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An early warning system to predict the speculative house price bubbles

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  • Dreger, Christian
  • Kholodilin, Konstantin A.

Abstract

In this paper, the authors construct country-specific chronologies of house price bubbles for 12 OECD countries over the period 1969:Q1-2009:Q4. These chronologies are obtained using a combination of fundamental and filter approaches. The resulting speculative bubble chronology is the one providing the highest concordance between these two techniques. In addition, the authors suggest an early warning system based on three alternative approaches: signaling approach, logit, and probit models. It is shown that the latter two models allow much more accurate predictions of house price bubbles than the signaling approach. The prediction accuracy of the logit and probit models is high enough to make them useful in forecasting the future speculative bubbles in the housing market. Thus, this method can be used by policymakers in their attempts to timely detect house price bubbles and to attenuate their devastating effects on the domestic and world economy.

Suggested Citation

  • Dreger, Christian & Kholodilin, Konstantin A., 2012. "An early warning system to predict the speculative house price bubbles," Economics Discussion Papers 2012-44, Kiel Institute for the World Economy (IfW Kiel).
  • Handle: RePEc:zbw:ifwedp:201244
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    Cited by:

    1. Hans-Eggert Reimers, 2012. "Early Warning Indicator Model of Financial Developments Using an Ordered Logit," Business and Economic Research, Macrothink Institute, vol. 2(2), pages 171-191, December.
    2. Lenarčič, Črt & Zorko, Robert & Herman, Uroš & Savšek, Simon, 2016. "A Primer on Slovene House Prices Forecast," MPRA Paper 103552, University Library of Munich, Germany.
    3. Kholodilin, Konstantin A. & Michelsen, Claus & Ulbricht, Dirk, 2018. "Speculative price bubbles in urban housing markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 55(4), pages 1957-1983.
    4. Brian Micallef, 2016. "Property price misalignment with fundamentals in Malta," CBM Working Papers WP/03/2016, Central Bank of Malta.
    5. 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.
    6. André, Christophe & Caraiani, Petre & Călin, Adrian Cantemir & Gupta, Rangan, 2022. "Can monetary policy lean against housing bubbles?," Economic Modelling, Elsevier, vol. 110(C).
    7. Janusz Sobieraj & Dominik Metelski, 2021. "Testing Housing Markets for Episodes of Exuberance: Evidence from Different Polish Cities," JRFM, MDPI, vol. 14(9), pages 1-29, September.
    8. Marsay, David, 2016. "Decision-making under radical uncertainty: An interpretation of Keynes' treatise," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-31.
    9. López-Laborda, Julio & Peña, Guillermo, 2017. "Does financial VAT affect the size of the financial sector?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-28.
    10. Boysen-Hogrefe, Jens & Gern, Klaus-Jürgen & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Plödt, Martin & van Roye, Björn & Scheide, Joachim & Schwarzmüller, Tim, 2015. "Das europäische Verfahren zur Vermeidung und Korrektur makroökonomischer Ungleichgewichte: Auswertung der bisherigen Erfahrung und mögliche Reformansätze," Kieler Beiträge zur Wirtschaftspolitik 7, Kiel Institute for the World Economy (IfW Kiel).
    11. Lenarčič, Črt & Damjanović, Milan, 2015. "Slovene Residential Property Prices Misalignment with Fundamentals," MPRA Paper 101198, University Library of Munich, Germany.
    12. Muellbauer, John & Geiger, Felix & Rupprecht, Manuel, 2016. "The housing market, household portfolios and the German consumer," Working Paper Series 1904, European Central Bank.

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    More about this item

    Keywords

    house prices; early warning system; OECD countries;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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