Large Language Models in Economics

Elliott Ash, Stephen Hansen and Yabra Muvdi

No 19479, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: This chapter explores the transformative impact of large language models (LLMs) on text analysis in economics. We trace the evolution from traditional methods like bag-of-words to advanced models such as BERT and GPT, highlighting how these models address limitations in understanding context and allowing higher-order reasoning. Although LLMs are complex, costly, and lacking in transparency, they are powerful tools for research, such as measuring sentiment or predicting metadata associated with documents.

Keywords: Large Language Models; Transformer models; Text as data; Unstructured Data (search for similar items in EconPapers)
JEL-codes: C18 C45 C55 (search for similar items in EconPapers)
Date: 2024-09
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