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Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit
[German Economy Spring 2018 - German economy closer to its limit]

Author

Listed:
  • Ademmer, Martin
  • Boysen-Hogrefe, Jens
  • Fiedler, Salomon
  • Groll, Dominik
  • Hauber, Philipp
  • Jannsen, Nils
  • Kooths, Stefan
  • Potjagailo, Galina

Abstract

Die Luft für den Aufschwung in Deutschland wird dünner. Nach dem kräftigen Anstieg von 2,2 Prozent im Jahr 2017 dürfte sich die gesamtwirtschaftliche Produktion weiter beschleunigen. Im laufenden Jahr wird das Bruttoinlandsprodukt wohl um 2,5 Prozent zulegen; für das kommende Jahr rechnen wir mit einem Anstieg um 2,3 Prozent. Bei bereits spürbar über normal ausgelasteten Kapazitäten driftet die deutsche Wirtschaft zusehends in die Hochkonjunktur. Besonders bemerkbar machen sich Kapazitätsengpässe bereits in der Bauwirtschaft. Dort schaffen es die Unternehmen offenbar kaum noch, die eingehenden Aufträge abzuarbeiten. Vor diesem Hintergrund dürfte die Bautätigkeit trotz der äußerst anregenden Rahmenbedingungen vorerst nur noch verhalten zulegen, dafür aber die Baupreise spürbar anziehen. Anspannungen machen sich zunehmend auch auf dem Arbeitsmarkt bemerkbar. Zwar dürfte die Beschäftigung vorerst noch weiter kräftig steigen, allerdings werden die zunehmenden Probleme der Unternehmen, geeignetes Fachpersonal zu finden, zu beschleunigt steigenden Effektivverdiensten führen. In der Folge werden die Bruttolöhne und -gehälter kräftig steigen und so den privaten Konsum stimulieren, der durch Abgabensenkungen und Leistungsausweitungen der neuen Bundesregierung zusätzlich angeregt wird. Wir rechnen damit, dass diese fiskalischen Maßnahmen zu großen Teilen ab dem Jahr 2019 wirksam werden und wesentlich dazu beitragen, dass die Nettolöhne und -gehälter mit einer Zuwachsrate von 5,4 Prozent so stark zulegen werden wie seit dem Jahr 1992 nicht mehr. Bei der zunehmenden Auslastung der Produktionskapazitäten dürften sich mehr und mehr Unternehmen dazu veranlasst sehen, ihre Kapazitäten zu erweitern, so dass auch die Unternehmensinvestitionen merklich anziehen werden. Trotz der im Koalitionsvertrag vereinbarten zusätzlichen Haushaltsbelastungen dürften die Budgetüberschüsse vorerst in der Tendenz weiter aufwärts gerichtet bleiben, da die hohe konjunkturelle Dynamik deutliche Einnahmezuwächse mit sich bringt.

Suggested Citation

  • Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2018. "Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit [German Economy Spring 2018 - German economy closer to its limit]," Kieler Konjunkturberichte 41, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwkkb:41
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    References listed on IDEAS

    as
    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Hinz, Julian, 2017. "Friendly fire: Zu den Handelsauswirkungen der Russlandsanktionen," Kiel Insight 2017.17, Kiel Institute for the World Economy (IfW Kiel).
    3. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    4. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    5. Jonas Dovern & Nils Jannsen, 2017. "Prognosen in verschiedenen Konjunkturphasen [Forecasts in Different Business Cycle States]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 97(7), pages 527-528, July.
    6. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    7. Blanchard, Oliver & Cerutti, Eugenio & SUmmers, Lawrence, 2015. "Inflation and Activity - Two Explorations and Their Monetary Policy Implications," Working Paper Series 15-070, Harvard University, John F. Kennedy School of Government.
    8. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
    9. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2013. "Pooling Versus Model Selection For Nowcasting Gdp With Many Predictors: Empirical Evidence For Six Industrialized Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 392-411, April.
    10. Gordon, Robert J, 1988. "The Role of Wages in the Inflation Process," American Economic Review, American Economic Association, vol. 78(2), pages 276-283, May.
    11. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
    12. Chih-Ping Chang & Kenneth M. Emery, 1996. "Do wages help predict inflation?," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q I, pages 2-9.
    13. Michael Biggs & Thomas Mayer & Andreas Pick, 2009. "Credit and economic recovery," DNB Working Papers 218, Netherlands Central Bank, Research Department.
    14. Carstensen, Kai & Wolters, Maik H., 2017. "Normaler Abschwung oder schwere Rezession? Ein neues Modell für die Prognose der Konjunkturphasen in Deutschland," Kiel Insight 2017.14, Kiel Institute for the World Economy (IfW Kiel).
    15. Dovern, Jonas & Jannsen, Nils, 2017. "Systematic errors in growth expectations over the business cycle," International Journal of Forecasting, Elsevier, vol. 33(4), pages 760-769.
    16. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
    17. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
    18. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    1. Fiedler, Salomon & Görg, Holger & Hornok, Cecília & Jannsen, Nils & Kooths, Stefan & Marchal, Léa & Potjagailo, Galina, 2018. "Direktinvestitionen im Ausland - Effekte auf die deutsche Leistungsbilanz und Spillovers in den Empfängerländern," Kieler Beiträge zur Wirtschaftspolitik 16, Kiel Institute for the World Economy (IfW Kiel).

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    More about this item

    Keywords

    Konsum; Prognosefehlerevaluierung; Konjunkturprognose; Stabilisierungspolitik; Frühindikatoren; Ausblick; Faktormodell;
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