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Quarterly GDP Estimates for the German States

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  • Lehmann, Robert
  • Wikman, Ida

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 2020, thereby improving the regional datbase in 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 find large heterogeneities in the duration and amplitudes of state-specific business cycles as well as in the degrees of cyclical concordance.

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  • Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:112642
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    Cited by:

    1. Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
    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 & 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.
    5. 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.
    6. 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 vectorautoregression; 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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