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Quantitative Easing and Tapering Uncertainty: Evidence from Twitter

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  • Annette Meinusch
  • Peter Tillmann

Abstract

In this paper we analyze the extent to which people’s changing beliefs about the timing of the exit from Quantitative Easing (“tapering”) impact asset prices. To quantify beliefs of market participants, we use data from Twitter, the social media application. Our data set covers the entire Twitter volume on Federal Reserve tapering in 2013. Based on the time series of beliefs about an early or late tapering, we estimate a structural VAR-X model under appropriate sign restrictions on the impulse responses to identify a belief shock. The results show that shocks to tapering beliefs have non-negligible effects on interest rates and exchange rates. We also derive measures of monetary policy uncertainty and disagreement of beliefs, respectively, and estimate their impact. The paper is the first to use social media data for analyzing monetary policy and also adds to the rapidly growing literature on macroeconomic uncertainty shocks.

Suggested Citation

  • Annette Meinusch & Peter Tillmann, 2016. "Quantitative Easing and Tapering Uncertainty: Evidence from Twitter," Working Papers wp15, South East Asian Central Banks (SEACEN) Research and Training Centre.
    • Handle: RePEc:sea:wpaper:wp15
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    Cited by:

    1. PANAGIOTIS Anastasiadis & EFTHIMIOS Katsaros & ANASTASIOS-TAXIARCHIS KOUTSIOUKIS, 2020. "Performance-Risk Nexus Of Global Low-Rated Etfs During The Qe-Tapering Period," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 15(1), pages 194-211, April.
    2. Jochen Lüdering & Peter Tillmann, 2016. "Monetary Policy on Twitter and its Effect on Asset Prices: Evidence from Computational Text Analysis," MAGKS Papers on Economics 201612, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Ehrmann, Michael & Wabitsch, Alena, 2022. "Central bank communication with non-experts – A road to nowhere?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 69-85.
    4. 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).
    5. CĂLIN, Adrian Cantemir, 2015. "The Effects Of The Federal Reserve’S Tapering Announcements On The Us Real Estate Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(3), pages 79-90.
    6. Alexander Jung & Patrick Kuehl, 2021. "Can central bank communication help to stabilise inflation expectations?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 298-321, July.
    7. 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.
    8. Yılmaz, Emrah Sıtkı & Ozpolat, Aslı & Destek, Mehmet Akif, 2022. "Do Twitter Sentiments Really Effective on Energy Stocks? Evidence from Intercompany Dependency," MPRA Paper 114155, University Library of Munich, Germany.
    9. Koji Takahashi & Sumiko Takaoka, 2025. "Corporate Bond Purchase Program and Corporate Debt Issuance: Evidence from Japanese Corporate Bond Marketing News," IMES Discussion Paper Series 25-E-11, Institute for Monetary and Economic Studies, Bank of Japan.
    10. Michael Stiefel & Rémi Vivès, 2019. "'Whatever it Takes' to Change Belief: Evidence from Twitter," Working Papers halshs-02053429, HAL.
    11. Chen, Hongyi & Tillmann, Peter, 2025. "Monetary policy spillovers: Is this time different?," Journal of International Money and Finance, Elsevier, vol. 152(C).
    12. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
    13. 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.
    14. Michael Stiefel & Rémi Vivès, 2022. "‘Whatever it takes’ to change belief: evidence from Twitter," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(3), pages 715-747, August.
    15. Travis Adams & Andrea Ajello & Diego Silva & Francisco Vazquez-Grande, 2023. "More than Words: Twitter Chatter and Financial Market Sentiment," Papers 2305.16164, arXiv.org.
    16. Donato Masciandaro & Oana Peia & Davide Romelli, 2024. "Central bank communication and social media: From silence to Twitter," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 365-388, April.
    17. Leighton Vaughan Williams & J. James Reade, 2016. "Prediction Markets, Social Media and Information Efficiency," Kyklos, Wiley Blackwell, vol. 69(3), pages 518-556, August.
    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. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
    20. Andrea Ajello & Diego Silva & Travis Adams & Francisco Vazquez-Grande, 2023. "More than Words: Twitter Chatter and Financial Market Sentiment," Finance and Economics Discussion Series 2023-034, Board of Governors of the Federal Reserve System (U.S.).
    21. Lucian Liviu ALBU & Radu LUPU & Adrian Cantemir CĂLIN, 2016. "Quantitative Easing, Tapering And Stock Market Indices," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 5-23.
    22. Lüdering, Jochen & Tillmann, Peter, 2020. "Monetary policy on twitter and asset prices: Evidence from computational text analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    23. Annette Meinusch, 2017. "When the Fed sneezes - Spillovers from U.S. Monetary Policy to Emerging Markets," MAGKS Papers on Economics 201730, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

    More about this item

    Keywords

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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