How Effectively Can Current LLMs Analyze Macrofinancial Issues?

2026

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This paper empirically evaluates the ability of current Large Language Models (LLMs) to analyze macrofinancial coverage in IMF Article IV staff reports, providing quantitative evidence on their accuracy and limitations.

* Assesses the performance of various GPT models in analyzing IMF Article IV staff reports against human economists' assessments.
* Examines accuracy on both qualitative ratings and binary questions, identifying strengths and weaknesses of LLMs in this domain.
* Discusses key limitations, including optimistic bias and challenges with open-ended questions requiring deep contextual judgment.

Tags: AI, Large Language Models, Macrofinancial Surveillance, Textual Analysis, IMF Staff Reports

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