Agent-Based Modeling in Economics and Finance: Past, Present, and Future

Agent-based modeling (ABM) is a novel computational methodology for representing the behavior of individuals in order to study social phenomena. Its use is rapidly growing in many fields. We review ABM in economics and finance and highlight how it can be used to relax conventional assumptions in standard economic models. ABM has enriched our understanding of markets, industrial organization, labor, macro, development, public policy, and environmental economics. In financial markets, substantial accomplishments include understanding clustered volatility, market impact, systemic risk, and housing markets. We present a vision for how ABMs might be used in the future to build more realistic models of the economy and review some of hurdles that must be overcome to achieve this. (JEL C63, D00, E00, G00)

Authors

Institutions

Publication Details

Journal
Journal of Economic Literature
Published
2025-03-01
DOI
https://doi.org/10.1257/jel.20221319
Citations
138
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
275.54
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Agent-Based Modeling in Economics and Finance: Past, Present, and Future

J. Doyne Farmer, Robert L. Axtell
138 citations
Journal of Economic Literature
Complex Systems and Time Series Analysis
275.54
article

Agent-Based Modeling in Economics and Finance: Past, Present, and Future

J. Doyne Farmer, Robert L. Axtell
article en
138 citations

Abstract

Agent-based modeling (ABM) is a novel computational methodology for representing the behavior of individuals in order to study social phenomena. Its use is rapidly growing in many fields. We review ABM in economics and finance and highlight how it can be used to relax conventional assumptions in standard economic models. ABM has enriched our understanding of markets, industrial organization, labor, macro, development, public policy, and environmental economics. In financial markets, substantial accomplishments include understanding clustered volatility, market impact, systemic risk, and housing markets. We present a vision for how ABMs might be used in the future to build more realistic models of the economy and review some of hurdles that must be overcome to achieve this. (JEL C63, D00, E00, G00)

Journal of Economic LiteratureVol. 63(1)
Santa Fe Institute (US), George Mason University (US), Institute for New Economic Thinking (US)
Openalex Percentile: Top 0%
Complex Systems and Time Series Analysis
275.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.