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"We're rolling". Our Uncertainty Perception Indicator (UPI) in Q4 2020: introducing RollingLDA, a new method for the measurement of evolving economic narratives

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  • Müller, Henrik
  • Rieger, Jonas
  • Hornig, Nico

Abstract

In this paper, we present a new dynamic topic modeling method to build stable models and consistent time series. We call this new method RollingLDA. It has the potential to overcome several difficulties researchers, who use unsupervised probabilistic topic models, have grappled with: namely the problem of arbitrary selection, which is aggravated when models are to be updated with new sequences of data. RollingLDA is derived by combining the LDAPrototype approach (Rieger, Jentsch and Rahnenführer, 2020) with an implementation that uses preceding LDA results as an initialization for subsequent quarters, while allowing topics to change over time. Squaring dual-process theory, employed in Behavioral Economics (Kahneman, 2011), with the evolving theory of Economic Narratives (Shiller, 2017), RollingLDA is applied to the measurement of economic uncertainty. The new version of our Uncertainty Perception Indicator (UPI), based on a newspaper corpus of 2.8 million German newspaper articles, published between 1 January 2001 and 31 December 2020, proves indeed capable of detecting an uncertainty narrative. The narrative, derived from the thorough quantitative-qualitative analysis of a key-topic of our model, can be interpreted as collective memory of past uncertainty shocks, their causes and the societal reactions to them. The uncertainty narrative can be seen as a collective intangible cultural asset (Haskel and Westlake, 2017), accumulated in the past, informing the present and potentially the future, as the story is being updated and partly overwritten by new experiences. This concept opens up a fascinating new field for future research. We would like to encourage researchers to use our data and are happy to share it on request.

Suggested Citation

  • Müller, Henrik & Rieger, Jonas & Hornig, Nico, 2021. ""We're rolling". Our Uncertainty Perception Indicator (UPI) in Q4 2020: introducing RollingLDA, a new method for the measurement of evolving economic narratives," DoCMA Working Papers 6, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
  • Handle: RePEc:zbw:docmaw:6
    DOI: 10.17877/DE290R-21974
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    References listed on IDEAS

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    1. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    2. N/A, 2011. "The UK economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 218(1), pages 3-3, October.
    3. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    4. N/A, 2011. "The UK economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 216(1), pages 3-3, April.
    5. 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).
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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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    Keywords

    Uncertainty; Narratives; Latent Dirichlet Allocation; Business Cycles; Covid-19; Text Mining; Computational Methods; Behavioral Economics;
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