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Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics

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  • Robert Lehmann
  • Ida Wikman

Abstract

To date, only annual information on economic activity is published for the 16 German states. In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to 2021, thereby improving the regional database for Germany. The new data set will regularly be updated when quarterly economic growth for Germany becomes available. We use the new data for an in-depth business cycle analysis and to estimate long-run growth dynamics. The business cycle analysis reveals large heterogeneities in the duration and amplitudes of state-specific fluctuations as well as in the degrees of cyclical concordance. Long-run trends are found to vary tremendously, with positive developments in economically strong regions and flat or even negative trends for economically much weaker states.

Suggested Citation

  • Robert Lehmann & Ida Wikman, 2023. "Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics," CESifo Working Paper Series 10280, CESifo.
    • Handle: RePEc:ces:ceswps:_10280
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    Cited by:

    1. Robert Lehmann & Sascha Möhrle, 2024. "Forecasting regional industrial production with novel high‐frequency electricity consumption data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1918-1935, September.
    2. Blagov, Boris & Schmidt, Torsten C., 2022. "Schätzung der Wirtschaftsentwicklung in NRW im dritten Quartal 2022: Ein Mixed-Frequency-Ansatz," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 73(4), pages 53-59.
    3. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    4. Robert Lehmann, 2024. "A real-time regional accounts database for Germany with applications to GDP revisions and nowcasting," Empirical Economics, Springer, vol. 67(2), pages 817-838, August.
    5. Robert Lehmann & Stefan Sauer & Klaus Wohlrabe & Timo Wollmershäuser, 2022. "Gesamtwirtschafliche ifo Kapazitätsauslastungen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 29(03), pages 19-25, June.
    6. Robert Lehmann & Ida Wikman, 2023. "Eine Analyse der Konjunkturzyklen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 30(02), pages 15-21, April.
    7. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.

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    More about this item

    Keywords

    regional economic activity; mixed-frequency Vector Autoregression; regional business cycles; concordance; Bayesian methods;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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