How Low Can House Prices Go? Estimating a Conservative Lower Bound
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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.
KeywordsHouse 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.
- Adam, K., Kuang, P., & Marcet, A. (2011). House price booms and the current account. NBER. Working Paper 17224.Google Scholar
- 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
- Glaeser, E.L., & Nathanson, C.G. (2015). An extrapolative model of house price dynamics. NBER. Working Paper 21037.Google Scholar
- Kahn, J. A. (2008). What drives house prices? Federal Reserve Bank of New York Staff Reports No. 345.Google Scholar
- Markowitz, H. M. (1952). Portfolio selection. Journal of Finance, 7(1), 77–91.Google Scholar
- Prais, S., & Winsten, C. (1954). Trend estimators and serial correlation. Cowles Foundation. Discussion Paper 383.Google Scholar
- Reinhart, C.M., & Rogoff, K.S. (2009). The aftermath of financial crises. NBER. Working Paper 14656.Google Scholar
- Rousová, L., & van den Noord, P. (2011). Predicting peaks and troughs in real house prices. OECD Economics Department Working Papers No. 882.Google Scholar
- 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
- Smith, S., & Weiher, J. (2012). Countercyclical capital regime: a proposed design and empirical evaluation. Federal Housing Finance Agency. Working Paper 12–2.Google Scholar