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The Value of News

Author

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  • Vegard H. Larsen
  • Leif Anders Thorsrud

Abstract

We decompose a major business newspaper according to the topics it writes about, and show that the topics have predictive power for key economic variables and, especially noteworthy, for asset prices. Unexpected innovations to an aggregated news index, derived as a weighted average of the topics with the highest predictive scores, cause large and persistent economic fluctuations, a permanent increase in productivity, and are especially associated with financial markets, credit and borrowing. Unexpected innovations to asset prices, orthogonal to news shocks and labeled as noise, have only temporary positive effects.

Suggested Citation

  • Vegard H. Larsen & Leif Anders Thorsrud, 2015. "The Value of News," Working Papers No 6/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    • Handle: RePEc:bny:wpaper:0034
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    References listed on IDEAS

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    Cited by:

    1. Lüdering Jochen & Winker Peter, 2016. "Forward or Backward Looking? The Economic Discourse and the Observed Reality," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(4), pages 483-515, August.
    2. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
    3. Lino Wehrheim, 2019. "Economic history goes digital: topic modeling the Journal of Economic History," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 13(1), pages 83-125, January.
    4. David Lenz & Peter Winker, 2020. "Measuring the diffusion of innovations with paragraph vector topic models," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
    5. 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.
    6. Vegard Høghaug Larsen & Leif Anders Thorsrud, 2022. "Asset returns, news topics, and media effects," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(3), pages 838-868, July.
    7. Vegard Høghaug Larsen, 2021. "Components Of Uncertainty," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 769-788, May.
    8. 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.
    9. Vegard H�ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Lino Wehrheim, 2017. "Economic History Goes Digital: Topic Modeling the Journal of Economic History," Working Papers 177, Bavarian Graduate Program in Economics (BGPE).
    11. Grajzl, Peter & Murrell, Peter, 2019. "Toward understanding 17th century English culture: A structural topic model of Francis Bacon's ideas," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 111-135.
    12. 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.
    13. 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).
    14. Leif Anders Thorsrud, 2016. "Nowcasting using news topics Big Data versus big bank," Working Papers No 6/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Jan Kinne & David Lenz, 2021. "Predicting innovative firms using web mining and deep learning," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.

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    Keywords

    Machine learning; Latent Dirichlet Allocation (LDA); Bayesian Dynamic Threshold Model; Business Cycles;
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