IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2020-007.html
   My bibliography  Save this paper

How Do Member Countries Receive IMF Policy Advice: Results from a State-of-the-art Sentiment Index

Author

Listed:
  • Ms. Ghada Fayad
  • Chengyu Huang
  • Yoko Shibuya
  • Peng Zhao

Abstract

This paper applies state-of-the-art deep learning techniques to develop the first sentiment index measuring member countries’ reception of IMF policy advice at the time of Article IV Consultations. This paper finds that while authorities of member countries largely agree with Fund advice, there is variation across country size, external openness, policy sectors and their assessed riskiness, political systems, and commodity export intensity. The paper also looks at how sentiment changes during and after a financial arrangement or program with the Fund, as well as when a country receives IMF technical assistance. The results shed light on key aspects on Fund surveillance while redefining how the IMF can view its relevance, value added, and traction with its member countries.

Suggested Citation

  • Ms. Ghada Fayad & Chengyu Huang & Yoko Shibuya & Peng Zhao, 2020. "How Do Member Countries Receive IMF Policy Advice: Results from a State-of-the-art Sentiment Index," IMF Working Papers 2020/007, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2020/007
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=48937
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    2. Tamar Gutner & Alexander Thompson, 2010. "The politics of IO performance: A framework," The Review of International Organizations, Springer, vol. 5(3), pages 227-248, September.
    3. 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.
    4. 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.
    5. 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. Manuel Bétin & Umberto Collodel, 2021. "The Complex Crises Database: 70 Years of Macroeconomic Crises," PSE Working Papers halshs-03268889, HAL.

    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. 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.
    2. Gómez-Cram, Roberto & Grotteria, Marco, 2022. "Real-time price discovery via verbal communication: Method and application to Fedspeak," Journal of Financial Economics, Elsevier, vol. 143(3), pages 993-1025.
    3. 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).
    4. 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.
    5. 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).
    6. Pierre L. Siklos, 2013. "The Global Financial Crisis and the Language of Central Banking: Central Bank Guidance in Good Times and in Bad," CAMA Working Papers 2013-58, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Hüning, Hendrik, 2017. "Asset market response to monetary policy news from SNB press releases," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 160-177.
    8. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    9. Hüning, Hendrik, 2016. "Asset market response to monetary policy news from SNB press releases," HWWI Research Papers 177, Hamburg Institute of International Economics (HWWI).
    10. Fraccaroli, Nicolò & Giovannini, Alessandro & Jamet, Jean-François & Persson, Eric, 2022. "Ideology and monetary policy. The role of political parties’ stances in the European Central Bank’s parliamentary hearings," European Journal of Political Economy, Elsevier, vol. 74(C).
    11. 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.
    12. Sami Diaf & Jörg Döpke & Ulrich Fritsche & Ida Rockenbach, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Macroeconomics and Finance Series 202001, University of Hamburg, Department of Socioeconomics.
    13. Pastwa, Anna M. & Shrestha, Prabal & Thewissen, James & Torsin, Wouter, 2021. "Unpacking the black box of ICO white papers: a topic modeling approach," LIDAM Discussion Papers LFIN 2021018, Université catholique de Louvain, Louvain Finance (LFIN).
    14. Latifi, Albina & Naboka-Krell, Viktoriia & Tillmann, Peter & Winker, Peter, 2024. "Fiscal policy in the Bundestag: Textual analysis and macroeconomic effects," European Economic Review, Elsevier, vol. 168(C).
    15. 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.
    16. Necmettin Alpay Koçak, 2020. "The Role of Ecb Speeches in Nowcasting German Gdp," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2020(2), pages 05-20.
    17. Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022. "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, vol. 4(1), pages 17-61, March.
    18. 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.
    19. Martin Haselmayer & Marcelo Jenny, 2017. "Sentiment analysis of political communication: combining a dictionary approach with crowdcoding," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2623-2646, November.
    20. 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).

    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:imf:imfwpa:2020/007. 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: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.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.