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Business News and Business Cycles

Author

Listed:
  • Leland Bybee
  • Bryan T. Kelly
  • Asaf Manela
  • Dacheng Xiu

Abstract

We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984–2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and explains 25% of aggregate stock market returns. A text-augmented VAR demonstrates the large incremental role of news text in modeling macroeconomic dynamics. We use this model to retrieve the narratives that underlie business cycle fluctuations.

Suggested Citation

  • Leland Bybee & Bryan T. Kelly & Asaf Manela & Dacheng Xiu, 2021. "Business News and Business Cycles," NBER Working Papers 29344, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29344
    Note: AP EFG
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    Citations

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    Cited by:

    1. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2024. "Panel data nowcasting: The case of price–earnings ratios," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 292-307, March.
    2. Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
    3. Park, Kwangyong, 2023. "Do more frequent price adjustments guarantee less effective monetary stimulus when uncertainty rises?," Journal of Macroeconomics, Elsevier, vol. 78(C).
    4. Biktimirov, Ernest N. & Biktimirova, Liana E., 2023. "All topics are not created equal: Sentiment and hype of business media topics and the bitcoin market," Economics Letters, Elsevier, vol. 231(C).
    5. Massimiliano Marcellino & Dalibor Stevanovic, 2022. "The demand and supply of information about inflation," CIRANO Working Papers 2022s-27, CIRANO.
    6. Kenza Bousedra & Pierre Pelletier, 2024. "A Rule-Based Methodology for Company Identification: Application to the Downstream Space Sector," Papers 2412.02342, arXiv.org.
    7. Pablo Ottonello & Wenting Song, 2022. "Financial Intermediaries and the Macroeconomy: Evidence from a High-Frequency Identification," Staff Working Papers 22-24, Bank of Canada.
    8. Zheng, Tingguo & Fan, Xinyue & Jin, Wei & Fang, Kuangnan, 2024. "Words or numbers? Macroeconomic nowcasting with textual and macroeconomic data," International Journal of Forecasting, Elsevier, vol. 40(2), pages 746-761.
    9. Lin Chen & Stephanie Houle, 2023. "Turning Words into Numbers: Measuring News Media Coverage of Shortages," Discussion Papers 2023-8, Bank of Canada.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G0 - Financial Economics - - General

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