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Media reports as an economic activity indicator

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  • Jan Grossarth-Maticek
  • Johannes Mayr

Abstract

The study examines the extent to which media reports on economic activity can themselves serve as economic indicators alongside the classical monthly business indicators, such as the Ifo Business Climate Index, industrial production or incoming orders in manufacturing. The study generated indicators on the basis of media reports and analysed their quality as forecasting instruments of economic activity. A comparison with the Ifo Business Climate Index shows that the indicators based on media reports indeed display forecasting qualities for real macroeconomic developments.

Suggested Citation

  • 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.
    • Handle: RePEc:ces:ifosdt:v:61:y:2008:i:07:p:17-29
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    References listed on IDEAS

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    1. Fritsche Ulrich & Stephan Sabine, 2002. "Leading Indicators of German Business Cycles. An Assessment of Properties / Frühindikatoren der deutschen Konjunktur. Eine Beurteilung ihrer Eigenschaften," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(3), pages 289-315, June.
    2. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    3. Kholodilin Konstantin Arkadievich & Siliverstovs Boriss, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(3), pages 234-259, June.
    4. Fritsche Ulrich & Kuzin Vladimir, 2005. "Prediction of Business Cycle Turning Points in Germany / Prognose konjunktureller Wendepunkte in Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(1), pages 22-43, February.
    5. Klaus Abberger & Klaus Wohlrabe, 2006. "Forecasting qualities of the Ifo Business Climate Index - a look at recent studies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
    6. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, April.
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    Citations

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    Cited by:

    1. Benjamin Beckers & Konstantin A. Kholodilin & Dirk Ulbricht, 2017. "Reading between the Lines: Using Media to Improve German Inflation Forecasts," Discussion Papers of DIW Berlin 1665, DIW Berlin, German Institute for Economic Research.
    2. Petar Soric & Ivana Lolic, 2017. "Economic uncertainty and its impact on the Croatian economy," Public Sector Economics, Institute of Public Finance, vol. 41(4), pages 443-477.
    3. Čižmešija Mirjana & Sorić Petar & Lolić Ivana, 2017. "The interrelationship between media reports and the recession in Croatia," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 3(1), pages 16-34, June.
    4. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    5. 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.
    6. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    7. 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).

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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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