IDEAS home Printed from https://ideas.repec.org/a/mnb/finrev/v24y2025i4p34-64.html

Which Text Method to Choose for Analysing Central Bank Communication? A Comparison of Artificial Intelligence and Previous Techniques

Author

Listed:
  • Zalan Kocsis

    (Magyar Nemzeti Bank)

  • Monika Matrai-Pitz

    (Magyar Nemzeti Bank)

Abstract

Our study compares the characteristics of text analysis methods on communications text samples of the US Federal Reserve and four Central and Eastern European central banks. Based on our results, methods based on BERT-type models are the most accurate at capturing the monetary policy, real economic and inflation information contained in central bank texts, outperforming OpenAI GPT-4.1 and GPT-5 models. BERT-type methods are faster than GPT models and can be run offline without a subscription, but their disadvantages are that the models require separate training, which entails hardware and labour costs, and that modifying the method is cumbersome. Conversely, GPT models are more flexible and have proven to be more accurate on new central bank samples. The dictionary-based methods used as benchmarks are significantly less accurate, but their use may be justified in certain cases due to their speed, cost-free operation and the transparency of the method.

Suggested Citation

  • Zalan Kocsis & Monika Matrai-Pitz, 2025. "Which Text Method to Choose for Analysing Central Bank Communication? A Comparison of Artificial Intelligence and Previous Techniques," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 24(4), pages 34-64.
  • Handle: RePEc:mnb:finrev:v:24:y:2025:i:4:p:34-64
    as

    Download full text from publisher

    File URL: https://hitelintezetiszemle.mnb.hu/sw/static/file/fer-24-4-st3-kocsis-matrai-pitz.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tatiana Evdokimova & Piroska Nagy Mohacsi & Olga Ponomarenko & Elina Ribakova, 2023. "Central banks and policy communication: How emerging markets have outperformed the Fed and ECB," Working Paper Series WP23-10, Peterson Institute for International Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
    2. 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.
    3. Claudia Voicila & Daniel Serbu, 2026. "A natural language processing toolbox for the National Bank of Romania," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Data science in central banking, volume 67, Bank for International Settlements.
    4. repec:osf:socarx:yrhka_v1 is not listed on IDEAS
    5. Shrimali, Suruchi & Ahmad, Wasim, 2025. "On the communication efforts of the central banks in emerging economies: The case of India," Emerging Markets Review, Elsevier, vol. 65(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mnb:finrev:v:24:y:2025:i:4:p:34-64. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Morvay Endre The email address of this maintainer does not seem to be valid anymore. Please ask Morvay Endre to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/mnbgvhu.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.