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Re-examining the Neighborhood Distribution of Higher Priced Mortgage Lending: Global versus Local Methods

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  • Yonghua Zou

Abstract

This paper demonstrates the application of the local geographically weighted regression (GWR) method to mortgage studies, using the Philadelphia metropolitan statistical area (MSA) as a case study. Previous related studies widely employed the global, ordinary least square (OLS) method to examine the spatial distribution of subprime/higher priced mortgages. The OLS method, however, masks the spatial variations in mortgage distributions. The innovative GWR method not only provides a significant improvement in model fitness but also reveals that the statistical relationships between neighborhood characteristics and the prevalence of higher priced mortgage shares are spatially varied. In addition, the GWR method can bring forward potential implications for place-based policy making. Improving upon previous methodologies in mortgage studies, this paper shows that the GWR method can advance our understanding of how neighborhood environments are associated with mortgage lending patterns.

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  • Yonghua Zou, 2015. "Re-examining the Neighborhood Distribution of Higher Priced Mortgage Lending: Global versus Local Methods," Growth and Change, Wiley Blackwell, vol. 46(4), pages 654-674, December.
    • Handle: RePEc:bla:growch:v:46:y:2015:i:4:p:654-674
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    1. Mark D. Partridge & Dan S. Rickman & Kamar Ali & M. Rose Olfert, 2008. "The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach," Land Economics, University of Wisconsin Press, vol. 84(2), pages 241-266.
    2. Kamar Ali & Mark D. Partridge & M. Rose Olfert, 2007. "Can Geographically Weighted Regressions Improve Regional Analysis and Policy Making?," International Regional Science Review, , vol. 30(3), pages 300-329, July.
    3. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, June.
    4. Richard Shearmur & Philippe Apparicio & Pauline Lizion & Mario Polèse, 2007. "Space, Time, and Local Employment Growth: An Application of Spatial Regression Analysis," Growth and Change, Wiley Blackwell, vol. 38(4), pages 696-722, December.
    5. Yefang Huang & Yee Leung, 2002. "Analysing regional industrialisation in Jiangsu province using geographically weighted regression," Journal of Geographical Systems, Springer, vol. 4(2), pages 233-249, June.
    6. Guangqing Chi & Stephen J. Ventura, 2011. "An Integrated Framework of Population Change: Influential Factors, Spatial Dynamics, and Temporal Variation," Growth and Change, Wiley Blackwell, vol. 42(4), pages 549-570, December.
    7. Paul Calem & Jonathan Hershaff & Susan Wachter, 2004. "Neighborhood patterns of subprime lending: Evidence from disparate cities," Housing Policy Debate, Taylor & Francis Journals, vol. 15(3), pages 603-622.
    8. Sandy Dall'Erba & Rachel Guillain & Julie Le Gallo, 2011. "The local vs global dilemma of the effects of structural funds," Post-Print halshs-01226500, HAL.
    9. Paul S. Calem & Kevin Gillen & Susan Wachter, 2004. "The Neighborhood Distribution of Subprime Mortgage Lending," The Journal of Real Estate Finance and Economics, Springer, vol. 29(4), pages 393-410, December.
    10. Christopher J. Mayer & Karen M. Pence, 2008. "Subprime mortgages: what, where, and to whom?," Finance and Economics Discussion Series 2008-29, Board of Governors of the Federal Reserve System (U.S.).
    11. Stuart A. Foster & Wilpen L. Gorr, 1986. "An Adaptive Filter for Estimating Spatially-Varying Parameters: Application to Modeling Police Hours Spent in Response to Calls for Service," Management Science, INFORMS, vol. 32(7), pages 878-889, July.
    12. Danlin Yu & Yehua Dennis Wei & Changshan Wu, 2007. "Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI," Environment and Planning B, , vol. 34(6), pages 1085-1102, December.
    13. David C Wheeler, 2007. "Diagnostic Tools and a Remedial Method for Collinearity in Geographically Weighted Regression," Environment and Planning A, , vol. 39(10), pages 2464-2481, October.
    14. Julie Le Gallo & Sandy Dall'Erba & Rachel Guillain, 2011. "The Local versus Global Dilemma of the Effects of Structural Funds," Growth and Change, Wiley Blackwell, vol. 42(4), pages 466-490, December.
    15. Scott Orford, 2000. "Modelling Spatial Structures in Local Housing Market Dynamics: A Multilevel Perspective," Urban Studies, Urban Studies Journal Limited, vol. 37(9), pages 1643-1671, August.
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