Skip to main content
SpringerLink
Log in

Social Capital and Mortgage Delinquency

  • Published:
The Journal of Real Estate Finance and Economics Aims and scope Submit manuscript

Abstract

This study offers a simple theoretical model and empirical evidence to address the impact of social capital on mortgage delinquency. Social capital includes the norms, values, trust, and information common to a social network, which enable cooperative and shared actions. Using a new county-level dataset between 1999 and 2011 for the U.S, we find new evidence to show that social capital significantly affects the likelihood of mortgage delinquency. In particular, we find that a one-standard-deviation increase in social capital leads to a 0.13 standard deviation decrease in mortgage delinquency. The effect of social capital remains significant after controlling for location fixed effects and addressing endogeneity. The primary explanation is that social norms or trust could limit opportunistic behavior among homeowners and negatively affect strategic default activities. We also find that the impact of social capital on mortgage delinquency increased after the recent financial crisis. Furthermore, we show that the impact of social capital is more pronounced when the default is more likely to be strategic. Our findings have important implications for players in the mortgage industry and for policymakers in that cooperative and shared actions can play an important role in the mortgage default process. Thus, the assessment of default risk should consider social capital in addition to the factors already documented in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. It is Federal Reserve estimates based on data from the Mortgage Bankers Association.

  2. Our sample covers a majority of the U.S. counties. It does not include all the counties due to data availability, which is discussed in more detail later in the paper. For example, mortgage delinquency information is not available for counties with a population less than 10,000. Moreover, the sample used in our empirical analysis covers the period of 1999–2011 due to data availability. Our mortgage delinquency data is available for the period of 1999–2011. More details on the data is provided later in the paper.

  3. We use interpolation for the years without available data for social capital and other demographic and cultural variables. The interpolation method is a commonly used method in literature (e.g. Kumar et al. 2011; Hilary and Hui 2009; Alesina and La Ferrara 2000; Hasan et al. 2017a, 2017b) .

  4. We employ the average social capital of the neighboring counties within a 100-mile radius as an instrumental variable for social capital. As stated in Jha and Cox (2015), this is a strong IV because the social capital of neighboring counties is similar to the social capital in the given county and the mortgage delinquency in a given county is unlikely to have an effect on the average social capital of the neighboring counties.

  5. Assuming Po ≥ L rules out unsecured debt.

  6. Seiler et al. (2012) document that disadvantages to defaulting include a substantially reduced FICO score, a greater expense and difficulty obtaining future credit, moving expenses (if the home is a primary residence), potential social backlash from family and friends, possible tax implications, and the chance of the lender pursing a deficiency judgment.

  7. It is assumed that in the case of a default the borrower will consume his income Y, instead of giving it to the lender. This assumption is inconsequential for the analysis.

  8. In practice, the lenders will not be able to offer different interest rates to areas with different social capital, as this may be perceived an indirect form of redlining in some cases.

  9. Note that the change in the upper bound of the distribution has no effect on the probability of default. It is the drop in the lower bound that expands the set of prices that fall below the default threshold level of B-D. It is this asymmetric impact of the changes in the upper versus lower bounds on the default probability that drives our next result.

  10. We thank Rupasingha, Goetz, and Freshwater for making their social capital index publicly available on http://aese.psu.edu/nercrd/community/social-capital-resources.

  11. Rupasingha et al. (2006) state that they use “data from the Bureau of the Census, County Business Patterns, USA Counties on CD, National Center for Charitable Statistics, and the Regional Economic Information System” in constructing the social capital index. They also use “the response rate for the Census Bureau’s decennial population and Housing Survey, the percentage of voters who voted in presidential elections, and per capita non-profit organizations obtained from National Center for Charitable Statistics” in constructing the social capital index.

  12. The related literature has widely employed the interpolation method when using local factors, such as demographic, religious, and other cultural factors, to examine the impact of local factors on financial and economic outcomes in their studies (e.g. Kumar et al. 2011; Hilary and Hui 2009; Alesina and La Ferrara 2000; Hasan et al. 2017a, 2017b). The main reason for linear interpolation for local variables such as social capital is that these variables have a consistent pattern over time and they have stable changes over time, when they change. Also note that some studies backfill data for the missing years instead of applying linear interpolation (e.g., Hilary and Hui 2009; Gompers et al. (2003); Hoi et al. 2018). When we use this alternative method and backfill the social capital data for the missing years, we find very similar results. These results can be provided by the authors upon request.

  13. Rupasingha et al. (2006) social capital index provides an updated data for the years 1990, 1997, 2005, 2009, and 2014 on the data website (http://aese.psu.edu/nercrd/community/social-capital-resources). We use interpolation for the years without available data.

  14. We thank the Federal Reserve Bank of New York (FRBNY) for providing the data.

  15. This variable is provided on the website https://geofred.stlouisfed.org/map/. The website states that source of this variable is the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (Federal Reserve Bank of New York and Equifax, Equifax Subprime Credit Population).

  16. It is in $000’s. Similarly, Change in MedianHouseValue is $000’s.

  17. We obtain the annual CPI values from the Minneapolis Fed’s website (https://www.minneapolisfed.org/community/financial-and-economic-education/cpi-calculator-information/consumer-price-index-and-inflation-rates-1913). Both income and median house value variables are standardized and adjusted for inflation. They are in 2000’s dollar values. When we repeat our empirical tests with unstandardized values, we have very similar results and these results can be provided upon request.

  18. Consistent with the literature, we use interpolations of the data for the years without available data for the Census variables as well as the other controls.

  19. We use inflation adjusted standardized income and median house values. When we repeat our empirical tests with unstandardized values, we have very similar results the ones provided in the paper. These results can be provided upon request.

  20. Note that the coefficient value for low social capital is 7–7.5 times the coefficient value for high social capital. However, the difference in the economic impact of Change in MedianHouseValue between two subsamples is small. A one-standard-deviation increase in Change in MedianHouseValue is associated with about a 0.195 standard deviation decrease in mortgage delinquency in the low social capital subsample, and a one-standard-deviation increase in Change in MedianHouseValue is associated with about a 0.13 standard deviation decrease in mortgage delinquency in the low social capital subsample. Thus, while the impact of Change in MedianHouseValue in both subsamples is significant, the difference between the two subsamples is small, and not as big as the impact suggested by the coefficient values.

  21. The propensity score matching analysis employs 0.1 caliper as the maximum distance level in estimating propensity scores.

References

  • Agarwal, S., Chang, Y., & Yavas, A. (2012). Adverse selection in mortgage securitization. Journal of Financial Economics, 105(3), 640–660.

    Google Scholar 

  • Alesina, A., & La Ferrara, E. (2000). Participation in heterogeneous communities. Quarterly Journal of Economics, 115, 847–904.

    Google Scholar 

  • Ambrose, B. W., Sanders, A. B., & Yavas, A. (2016). Servicers and mortgage-backed securities default: Theory and evidence. Real Estate Economics, 44(2), 462–489.

    Google Scholar 

  • Anenberg, E., & Kung, E. (2014). Estimates of the size and source of Price declines due to nearby foreclosures. American Economic Review, 104(8), 2527–2551.

    Google Scholar 

  • Bubb, R., and Kaufman, A. (2009). Securitization and Moral Hazard: Evidence from Lender Cutoff Rule. Federal Reserve Bank of Boston Public Policy Discussion Papers, (09–5).

  • Campbell, J. Y. (2012). Mortgage Market Design. Review of Finance, 17, 1–33.

    Google Scholar 

  • Campbell, J. Y., Giglio, S., & Pathak, P. (2011). Forced sales and house prices. American Economic Review, 101, 2108–2131.

    Google Scholar 

  • Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, S95–S120.

    Google Scholar 

  • Coleman, J. S. (1990). Foundations of social theory. Cambridge: Harvard University Press.

    Google Scholar 

  • Deng, Y., Quigley, J. M., & Van Order, R. (2000). Mortgage terminations, heterogeneity and the exercise of mortgage options. Econometrica, 2, 275–307.

    Google Scholar 

  • Doms, M., Furlong, F., and Krainer, J. (2007). Subprime Mortgage Delinquency Rates. Working paper, SFFRB working paper No. 2007–33.

  • Elul, R. (2016). Securitization and mortgage default. Journal of Financial Services Research, 49, 281–309.

  • FED. (2012). The U.S. Housing Market: Current Conditions and Policy Considerations. White Paper, Board of Governors of the Federal Reserve System.

  • Ferris, S., Javakhadze, D., & Rajkovic, T. (2017). The international effect of managerial social Captial on the cost of equity. Journal of Banking and Finance, 74, 69–84.

    Google Scholar 

  • FICO. (2011). Predicting strategic default. April, white paper.

  • Fisher, L., Lambie-Hanson, L., & Willen, P. S. (2015). The role of proximity in foreclosure externalities: Evidence from condominiums. American Economic Journal: Economic Policy, 7, 119–140.

    Google Scholar 

  • Gerardi, K., Shapiro, A. H., and Willen, P. S. (2008). Subprime outcomes: Risky mortgages, home ownership experiences, and foreclosures. Working paper.

  • Gerardi, K. S., Lehnert, A., Sherlund, S. M., and Willen, P. S. (2009). Making sense of the subprime crisis. Brookings Papers on Economic Activity.

  • Gerardi, K., Rosenblatt, E., Willen, P. S., & Yao, V. (2015). Foreclosure externalities: New evidence. Journal of Urban Economics, 87, 42–56.

    Google Scholar 

  • Ghent, A. C., & Kudlyak, M. (2011). Recourse and residential mortgage default: Evidence from US states. Review of Financial Studies, 24, 3139–3186.

    Google Scholar 

  • Gompers, P., Ishii, J., & Metrick, A. (2003). Corporate governance and equity prices. Quarterly Journal of Economics, 118, 107–155.

    Google Scholar 

  • Guiso, L., Sapienza, P., & Zingales, L. (2004). The role of social capital in financial development. American Economic Review, 94, 526–556.

    Google Scholar 

  • Guiso, L., Sapienza, P., & Zingales, L. (2010). Civic capital as the missing link. In J. Benhabib, A. Bisin, & M. Jackson (Eds.), Handbook of social economics. Oxford: Elsevier Science.

    Google Scholar 

  • Guiso, L., Sapienza, P., & Zingales, L. (2013). Determinants of attitudes toward strategic default on mortgages. Journal of Finance, 68(4), 1473–1515.

    Google Scholar 

  • Gupta, A., Raman, K., and Shang, C. (2016). Social capital and corporate innovation. Bentley University Working Paper.

  • Gupta, A., Raman, K., & Shang, C. (2018). Social capital and the cost of equity. Journal of Banking and Finance, 87(C), 102–117.

    Google Scholar 

  • Harding, J. P., Rosenblatt, E., & Yao, V. (2009). The contagion effect of foreclosed properties. Journal of Urban Economics, 66, 164–178.

    Google Scholar 

  • Hasan, I., Hoi, C., Wu, Q., & Zhang, H. (2017a). Does social capital matter in corporate decisions? Evidence from corporate tax avoidance. Journal of Accounting Review, 55(3), 629–668.

    Google Scholar 

  • Hasan, I., Hoi, C., Wu, Q., & Zhang, H. (2017b). Social capital and debt contracting: Evidence from Bank loans and public bonds. Journal of Financial and Quantitative Analysis, 52(3), 1017–1047.

    Google Scholar 

  • Hasan I., Clark, B., Lai, H., Li, F., & Siddique, A (2020). Social capital and consumer defaults. Journal of Financial Stability.

  • Hilary, G., & Hui, K. W. (2009). Does religion matter in corporate decision making in America? Journal of Financial Economics, 93, 455–473.

    Google Scholar 

  • Hoi, C.H., Q. Wu, and H. Zhang(2018). Does social capital mitigate agency problems? Evidence from chief executive officer (CEO) compensation. Journal of Financial Economics, Forthcoming.

  • Immergluck, D., & Geoff, S. (2006). The impact of single-family mortgage foreclosures on neighborhood crime. Housing Studies, 21, 851–856.

    Google Scholar 

  • Jackson, M. O. (2014). Networks in the understanding of economic behaviors. Journal of Economic Perspectives, 28, 3–22.

    Google Scholar 

  • Jackson, M. O., Rodriguez-Barraquer, T., & Xu, T. (2012). Social capital and social quilts: Network patterns of favor exchange. American Economic Review, 102, 1857–1897.

    Google Scholar 

  • Javakhadze, D., Ferris, S. P., & French, D. W. (2016). Social capital, investments, and external financing. Journal of Corporate Finance, 37, 38–55.

    Google Scholar 

  • Jha, A., & Chen, Y. (2015). Audit fees and social capital. The Accounting Review, 90, 611–639.

    Google Scholar 

  • Jha, A., & Cox, J. (2015). Corporate social responsibility and social capital. Journal of Banking & Finance, 60, 252–270.

    Google Scholar 

  • Keys, B. J., Mukherjee, T. K., Seru, A., & Vig, V. (2010). Did securitization Lead to lax screening? Evidence from subprime loans. The Quarterly Journal of Economics, 125, 307–362.

    Google Scholar 

  • Knack, S., & Keefer, P. (1997). Does social capital have an economic pay off? A cross-country investigation. Quarterly Journal of Economics, 112, 1251–1288.

    Google Scholar 

  • Krainer, J., & Laderman, E. (2014). Mortgage loan securitization and relative loan performance. Journal of Financial Services Research, 45, 39–66.

    Google Scholar 

  • Kumar, A., Page, J. K., & Spalt, O. G. (2011). Religious beliefs, gambling attitudes, and financial market outcomes. Journal of Financial Economics, 102, 671–708.

    Google Scholar 

  • La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. W. (1997). Trust in large organizations. American Economic Review, 87, 333–338.

    Google Scholar 

  • Li, L. (2017). Why are foreclosures contagious? Real Estate Economics, 45(4), 979–997.

    Google Scholar 

  • Putnam, R. D. (1993). Making democracy work: Civic traditions in modern Italy. Princeton: Princeton University Press.

    Google Scholar 

  • Rupasingha, A., Goetz, S. J., & Freshwater, D. (2006). The production of social capital in US counties. The Journal of Socio-Economics, 35, 83–101.

    Google Scholar 

  • Seiler, M. J. (2014). The effect of perceived lender characteristics and market conditions on strategic mortgage defaults. Journal of Real Estate Finance and Economics, 48(2), 256–270.

    Google Scholar 

  • Seiler, M. J., & Walden, E. (2014). Lender characteristics and the neurological reasons for strategic mortgage default. Journal of Real Estate Research, 36(3), 341–362.

    Google Scholar 

  • Seiler, M. J., Seiler, V. L., Lane, M. A., & Harrison, D. M. (2012). Fear, shame, and guilt: Economic and behavioral motivations for strategic default. Real Estate Economics, 40, S199–S233.

    Google Scholar 

  • Seiler, M. J., Lane, M. A., & Harrison, D. M. (2014). Mimetic herding behavior and the decision to strategically default. Journal of Real Estate Finance and Economics, 49(4), 621–653.

    Google Scholar 

  • Treasury (2009). Homeowner Affordability and Stability Plan Fact Sheet. Available at http://www.treasury.gov/press-center/press-releases/Pages/20092181117388144.aspx.

  • White, B. (2010). Underwater and not walking away: Shame, fear, and the social management of the housing crisis. Wake Forest Law Review, 45, 971–1023.

    Google Scholar 

  • Wilkinson-Ryan, T. (2011). Breaching the mortgage contract: The behavioral economics of strategic default. Vanderbilt Law Review, 64(5), 1547–1583.

    Google Scholar 

  • Woolcock, M. (1998). Social capital and economic development: Toward a theoretical synthesis and policy framework. Theory and Society, 27, 151–208.

    Google Scholar 

  • Woolcock, M. (2001). The place of social capital in understanding social and economic outcomes. Canadian Journal of Public Policy, 2, 11–17.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Mihaylo College of Business and Economics, California State University Fullerton, 800 N. State College Blvd, Fullerton, CA, 92831, USA

    Lingxiao Li & Erdem Ucar

  2. School of Business, University of Wisconsin-Madison, 975 University Ave, Madison, WI, 53706, USA

    Abdullah Yavas

Authors
  1. Lingxiao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erdem Ucar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abdullah Yavas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lingxiao Li.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, L., Ucar, E. & Yavas, A. Social Capital and Mortgage Delinquency. J Real Estate Finan Econ 64, 379–403 (2022). https://doi.org/10.1007/s11146-020-09775-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11146-020-09775-4

Keywords

Search

Navigation