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The role of neighborhood characteristics in mortgage default risk: evidence from New York City

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  • Chan, Sewin
  • Gedal, Michael
  • Been, Vicki
  • Haughwout, Andrew
Abstract
Using a rich database of non-prime mortgages from New York City, we find that census tract level neighborhood characteristics are important predictors of default behavior, even after controlling for an extensive set of controls for loan and borrower characteristics. First, default rates increase with the rate of foreclosure notices and the number of lender-owned properties (REOs) in the tract. Second, default rates on home purchase mortgages are higher in census tracts with larger shares of black residents, regardless of the borrower’s own race. We explore possible explanations for this second finding and conclude that it likely reflects differential treatment of black neighborhoods by the mortgage industry in ways that are unobserved in our data.

Suggested Citation

  • Chan, Sewin & Gedal, Michael & Been, Vicki & Haughwout, Andrew, 2011. "The role of neighborhood characteristics in mortgage default risk: evidence from New York City," MPRA Paper 33941, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:33941
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    Cited by:

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    2. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
    3. J. Michael Collins & Carolina Reid, 2010. "Who receives a mortgage modification? Race and income differentials in loan workouts," Community Development Working Paper 2010-07, Federal Reserve Bank of San Francisco.
    4. M. Dietsch & C. Welter-Nicol, 2014. "Do LTV and DSTI caps make banks more resilient?," Débats économiques et financiers 13, Banque de France.
    5. Thomas P. Boehm & Alan M. Schlottmann, 2020. "Achieving Effective Mortgage Modifications: The Importance of Household Characteristics," The Journal of Real Estate Finance and Economics, Springer, vol. 61(2), pages 151-182, August.
    6. Bouras, Christos & Christou, Christina & Gupta, Rangan & Lesame, Keagile, 2023. "Forecasting state- and MSA-level housing returns of the US: The role of mortgage default risks," Research in International Business and Finance, Elsevier, vol. 65(C).
    7. Patricia D. Posey, 2023. "Information Inequality: How Race and Financial Access Reflect the Information Needs of Lower-Income Individuals," The ANNALS of the American Academy of Political and Social Science, , vol. 707(1), pages 125-141, May.
    8. Stephen L. Ross & Yuan Wang, 2022. "Mortgage Lenders and the Geographic Concentration of Foreclosures," Working Papers 2022-001, Human Capital and Economic Opportunity Working Group.
    9. Jacob W. Faber & Peter M. Rich, 2018. "Financially Overextended: College Attendance as a Contributor to Foreclosures During the Great Recession," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1727-1748, October.
    10. Been, Vicki & Weselcouch, Mary & Voicu, Ioan & Murff, Scott, 2013. "Determinants of the incidence of U.S. Mortgage Loan Modifications," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3951-3973.
    11. Selma Hepp, 2013. "Zoning Restrictiveness and Housing Foreclosures: Exploring a New Link to the Subprime Mortgage Crisis," Housing Policy Debate, Taylor & Francis Journals, vol. 23(2), pages 460-462, April.
    12. Sewin Chan & Claudia Sharygin & Vicki Been & Andrew Haughwout, 2014. "Pathways After Default: What Happens to Distressed Mortgage Borrowers and Their Homes?," The Journal of Real Estate Finance and Economics, Springer, vol. 48(2), pages 342-379, February.
    13. Fernando Ferreira & Joseph Gyourko, 2015. "A New Look at the U.S. Foreclosure Crisis: Panel Data Evidence of Prime and Subprime Borrowers from 1997 to 2012," NBER Working Papers 21261, National Bureau of Economic Research, Inc.
    14. Emily S. Taylor Poppe, 2016. "Homeowner Representation in the Foreclosure Crisis," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 13(4), pages 809-836, December.
    15. Lee, Hyojung & Bostic, Raphael W., 2020. "Bank adaptation to neighborhood change: Mortgage lending and the Community Reinvestment Act," Journal of Urban Economics, Elsevier, vol. 116(C).
    16. Schweikert, Jochen & Höchstötter, Markus, 2018. "Epidemiological spreading of mortgage default," Working Paper Series in Economics 112, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    17. Chan, Sewin & Haughwout, Andrew & Tracy, Joseph, 2015. "How Mortgage Finance Affects the Urban Landscape," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 987-1045, Elsevier.
    18. Disli, Mustafa & Jalaly, Shakir, 2024. "The performance of Islamic and conventional microfinance loans in Afghanistan: The Taliban and beyond," Emerging Markets Review, Elsevier, vol. 59(C).
    19. Dietsch, Michel & Petey, Joël, 2015. "The credit-risk implications of home ownership promotion: The effects of public subsidies and adjustable-rate loans," Journal of Housing Economics, Elsevier, vol. 28(C), pages 103-120.
    20. Saty Patrabansh, 2015. "The Marginal Effect of First-Time Homebuyer Status on Mortgage Default and Prepayment," FHFA Staff Working Papers 15-02, Federal Housing Finance Agency.
    21. Chernick, Howard & Reschovsky, Andrew & Newman, Sandra, 2021. "The effect of the housing crisis on the finances of central cities," Journal of Housing Economics, Elsevier, vol. 54(C).
    22. Selma Hepp, 2013. "Foreclosures and Metropolitan Spatial Structure: Establishing the Connection," Housing Policy Debate, Taylor & Francis Journals, vol. 23(3), pages 497-520, July.
    23. Jacob Faber, 2021. "Contemporary echoes of segregationist policy: Spatial marking and the persistence of inequality," Urban Studies, Urban Studies Journal Limited, vol. 58(5), pages 1067-1086, April.

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    More about this item

    Keywords

    mortgage; default; neighborhoods; race;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics

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