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The ECB's tracker: nowcasting the press conferences of the ECB

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  • Marozzi, Armando

Abstract

This paper proposes an econometric framework for nowcasting the monetary policy stance and decisions of the European Central Bank (ECB) exploiting the ow of conventional and textual data that become available between two consecutive press conferences. Decompositions of the updated nowcasts into variables' marginal contribution are also provided to shed light on the main drivers of the ECB's reaction function at every point in time. In out-of-sample nowcasting experiments, the model provides an accurate tracking of the ECB monetary policy stance and decisions. The inclusion of textual variables contributes significantly to the gradual improvement of the model performance. JEL Classification: E37, E47, E52

Suggested Citation

  • Marozzi, Armando, 2021. "The ECB's tracker: nowcasting the press conferences of the ECB," Working Paper Series 2609, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20212609
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    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp2609~e49d2ad922.en.pdf
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    References listed on IDEAS

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    1. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    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. 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.
    4. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
    5. Jing Cynthia Wu & Fan Dora Xia, 2016. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
    6. Jan-Egbert Sturm & Jakob Haan, 2011. "Does central bank communication really lead to better forecasts of policy decisions? New evidence based on a Taylor rule model for the ECB," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 147(1), pages 41-58, April.
    7. 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.
    8. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    9. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    10. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
    11. Janko Gorter & Jan Jacobs & Jakob De Haan, 2008. "Taylor Rules for the ECB using Expectations Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 110(3), pages 473-488, September.
    12. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    13. Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
    14. Leif Anders Thorsrud, 2020. "Words are the New Numbers: A Newsy Coincident Index of the Business Cycle," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 393-409, April.
    15. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    16. Armando Marozzi, 2021. "The ECB and the Cost of Independence. Unearthing a New Doom-Loop in the European Monetary Union," BAFFI CAREFIN Working Papers 21152, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    17. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    18. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
    19. Dustin S. Stoltz & Marshall A. Taylor, 2019. "Concept Mover’s Distance: measuring concept engagement via word embeddings in texts," Journal of Computational Social Science, Springer, vol. 2(2), pages 293-313, July.
    20. 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.
    21. Adam Hale Shapiro & Daniel J Wilson, 2022. "Taking the Fed at its Word: A New Approach to Estimating Central Bank Objectives using Text Analysis [Inflation Targeting Does Not Anchor Inflation Expectations: Evidence from Firms in New Zealand]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(5), pages 2768-2805.
    22. Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
    23. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    24. Armando Marozzi, 2021. "The ECB and the Cost of Independence. Unearthing a New Doom-Loop in the European Monetary Union," BAFFI CAREFIN Working Papers 21152, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    25. 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.
    26. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
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    More about this item

    Keywords

    dynamic factor model; forecasting; monetary policy; natural language processing;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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