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An analysis of foreclosure rate differentials in soft markets

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  • Francisca Richter

Abstract

A quantile regression model is used to identify the main neighborhood characteristics associated with high foreclosure rates in weak market neighborhoods, specifically for two counties in Ohio and one in Pennsylvania. A decomposition technique by Machado and Mata (2005) allows separating foreclosure filing rate differentials across counties into two components: the first due to differences in the levels of neighborhood characteristics and the second due to differences in the model parameters. At higher than median rates, foreclosure rate differentials between counties in Ohio are mainly explained by the levels of these characteristics. However, foreclosure rate differences between counties across states are mainly explained by the parameter component, suggesting that state level effects might have contributed to shape foreclosure rate outcomes.

Suggested Citation

  • Francisca Richter, 2008. "An analysis of foreclosure rate differentials in soft markets," Working Papers (Old Series) 0811, Federal Reserve Bank of Cleveland.
  • Handle: RePEc:fip:fedcwp:0811
    DOI: 10.26509/frbc-wp-200811
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    References listed on IDEAS

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    Cited by:

    1. Blackburn, McKinley L. & Vermilyea, Todd, 2012. "The prevalence and impact of misstated incomes on mortgage loan applications," Journal of Housing Economics, Elsevier, vol. 21(2), pages 151-168.

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    Keywords

    Foreclosure; Federal Reserve District; 4th; Economic conditions - Ohio; Economic conditions - Pennsylvania;
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