Measuring economic sentiment from open-ended survey comments using large language models

Pascal Seiler

Economics Letters, 2025, vol. 256, issue C

Abstract: This article develops a novel economic sentiment indicator (LLM-ESI) by applying large language models to open-ended responses from Swiss business tendency surveys. Using a BERT-based transformer model, it extracts firm-level sentiment from free-text survey comments and aggregates it into a high-frequency indicator of macroeconomic conditions. The LLM-ESI closely tracks the business cycle and performs on par with, or better than, traditional benchmarks in nowcasting GDP. These results highlight the potential of large language models and open-ended survey responses to deliver timely and nuanced signals for real-time economic analysis.

Keywords: Economic sentiment; Large language model; Business tendency surveys; Survey comments; Textual analysis; Forecasting (search for similar items in EconPapers)
JEL-codes: C53 C55 E32 E37 E66 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:256:y:2025:i:c:s0165176525004598

DOI: 10.1016/j.econlet.2025.112622

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