Local House Price Paths: Accelerations, Declines, and Recoveries
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Local House Price Paths: Accelerations, Declines, and Recoveries Alexander N. Bogin 1 & William M. Doerner 1 & William D. Larson 1
# This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2017
Abstract Mortgage credit risk measurement hinges on the choice of a house price stress path, which is used to project loan losses and determine financial capital requirements. House price paths are commonly constructed at national or state levels and shock scenarios are created to mimic historical adverse market conditions. We provide evidence that this level of geographic aggregation is not granular enough in many cases—collateral risk often varies within cities. Using local house price indices that cover the United States from 1975 to 2016, we focus on house price performance in the years immediately following sustained periods of rapid acceleration. Price accelerations tend to exhibit temporal clustering and occur with greater frequency in large versus small cities. We exploit within-city variation in price dynamics to provide evidence that price initially overshoot sustainable levels but, in some areas, dynamics may reflect positive underlying economic fundamentals and can be sustained. After accelerating, price reach their trough after 4 or 5 years. Small cities show uniform declines whereas large cities exhibit greater price decreases farther away from city centers. These findings suggest differential collateral risk exists in large cities, financial losses can be predictable based on real estate location theory, and localized house price paths could aid credit risk management. Keywords House price cycles . Credit risk . Mortgage collateral . Stress testing
* William M. Doerner [email protected] Alexander N. Bogin [email protected] William D. Larson [email protected]
1
Federal Housing Finance Agency, Office of Policy Analysis and Research, 400 7th Street SW, Washington, DC 20219, USA
A. N. Bogin et al.
Introduction Mortgage risk management involves assessing credit risk at different points in the housing cycle. The goal is to estimate the extent of losses under a plausible yet stressful economic scenario. House price paths are a key input for determining how severe a scenario will be and how long it will last. Often, these paths are based on projected changes to national or state house price levels.1 This paper provides evidence that additional granularity may be informative for risk management because house price cycles can vary significantly between and within cities. Leading up to the Great Recession, many areas of the country experienced rapid house price growth, yet we have observed substantial variation in post-boom price dynamics. How might we determine whether a rapid rise in house price is sustainable, or if price will eventually fall? As Case and Shiller (2003) make clear, price dynamics following a positive demand shock are dependent on the extent of new construction in the area. However, within a city, there is substanti
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