LLM Survey Framework: Coverage, Reasoning, Dynamics, Identification

Jing Cynthia Wu, Jin Xi and Shihan Xie

No 34308, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We propose a new LLM-based survey framework that enables retrospective coverage, economic reasoning, dynamic effects, and clean identification. We recover human-comparable treatment effects in a multi-wave randomized controlled trial of inflation expectations surveys, at 1/1000 the cost. To demonstrate the framework’s full potential, we extend the benchmark human survey (10 waves, 2018–2023) to over 50 waves dating back to 1990. We further examine the economic mechanisms underlying agents’ expectation formation, identifying the mean-reversion and individual-attention channels. Finally, we trace dynamic treatment effects and demonstrate clean identification. Together, these innovations demonstrate that LLM surveys enable research designs unattainable with human surveys.

JEL-codes: C83 E31 E52 (search for similar items in EconPapers)
Date: 2025-10
New Economics Papers: this item is included in nep-ain, nep-ecm and nep-exp
Note: AP EFG ME
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