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作者

来源

JOURNAL OF REAL ESTATE FINANCE AND ECONOMICS,Vol.58,Issue2,P.201-222

语言

英文

关键字

House price cycles; Credit risk; Mortgage collateral; Stress testing; DYNAMICS; MARKET; INCOME; MODEL

作者单位

[Bogin, Alexander N.; Doerner, William M.; Larson, William D.] Fed Housing Finance Agcy, Off Policy Anal & Res, 400 7th St SW, Washington, DC 20219 USA. Doerner, WM (reprint author), Fed Housing Finance Agcy, Off Policy Anal & Res, 400 7th St SW, Washington, DC 20219 USA. E-Mail: alexander.bogin@fhfa.gov; william.doerner@fhfa.gov; william.larson@fhfa.gov

摘要

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 casescollateral 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 5years. 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.