Analysis of CBDC narratives of central banks using large language models - 0 views
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John Kiff on 15 Aug 23The Banco de España (BDE) published a paper that proposes the use of different Natural Language Processing (NLP) techniques to better understand central banks' stance towards central bank digital currency (CBDC), analyzing a set of central bank discourses from 2016 to 2022. It uses dictionary-based methods, and two large language models (LLMs) (Bert and ChatGPT), concluding that LLMs better reflect the stance identified by human experts. ChatGPT appears to exhibit a higher degree of alignment because it can capture subtler information than BERT. The study suggests that LLMs are an effective tool to improve sentiment measurements for policy-specific texts, though they are not infallible and may be subject to new risks.