IDEAS home Printed from https://ideas.repec.org/p/bis/biswps/1021.html
   My bibliography  Save this paper

Seeing the forest for the trees: Using hLDA models to evaluate communication in Banco Central do Brasil

Author

Listed:
  • Angelo M Fasolo
  • Flávia M Graminho
  • Saulo B Bastos

Abstract

Central bank communication is a key tool in managing inflation expectations. This paper proposes a hierarchical Latent Dirichlet Allocation (hLDA) model combined with feature selection techniques to allow an endogenous selection of topic structures associated with documents published by Banco Central do Brasil's Monetary Policy Committee (Copom). These computational linguistic techniques allow building measures of the content and tone of Copom's minutes and statements. The effects of the tone are measured in different dimensions such as inflation, inflation expectations, economic activity, and economic uncertainty. Beyond the impact on the economy, the hLDA model is used to evaluate the coherence between the statements and the minutes of Copom's meetings.

Suggested Citation

  • Angelo M Fasolo & Flávia M Graminho & Saulo B Bastos, 2022. "Seeing the forest for the trees: Using hLDA models to evaluate communication in Banco Central do Brasil," BIS Working Papers 1021, Bank for International Settlements.
    • Handle: RePEc:bis:biswps:1021
    as

    Download full text from publisher

    File URL: https://www.bis.org/publ/work1021.pdf
    File Function: Full PDF document
    Download Restriction: no
    File URL: https://www.bis.org/publ/work1021.htm
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jitmaneeroj, Boonlert & Lamla, Michael J. & Wood, Andrew, 2019. "The implications of central bank transparency for uncertainty and disagreement," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 222-240.
    2. Stephen Hansen & Michael McMahon, 2016. "Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication," NBER Chapters, in: NBER International Seminar on Macroeconomics 2015, National Bureau of Economic Research, Inc.
    3. repec:hal:spmain:info:hdl:2441/7mota32nad8aopst8f7d5aebpo is not listed on IDEAS
    4. Scott Hendry, 2012. "Central Bank Communication or the Media’s Interpretation: What Moves Markets?," Staff Working Papers 12-9, Bank of Canada.
    5. Stephen Hansen & Michael McMahon & Andrea Prat, 2018. "Transparency and Deliberation Within the FOMC: A Computational Linguistics Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(2), pages 801-870.
    6. Swanson, Eric T., 2006. "Have Increases in Federal Reserve Transparency Improved Private Sector Interest Rate Forecasts?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(3), pages 791-819, April.
    7. Scott Hendry & Alison Madeley, 2010. "Text Mining and the Information Content of Bank of Canada Communications," Staff Working Papers 10-31, Bank of Canada.
    8. Rosa, Carlo & Verga, Giovanni, 2007. "On the consistency and effectiveness of central bank communication: Evidence from the ECB," European Journal of Political Economy, Elsevier, vol. 23(1), pages 146-175, March.
    9. Paul Hubert & Fabien Labondance, 2016. "Central Bank Sentiment and Policy Expectations," SciencePo Working papers Main hal-03459227, HAL.
    10. G. C. Montes & L. V. Oliveira & A. Curi & R. T. F. Nicolay, 2016. "Effects of transparency, monetary policy signalling and clarity of central bank communication on disagreement about inflation expectations," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 590-607, February.
    11. repec:hal:spmain:info:hdl:2441/64veevce0i99oav223j3pkv1hf is not listed on IDEAS
    12. Ricardo Correa & Keshav Garud & Juan M Londono & Nathan Mislang, 2021. "Sentiment in Central Banks’ Financial Stability Reports," Review of Finance, European Finance Association, vol. 25(1), pages 85-120.
    13. David O. Lucca & Francesco Trebbi, 2009. "Measuring Central Bank Communication: An Automated Approach with Application to FOMC Statements," NBER Working Papers 15367, National Bureau of Economic Research, Inc.
    14. Neuenkirch, Matthias, 2012. "Managing financial market expectations: The role of central bank transparency and central bank communication," European Journal of Political Economy, Elsevier, vol. 28(1), pages 1-13.
    15. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    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. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2021. "Monetary policy and financial markets: evidence from Twitter traffic," BAFFI CAREFIN Working Papers 21160, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. Lin, Jianhao & Mei, Ziwei & Chen, Liangyuan & Zhu, Chuanqi, 2023. "Is the People's Bank of China consistent in words and deeds?," China Economic Review, Elsevier, vol. 78(C).
    3. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2021. "Monetary policy, Twitter and financial markets: evidence from social media traffic," BAFFI CAREFIN Working Papers 21160, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    4. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2020. "Tweeting on Monetary Policy and Market Sentiments: The Central Bank Surprise Index," BAFFI CAREFIN Working Papers 20134, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    5. Stephen Hansen & Michael McMahon, 2016. "Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication," NBER Chapters, in: NBER International Seminar on Macroeconomics 2015, National Bureau of Economic Research, Inc.
    6. Donato Masciandaro & Oana Peia & Davide Romelli, 2024. "Central bank communication and social media: From silence to Twitter," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 365-388, April.
    7. Baranowski, Pawel & Bennani, Hamza & Doryń, Wirginia, 2021. "Do the ECB's introductory statements help predict monetary policy? Evidence from a tone analysis," European Journal of Political Economy, Elsevier, vol. 66(C).
    8. Istrefi, Klodiana & Odendahl, Florens & Sestieri, Giulia, 2023. "Fed communication on financial stability concerns and monetary policy decisions: Revelations from speeches," Journal of Banking & Finance, Elsevier, vol. 151(C).
    9. Kawamura, Kohei & Kobashi, Yohei & Shizume, Masato & Ueda, Kozo, 2019. "Strategic central bank communication: Discourse analysis of the Bank of Japan’s Monthly Report," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 230-250.
    10. Yusuke Oshima & Yoichi Matsubayashi, 2018. "Monetary Policy Communication of the Bank of Japan: Computational Text Analysis," Discussion Papers 1816, Graduate School of Economics, Kobe University.
    11. Magdalena Szyszko & Aleksandra Rutkowska, 2022. "Do words transform into actions? The consistency of central banks’ communications and decisions," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(1), pages 31-49, March.
    12. Parle, Conor, 2022. "The financial market impact of ECB monetary policy press conferences — A text based approach," European Journal of Political Economy, Elsevier, vol. 74(C).
    13. Jochen Lüdering & Peter Tillmann, 2016. "Monetary Policy on Twitter and its Effect on Asset Prices: Evidence from Computational Text Analysis," MAGKS Papers on Economics 201612, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. Szyszko, Magdalena & Rutkowska, Aleksandra & Kliber, Agata, 2022. "Do words affect expectations? The effect of central banks communication on consumer inflation expectations," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 221-229.
    15. David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015. "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, April.
    16. Aakriti Mathur & Rajeswari Sengupta, 2019. "Analysing monetary policy statements of the Reserve Bank of India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-012, Indira Gandhi Institute of Development Research, Mumbai, India.
    17. Paul Hubert & Fabien Labondance, 2019. "Central bank tone and the dispersion of views within monetary policy committees," SciencePo Working papers Main hal-03403256, HAL.
    18. Curti, Filippo & Kazinnik, Sophia, 2023. "Central bank communication and website characteristics," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 1216-1241.
    19. Justyna Klejdysz & Robin L. Lumsdaine, 2023. "Shifts in ECB Communication: A Textual Analysis of the Press Conference," International Journal of Central Banking, International Journal of Central Banking, vol. 19(2), pages 473-542, June.
    20. André Binette & Dmitri Tchebotarev, 2019. "Canada’s Monetary Policy Report: If Text Could Speak, What Would It Say?," Staff Analytical Notes 2019-5, Bank of Canada.

    More about this item

    Keywords

    communication; monetary policy; latent dirichlet allocation; Brazil; Central Bank;
    All these keywords.

    JEL classification:

    • E02 - Macroeconomics and Monetary Economics - - General - - - Institutions and the Macroeconomy
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bis:biswps:1021. 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: Martin Fessler (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.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.