JSAI2025

Presentation information

Poster Session

Poster session » Poster Session

[1Win4] Poster session 1

Tue. May 27, 2025 3:30 PM - 5:30 PM Room W (Event hall D-E)

[1Win4-105] EconGrowthAgent: Macroeconomic Simulation based on LLM-powered Agents and Economic Growth Theory

〇Terufumi Morishita1, Masaya Tsunokake1, Atsuki Yamaguchi2, Koichi Nagatsuka1, Hikaru Tomonari1, Gaku Morio1, Osamu Imaichi1, Yasuhiro Sogawa1 (1.Research and Development Group, Hitachi., 2.University of Sheffield)

Keywords:Large Language Model, economics, Agent, Macroeconomics, multi agent

Economic growth is an essential phenomenon that brings prosperity to human society.
To analyze economic growth, we propose "EconGrowthAgent", an economic simulation environment with LLM agents.
According to macroeconomics, economic growth occurs in two stages: 1. Economic agents, including households and firms, make economic decisions, such as labor, consumption, savings, investment, and production, and 2. The interactions of these decisions in production dynamics lead to increased goods production.
Therefore, EconGrowthAgent models economic agent decision-making through LLM agents and incorporates production dynamics that represent their interactions.
We conducted a 20-year economic simulation on EconGrowthAgent using 100 GPT-4o agents and confirmed its ability to replicate economic growth and related phenomena.
This demonstrates the validity of EconGrowthAgent.
Additionally, we simulated scenarios of "transition to an extremely small government" and "approach of an extinction-level asteroid" to analyze their impacts on economic growth.
The ability to freely examine such scenarios, which would be difficult to verify in the real world, provides significant practical value.

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