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
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Buchanan, J., Hill, S., & Shapoval, O. (2024). ChatGPT Hallucinates Non-existent Citations: Evidence from Economics. American Economist, 69(1), 80–87. https://doi.org/10.1177/05694345231218454
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