From Text to Evidence: LLMs in Economics and Finance

Zongwu Cai, Ying Fang, Ming Lin and Zeqin Liu
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Zongwu Cai: Department of Economics, The University of Kansas, Lawrence, KS 66045, USA
Ying Fang: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China and Department of Statistics & Data Science, School of Economics, Xiamen University, Xiamen, Fujian 361005, China
Ming Lin: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China and Department of Statistics & Data Science, School of Economics, Xiamen University, Xiamen, Fujian 361005, China
Zeqin Liu: School of Statistics, Shanxi University of Finance and Economics, Taiyuan, Shanxi 030006, China

No 202618, WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS from University of Kansas, Department of Economics

Abstract: We review applications of large language models (LLMs) in economic and financial research, focusing on text analysis and variable construction, forecasting and decision support, simulation of economic agents, and research assistance and automation. We examine what researchers use LLMs to do, how the reported results compare with existing methods, and what limits their use. Contextual interpretation improves several classification tasks, but variable construction and measurement error affect subsequent analysis. Some forecasts improve on benchmarks, although gains vary and predictive signals need not yield trading profits. Human observations help calibrate agents and improve predictions of survey responses. Automated systems generate economic mechanisms and connect empirical analysis with drafting, while researchers still judge questions and explanations. We then discuss future directions for improving research quality and making better use of researchers' expertise.

Keywords: Large language models; text analysis; economic forecasting; economic agent simulation; research assistance and automation (search for similar items in EconPapers)
Date: 2026-09, Revised 2026-09
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Persistent link: https://EconPapers.repec.org/RePEc:kan:wpaper:202618

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