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Predicting Peaks and Troughs in Real House Prices

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  • Linda Rousová

    (OECD)

  • Paul van den Noord

Abstract

OECD work prior to the financial crisis suggested that real prices in several housing markets had become vulnerable to a change in financial and economic conditions, with the risk of a subsequent downturn becoming increasingly possible, as proved to be the case. With corrections in many, but not all, housing markets having now occurred, and, in some countries, prices having rebounded rapidly in the low interest rate environment, the issue of whether prices are now close to another turning point is again of considerable policy interest. As a means of addressing this issue, probit models have been estimated to provide an indication of possible peaks and troughs in real house prices in 2011 and 2012, using data for 20 OECD countries. Predictions based on these models have been reported in OECD Economic Outlook, No. 89 and this paper provides information on the methodology underpinning these predictions. Comment prévoir les fluctuations des prix réels des logements ? Les travaux menés par l’OCDE avant la crise financière laissaient entendre que les prix réels sur plusieurs marchés du logement ne sauraient résister à une modification des conditions financières et économiques, alors que le risque que leur vulnérabilité n’entraîne une crise économique devenait de plus en plus probable, ainsi que les événements ultérieurs l’ont d’ailleurs démontré. Les prix s’étant désormais rétablis sur un grand nombre, bien que pas sur la totalité, des marchés du logement, et ayant même, dans certains pays, enregistré une remontée rapide favorisée par la faiblesse des taux d’intérêt, la question de savoir s’ils font aujourd’hui face à un nouveau changement de cap mobilise fortement l’intérêt des gouvernements. Pour tenter de répondre à cette question, des modèles probits, dont on estime qu’ils pourraient fournir une indication des fluctuations possibles des prix réels des logements en 2011 et 2012, ont été sollicités et utilisés avec des données concernant 20 pays de l’OCDE. Les prévisions établies sur la base de ces modèles ont été reproduites dans les Perspectives économiques de l'OCDE, n°89, et le présent document donne des informations sur la méthodologie employée à cet effet.

Suggested Citation

  • Linda Rousová & Paul van den Noord, 2011. "Predicting Peaks and Troughs in Real House Prices," OECD Economics Department Working Papers 882, OECD Publishing.
  • Handle: RePEc:oec:ecoaaa:882-en
    DOI: 10.1787/5kg89j38k17c-en
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    Citations

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    Cited by:

    1. Alexander N. Bogin & Stephen D. Bruestle & William M. Doerner, 2017. "How Low Can House Prices Go? Estimating a Conservative Lower Bound," The Journal of Real Estate Finance and Economics, Springer, vol. 54(1), pages 97-116, January.
    2. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
    3. Douglas Sutherland & Peter Hoeller & Rossana Merola & Volker Ziemann, 2012. "Debt and Macroeconomic Stability," OECD Economics Department Working Papers 1003, OECD Publishing.
    4. Bolt, W. & Demertzis, D. & Diks, C.G.H. & Van der Leij, M.J., 2011. "Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices," CeNDEF Working Papers 11-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    5. Douglas Sutherland & Peter Hoeller, 2012. "Debt and Macroeconomic Stability: An Overview of the Literature and Some Empirics," OECD Economics Department Working Papers 1006, OECD Publishing.
    6. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
    7. Helmut Herwartz & Konstantin A. Kholodilin, 2014. "In‐Sample and Out‐of‐Sample Prediction of stock Market Bubbles: Cross‐Sectional Evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 15-31, January.
    8. Bolt, W. & Demertzis, D. & Diks, C.G.H. & Van der Leij, M.J., 2011. "Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices," CeNDEF Working Papers 11-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    9. Konstantin A. Kholodilin & Andreas Mense, 2012. "Internet-Based Hedonic Indices of Rents and Prices for Flats: Example of Berlin," Discussion Papers of DIW Berlin 1191, DIW Berlin, German Institute for Economic Research.
    10. Czerniak, Adam & Borowski, Jakub & Boratyński, Jakub & Rosati, Dariusz, 2020. "Asset price bubbles in a monetary union: Mind the convergence gap," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 288-302.

    More about this item

    Keywords

    bulles immobilière; business cycles; cycle économique; house prices; housing bubbles; prix des logements;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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