ChatGPT Hallucinates Non-existent Citations: Evidence from Economics

Joy Buchanan, Stephen Hill and Olga Shapoval

The American Economist, 2024, vol. 69, issue 1, 80-87

Abstract: In this study, we generate prompts derived from every topic within the Journal of Economic Literature to assess the abilities of both GPT-3.5 and GPT-4 versions of the ChatGPT large language model (LLM) to write about economic concepts. ChatGPT demonstrates considerable competency in offering general summaries but also cites non-existent references. More than 30% of the citations provided by the GPT-3.5 version do not exist and this rate is only slightly reduced for the GPT-4 version. Additionally, our findings suggest that the reliability of the model decreases as the prompts become more specific. We provide quantitative evidence for errors in ChatGPT output to demonstrate the importance of LLM verification. JEL Codes: B4; O33; I2

Keywords: artificial intelligence; large language models; ChatGPT; writing; research methods (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:amerec:v:69:y:2024:i:1:p:80-87

DOI: 10.1177/05694345231218454

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