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"I heard the News today, oh Boy": An updated Version of our Uncertainty Perception Indicator (UPI) – and some general thoughts on news-based economic indicators

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  • Müller, Henrik
  • Hornig, Nico

Abstract

News-based indicators are in vogue in economics. But they tend to be applied with little consideration for the properties of news itself. In this paper, we try to shed light on the nature of this type of data. Drawing from established findings in communication science and journalism studies we argue that news-based indicators should be taken with a pinch of salt, since news is a somewhat biased representation of political and social reality. Contrary to economics and other social sciences, journalism tends to be driven by outliers, the outrageous, and the outraged. This structural dissonance between journalism and other disciplines needs to be born in mind when dealing with news content as data, and it is of particular concern in the context of economic developments. While economics and statistics are inherently backward looking, trying to make sense of the (immediate) past using models and probability distributions derived from bygone observations, journalism is about the present, and sometimes about the future. What’s going on right now? And where does it lead us? Seeking answers to these questions makes news a valuable data input, as a measure of what drives society at a given point in time. We show how taking the properties of news into consideration influences the entire process of large-scale news analysis. As an example, we update our Uncertainty Perception Indicator (Müller and Hornig 2020), setting it on a firmer footing by enlarging the newspaper corpus considerably. The new version of the UPI for Germany yields some remarkable results. At the trough of the Covid-19-induced economic crisis in Q2 of 2020, the overall indicator already decreased considerably, although it stayed at elevated levels. Deconstructing the UPI by applying the topic modelling approach Latent Dirichlet Allocation (LDA), shows that the coverage of the pandemic has merged with the issue of climate change and its mitigation. In the past decade or so incalculable politics was the main driver of economic uncertainty perception. Now truly exogenous developments, neither elicited by the economy nor by politics, come to the fore, adding to the sense of an inherently unstable world.

Suggested Citation

  • Müller, Henrik & Hornig, Nico, 2020. ""I heard the News today, oh Boy": An updated Version of our Uncertainty Perception Indicator (UPI) – and some general thoughts on news-based economic indicators," DoCMA Working Papers 2-2020, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    • Handle: RePEc:zbw:docmaw:22020
    DOI: 10.17877/DE290R-21669
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    References listed on IDEAS

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    1. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    2. Dirk Ulbricht & Konstantin A. Kholodilin & Tobias Thomas, 2017. "Do Media Data Help to Predict German Industrial Production?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 483-496, August.
    3. Kholodilin, Konstantin & Kolmer, Christian & Thomas, Tobias & Ulbricht, Dirk, 2015. "Asymmetric perceptions of the economy: Media, firms, consumers, and experts," DICE Discussion Papers 188, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    4. Robert J. Shiller, 2017. "Narrative Economics," American Economic Review, American Economic Association, vol. 107(4), pages 967-1004, April.
    5. Anthony Downs, 1957. "An Economic Theory of Political Action in a Democracy," Journal of Political Economy, University of Chicago Press, vol. 65(2), pages 135-135.
    6. 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.
    7. Müller, Henrik & Hornig, Nico, 2020. "Expecting the Unexpected: A new Uncertainty Perception Indicator (UPI) – concept and first results," DoCMA Working Papers 1-2020, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    8. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2020. "The Tail That Wags the Economy: Beliefs and Persistent Stagnation," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2839-2879.
    9. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    10. Patrick Bolton & Morgan Despres & Luiz Awazu Pereira da Silva & Frédéric Samama & Romain Svartzman, 2020. "The green swan," BIS Books, Bank for International Settlements, number 31.
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    Cited by:

    1. Brandt, Richard, 2021. "Economic Policy Uncertainty Index: Extension and optimization of Scott R. Baker, Nicholas Bloom and Steven J. Davis's search term," DoCMA Working Papers 5, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    2. Müller, Henrik & Hornig, Nico & Rieger, Jonas, 2021. ""For the times they are a-changin": Gauging Uncertainty Perception over Time," DoCMA Working Papers 3, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).

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    Keywords

    uncertainty; economic policy; business cycles; Covid-19; Latent Dirichlet Allocation;
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