by Calculated Risk on 5/14/2015 09:55:00 AM

An FHFA paper from Alex Bogin, Senior Economist; Stephen Bruestle, Lecturer; William M. Doerner, Senior ​Economist How Low Can House Prices Go? Estimating a Conservative Lower Bound

The researchers have developed a conservative lower bound (CLB) for house prices. This tool could be used as part of stress testing banks (and could be applied to other countries like Canada and Australia that might have housing bubbles right now).

Abstract:

We develop a theoretically-based statistical technique to identify a conservative lower bound for house prices. Leveraging a model based upon consumer and investor incentives, we are able to explain 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, our 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 outof- sample. Our measure of a conservative lower bound is attractive because it (1) provides a leading indicator of the severity of future downturns and (2) allows trough estimates to dynamically adjust as markets conditions change. This estimation technique could prove particularly helpful in measuring the credit risk associated with portfolios of mortgage assets as part of evaluating static stress tests or designing dynamic stress tests.

Conclusion:

Since the recent financial crisis, there has been an increasing focus on improving stress testing. Thus far, the stressed housing paths have been largely static in nature, essentially ignoring current market conditions. This paper proposes a conservative lower bound with a theoretical foundation that is supported by empirical evidence. Our CLB approach provides a dynamic path that would vary with market conditions. The regression results compare the efficacy of this approach relative to the historical precedent approach of Smith & Weiher across two different housing cycles where the underlying data cover house price transactions across the United States. As demonstrated, the CLB is able to adapt successfully to changing market conditions and acts as a leading indicator for future market downturns. In addition to accurately capturing the severity of downturns, it also allows estimated troughs to recover as markets return to baseline conditions. The approach performs well in both in-sample and out-of-sample historical back-testing. Although it is more complicated to implement than the Smith & Weiher method, the CLB reduces the potential for understating the extent of future state-level house price declines, allowing for more accurate stress testing.

I'd like to see state and local estimates of the CLB right now!