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L’évolution des crédits à l’habitat en France : une grille d’analyse en termes de cycles

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  • Kierzenkowski, R.
  • Oung, V.
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    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.

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    File URL: http://www.banque-france.fr/uploads/tx_bdfdocumentstravail/ner172.pdf
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    Bibliographic Info

    Paper provided by Banque de France in its series Working papers with number 172.

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    Length: 47 pages
    Date of creation: 2007
    Date of revision:
    Handle: RePEc:bfr:banfra:172

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    Postal: Banque de France 31 Rue Croix des Petits Champs LABOLOG - 49-1404 75049 PARIS
    Web page: http://www.banque-france.fr/
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    Related research

    Keywords: Credit cycle ; Band-pass filters ; Markov Switching; Disequilibrium.;

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    2. Artis, Michael J & Marcellino, Massimiliano & Proietti, Tommaso, 2004. "Characterizing the Business Cycle for Accession Countries," CEPR Discussion Papers 4457, C.E.P.R. Discussion Papers.
    3. 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.
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    8. G. B. Gorton & Ping He, 2008. "Bank Credit Cycles," Review of Economic Studies, Oxford University Press, vol. 75(4), pages 1181-1214.
    9. 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.
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    13. Hans-Martin Krolzig, 2000. "Predicting Markov-Switching Vector Autoregressive Processes," Economics Series Working Papers 2000-W31, University of Oxford, Department of Economics.
    14. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-30, November.
    15. 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.
    16. 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.
    17. 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.).
    18. 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 C47-C75.
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