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The investment narrative: Improving private investment forecasts with media data

Author

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  • Blagov, Boris
  • Müller, Henrik
  • Jentsch, Carsten
  • Schmidt, Torsten

Abstract

Corporate investment in Germany has been relatively weak for a prolonged period after the financial crisis. This was remarkable given that interest rates and overall economic activity, important determinants of corporate investment, developed quite favourably during that time. These developments highlight the fact that the dynamics of business cycles varies over time: each cycle is somewhat different. A promising new line of research to identify the driving factors of business cycles is the use of narratives (Shiller 2017, 2020). Widely shared stories capture expectations and beliefs about the workings of the economy that may influence economic behavior, such as investment decisions. In this paper, we use Latent Dirichlet Allocation (LDA) to identify topics from news (text) data related to corporate investment in Germany and to construct suitable indicators. Furthermore, we focus on isolating those investment narratives that show the potential to lead to substantial improvement of the forecasting performance of econometric models. In our analysis, we demonstrate the benefit of using media-based indicators to improve econometric forecasts of business equipment investment. Newspaper data carries important information both on the future developments of investment (forecasting) as well as on current developments (nowcasting). Moreover, the identified investment narrative enables the researcher to improve her/his understanding of the investment process in general and allows to incorporate exogenous developments as well as economic sentiment, news and other relevant events to the analysis.

Suggested Citation

  • Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021. "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:921
    DOI: 10.4419/96973067
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    References listed on IDEAS

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    8. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
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    10. Döhrn, Roland & Barabas, György & Blagov, Boris & Fuest, Angela & Jäger, Philipp & Jessen, Robin & Micheli, Martin & Rujin, Svetlana, 2018. "Die wirtschaftliche Entwicklung im Inland: Aufschwung setzt sich fort, Gefährdungen nehmen zu," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 69(3), pages 21-56.
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    Cited by:

    1. Müller, Henrik & Schmidt, Tobias & Rieger, Jonas & Hufnagel, Lena Marie & Hornig, Nico, 2022. "A German inflation narrative. How the media frame price dynamics: Results from a RollingLDA analysis," DoCMA Working Papers 9, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    2. Dorine Boumans & Henrik Müller & Stefan Sauer, 2022. "How Media Content Influences Economic Expectations: Evidence from a Global Expert Survey," ifo Working Paper Series 380, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

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    More about this item

    Keywords

    narrative economics; mixed-frequency; nowcasting via media data;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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