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Asymmetric Perceptions of the Economy: Media, Firms, Consumers, and Experts

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Listed:
  • Konstantin A. Kholodilin
  • Christian Kolmer
  • Tobias Thomas
  • Dirk Ulbricht

Abstract

This article sheds light on the interaction of media, economic actors, and economic experts. Based on a unique data set of 86,000 news items rated by professional analysts of Media Tenor International and survey data, we first analyze the overall tone of the media, consumers’, firms’, and economic experts’ opinions on the state and outlook of the economy. Second, we assess the protagonist’s ability at correctly predicting GDP. Third, we use Granger causality tests to uncover who is influencing whom when it comes to the formation of opinions on the economy. We find that media reports have a significant negative bias. The economic sentiment of the media, consumers and firms does not reflect the actual situation. Finally, we find that media sentiment is not influenced by any other actor. In contrast, media appear to affect all other actors.

Suggested Citation

  • Konstantin A. Kholodilin & Christian Kolmer & Tobias Thomas & Dirk Ulbricht, 2015. "Asymmetric Perceptions of the Economy: Media, Firms, Consumers, and Experts," Discussion Papers of DIW Berlin 1490, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1490
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    References listed on IDEAS

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    1. Jan Grossarth-Maticek & Johannes Mayr, 2008. "Media reports as an economic activity indicator," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(07), pages 17-29, April.
    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. Bernhardt, Dan & Krasa, Stefan & Polborn, Mattias, 2008. "Political polarization and the electoral effects of media bias," Journal of Public Economics, Elsevier, vol. 92(5-6), pages 1092-1104, June.
    4. Tim Groseclose & Jeffrey Milyo, 2005. "A Measure of Media Bias," The Quarterly Journal of Economics, Oxford University Press, vol. 120(4), pages 1191-1237.
    5. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    6. Klaus Abberger, 2007. "Forecasting Quarter-on-Quarter Changes of German GDP with Monthly Business Tendency Survey Results," ifo Working Paper Series 40, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Justus Haucap & Tobias Thomas & Gert G. Wagner, 2015. "Zu wenig Einfluss des ökonomischen Sachverstands? Empirische Befunde zum Einfluss von Ökonomen und anderen Wissenschaftlern auf die Wirtschaftspolitik," Discussion Papers of DIW Berlin 1449, DIW Berlin, German Institute for Economic Research.
    8. Schröder, Michael & Hüfner, Felix P., 2002. "Forecasting economic activity in Germany: how useful are sentiment indicators?," ZEW Discussion Papers 02-56, ZEW - Leibniz Centre for European Economic Research.
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    Cited by:

    1. Ralf Dewenter & Ulrich Heimeshoff & Tobias Thomas, 2016. "Media Coverage and Car Manufacturers' Sales," Economics Bulletin, AccessEcon, vol. 36(2), pages 976-982.
    2. 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).
    3. Céline Bonnet & Jan Philip Schain, 2020. "An Empirical Analysis Of Mergers: Efficiency Gains And Impact On Consumer Prices," Journal of Competition Law and Economics, Oxford University Press, vol. 16(1), pages 1-35.
    4. 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).

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    More about this item

    Keywords

    media bias; consensus forecasts; consumer and business sentiment;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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