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A comprehensive German business cycle chronology

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Abstract

Business cycle chronologies offer reference points for empirical studies used as benchmarks for business cycle and recession theory. A quasi-official chronology exists for the US economy, but not for most European countries, including Germany. While most papers dealing with business cycle dates rely on one specific method, I present and discuss a number of different dating approaches based on the classical business cycle. These are applied to German GDP data comprising 1970–2006. Finally, based on the results of the different methods, a consensus business cycle chronology for the German economy is suggested.

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References

  • Altissimo F, Bassanetti A, Cristadoro R et al (2001) A real time coincident indicator of the Euro area business cycle. CEPR Discussion Paper 3108

  • Altissimo F, Cristadoro R, Forni M et al (2006) New Eurocoin: tracking economic growth in real time. CEPR Discussion Paper 5633

  • Artis MJ, Kontolemis ZG, Osborn DR (1997) Business cycles for G7 and European countries. J Bus 70: 249–279

    Article  Google Scholar 

  • Artis MJ, Marcellino M, Proietti T (2004) Dating business cycles: a methodological contribution with an application to the Euro area. Oxf Bull Econ Stat 66: 537–565

    Article  Google Scholar 

  • Azuvedo JV, Koopman SJ, Rua A (2006) Tracking the business cycle of the Euro area: a multivariate model-based band-pass filter. J Bus Econ Stat 24: 278–290

    Article  Google Scholar 

  • Bengoechea P, Camacho M, Perez-Quiros G (2006) A useful tool for forecasting the Euro-area business cycle phases. Int J Forecast 22: 735–749

    Article  Google Scholar 

  • Boldin MD (1994) Dating turning points in the business cycle. J Bus 67: 97–131

    Article  Google Scholar 

  • Breunig R, Najarian S, Pagan A (2003) Specification testing of Markov switching models. Oxf Bull Econ Stat 65: 703–725

    Article  Google Scholar 

  • Bry G., Boschan C (1971) Cyclical analysis of time series: selected procedures and computer programs. National Bureau of Economic Research, New York

    Google Scholar 

  • Burns AF, Mitchell WC (1946) Measuring business cycles. National Bureau of Economic Research, New York

    Google Scholar 

  • Cooley TF, Prescott EC (1995) Economic growth and business cycles. In: Cooley TF, Prescott EC(eds) Frontiers of business cycle research. Princeton University Press, Princeton, pp 1–38

    Google Scholar 

  • Davies RB (1977) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 64: 247–254

    Article  Google Scholar 

  • Davies RB (1987) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 74: 33–43

    Google Scholar 

  • Denis C, McMorrow K, Röger W (2002) Production function approach to calculating potential growth and output gaps—estimates for the EU member States and the US. European Commission Economic Papers 176

  • Diebold FX, Rudebusch GD (1996) Measuring business cycles: a modern perspective. Rev Econ Stat 78: 67–77

    Article  Google Scholar 

  • Doornik JA (2002) Object-oriented matrix programming using Ox. http://www.doornik.com

  • Döpke J (2004) Real-time data and business cycle analysis in Germany. J Bus Cycle Meas Anal 1: 337–361

    Google Scholar 

  • Fritsche U, Kouzine V (2005) Prediction of business cycle turning points in Germany. Jahrb für Nationalökonomie und Stat 225: 22–43

    Google Scholar 

  • Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57: 357–384

    Article  Google Scholar 

  • Hamilton JD (2003) Comment on a comparison of two business cycle dating methods. J Econ Dyn Control 27: 1691–1693

    Article  Google Scholar 

  • Hamilton JD, Raj B (2002) New directions in business cycle research and financial analysis. Empir Econ 27: 149–162

    Article  Google Scholar 

  • Hansen BE (1992) The likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP. J Appl Econom 7: S61–82

    Article  Google Scholar 

  • Hansen BE (1996) Erratum: the likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP. J Appl Econom 11: 195–98

    Article  Google Scholar 

  • Harding D, Pagan A (2000) Knowing the cycle. In: Backhouse RE, Salanti A(eds) Macroeconomics in the real world. Oxford University Press, Oxford, pp 23–41

    Google Scholar 

  • Harding D, Pagan A (2002) Dissection the cycle: a methodological investigation. J Monet Econ 49: 365–381

    Article  Google Scholar 

  • Harding D, Pagan A (2003a) A comparison of two business cycle dating methods. J Econ Dyn Control 27: 1681–1690

    Article  Google Scholar 

  • Harding D, Pagan A (2003b) Rejoinder to James Hamilton. J Econ Dyn Control 27: 1695–1698

    Article  Google Scholar 

  • Harding D, Pagan A (2005) A suggested framework for classifying the modes of cycle research. J Appl Econom 20: 151–159

    Article  Google Scholar 

  • Harvey AC, Trimbur TM (2003) General model-based filters for extracting cycles and trends in economic time series. Rev Econ Stat 85: 244–255

    Article  Google Scholar 

  • Kholodilin KA (2005) Forecasting the turns of German business cycle: dynamic bi-factor model with Markov switching. Jahrb für Nationalökonomie und Stat 225: 653–674

    Google Scholar 

  • Kholodilin KA, Yao VW (2005) Measuring and predicting turning points using a dynamic bi-factor model. Int J Forecast 21: 525–537

    Article  Google Scholar 

  • Krolzig HM (1997) Markov-switching vector autoregressions: modelling, statistical inference, and application to business cycle analysis. Springer, Berlin

    Google Scholar 

  • Krolzig HM (2005) MSVAR package for Ox. http://www.krolzig.co.uk

  • Mariano RS, Murasawa Y (2003) A new coincident index of business cycles based on monthly and quarterly series. J Appl Econom 18: 427–443

    Article  Google Scholar 

  • Potter SM (1995) A nonlinear approach to US GNP. J Appl Econom 10: 109–125

    Article  Google Scholar 

  • Romer D (2006) Advanced macroeconomics, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  • Sichel DE (1994) Inventories and the three phases of the business cycle. J Bus Econ Stat 12: 269–77

    Article  Google Scholar 

  • Stock JH, Watson MW (1989) New indexes of coincident and leading economic indicators. In: Blanchard OJ, Fischer S(eds) NBER macroeconomics annual. MIT Press, Cambridge/London, pp 351–394

    Google Scholar 

  • Teräsvirta T, Anderson HM (1992) Characterizing nonlinearities in business cycles using smooth transition autoregressive models. J Appl Econom 7: 119–136

    Article  Google Scholar 

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Authors and Affiliations

  1. Ifo Institute for Economic Research, Einsteinstraße 3, 01069, Dresden, Germany

    Beate Schirwitz

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  1. Beate Schirwitz
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Correspondence to Beate Schirwitz.

Additional information

I gratefully acknowledge comments and suggestions from Klaus Wälde and two anonymous referees. I also benefited from comments by Klaus-Jürgen Gern and the participants of a workshop in Dresden and a seminar in Würzburg.

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Schirwitz, B. A comprehensive German business cycle chronology. Empir Econ 37, 287–301 (2009). https://doi.org/10.1007/s00181-008-0233-y

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  • DOI: https://doi.org/10.1007/s00181-008-0233-y

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