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L volution des cr dits l habitat en France : une grille d analyse en termes de cycles

Author

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  • Kierzenkowski, R.
  • Oung, V.

Abstract

This article puts forward a framework based primarily on probabilistic tools to analyse the nature of housing loan cycles in France. The continued high growth rate of housing loans may indeed raise concerns as to the duration and determinants of the cycle which currently prevails. The results obtained suggest that the current cycle is actually exceptional in many respects. One the one hand, it is the longest housing loans cycle observed over the last thirty years, while its occurrence appears to be structurally decoupled with several indicators of the real economy. On the other hand, this cycle may also be related to the existence of an excess supply regime, which could prove an important explanatory factor of a decoupling with the real economy.

Suggested Citation

  • Kierzenkowski, R. & Oung, V., 2007. "L volution des cr dits l habitat en France : une grille d analyse en termes de cycles," Working papers 172, Banque de France.
    • Handle: RePEc:bfr:banfra:172
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    1. Lown, Cara & Morgan, Donald P., 2006. "The Credit Cycle and the Business Cycle: New Findings Using the Loan Officer Opinion Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1575-1597, September.
    2. Avouyi-Dovi, S. & Matheron, J., 2003. "Interactions between business cycles, stock market cycles and interest rates: the stylised facts," Financial Stability Review, Banque de France, issue 3, pages 80-99, November.
    3. Artis, Michael & Marcellino, Massimiliano & Proietti, Tommaso, 2004. "Characterizing the Business Cycle for Accession Countries," CEPR Discussion Papers 4457, C.E.P.R. Discussion Papers.
    4. Éric Heyer & Xavier Timbeau, 2006. "Immobilier et politique monétaire," Revue de l'OFCE, Presses de Sciences-Po, vol. 96(1), pages 115-151.
    5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    6. Hurlin, Christophe & Kierzenkowski, Rafal, 2007. "Credit market disequilibrium in Poland: Can we find what we expect?: Non-stationarity and the short-side rule," Economic Systems, Elsevier, vol. 31(2), pages 157-183, June.
    7. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    8. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, vol. 85(Mar), pages 47-61.
    9. G. B. Gorton & Ping He, 2008. "Bank Credit Cycles," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(4), pages 1181-1214.
    10. Giovanni Dell'Ariccia & Robert Marquez, 2006. "Lending Booms and Lending Standards," Journal of Finance, American Finance Association, vol. 61(5), pages 2511-2546, October.
    11. Hamilton, James D., 2003. "Comment on "A comparison of two business cycle dating methods"," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1691-1693, July.
    12. Atanasova Christina, 2003. "Credit Market Imperfections and Business Cycle Dynamics: A Nonlinear Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-22, December.
    13. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-1030, November.
    14. Nathalie Girouard & Mike Kennedy & Paul van den Noord & Christophe André, 2006. "Recent House Price Developments: The Role of Fundamentals," OECD Economics Department Working Papers 475, OECD Publishing.
    15. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 47-75.
    16. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    17. Hans-Martin Krolzig, 2000. "Predicting Markov-Switching Vector Autoregressive Processes," Economics Series Working Papers 2000-W31, University of Oxford, Department of Economics.
    18. Mark W. French, 2001. "Estimating changes in trend growth of total factor productivity: Kalman and H-P filters versus a Markov-switching framework," Finance and Economics Discussion Series 2001-44, Board of Governors of the Federal Reserve System (U.S.).
    19. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    20. Nathan S. Balke, 2000. "Credit and Economic Activity: Credit Regimes and Nonlinear Propagation of Shocks," The Review of Economics and Statistics, MIT Press, vol. 82(2), pages 344-349, May.
    21. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
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    More about this item

    Keywords

    Credit cycle ; Band-pass filters ; Markov Switching; Disequilibrium.;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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