Learning to Speculate: Experiments with Arti cial and Real Agents

This paper employs an arti cial agent{based computational approach to understanding and designing laboratory environments in which to test Kiyotaki and Wright's search model of money. The behavioral rules of the arti cial agents are modeled on the basis of prior evidence from human subject experiments. Simulations of the arti cial agent{based model are conducted in two new versions of the Kiyotaki{Wright environment and yield some testable predictions. These predictions are examined using data from new, human subject experiments. The results are encouraging and suggest that arti cial agent{based modeling may be a useful device for both understanding and designing human subject experiments. JEL classi cation: D83, C73, C90, E40.