Simulating Macroeconomic Expectations in Survey Experiments with LLM-based Economic Agents

Jianhao Lin, Lexuan Sun and Yixin Yan

Papers from arXiv.org

Abstract: We introduce a framework for simulating macroeconomic expectations in survey experiments using LLM-based economic agents (LLM Agents). We construct LLM Agents equipped with several functional modules that retrieve personal characteristics, prior expectations, and dynamic external information. We validate our framework by recapitulating three representative survey designs covering various expectations across different types of respondents. Our results show that LLM Agents generate expectation distributions highly similar to human data and capture human-aligned qualitative patterns in open-ended responses. Evaluation reveals that priors are crucial for matching distributions, whereas personal and external information drive human-like thought processes. Our findings offer guidance for narrowing the belief gap between generative AI and humans at the aggregate level while delineating the boundaries of the framework.

Date: 2025-05, Revised 2026-06
New Economics Papers: this item is included in nep-ain, nep-cmp, nep-exp and nep-mac
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