The adoption of Large Language Models in economics research

Abstract

This paper develops a novel methodology for estimating the adoption of Large Language Models (LLMs) in economics research by exploiting their distinctive linguistic footprint. Using a rigorously constructed difference-in-differences framework, the analysis examines 25 leading economics journals over 24 years (2001–2024), analyzing differential frequencies between LLM-characteristic terms and conventional economic language. The empirical findings document significant and accelerating LLM adoption following ChatGPT’s release, with a 4.76 percentage point increase in LLM-associated terms during 2023–2024. The effect more than doubles from 2.85 percentage points in 2023 to 6.67 percentage points in 2024, suggesting rapid integration of language models in economics research. These results, robust across multiple fixed effects specifications, provide the first systematic evidence of LLM adoption in economics research and establish a framework for estimating technological transitions in scientific knowledge production.