IDEAS home Printed from https://ideas.repec.org/p/yon/wpaper/2018rwp-132.html
   My bibliography  Save this paper

Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea

Author

Listed:
  • Youngjoon Lee

    (Yonsei University)

  • Soohyon Kim

    (Bank of Korea)

  • Ki Young Park

    (Yonsei University)

Abstract

We quantify the Monetary Policy Committee (MPC) minutes of the Bank of Korea (BOK) using text mining approach. We propose a novel approach using a field-specific Korean dictionary and contiguous sequence of words (n-grams) to better capture the subtlety of central bank communication. We find that our lexicon-based indicators help explain the current and future BOK monetary policy decisions when considering an augmented Taylor rule, suggesting that they contain additional information beyond the currently available macroeconomic variables. Our indicators remarkably outper- form English-based textual classifications, a media-based measure of economic policy uncertainty, and a data-based measure of macroeconomic uncertainty. Our empirical re- sults also emphasize the importance of using a field-specific dictionary and the original Korean text.

Suggested Citation

  • Youngjoon Lee & Soohyon Kim & Ki Young Park, 2018. "Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea," Working papers 2018rwp-132, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2018rwp-132
    as

    Download full text from publisher

    File URL: http://121.254.254.220/repec/yon/wpaper/2018rwp-132.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nyman, Rickard & Kapadia, Sujit & Tuckett, David, 2021. "News and narratives in financial systems: Exploiting big data for systemic risk assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    2. Picault, Matthieu & Renault, Thomas, 2017. "Words are not all created equal: A new measure of ECB communication," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 136-156.
    3. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.
    4. 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.
    5. 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.
    6. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    7. Mark Gertler & Peter Karadi, 2015. "Monetary Policy Surprises, Credit Costs, and Economic Activity," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 44-76, January.
    8. Annette Meinusch & Peter Tillmann, 2017. "Quantitative Easing and Tapering Uncertainty: Evidence from Twitter," International Journal of Central Banking, International Journal of Central Banking, vol. 13(4), pages 227-258, December.
    9. Jegadeesh, Narasimhan & Wu, Di, 2013. "Word power: A new approach for content analysis," Journal of Financial Economics, Elsevier, vol. 110(3), pages 712-729.
    10. Soderlind, Paul & Svensson, Lars, 1997. "New techniques to extract market expectations from financial instruments," Journal of Monetary Economics, Elsevier, vol. 40(2), pages 383-429, October.
    11. Bholat, David & Brookes, James & Cai, Chris & Grundy, Katy & Lund, Jakob, 2017. "Sending firm messages: text mining letters from PRA supervisors to banks and building societies they regulate," Bank of England working papers 688, Bank of England.
    12. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    13. McLaren, Nick & Shanbhogue, Rachana, 2011. "Using internet search data as economic indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 134-140.
    14. Apel Mikael & Grimaldi Marianna Blix, 2014. "How Informative Are Central Bank Minutes?," Review of Economics, De Gruyter, vol. 65(1), pages 53-76, April.
    15. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    16. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    17. Matthieu Picault & Thomas Renault, 2017. "Words are not all created equal: A new measure of ECB communication," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205121, HAL.
    18. Benjamin Born & Michael Ehrmann & Marcel Fratzscher, 2014. "Central Bank Communication on Financial Stability," Economic Journal, Royal Economic Society, vol. 124(577), pages 701-734, June.
    19. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    20. Hamza Bennani & Matthias Neuenkirch, 2017. "The (home) bias of European central bankers: new evidence based on speeches," Applied Economics, Taylor & Francis Journals, vol. 49(11), pages 1114-1131, March.
    21. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mario Gonzalez and Raul Cruz Tadle & Raul Cruz Tadle, 2022. "Monetary policy press releases: an international comparison," BIS Working Papers 1023, Bank for International Settlements.
    2. Mario Gonzalez & Raul Cruz Tadle, 2021. "Monetary Policy Press Releases: An International Comparison," Working Papers Central Bank of Chile 912, Central Bank of Chile.

    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. Young Joon Lee & Soohyon Kim & Ki Young Park, 2019. "Deciphering Monetary Policy Board Minutes with Text Mining: The Case of South Korea," Korean Economic Review, Korean Economic Association, vol. 35, pages 471-511.
    2. Fulop, Andras & Kocsis, Zalan, 2023. "News indices on country fundamentals," Journal of Banking & Finance, Elsevier, vol. 154(C).
    3. repec:hal:spmain:info:hdl:2441/3mgbd73vkp9f9oje7utooe7vpg is not listed on IDEAS
    4. Martin Baumgaertner & Johannes Zahner, 2021. "Whatever it takes to understand a central banker - Embedding their words using neural networks," MAGKS Papers on Economics 202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Mikael Apel & Marianna Blix Grimaldi & Isaiah Hull, 2022. "How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC's Minutes and Transcripts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1459-1490, August.
    6. Paul Hubert & Fabien Labondance, 2019. "Central bank tone and the dispersion of views within monetary policy committees," Sciences Po publications 2019 – 08, Sciences Po.
    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. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
    9. 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).
    10. repec:hal:spmain:info:hdl:2441/7v8fvu0bf08jcoi4epn8cutjm8 is not listed on IDEAS
    11. 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.
    12. Firrell, Alastair & Reinold, Kate, 2020. "Uncertainty and voting on the Bank of England’s Monetary Policy Committee," Bank of England working papers 898, Bank of England.
    13. 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.
    14. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    15. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    16. Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
    17. Nicolò Fraccaroli & Alessandro Giovannini & Jean-François Jamet & Eric Persson, 2023. "Central Banks in Parliaments: A Text Analysis of the Parliamentary Hearings of the Bank of England, the European Central Bank, and the Federal Reserve," International Journal of Central Banking, International Journal of Central Banking, vol. 19(2), pages 543-600, June.
    18. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
    19. Bohl, Martin T. & Kanelis, Dimitrios & Siklos, Pierre L., 2023. "Central bank mandates: How differences can influence the content and tone of central bank communication," Journal of International Money and Finance, Elsevier, vol. 130(C).
    20. Baumgärtner, Martin & Zahner, Johannes, 2023. "Whatever it takes to understand a central banker: Embedding their words using neural networks," IMFS Working Paper Series 194, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    21. Niţoi, Mihai & Pochea, Maria-Miruna & Radu, Ştefan-Constantin, 2023. "Unveiling the sentiment behind central bank narratives: A novel deep learning index," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    22. 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).

    More about this item

    Keywords

    monetary policy; text mining; central banking; Bank of Korea; Taylor rule;
    All these keywords.

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • 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

    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:yon:wpaper:2018rwp-132. 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: YERI (email available below). General contact details of provider: https://edirc.repec.org/data/eryonkr.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.