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Working Paper

An Analysis of Foreclosure Rate Differentials in Soft Markets

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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.
11.01.2008ISSN 2573-7953 WP 08-11DOI 10.26509/frbc-wp-200811
Keywords foreclosure, quantile regression, decomposition analysis
JEL Classification Codes G21, R23

Working Papers of the Federal Reserve Bank of Cleveland are preliminary materials circulated to stimulate discussion and critical comment on research in progress. They may not have been subject to the formal editorial review accorded official Federal Reserve Bank of Cleveland publications. The views expressed in this paper are those of the authors and do not represent the views of the Federal Reserve Bank of Cleveland or the Federal Reserve System.

Suggested Citation

Richter, Francisca García-Cobián. 2008. “An Analysis of Foreclosure Rate Differentials in Soft Markets.” Federal Reserve Bank of Cleveland, Working Paper No. 08-11. https://doi.org/10.26509/frbc-wp-200811