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Detecting imbalances in house prices: What goes up must come down?

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Abstract

With the aid of econometric modeling, I investigate whether rapidly increasing house prices necessarily imply the existence of a bubble that will eventually burst. I consider four alternative econometric methods to construct indicators of housing market imbalances for the US, Finland and Norway. The four approaches are used to study if house prices in these countries in the 2000s can be explained by underlying economic fundamentals, or whether the developments are best characterized by bubble-dynamics. For the US, all measures unanimously suggest a bubble in the early to mid 2000s, whereas current US house prices are found to be aligned with economic fundamentals. Only one of the measures indicate imbalances in the Finnish housing market, while none of the measures suggest a bubble in Norway.

Suggested Citation

  • André K. Anundsen, 2016. "Detecting imbalances in house prices: What goes up must come down?," Working Paper 2016/11, Norges Bank.
    • Handle: RePEc:bno:worpap:2016_11
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    File URL: http://www.norges-bank.no/en/Published/Papers/Working-Papers/2016/112016/
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    Cited by:

    1. Whitehouse, E.J. & Harvey, D.I. & Leybourne, S.J., 2025. "Real-time monitoring procedures for early detection of bubbles," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1260-1277.
    2. Federica Ciocchetta & Elisa Guglielminetti & Alessandro Mistretta, 2024. "What Drives House Prices in Europe?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(5), pages 1089-1121, October.
    3. Juan Carlos Cuestas & Merike Kukk & Natalia Levenko, 2023. "Misalignments in house prices and economic growth in Europe," Applied Economics, Taylor & Francis Journals, vol. 55(28), pages 3215-3237, June.
    4. Jinwoong Lee, 2024. "What factors drive house prices in the USA? Sign restricted VAR approach," Empirical Economics, Springer, vol. 66(6), pages 2533-2556, June.
    5. Pål Boug & Håvard Hungnes & Takamitsu Kurita, 2024. "The empirical modelling of house prices and debt revisited: a policy-oriented perspective," Empirical Economics, Springer, vol. 66(1), pages 369-404, January.
    6. Emily J. Whitehouse & David I. Harvey & Stephen J. Leybourne, 2023. "Real‐Time Monitoring of Bubbles and Crashes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 482-513, June.
    7. Laurynas Narusevicius & Tomas Ramanauskas & Laura Gudauskaitė & Tomas Reichenbachas, 2019. "Lithuanian house price index: modelling and forecasting," Bank of Lithuania Occasional Paper Series 28, Bank of Lithuania.
    8. Sara Ferreira Filipe, 2018. "Housing prices and mortgage credit in Luxembourg," BCL working papers 117, Central Bank of Luxembourg.

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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G01 - Financial Economics - - General - - - Financial Crises
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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