Agent-Based Computational Economics: A Constructive Approach to Economic Theory
In: Handbook of Computational Economics
Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions.
|This chapter was published in: ||This item is provided by Elsevier in its series Handbook of Computational Economics with number
2-16.||Handle:|| RePEc:eee:hecchp:2-16||Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/bookseriesdescription.cws_home/BS_HE/description|
When requesting a correction, please mention this item's handle: RePEc:eee:hecchp:2-16. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.