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

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  • 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
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    References listed on IDEAS

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    1. 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.
    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. Feinerer, Ingo & Hornik, Kurt & Meyer, David, 2008. "Text Mining Infrastructure in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i05).
    4. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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. 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.
    13. 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.
    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.
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    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

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