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Regionale Konjunkturzyklen in Deutschland – Teil I: Die Datenlage

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  • Beate Schirwitz
  • Christian Seiler
  • Klaus Wohlrabe

    ()

Abstract

Die Analyse und Prognose regionaler Konjunkturzyklen gewinnt immer mehr an Bedeutung. Bisher liegt aber keine kohärente Beschreibung und Analyse regionaler Konjunkturzyklen für die 16 Bundesländer in Deutschland vor. In einer dreiteiligen Reihe im ifo Schnelldienst wird beschrieben, wie regionale Konjunkturzyklen in Deutschland definiert und datiert werden können, und untersucht, inwieweit die regionale Wirtschaftsentwicklung im Zeitablauf konvergiert. Der erste Beitrag in dieser Ausgabe beschreibt die Datenlage in den Bundesländern. Aufgrund fehlender Unterjährigkeit des Bruttoinlandsproduktes in den Bundesländern wird gezeigt, wie die monatlichen Umsätze im verarbeitenden Gewerbe näherungsweise als repräsentativ für den Konjunkturzyklus interpretiert werden können.

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Bibliographic Info

Article provided by Ifo Institute for Economic Research at the University of Munich in its journal ifo Schnelldienst.

Volume (Year): 62 (2009)
Issue (Month): 13 (07)
Pages: 18-24

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Handle: RePEc:ces:ifosdt:v:62:y:2009:i:13:p:18-24

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Keywords: Regionaler Konjunkturzyklus; Messung; Datenqualität; Deutschland;

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References

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  1. Wolfgang Nierhaus, 2007. "Vierteljährliche volkswirtschaftliche Gesamtrechnungen für Sachsen mit Hilfe temporaler Disaggregation," ifo Dresden berichtet, Ifo Institute for Economic Research at the University of Munich, Ifo Institute for Economic Research at the University of Munich, vol. 14(04), pages 24-36, 08.
  2. Christian Dreger & Konstantin A. Kholodilin, 2007. "Prognosen der regionalen Konjunkturentwicklung," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, DIW Berlin, German Institute for Economic Research, vol. 76(4), pages 47-55.
  3. Udo Ludwig, 2004. "IWH-Konjunkturbarometer," Wirtschaft im Wandel, Halle Institute for Economic Research, Halle Institute for Economic Research, vol. 10(16), pages 458-458.
  4. Konstantin A. Kholodilin & Stefan Kooths & Boriss Siliverstovs, 2008. "Konjunkturprognosen für Bundesländer setzen Verbesserung der Datensituation voraus," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 75(24), pages 318-325.
  5. Erich Langmantel, 1999. "Das ifo Geschäftsklima als Indikator für die Prognose des Bruttoinlandsprodukts," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 52(16-17), pages 16-21, October.
  6. Christian Seiler, 2009. "Prediction Qualities of the Ifo Indicators on a Temporal Disaggregated German GDP," Ifo Working Paper Series Ifo Working Paper No. 67, Ifo Institute for Economic Research at the University of Munich.
  7. Klaus Abberger & Wolfgang Nierhaus, 2008. "Die ifo Konjunkturuhr: Ein Präzisionswerk zur Analyse der Wirtschaft," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 61(23), pages 16-24, December.
  8. Harm Bandholz & Michael Funke, 2003. "Die Konstruktion und Schätzung eines Frühindikators für die Konjunkturentwicklung in der Freien und Hansestadt Hamburg," Quantitative Macroeconomics Working Papers, Hamburg University, Department of Economics 20305, Hamburg University, Department of Economics.
  9. Klaus Abberger & Wolfgang Nierhaus, 2008. "Die ifo Kapazitätsauslastung - ein gleichlaufender Indikator der deutschen Industriekonjunktur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 61(16), pages 15-23, 08.
  10. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November.
  11. Wolfgang Nierhaus, 2008. "Vierteljährliche Volkswirtschaftliche Gesamtrechnungen für Sachsen : Ergebnisse für das erste Quartal," ifo Dresden berichtet, Ifo Institute for Economic Research at the University of Munich, Ifo Institute for Economic Research at the University of Munich, vol. 15(04), pages 12-16, 08.
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Citations

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Cited by:
  1. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting GDP at the regional level with many predictors," ERSA conference papers ersa13p15, European Regional Science Association.
  2. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil II: Die Zyklendatierung," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, 07.
  3. Wenzel, Lars & Wolf, André, 2013. "Short-term forecasting with business surveys: Evidence for German IHK data at federal state level," HWWI Research Papers, Hamburg Institute of International Economics (HWWI) 140, Hamburg Institute of International Economics (HWWI).
  4. Jan Kluge, 2011. "Wachstum und Beschäftigung am Wirtschaftsstandort Dresden – Warum wächst Dresden langsamer als der Rest Sachsens?," ifo Dresden berichtet, Ifo Institute for Economic Research at the University of Munich, Ifo Institute for Economic Research at the University of Munich, vol. 18(05), pages 11-19, October.
  5. Jürgen Bierbaumer-Polly, 2012. "Regional Business Cycles in the Austrian Economy," WIFO Monatsberichte (monthly reports), WIFO, vol. 85(11), pages 833-848, November.
  6. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil III: Konvergenz," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(15), pages 23-32, 08.

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