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Econometric regime shifts and the US subprime bubble

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  • André K. Anundsen

    (Department of Economics, University of Oslo)

Abstract

Using aggregate quarterly data for the period 1975q1–2010q4, I find that the US housing market changed from a stable regime with prices determined by fundamentals, to a highly unstable regime at the beginning of the previous decade. My results indicate that these imbalances could have been detected with the aid of real time econometric modeling and that they were caused by the sharp rise in subprime lending in the early to mid 2000s. These results are based on the detection of huge parameter non-constancies and a loss of equilibrium correction in two theory derived cointegrating relationships shown to be very stable for earlier periods. Controlling for the increased subprime exposure during this period, enables me to reestablish the pre-break relationships also for the full sample. This suggests that the US housing bubble was caused by the increased borrowing to a more risky segment of the market, which may have allowed for a latent frenzy behavior that previously was constrained by the lack of financing. With reference to Stiglitz’s general conception of a bubble, I use the econometric results to construct two bubble indicators, which clearly demonstrate the transition to an unstable regime. Such indicators can be part of an early warning system and are shown to Granger cause a set of coincident indicators and financial (in)stability measures.

Suggested Citation

  • André K. Anundsen, 2012. "Econometric regime shifts and the US subprime bubble," NBP Working Papers 126, Narodowy Bank Polski.
  • Handle: RePEc:nbp:nbpmis:126
    Note: The paper has been presented at the Central Bank Macroeconomic Modeling Workshop: Modeling Imbalances in Warsaw, 13.–14. September 2012.
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    References listed on IDEAS

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    Cited by:

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    2. Jiao, Xiyu & Pretis, Felix & Schwarz, Moritz, 2024. "Testing for coefficient distortion due to outliers with an application to the economic impacts of climate change," Journal of Econometrics, Elsevier, vol. 239(1).
    3. Sara Ferreira Filipe, 2018. "Housing prices and mortgage credit in Luxembourg," BCL working papers 117, Central Bank of Luxembourg.
    4. Vinicius Phillipe de Albuquerquemello & Cássio Besarria, 2020. "Rental market and macroeconomics: evidence for the US," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(3), pages 587-603, August.
    5. André K. Anundsen & Karsten Gerdrup & Frank Hansen & Kasper Kragh‐Sørensen, 2016. "Bubbles and Crises: The Role of House Prices and Credit," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1291-1311, November.
    6. Diego Ardila & Dorsa Sanadgol & Peter Cauwels & Didier Sornette, 2017. "Identification and critical time forecasting of real estate bubbles in the USA," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 613-631, April.
    7. André K. Anundsen, 2019. "Detecting Imbalances in House Prices: What Goes Up Must Come Down?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(4), pages 1587-1619, October.
    8. Martínez-García, Enrique & Grossman, Valerie, 2020. "Explosive dynamics in house prices? An exploration of financial market spillovers in housing markets around the world," Journal of International Money and Finance, Elsevier, vol. 101(C).
    9. Martin Wagner & Dominik Wied, 2017. "Consistent Monitoring of Cointegrating Relationships: The US Housing Market and the Subprime Crisis," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 960-980, November.
    10. Bergman, U. Michael & Sørensen, Peter Birch, 2021. "The interaction of actual and fundamental house prices: A general model with an application to Sweden," Journal of Housing Economics, Elsevier, vol. 54(C).
    11. André K. Anundsen & Eilev S. Jansen, 2013. "Self-reinforcing effects between housing prices and credit: an extended version," Discussion Papers 756, Statistics Norway, Research Department.
    12. Alisa Yusupova & Nicos G. Pavlidis & Efthymios G. Pavlidis, 2019. "Adaptive Dynamic Model Averaging with an Application to House Price Forecasting," Papers 1912.04661, arXiv.org.
    13. Lorenzo Trapani & Emily Whitehouse, 2020. "Sequential monitoring for cointegrating regressions," Papers 2003.12182, arXiv.org.
    14. Anundsen, André K. & Jansen, Eilev S., 2013. "Self-reinforcing effects between housing prices and credit," Journal of Housing Economics, Elsevier, vol. 22(3), pages 192-212.
    15. Damen, Sven & Vastmans, Frank & Buyst, Erik, 2016. "The effect of mortgage interest deduction and mortgage characteristics on house prices," Journal of Housing Economics, Elsevier, vol. 34(C), pages 15-29.

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    More about this item

    Keywords

    Cointegration; Regime Shifts; US Housing Bubble; Subprime lending; Bubble Indicator;
    All these keywords.

    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
    • G01 - Financial Economics - - General - - - Financial Crises
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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