Junjie Yang
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2026
WonderEcon: An Interactive LLM-Agent System for Simulating Economies
Jing Qian | Boyu Liu | Wenyuan Gu | Hang Ruan | Cheng Huo | Junjie Yang | Mingyu Deng | Jiale Han | Benyou Wang
Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Jing Qian | Boyu Liu | Wenyuan Gu | Hang Ruan | Cheng Huo | Junjie Yang | Mingyu Deng | Jiale Han | Benyou Wang
Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
How an economic shock propagates through the heterogeneous decisions of diverse economic roles and emerges as aggregate fluctuations is a central question in economics. Traditional agent-based models hard-code behavioral rules and cannot read language, while recent LLM-agent simulations often omit explicit belief formation, endogenous price formation, or mechanism-grounded state transitions, and rarely let a human step into the loop. We present WonderEcon, a configurable, LLM-driven yet economic-rule-grounded multi-agent simulation system in which households, firms, commercial banks, a central bank, and a government interact across five markets, forming a self-consistent macroeconomic loop. Every agent decides through a four-step natural-language pipeline, reading real news alongside structured data, with every step observable. A player mode, with dedicated scene and character modeling, lets a human take over one household agent, yielding a counterfactual comparison and the Economic Personality Type Indicator (EPTI). On an interest-rate hiking cycle, WonderEcon demonstrates directional plausibility with respect to six well-known economic principles across four LLMs, and 33 participants find the player system satisfying. The engine and interfaces are publicly available.