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This article describes an experiment in a Kydland/Prescott type of environment with cheap talk. Individual evolutionary learning (IEL) acts as a policy maker that makes inflation announcements and decides on actual inflation rates. IEL evolves a set of strategies based on the evaluation of their counterfactual payoffs measured in terms of disutility of inflation and unemployment. Two types of private agents make inflation forecasts. Type 1 agents are automated and they set their forecast equal to the announced inflation rate. Type 2 agents are human subjects who submit their inflation forecast and are rewarded based on their forecast error. The fraction of each type evolves over time based on their performance. Experimental economies result in outcomes that are better than the Nash equilibrium. This article is the first to use an automated policy maker that changes and adapts its rules over time in response to the environment in which human subjects make choices.

This article discusses the methodology of using laboratory methods to address macroeconomic questions. It also provides summaries of the articles in this volume.

This article explores the importance of accessible and focal information in influencing beliefs and attention in a learning-to-forecast laboratory experiment where subjects are incentivized to form accurate expectations about inflation and the output gap. We consider the effects of salient and accessible forecast error information and learning on subjects’ forecasting accuracy and heuristics, and on aggregate stability. Experimental evidence indicates that, while there is considerable heterogeneity in the heuristics used, subjects’ forecasts can be best described by a constant gain learning model where subjects respond to forecast errors. Salient forecast error information reduces subjects’ overreaction to their errors and leads to greater forecast accuracy, coordination of expectations, and macroeconomic stability. The benefits of this focal information are short-lived and diminish with learning.

The purpose of this paper is to explore the ability of monetary policy to generate real effects in laboratory general equilibrium production economies.

To understand why monetary policy is not consistently effective at stabilizing economic activity, the author vary the types of agents interacting in the economy and consider treatments where subjects are playing the role of households (firms) in an economy where automated firms (households) are programmed to behave rationally.

While the majority of participants’ expectations respond to monetary policy in the direction intended, subjects do form expectations adaptively, relying heavily on past variables and forecasts in forming two-steps-ahead forecasts. Moreover, in the presence of counterparts that are boundedly rational, forecast accuracy worsens significantly. When interacting with automated households, updating firms’ prices respond modestly to monetary policy and significantly to anticipated marginal costs and future prices. The greatest deviations in behavior from theoretical predictions arise from human households (HH). Households persistent oversupply of labor and under-consumption is attributed to precautionary saving and debt aversion. The results provide evidence that the effects of monetary policy on decision making hinge on the distribution of indebtedness of households.

The author present causal evidence of the effects of potential bounded rationality on agents’ consumption and labor decisions.