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Appraisal Accuracy, Automated Valuation Models, And Credit Modeling in Rural Areas

Author

Listed:
  • Alexander N. Bogin

    (Federal Housing Finance Agency)

  • Jessica Shui

    (Federal Housing Finance Agency)

Abstract

Accurate and unbiased property value estimates are essential to credit risk management. Along with loan amount, they determine a mortgage’s loan-to-value ratio, which captures the degree of homeowner equity and is a key determinant of borrower credit risk. For home purchases, lenders generally require an independent appraisal, which, in addition to a home’s sales price, is used to calculate a value for the underlying collateral. A number of empirical studies have shown that property appraisals tend to be biased upwards, and over 90 percent of the time, either confirm or exceed the associated contract price. Our data suggest that appraisal bias is particularly pervasive in rural areas where over 25 percent of rural properties are appraised at more than five percent above contract price. Given this significant upward bias, we examine a host of alternate valuation techniques to more accurately estimate rural property values. We then include these alternate value estimates when modeling delinquencies and examine their explanatory power.

Suggested Citation

  • Alexander N. Bogin & Jessica Shui, 2018. "Appraisal Accuracy, Automated Valuation Models, And Credit Modeling in Rural Areas," FHFA Staff Working Papers 18-03, Federal Housing Finance Agency.
    • Handle: RePEc:hfa:wpaper:18-03
    DOI: 10.1007/s11146-019-09712-0
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    References listed on IDEAS

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    Cited by:

    1. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
    2. R. Kelley Pace & Darren Hayunga, 2020. "Examining the Information Content of Residuals from Hedonic and Spatial Models Using Trees and Forests," The Journal of Real Estate Finance and Economics, Springer, vol. 60(1), pages 170-180, February.

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    More about this item

    Keywords

    automated valuation models; appraisal; property value; credit risk; rural;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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