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Measures of mortgage default risk and local house price dynamics

Author

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  • Damian Damianov
  • Cheng Yan
  • Xiangdong Wang

Abstract

Following the financial crisis, a voluminous literature has developed that aims to shed light on the endogenous relationship between mortgage default risk and house prices. In this paper we contribute to this literature by using measures of mortgage default risk reflecting different stages of the household default decision: from early online searches to actual default, to the resale of the foreclosed home. We use a Panel Vector Autoregressive (PVAR) model to examine the impact of these default risk measures on two segments of residential real estate markets (top and bottom price tiers) from 92 metropolitan areas in 25 US states. We find that the default risk derived from households’ Google searches has the strongest negative impact on high value homes while the percentage of home foreclosed and the foreclosure resales have the strongest negative impact on the prices of low value homes. These results hold for both judicial and non-judicial foreclosure states as well as ‘recourse’ states. In ‘non-recourse’ states the number of homes foreclosed has the strongest negative impact on high value homes, which we interpret as evidence in support of the ”double trigger hypothesis.” That is, households default not only because they are in financial distress but also because they end up with a negative equity in their homes considering current house prices.

Suggested Citation

  • Damian Damianov & Cheng Yan & Xiangdong Wang, 2018. "Measures of mortgage default risk and local house price dynamics ," ERES eres2018_163, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2018_163
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    References listed on IDEAS

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    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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