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Tales of Turbulence: BERT-based Multimodal Analysis of FED Communication Dynamics Amidst COVID-19 Through FOMC Minutes

Author

Listed:
  • Bilal Taskin

    (Hacettepe University)

  • Fuat Akal

    (Hacettepe University)

Abstract

This study analyzes Federal Open Market Committee (FOMC) minutes using state-of-the-art Natural Language Processing techniques. We sought to investigate the effect of the global COVID-19 crisis on the FOMC minutes’ pattern and the strength of the Federal Reserve to influence inflation expectations through its primary press releases. To this end, we first quantified minutes leveraging domain-specific pre-trained Bidirectional Encoder Representations from Transformers models (FinBERTs). Then, we applied dynamic time warping to measure temporal sequence proximity over time. In addition, we built multivariable autoregressive integrated moving average models to verify our findings by injecting exogenous variables as indicator functions into the time series. The results suggest that the Federal Reserve has abstained from adjusting its tone and the forward-lookingness settings of its statements for the global pandemic. Therefore, the longstanding association of the FED's tone and forward-lookingness with consumers’ inflation expectations index has weakened during the global health crisis.

Suggested Citation

  • Bilal Taskin & Fuat Akal, 2025. "Tales of Turbulence: BERT-based Multimodal Analysis of FED Communication Dynamics Amidst COVID-19 Through FOMC Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 65(1), pages 117-146, January.
    • Handle: RePEc:kap:compec:v:65:y:2025:i:1:d:10.1007_s10614-023-10533-w
    DOI: 10.1007/s10614-023-10533-w
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    References listed on IDEAS

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    1. Alan S. Blinder & Michael Ehrmann & Marcel Fratzscher & Jakob De Haan & David-Jan Jansen, 2008. "Central Bank Communication and Monetary Policy: A Survey of Theory and Evidence," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 910-945, December.
    2. Hansen, Stephen & McMahon, Michael, 2016. "Shocking language: Understanding the macroeconomic effects of central bank communication," Journal of International Economics, Elsevier, vol. 99(S1), pages 114-133.
    3. Omotosho, Babatunde S. & Tumala, Mohammed M., 2019. "A Text Mining Analysis of Central Bank Monetary Policy Communication in Nigeria," MPRA Paper 98850, University Library of Munich, Germany.
    4. Pekka Malo & Ankur Sinha & Pekka Korhonen & Jyrki Wallenius & Pyry Takala, 2014. "Good debt or bad debt: Detecting semantic orientations in economic texts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 782-796, April.
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    6. Alan S. Blinder & Michael Ehrmann & Marcel Fratzscher & Jakob De Haan & David-Jan Jansen, 2008. "Central Bank Communication and Monetary Policy: A Survey of Theory and Evidence," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 910-945, December.
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    More about this item

    Keywords

    Natural language processing; Semantic analysis; Central banking communication; COVID-19;
    All these keywords.

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • Y80 - Miscellaneous Categories - - Related Disciplines - - - Related Disciplines

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