Modeling Spatially Interdependent Mortgage Decisions

Posted: 14 Nov 2014

See all articles by Shuang Zhu

Shuang Zhu

Kansas State University - Department of Finance

R. Kelley Pace

Louisiana State University - E.J. Ourso College of Business Administration

Multiple version iconThere are 2 versions of this paper

Date Written: November 12, 2014

Abstract

House price regression residuals often display spatial dependence but historically mortgage models, which employ house prices, assume independence and use only the own borrower/loan characteristics. This manuscript uses a spatial probit model to investigate spatial dependence among the disturbances and the effect of borrower/loan characteristics from nearby properties on own default propensity. We find that allowing spatial dependence in the disturbances greatly improve the predictive accuracy of a probit default model, and that spillovers from risky neighbor characteristics have statistically significant and material effects on own payment default propensity. In addition, measurement of spatial effects can improve policy analysis.

Keywords: Mortgage; Spillovers; Mortgage default; Interdependence; Spatial probit

Suggested Citation

Zhu, Shuang and Pace, R. Kelley, Modeling Spatially Interdependent Mortgage Decisions (November 12, 2014). Journal of Real Estate Finance and Economics, Vol. 49, No. 4, 2014, Available at SSRN: https://ssrn.com/abstract=2523551

Shuang Zhu (Contact Author)

Kansas State University - Department of Finance ( email )

Manhattan, KS 66506
United States

R. Kelley Pace

Louisiana State University - E.J. Ourso College of Business Administration ( email )

Department of Finance
2164 B Patrick F. Taylor Hall
Baton Rouge, LA 70803-6308
United States
(225)-578-6256 (Phone)
(225)-578-9065 (Fax)

HOME PAGE: http://www.spatial-statistics.com

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