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Large Language Models in Economics

Author

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  • Ash, Elliott
  • Hansen, Stephen
  • Muvdi, Yabra

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.

Suggested Citation

  • Ash, Elliott & Hansen, Stephen & Muvdi, Yabra, 2024. "Large Language Models in Economics," CEPR Discussion Papers 19479, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:19479
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    File URL: https://cepr.org/publications/DP19479
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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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