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A latent weekly GDP indicator for Germany

Author

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  • Eraslan, Sercan
  • Reif, Magnus

Abstract

This paper introduces a weekly GDP indicator to track real economic activity in Germany in real-time. We use a mixed-frequency dynamic factor model with quarterly, monthly, and weekly indicators and obtain the weekly GDP indicator as the weighted common component of the mixed-frequency dataset. Our indicator is able to approximate latent week-on-week growth of German GDP. In addition, it enables computing a weekly GDP series in levels, which is also of great interest for central bankers, policy makers, and practitioners interested in analysing the current state of the economy in a timely manner. Finally, we demonstrate the benefits of our indicator for high-frequency tracking of the German economy using a recursive nowcasting exercise.

Suggested Citation

  • Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubtps:283352
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    References listed on IDEAS

    as
    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    3. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    4. Ferrara, Laurent & Mogliani, Matteo & Sahuc, Jean-Guillaume, 2022. "High-frequency monitoring of growth at risk," International Journal of Forecasting, Elsevier, vol. 38(2), pages 582-595.
    5. Daniel Ollech & Deutsche Bundesbank, 2023. "Economic analysis using higher-frequency time series: challenges for seasonal adjustment," Empirical Economics, Springer, vol. 64(3), pages 1375-1398, March.
    6. Robert Lehmann & Magnus Reif, 2021. "Predicting the German Economy: Headline Survey Indices Under Test," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 215-232, November.
    7. Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2022. "Measuring real activity using a weekly economic index," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 667-687, June.
    8. Eraslan, Sercan & Götz, Thomas, 2021. "An unconventional weekly economic activity index for Germany," Economics Letters, Elsevier, vol. 204(C).
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Business cycle; dynamic factor model; economic indicator;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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