How Low Can House Prices Go? Estimating a Conservative Lower Bound

  • Alexander N. Bogin
  • Stephen D. Bruestle
  • William M. DoernerEmail author


In risk management, the credit risk and required capital associated with mortgage assets is often estimated through stress testing where the house price path is an important determinant of the severity of the stress test. Specifically, the extent of credit-related losses is a function of how far house prices are above long-term trend and the extent to which they can fall below trend. Focusing on the latter, we develop a theoretically-based statistical technique to identify a conservative lower bound (CLB) for house prices. Leveraging a model based upon investor incentives, the CLB explains the depth of housing market downturns at both the national and state level over a variety of market environments. This approach performs well in several historical back tests and has strong out-of-sample predictive ability. When back-tested, the estimation approach does not understate house price declines in any state over the 1987 to 2001 housing cycle and only understates declines in three states during the most recent financial crisis. This latter result is particularly noteworthy given that the post-2001 estimates are performed out-of-sample. The CLB is attractive because it (1) provides a leading indicator of the severity of future downturns and (2) allows estimates of trough to recover or decrease in magnitude as markets return to baseline conditions. This estimation technique could prove helpful in measuring the credit risk associated with portfolios of mortgage assets as part of evaluating static or designing dynamic stress tests.


House prices Trough Lower bound Trend Financial stress testing 



The authors are grateful to Scott Smith for his insight and guidance, which made this paper possible. The authors also thank Chi-Cheol Chung, Debra Fuller, Nataliya Polkovnichenko, Bertram Steininger, and Jesse Weiher. Helpful comments were provided by participants at the American Real Estate and Urban Economics Association national conference, American Real Estate Society annual conference, and the Federal Reserve Bank of Richmond regional research workshop. An earlier version of this manuscript was selected as the best paper in 2015 in real estate cycles by the American Real Estate Society.

Conflict of Interest

The authors declare that they have no conflict of interest and no outside funding was received.


  1. Adam, K., Kuang, P., & Marcet, A. (2011). House price booms and the current account. NBER. Working Paper 17224.Google Scholar
  2. Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343.CrossRefGoogle Scholar
  3. Borgy, V., Clerc, L., & Renne, J. P. (2014). Measuring aggregate risk: can we robustly identify asset-price boom-bust cycles? Journal of Banking & Finance, 46, 132–150.CrossRefGoogle Scholar
  4. Brueckner, J. K. (1997). Consumption and investment motives and the portfolio choices of homeowners. Journal of Real Estate Finance and Economics, 15(2), 159–180.CrossRefGoogle Scholar
  5. Capozza, D. R., Hendershott, P. H., & Mack, C. (2004). An anatomy of price dynamics in illiquid markets: analysis and evidence from local housing markets. Real Estate Economics, 32(1), 1–32.CrossRefGoogle Scholar
  6. Case, K.E., & Shiller, R.J. (2003). Is there a bubble in the housing market? Brooking Papers on Economic Activity, 2, 299–362.Google Scholar
  7. Chien, M. S. (2010). Structural breaks and the convergence of regional house prices. Journal of Real Estate Finance and Economics, 40(1), 77–88.CrossRefGoogle Scholar
  8. Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605.CrossRefGoogle Scholar
  9. Davidoff, T. (2013). Supply elasticity and the housing cycle of the 2000s. Real Estate Economics, 41(4), 793–813.CrossRefGoogle Scholar
  10. Dusansky, R., Koç, Ç., & Onur, I. (2012). Household housing demand: empirical analysis and theoretical reconciliation. Journal of Real Estate Finance and Economics, 44(4), 429–445.CrossRefGoogle Scholar
  11. Englund, P., Hwang, M., & Quigley, J. M. (2002). Hedging housing risk. Journal of Real Estate Finance and Economics, 24(1), 167–200.CrossRefGoogle Scholar
  12. Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23–49.CrossRefGoogle Scholar
  13. Freund, R. J. (1956). The introduction of risk into a programming model. Econometrica, 24(3), 253–263.CrossRefGoogle Scholar
  14. Gao, A., Lin, Z., & Na, C. F. (2009). Housing market dynamics: evidence of mean reversion and downward rigidity. Journal of Housing Economics, 18(3), 256–266.CrossRefGoogle Scholar
  15. Glaeser, E. L., Gyourko, J., & Saks, R. E. (2005). Why have housing prices gone up? The American Economic Review, 95(2), 329–333.CrossRefGoogle Scholar
  16. Glaeser, E.L., & Nathanson, C.G. (2015). An extrapolative model of house price dynamics. NBER. Working Paper 21037.Google Scholar
  17. Gupta, R., Kabundi, A., & Miller, S. M. (2011). Forecasting the US real house price index: structural and non-structural models with and without fundamentals. Economic Modelling, 28(4), 2013–2021.CrossRefGoogle Scholar
  18. Han, L. (2013). Understanding the puzzling risk-return relationship for housing. The Review of Financial Studies, 26(4), 877–928.CrossRefGoogle Scholar
  19. Hoffman, M., Krause, M. U., & Laubach, T. (2012). Trend growth expectations and U.S. house prices before and after the crisis. Journal of Economic Behavior & Organization, 83(3), 394–409.CrossRefGoogle Scholar
  20. Huang, H., & Tang, Y. (2012). Residential land use regulation and the US housing price cycle between 2000 and 2009. Journal of Urban Economics, 71(1), 93–99.CrossRefGoogle Scholar
  21. Jin, H., & Zhou, X. Y. (2013). Greed, leverage, and potential losses: a prospect theory perspective. Mathematical Finance, 23(1), 122–142.CrossRefGoogle Scholar
  22. Kahn, J. A. (2008). What drives house prices? Federal Reserve Bank of New York Staff Reports No. 345.Google Scholar
  23. Mankiw, G. N., & Weil, D. N. (1989). The baby boom, the baby bust, and the housing market. Regional Science and Urban Economics, 19(2), 235–258.CrossRefGoogle Scholar
  24. Markowitz, H. M. (1952). Portfolio selection. Journal of Finance, 7(1), 77–91.Google Scholar
  25. Prais, S., & Winsten, C. (1954). Trend estimators and serial correlation. Cowles Foundation. Discussion Paper 383.Google Scholar
  26. Reinhart, C.M., & Rogoff, K.S. (2009). The aftermath of financial crises. NBER. Working Paper 14656.Google Scholar
  27. Rousová, L., & van den Noord, P. (2011). Predicting peaks and troughs in real house prices. OECD Economics Department Working Papers No. 882.Google Scholar
  28. Shiller, R. J. (2007). Understanding recent trends in house prices and homeownership (pp. 89–123). Federal Reserve Bank of Kansas City: Proceedings - Economic Policy Symposium - Jackson Hole.CrossRefGoogle Scholar
  29. Smith, S., Fuller, D., Bogin, A., Polkovnichenko, N., & Weiher, J. (2014). Countercyclical capital regime revisited: tests of robustness. Federal Housing Finance Agency. Working Paper 14–1.Google Scholar
  30. Smith, S., & Weiher, J. (2012). Countercyclical capital regime: a proposed design and empirical evaluation. Federal Housing Finance Agency. Working Paper 12–2.Google Scholar
  31. Van Nieuwerburgh, S., & Weill, P. O. (2010). Why has house price dispersion gone up? The Review of Economic Studies, 77(4), 1567–1606.CrossRefGoogle Scholar
  32. Zietz, J., & Traian, A. (2014). When was the US housing downturn predictable? A comparison of univariate forecasting methods. The Quarterly Review of Economics and Finance, 54, 271–281.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside the USA) 2015

Authors and Affiliations

  • Alexander N. Bogin
    • 1
  • Stephen D. Bruestle
    • 2
  • William M. Doerner
    • 1
    Email author
  1. 1.Office of Policy Analysis and Research, Capital Policy BranchFederal Housing Finance AgencyWashingtonUSA
  2. 2.School of BusinessPenn State ErieErieUSA

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