Measuring Economic Sentiment from Open-Ended Survey Comments Using Large Language Models
OPEN ACCESS
Loading...
Author / Producer
Date
2025-10
Publication Type
Working Paper
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
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 firmlevel sentiment from free-text survey comments and aggregates it into a highfrequency 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.
Permanent link
Publication status
published
External links
Editor
Book title
Journal / series
Volume
526
Pages / Article No.
Publisher
KOF Swiss Economic Institute, ETH Zurich
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Economic Sentiment; Large Language Model; Business Tendency Surveys; Survey Comments; Textual Analysis; Forecasting
Organisational unit
02525 - KOF Konjunkturforschungsstelle / KOF Swiss Economic Institute
06331 - KOF FB Konjunkturumfragen / KOF Business Tendency Surveys