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Prognosen des Wirtschaftswachstums der deutschen Bundesländer unter Echtzeitbedingungen

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  • Robert Lehmann

Abstract

Die Beurteilung der Prognosegüte von diversen Konjunkturindikatoren und Prognosemodellen für die praktische Prognosearbeit sollte immer unter realistischen Bedingungen erfolgen. Hierfür benötigt es insbesondere Echtzeitdaten für die zu prognostizierenden Größen wie dem preisbereinigten Bruttoinlandsprodukt einer Region. Echtzeitdaten für die Volkswirtschaftlichen Gesamtrechnungen der Länder sind jedoch derzeit nicht verfügbar. Der vorliegende Artikel stellt einen neuen Echtzeitdatensatz vor und führt ein Prognoseexperiment für das Wirtschaftswachstum aller 16 Bundesländer simultan durch. Das hier verwendete Prognosemodell liefert recht treffsichere Vorhersagen und könnte damit auch in der praktischen Prognosearbeit zur Anwendung kommen.

Suggested Citation

  • Robert Lehmann, 2024. "Prognosen des Wirtschaftswachstums der deutschen Bundesländer unter Echtzeitbedingungen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 31(04), pages 03-07, August.
    • Handle: RePEc:ces:ifodre:v:31:y:2024:i:04:p:03-07
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    References listed on IDEAS

    as
    1. João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
    2. 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.
    3. Lehmann Robert & Wohlrabe Klaus, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, De Gruyter, vol. 16(2), pages 226-254, May.
    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. Bokun, Kathryn O. & Jackson, Laura E. & Kliesen, Kevin L. & Owyang, Michael T., 2023. "FRED-SD: A real-time database for state-level data with forecasting applications," International Journal of Forecasting, Elsevier, vol. 39(1), pages 279-297.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
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    More about this item

    Keywords

    Wirtschaftsentwicklung; Wirtschaftswachstum; Datenerhebung; Erhebungstechnik; Deutschland;
    All these keywords.

    JEL classification:

    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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