiences they remember are the only ones that occurred. To understand the long-run effects of selective memory, we propose selective-memory equilibrium. We show that if the agent’s behavior converges, their limit strategy is a selective-memory equilibrium, and we provide a sufficient condition for behavior to converge. We use this equilibrium concept to explore the consequences of several well-documented biases. We also show that there is a close connection between selective-memory equilibria and the outcomes of misspecified learning.