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Explaining the Boom-Bust Cycle in the U.S. Housing Market: A Reverse-Engineering Approach

Author

Listed:
  • Paolo Gelain

    (Norges Bank (Central Bank of Norway))

  • Kevin J. Lansing

    (Federal Reserve Bank San Francisco)

  • Gisle J. Natvik

    (BI Norwegian Business School)

Abstract

We use a simple quantitative asset pricing model to "reverse-engineer" the sequences of stochastic shocks to housing demand and lending standards that are needed to exactly replicate the boom-bust patterns in U.S. household real estate value and mortgage debt over the period 1995 to 2012. Conditional on the observed paths for U.S. disposable income growth and the mortgage interest rate, we consider four different specifications of the model that vary according to the way that household expectations are formed (rational versus moving average forecast rules) and the maturity of the mortgage contract (one-period versus long-term). We find that the model with moving average forecast rules and long-term mortgage debt does best in plausibly matching the patterns observed in the data. Counterfactual simulations show that shifting lending standards (as measured by a loan-to-equity limit) were an important driver of the episode while movements in the mortgage interest rate were not. All models deliver rapid consumption growth during the boom, negative consumption growth during the Great Recession, and sluggish consumption growth during the recovery when households are deleveraging.

Suggested Citation

  • Paolo Gelain & Kevin J. Lansing & Gisle J. Natvik, 2015. "Explaining the Boom-Bust Cycle in the U.S. Housing Market: A Reverse-Engineering Approach," Working Paper 2015/11, Norges Bank.
    • Handle: RePEc:bno:worpap:2015_11
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    Cited by:

    1. Paolo Gelain & Kevin J Lansing & Gisle James Natvik, 2018. "Leaning Against the Credit Cycle," Journal of the European Economic Association, European Economic Association, vol. 16(5), pages 1350-1393.
    2. Jørgensen, Peter Lihn, 2023. "The global savings glut and the housing boom," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    3. Lansing, Kevin J., 2024. "Replicating business cycles and asset returns with sentiment and low risk aversion," Journal of Economic Dynamics and Control, Elsevier, vol. 167(C).
    4. Dominik Hecker & Maik Wolters & Maik H. Wolters, 2025. "Nonlinear Estimation of a New Keynesian Model with Endogenous Inflation De-Anchoring," CESifo Working Paper Series 12280, CESifo.
    5. Chi-Young Choi & Soojin Jo, 2020. "How Do Housing Markets Affect Local Consumer Prices? – Evidence from U.S. Cities," Globalization Institute Working Papers 398, Federal Reserve Bank of Dallas.
    6. Gabrovski, Miroslav & Ortego-Marti, Victor, 2021. "Search and credit frictions in the housing market," European Economic Review, Elsevier, vol. 134(C).
    7. Miroslav Gabrovski & Victor Ortego-Marti, 2025. "Home Construction Financing and Search Frictions in the Housing Market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 55, January.
    8. William Gatt, 2022. "MEDSEA-FIN: an estimated DSGE model with housing and financial frictions for Malta," CBM Working Papers WP/05/2022, Central Bank of Malta.
    9. Hull, Isaiah, 2015. "What Broke First? Characterizing Sources of Structural Change Prior to the Great Recession," Working Paper Series 301, Sveriges Riksbank (Central Bank of Sweden).
    10. Bechlioulis, Alexandros P. & Brissimis, Sophocles N., 2019. "Consumer debt non-payment and the borrowing constraint: Implications for consumer behavior," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 161-172.
    11. Lansing, Kevin J., 2021. "Endogenous forecast switching near the zero lower bound," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 153-169.
    12. Miroslav Gabrovski & Victor Ortego-Marti, 2021. "Efficiency in the Housing Market with Search Frictions," Working Papers 202108, University of California at Riverside, Department of Economics.
    13. Tang, Yang & Zeng, Ting & Zhu, Shenghao, 2020. "Bubbles and house price dispersion in the United States during 1975–2017," Journal of Macroeconomics, Elsevier, vol. 63(C).
    14. Anja Janischewski & Michael Heinrich Baumann, 2025. "What are Asset Price Bubbles? A Survey on Definitions of Financial Bubbles," Chemnitz Economic Papers 065, Department of Economics, Chemnitz University of Technology.
    15. Nelson Lind, 2017. "Credit Regimes and the Seeds of Crisis," 2017 Meeting Papers 1474, Society for Economic Dynamics.
    16. Olivier Mesly & David W. Shanafelt & Nicolas Huck, 2021. "Dysfunctional Markets: A Spray of Prey Perspective," Journal of Economic Issues, Taylor & Francis Journals, vol. 55(3), pages 797-819, July.
    17. Granziera, Eleonora & Kozicki, Sharon, 2015. "House price dynamics: Fundamentals and expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 152-165.
    18. Leung, Charles Ka Yui, 2022. "Housing and Macroeconomics," MPRA Paper 115500, University Library of Munich, Germany.

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    Keywords

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    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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