IDEAS home Printed from https://ideas.repec.org/a/vls/finstu/v25y2021i1p6-29.html
   My bibliography  Save this article

The Impacts Of Speeches On Nowcasting Gdp: A Case Study On Euro Area Markets

Author

Listed:
  • KOCAK, Necmettin Alpay

    (Department of Economics and Administrative Sciences, Hacettepe University, Ankara, Turkey)

Abstract

The use of speech data in nowcasting models is a new topic while the use of sentiment and emotion indicators from microblogs and internet platforms in nowcasting models has been discussed in the literature. The effect of the speech data of European Central Bank’s (ECB) officials on nowcasting Euro Area GDP is investigated in this paper. After performing a detailed descriptive analysis of the speech data, five emotion indicators are obtained as a result of the emotion analysis. The contribution of these emotion indicators is examined to a nowcasting model including indicators from the real sector and household/business surveys related to the Euro Area for the period of 1995:01-2019:12. The effects of emotion indicators on model are analysed root mean squared error (RMSE), impulse-response functions, variance decomposition analysis and revision analysis. Findings show that emotion indicators provide a decrease in RMSE of nowcasting model. It is found out that the shocks in the emotion indicators are significant on the GDP in the long term, and the emotion indicators are effective in explaining the variance of the forecast error variance of GDP. Revision analysis indicates that emotion indicators do not increase the revision of GDP nowcasts. As a result, it can be claimed that the emotion indicators obtained from the speeches of ECB officials have a noticeable effect on the nowcasting the Euro Area GDP.

Suggested Citation

  • KOCAK, Necmettin Alpay, 2021. "The Impacts Of Speeches On Nowcasting Gdp: A Case Study On Euro Area Markets," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 25(1), pages 6-29, March.
    • Handle: RePEc:vls:finstu:v:25:y:2021:i:1:p:6-29
    as

    Download full text from publisher

    File URL: http://www.icfm.ro/RePEc/vls/vls_pdf/vol25i1p6-29.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    2. Hatice Burcu Eskici & Necmettin Alpay Kocak, 2018. "A text mining application on monthly price developments reports," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(2), pages 51-60.
    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. Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading the Newspapers," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 17-33.
    5. 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.
    6. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
    7. Feinerer, Ingo & Hornik, Kurt & Meyer, David, 2008. "Text Mining Infrastructure in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i05).
    8. 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.
    9. Marta Bańbura & Michele Modugno, 2014. "Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 133-160, January.
    10. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    11. James H. James & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," Working Papers 2005-2, Princeton University. Economics Department..
    12. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    13. Raïsa Basselier & David de Antonio Liedo & Geert Langenus,, 2017. "Nowcasting real economic activity in the euro area : Assessing the impact of qualitative surveys," Working Paper Research 331, National Bank of Belgium.
    14. 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.
    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. 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.
    2. 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.
    3. Gardner, Ben & Scotti, Chiara & Vega, Clara, 2022. "Words speak as loudly as actions: Central bank communication and the response of equity prices to macroeconomic announcements," Journal of Econometrics, Elsevier, vol. 231(2), pages 387-409.
    4. 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).
    5. 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.
    6. Schmeling, Maik & Wagner, Christian, 2019. "Does Central Bank Tone Move Asset Prices?," CEPR Discussion Papers 13490, C.E.P.R. Discussion Papers.
    7. Bennani, Hamza, 2019. "Does People's Bank of China communication matter? Evidence from stock market reaction," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
    8. 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).
    9. Bennett Schmanski & Chiara Scotti & Clara Vega, 2023. "Fed Communication, News, Twitter, and Echo Chambers," Finance and Economics Discussion Series 2023-036, Board of Governors of the Federal Reserve System (U.S.).
    10. 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.
    11. 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.
    12. Fulop, Andras & Kocsis, Zalan, 2023. "News indices on country fundamentals," Journal of Banking & Finance, Elsevier, vol. 154(C).
    13. Mario Gonzalez & Raul Cruz Tadle, 2021. "Monetary Policy Press Releases: An International Comparison," Working Papers Central Bank of Chile 912, Central Bank of Chile.
    14. Bennani, Hamza, 2018. "Media coverage and ECB policy-making: Evidence from an augmented Taylor rule," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 26-38.
    15. 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).
    16. Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
    17. Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
    18. 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.
    19. An, Suwei, 2023. "Essays on incentive contracts, M&As, and firm risk," Other publications TiSEM dd97d2f5-1c9d-47c5-ba62-f, Tilburg University, School of Economics and Management.
    20. Chris Florakis & Christodoulos Louca & Roni Michaely & Michael Weber, 2020. "Cybersecurity Risk," Working Papers 2020-178, Becker Friedman Institute for Research In Economics.

    More about this item

    Keywords

    Emotion analysis; ECB speeches; Nowcasting; Euro Area;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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:vls:finstu:v:25:y:2021:i:1:p:6-29. 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: Daniel Mateescu (email available below). General contact details of provider: https://edirc.repec.org/data/cfiarro.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.