EconGym: A Scalable AI Testbed with Diverse Economic Tasks

TL;DR

EconGym is a scalable, modular AI testbed designed for complex economic simulations, enabling diverse multi-agent tasks, policy learning, and benchmarking with high realism and efficiency.

Contribution

This paper introduces EconGym, a novel simulation platform that models diverse economic roles and tasks, supporting scalable, multi-agent AI research in economics.

Findings

Supports over 25 economic tasks including policy coordination

Enables benchmarking across AI and economic methods

Scales to 10,000 agents with high realism

Abstract

Artificial intelligence (AI) has become a powerful tool for economic research, enabling large-scale simulation and policy optimization. However, applying AI effectively requires simulation platforms for scalable training and evaluation-yet existing environments remain limited to simplified, narrowly scoped tasks, falling short of capturing complex economic challenges such as demographic shifts, multi-government coordination, and large-scale agent interactions. To address this gap, we introduce EconGym, a scalable and modular testbed that connects diverse economic tasks with AI algorithms. Grounded in rigorous economic modeling, EconGym implements 11 heterogeneous role types (e.g., households, firms, banks, governments), their interaction mechanisms, and agent models with well-defined observations, actions, and rewards. Users can flexibly compose economic roles with diverse agent algorithms to simulate rich multi-agent trajectories across 25+ economic tasks for AI-driven policy learning and analysis. Experiments show that EconGym supports diverse and cross-domain tasks-such as coordinating fiscal, pension, and monetary policies-and enables benchmarking across AI, economic methods, and hybrids. Results indicate that richer task composition and algorithm diversity expand the policy space, while AI agents guided by classical economic methods perform best in complex settings. EconGym also scales to 10k agents with high realism and efficiency.