Learning to speculate: Experiments with artificial and real agents

Authored by J Duffy

Date Published: 2001-03

DOI: 10.1016/s0165-1889(00)00028-2

Sponsors: United States National Science Foundation (NSF)

Platforms: C++

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

This paper employs an artificial agent-based computational approach to understanding and designing laboratory environments in which to lest Kiyotaki and Wright's search model of money. The behavioral rules of the artificial agents are modeled on the basis of prior evidence from human subject experiments. Simulations of the artificial 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 artificial agent-based modeling may be a useful device for both understanding and designing human subject experiments. (C) 2001 Elsevier Science B.V. Ail rights reserved. JEL classification: D83; C73; C90; E40.

Tags

Agent-Based Computational Economics Learning experimental design Search money