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Introducing Textual Measures of Central Bank Policy-Linkages Using ChatGPT

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  • Leek, Lauren Caroline

    (European University Institute)

  • Bischl, Simeon
  • Freier, Maximilian

Abstract

While institutionally independent, monetary policy-makers do not operate in a vacuum. The policy choices of a central bank are intricately linked to government policies and financial markets. We present novel indices of monetary, fiscal and financial policy-linkages based on central bank communication, namely, speeches by 118 central banks worldwide from 1997 to mid-2023. Our indices measure not only instances of monetary, fiscal or financial dominance but, importantly, also identify communication that aims to coordinate monetary policy with the government and financial markets. To create our indices, we use a Large Language Model (ChatGPT 3.5-0301) and provide transparent prompt-engineering steps, considering both accuracy on the basis of a manually coded dataset as well as efficiency regarding token usage. We also test several model improvements and provide descriptive statistics of the trends of the indices over time and across central banks including correlations with political-economic variables.

Suggested Citation

  • Leek, Lauren Caroline & Bischl, Simeon & Freier, Maximilian, 2024. "Introducing Textual Measures of Central Bank Policy-Linkages Using ChatGPT," SocArXiv 78wnp, Center for Open Science.
    • Handle: RePEc:osf:socarx:78wnp
    DOI: 10.31219/osf.io/78wnp
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    References listed on IDEAS

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    Cited by:

    1. Leek, Lauren Caroline & Bischl, Simeon, 2024. "How Central Bank Independence Shapes Monetary Policy Communication: A Large Language Model Application," SocArXiv yrhka, Center for Open Science.
    2. Leek, Lauren Caroline & Bischl, Simeon, 2024. "How Central Bank Independence Shapes Monetary Policy Communication: A Large Language Model Application," SocArXiv yrhka_v1, Center for Open Science.

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