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

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  • Dieter Gerdesmeier
  • Andreja Lenarčič
  • Barbara Roffia

Abstract

This article develops a model-based method to detect booms and busts in the Euro area housing market. A model is constructed and tested, whereby the user cost rate, a demographic variable, unemployment rate, disposable income, debt-to-income ratio and housing stock are fundamental variables significantly explaining house price (HP) developments. Booms/busts are identified as episodes when the HP index exceeds the levels implied by those economic fundamentals. Furthermore, a cross-check with boom/bust episodes based on other methods is carried out to substantiate the results, while the ability of the model in predicting booms/busts in real time is also tested.

Suggested Citation

  • Dieter Gerdesmeier & Andreja Lenarčič & Barbara Roffia, 2015. "An alternative method for identifying booms and busts in the Euro area housing market," Applied Economics, Taylor & Francis Journals, vol. 47(5), pages 499-518, January.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:5:p:499-518
    DOI: 10.1080/00036846.2014.975328
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    2. Brian Micallef, 2016. "Property price misalignment with fundamentals in Malta," CBM Working Papers WP/03/2016, Central Bank of Malta.
    3. 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.
    4. 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.
    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. 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.
    8. Carlos Cañizares Martínez & Gabe J. de Bondt & Arne Gieseck, 2023. "Forecasting housing investment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 543-565, April.
    9. 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.
    10. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    11. 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.
    12. Lenarčič, Črt & Damjanović, Milan, 2015. "Slovene Residential Property Prices Misalignment with Fundamentals," MPRA Paper 101198, 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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    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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