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An alternative method for identifying booms and busts in the euro area housing market

Author

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  • Gerdesmeier, Dieter
  • Roffia, Barbara
  • Lenarčič, Andreja

Abstract

The main aim of this paper is to apply a method based on fundamentals ─ which has already been applied in the stock market analysis ─ to detect boom/bust in the housing market, with a focus on the euro area. In this context, an underlying model is developed and tested. It turns out that the user cost rate, a demographic variable, the unemployment rate, disposable income (or disposable income per capita), the debt-to-income ratio and, finally, the housing stock are fundamental variables which significantly explain house price developments. Booms and busts are then selected as episodes when the house price index deviates excessively from the levels which would be implied by these economic fundamentals. In addition, a cross-check of the boom/bust episodes based on this method and other statistical and fundamental ones is carried out in order to substantiate the results obtained. Finally, money and credit aggregates are included in the specifications and are found to be useful in explaining boom/busts cycles in house prices. JEL Classification: E37, E44, E51

Suggested Citation

  • Gerdesmeier, Dieter & Roffia, Barbara & Lenarčič, Andreja, 2012. "An alternative method for identifying booms and busts in the euro area housing market," Working Paper Series 1493, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20121493
    Note: 190719
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    References listed on IDEAS

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    2. Bengtsson, Elias & Grothe, Magdalena & Lepers, Etienne, 2020. "Home, safe home: Cross-country monitoring framework for vulnerabilities in the residential real estate sector," Journal of Banking & Finance, Elsevier, vol. 112(C).
    3. Brian Micallef, 2016. "Property price misalignment with fundamentals in Malta," CBM Working Papers WP/03/2016, Central Bank of Malta.
    4. Stijn Ferrari & Mara Pirovano, 2014. "Evaluating early warning indicators for real estate related risks," Financial Stability Review, National Bank of Belgium, vol. 12(1), pages 123-140, June.
    5. Martin Schneider, 2013. "Are Recent Increases of Residential Property Prices in Vienna and Austria Justified by Fundamentals?," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 29-46.
    6. Akcay, Belgin & Yucel, Eray, 2014. "Unveiling the House Price Movements and Financial Development," MPRA Paper 59377, University Library of Munich, Germany, revised 19 Oct 2014.
    7. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    8. John Cotter & Stuart Gabriel & Richard Roll, 2015. "Can Housing Risk Be Diversified? A Cautionary Tale from the Housing Boom and Bust," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 913-936.
    9. Stijn Ferrari & Mara Pirovano & Wanda Cornacchia, 2015. "Identifying early warning indicators for real estate-related banking crises," ESRB Occasional Paper Series 08, European Systemic Risk Board.
    10. Lenarčič, Črt & Damjanović, Milan, 2015. "Slovene Residential Property Prices Misalignment with Fundamentals," MPRA Paper 101198, University Library of Munich, Germany.
    11. Kajuth, Florian & Knetsch, Thomas A. & Pinkwart, Nicolas, 2013. "Assessing house prices in Germany: Evidence from an estimated stock-flow model using regional data," Discussion Papers 46/2013, Deutsche Bundesbank.
    12. Dreger, Christian & Gerdesmeier, Dieter & Roffia, Barbara, 2020. "The impact of credit for house price overvaluations in the euro area: Evidence from threshold models," MPRA Paper 99523, University Library of Munich, Germany.
    13. Le Roux, Julien & Roma, Moreno, 2019. "Accuracy and determinants of self-assessed euro area house prices," Working Paper Series 2328, European Central Bank.

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    More about this item

    Keywords

    booms; busts; house prices; monetary and credit aggregates; quantile regressions;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • 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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