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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
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    References listed on IDEAS

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    1. Paul Hubert & Fabien Labondance, 2016. "Central Bank Sentiment and Policy Expectations," SciencePo Working papers Main hal-03459227, HAL.
    2. 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.
    3. 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.
    4. 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.
    5. repec:hal:spmain:info:hdl:2441/64veevce0i99oav223j3pkv1hf is not listed on IDEAS
    6. repec:hal:spmain:info:hdl:2441/7mota32nad8aopst8f7d5aebpo is not listed on IDEAS
    7. 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.
    8. 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.
    9. Scott Hendry, 2012. "Central Bank Communication or the Media’s Interpretation: What Moves Markets?," Staff Working Papers 12-9, Bank of Canada.
    10. 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.
    11. 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.
    12. Scott Hendry & Alison Madeley, 2010. "Text Mining and the Information Content of Bank of Canada Communications," Staff Working Papers 10-31, Bank of Canada.
    13. 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.
    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)

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    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

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