IDEAS home Printed from
   My bibliography  Save this paper

Common business and housing market cycles in the Euro area from a multivariate decomposition


  • Ferrara, L.
  • Koopman, S J.


The 2007 sub-prime crisis in the United States, prolonged by a severe economic recession spread over many countries around the world, has led many economic researchers to focus on the recent fluctuations in housing prices and their relationships with macroeconomics and monetary policies. The existence of common housing cycles among the countries of the euro zone could lead the European Central Bank to integrate more specifically the evolution of such asset prices in its assessment. In this paper, we implement a multivariate unobserved component model on housing market variables in order to assess the common euro area housing cycle and to evaluate its relationship with the economic cycle. Among the general class of multivariate unobserved component models, we implement the band-pass filter based on the trend plus cycle decomposition model and we allow the existence of two cycles of different periods. The dataset consists of gross domestic product and real house prices series for four main euro area countries (Germany, France, Italy and Spain). Empirical results show a strong relationship for business cycles in France, Italy and Spain. Moreover, French and Spanish house prices cycles appear to be strongly related, while the German one possesses its own dynamics. Finally, we find that GDP and house prices cycles are related in the medium-term for fluctuations between 4 and 8 years, while the housing market contributes to the long-term economic growth only in Spain and Germany.

Suggested Citation

  • Ferrara, L. & Koopman, S J., 2010. "Common business and housing market cycles in the Euro area from a multivariate decomposition," Working papers 275, Banque de France.
  • Handle: RePEc:bfr:banfra:275

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Álvarez, L-J. & Bulligan, G. & Cabrero, A. & Ferrara, L. & Stahl, H., 2009. "Housing cycles in the major euro area countries," Working papers 269, Banque de France.
    2. anonymous, 2009. "Monetary policy report to the Congress," Web Site 70, Board of Governors of the Federal Reserve System (U.S.).
    3. Pietro Catte & Nathalie Girouard & Robert W. R. Price & Christophe André, 2004. "Housing Markets, Wealth and the Business Cycle," OECD Economics Department Working Papers 394, OECD Publishing.
    4. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, September.
    5. Edward E. Leamer, 2007. "Housing is the business cycle," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 149-233.
    6. Rose Cunningham & Ilan Kolet, 2007. "Housing Market Cycles and Duration Dependence in the United States and Canada," Staff Working Papers 07-2, Bank of Canada.
    7. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.
    8. Siem Jan Koopman & João Valle E Azevedo, 2008. "Measuring Synchronization and Convergence of Business Cycles for the Euro area, UK and US," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 23-51, February.
    9. Mohamadou Fadiga & Yongsheng Wang, 2009. "A multivariate unobserved component analysis of US housing market," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(1), pages 13-26, January.
    10. Valle e Azevedo, Joao & Koopman, Siem Jan & Rua, Antonio, 2006. "Tracking the Business Cycle of the Euro Area: A Multivariate Model-Based Bandpass Filter," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 278-290, July.
    11. Claudio Borio & Patrick McGuire, 2004. "Twin peaks in equity and housing prices?," BIS Quarterly Review, Bank for International Settlements, March.
    12. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874, June.
    13. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    2. Aye, Goodness C. & Balcilar, Mehmet & Bosch, Adél & Gupta, Rangan, 2014. "Housing and the business cycle in South Africa," Journal of Policy Modeling, Elsevier, vol. 36(3), pages 471-491.
    3. International Monetary Fund, 2012. "Côte d’Ivoire; Joint Staff Advisory Note on the Progress Report of the Poverty Reduction Strategy Paper," IMF Staff Country Reports 12/184, International Monetary Fund.
    4. Christophe André, 2010. "A Bird's Eye View of OECD Housing Markets," OECD Economics Department Working Papers 746, OECD Publishing.
    5. Rangan Gupta & Christophe André & Luis Gil-Alana, 2015. "Comovement in Euro area housing prices: A fractional cointegration approach," Urban Studies, Urban Studies Journal Limited, vol. 52(16), pages 3123-3143, December.
    6. International Monetary Fund, 2013. "France; Financial Sector Assessment Program—Technical Note on Housing Prices and Financial Stability," IMF Staff Country Reports 13/184, International Monetary Fund.
    7. Ferrara, L. & Vigna, O., 2009. "Cyclical relationships between GDP and housing market in France: Facts and factors at play," Working papers 268, Banque de France.

    More about this item


    House prices; Business cycles; Euro area; Unobserved components model.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bfr:banfra:275. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael brassart). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.