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Prognosen der regionalen Konjunkturentwicklung

Author

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  • Christian Dreger
  • Konstantin A. Kholodilin

Abstract

Prognosen der konjunkturellen Entwicklung in Deutschland beziehen sich zumeist auf die nationale Ebene. Die Ergebnisse sind jedoch nicht ohne Weiteres auf die regionalen Verhältnisse übertragbar. Ein wichtiger Grund dafür ist, dass die Branchenstrukturen der Regionen mehr oder weniger stark von derjenigen des gesamten Landes abweichen. In diesem Wochenbericht wird ein Verfahren zur Prognose der regionalen Wirtschaftsentwicklung für die einzelnen Bundesländer vorgestellt. Zum einen werden die Ergebnisse der nationalen Konjunkturprognose, zum anderen regionenspezifische Indikatoren herangezogen. Das Verfahren erlaubt eine empirisch fundierte Vorhersage der wirtschaftlichen Entwicklung in den einzelnen Bundesländern für das laufende und das folgende Jahr. Die Methode wird hier exemplarisch auf das Land Berlin angewandt. Danach wird die gesamtwirtschaftliche Produktion in Berlin 2006 und 2007 zwar schwächer expandieren als in Deutschland insgesamt, die jahrelange Phase der Schrumpfung setzt sich aber nicht mehr fort.

Suggested Citation

  • Christian Dreger & Konstantin A. Kholodilin, 2006. "Prognosen der regionalen Konjunkturentwicklung," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 73(34), pages 469-474.
  • Handle: RePEc:diw:diwwob:73-34-1
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    References listed on IDEAS

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    1. Marcellino, Massimiliano & Banerjee, Anindya & Masten, Igor, 2005. "Forecasting macroeconomic variables for the new member states of the European Union," Working Paper Series 482, European Central Bank.
    2. Tommaso Proietti, 2006. "Temporal disaggregation by state space methods: Dynamic regression methods revisited," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 357-372, November.
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    Cited by:

    1. Wenzel, Lars, 2013. "Forecasting regional growth in Germany: A panel approach using business survey data," HWWI Research Papers 133, Hamburg Institute of International Economics (HWWI).
    2. Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, May.
    3. Robert Lehmann & Klaus Wohlrabe, 2014. "Forecasting gross value-added at the regional level: are sectoral disaggregated predictions superior to direct ones?," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 34(1), pages 61-90, February.
    4. Joachim Ragnitz & Stefan Arent & Wolfgang Nierhaus & Beate Schirwitz & Johannes Steinbrecher & Gerit Vogt & Björn Ziegenbalg, 2010. "Methodenexpertise zur Analyse der Auswirkungen der internationalen Finanz- und Wirtschaftskrise auf die Wirtschaft im Land Brandenburg : Gutachten im Auftrag des Ministeriums für Wirtschaft des Landes," ifo Dresden Studien, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 53, October.
    5. Wenzel, Lars & Wolf, André, 2013. "Short-term forecasting with business surveys: Evidence for German IHK data at federal state level," HWWI Research Papers 140, Hamburg Institute of International Economics (HWWI).
    6. Rüdiger Hamm, 2011. "Creative Class as a Determinant of Economic Development - Empirical Considerations for Northrhine-Westphalian Regions based on Time-Series Analysis," ERSA conference papers ersa11p828, European Regional Science Association.
    7. Konstantin Arkadievich Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2008. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(2), pages 195-207.
    8. Robert Lehmann & Klaus Wohlrabe, 2012. "Die Prognose des Bruttoinlandsprodukts auf regionaler Ebene," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(21), pages 17-23, November.
    9. Robert Lehmann & Klaus Wohlrabe, 2014. "Regional economic forecasting: state-of-the-art methodology and future challenges," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 218-231.
    10. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland - Teil I: Die Datenlage," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(13), pages 18-24, July.

    More about this item

    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
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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