«Urban Problems and sPatial methods VolUme 17, nUmber 1 • 2015 U.S. Department of Housing and Urban Development | Office of Policy Development and ...»
Furthermore, in many cases, this step will be only the first in a more indepth spatial analysis, especially because the hexagonal lattice is a very suitable input for further analysis with subsequent spatial statistical techniques (for example, cluster detection or spatial regression models).
Acknowledgments The Department of Geography and the Vice President for Research at the University of Kentucky supported this work.
Authors Ate Poorthuis is a Ph.D. candidate in the Department of Geography at the University of Kentucky.
Matthew Zook is a professor in the Department of Geography at the University of Kentucky.
References Bland, J. Martin, and Douglas G. Altman. 2000. “The Odds Ratio,” BMJ 320 (7247): 1468.
Burt, Peter J. 1980. “Tree and Pyramid Structures for Coding Hexagonally Sampled Binary Images,” Computer Graphics and Image Processing 14 (3): 271–280.
Carr, Daniel B., Anthony R. Olsen, and Denis White. 1992. “Hexagon Mosaic Maps for Display of Univariate and Bivariate Geographical Data,” Cartography and Geographic Information Systems 19 (4): 228–236.
Clauset, Aaron, Cosma R. Shalizi, and Mark E. Newman. 2009. “Power-Law Distributions in Empirical Data,” SIAM Review 51 (4): 661–703.
Crampton, Jeremy W., Mark Graham, Ate Poorthuis, Taylor Shelton, Monica Stephens, Matthew W. Wilson, and Matthew Zook. 2013. “Beyond the Geotag: Situating ‘Big Data’ and Leveraging the Potential of the Geoweb,” Cartography and Geographic Information Science 40 (2): 130–139.
Edwards, Anthony W. 1963. “The Measure of Association in a 2 x 2 Table,” Journal of the Royal Statistical Society Series A (General): 109–114.
Morris, Julie A., and Martin J. Gardner. 1988. “Statistics in Medicine: Calculating Confidence Intervals for Relative Risks (Odds Ratios) and Standardised Ratios and Rates,” British Medical Journal (Clinical Research ed.) 296 (6632): 1313–1316.
Poorthuis, Ate, and Matthew Zook. 2014. “Artists and Bankers and Hipsters, Oh My! Mapping Tweets in the New York Metropolitan Region,” Cityscape 16 (2): 169–172.
R Core Team. 2014. R: A Language and Environment for Statistical Computing. Vienna, Austria:
R Foundation for Statistical Computing. http://www.R-project.org/.
Scott, David W. 1988. “A Note on Choice of Bivariate Histogram Bin Shape,” Journal of Official Statistics 4 (1): 47–51.
Shelton, Taylor, Ate Poorthuis, Mark Graham, and Matthew Zook. 2014. “Mapping the Data Shadows of Hurricane Sandy: Uncovering the Sociospatial Dimensions of ‘Big Data,’” Geoforum 52:
Snow, John. 1855. On the Mode of Communication of Cholera. London, United Kingdom: Churchill.
Wilson, Ron. 2013. “Changing Geographic Units and the Analytical Consequences: An Example of Simpson’s Paradox,” Cityscape 15 (2): 289–304.
160 Urban Problems and Spatial Methods Refereed Papers Refereed papers that appear in Cityscape have undergone a thorough and timely double-blind review by highly qualified referees. The managing editor reviews submitted manuscripts or outlines of proposed papers to determine their suitability for inclusion in this section. To submit a manuscript or outline, send an e-mail to email@example.com.
Carolina K. Reid University of California, Berkeley Carly Urban Montana State University Abstract As mortgage foreclosures spiked beginning in 2007, federal policymakers focused on loan modifications as a primary tool for preventing foreclosure and initiated programs to increase the number and effectiveness of loan renegotiations. Yet, loan modifications are largely undertaken at the discretion of private loan servicers and are not as transparent as lender mortgage decisions. Systematic differences are possible in the types of loan modifications that borrowers receive. To be specific, borrowers of color may be receiving less favorable modification terms than comparably situated White borrowers.
Because the terms of a loan modification influence the likelihood that a borrower will be able to retain his or her home, it is important to understand who gets what kind of modification and whether that modification succeeds in preventing foreclosure.
This study uses data on a national sample of approximately 42,000 privately securitized subprime loans originated between 2004 and 2006 to examine modification types and foreclosure outcomes by race and ethnicity. We find no evidence of significant differences in modification types across borrowers; indeed, we find that Black, Hispanic, and Asian borrowers receive slightly larger reductions in monthly payments than comparably situated non-Hispanic White borrowers. The results also reveal that loan modifications that entail payment reductions reduce the likelihood of redefault and foreclosure 1 year after modification. This finding is consistent across all racial and ethnic demographic
(continued) groups. The research suggests that federal efforts to incentivize modifications have helped keep borrowers in their homes, but the research also reveals the need for additional research into servicing and loss-mitigation practices and their role in sustaining homeownership during periods of economic distress.
Introduction The recent foreclosure crisis and the resulting erosion of family wealth and neighborhood stability have raised critical questions about the policies and programs that are needed to sustain homeownership. While policy has focused on consumer protections in the mortgage lending market and the terms by which borrowers access credit, an equally important focus is what happens after loan origination. Mortgage-servicing, collections, and loss-mitigation practices should be central to the dialogue around how to promote homeownership while reducing the costs of foreclosures on borrowers, communities, and the overall U.S. economy.
Compared with the vast research and literature about mortgage loan application and origination outcomes, however, mortgage-servicing practices have received fairly little research attention. One barrier to studying loan servicing and loss-mitigation practices is that mortgage modifications are largely at the discretion of loan servicing firms, and modification terms and outcomes are not as systematically transparent as loan application approvals and denials.
This lack of information stands in stark contrast to the highly transparent process used to track mortgage loan application approvals and denials under the Home Mortgage Disclosure Act (HMDA). In addition, the process of modifying a loan is highly individualized, time consuming, and “more art than science.”1 As a result, consumer advocates have raised the concern that the loan modification process could unfairly burden historically underserved borrowers—especially those who lack experience and knowledge of dealing with a lending institution. For example, borrowers who do not speak English or who may distrust banking institutions may fail to pursue a loan modification, or they may not be able to negotiate the best modification terms.
Race or perceived race could also serve as a proxy that servicers use for decisionmaking on modifications, especially if these borrowers are deemed less sophisticated, more time consuming, and, therefore, more costly to serve. Understanding whether modification outcomes are different by race or ethnicity is especially important given the disparate impact of the foreclosure crisis on Black and Hispanic households (Bocian et al., 2011) and the role that homeownership plays in the racial wealth gap (Oliver and Shapiro, 2006).
As quoted in Andrews and Witt (2009: 1): “It’s more art than science,” said Guy Cecala, publisher of Inside Mortgage Finance. “Who knows whether the borrower will default, what the value of the property is, what will happen to home values,” he said. “I’m skeptical of all of it.”
In this article, we use a unique dataset that merges national data on the loan performance of subprime home mortgages from more than 100 servicers with data on borrower demographics reported as part of HMDA. With these data, we are able to examine national trends in loan modification types by borrowers’ race and ethnicity and to assess the subsequent outcomes of those modified loans for a large sample of subprime loans. Previous research to date has not found racial disparities in the incidence of loan modifications (Been et al., 2013; Collins and Reid, 2010), but these studies have not examined the changes in loan terms by race, nor have they assessed whether differences in modification terms lead to different rates of redefault after.
Our findings suggest that, conditional on a loan having modified terms, there are no significant racial or ethnic differences in the types of modifications that borrowers receive. In fact, we find that controlling for a range of borrower, loan, and housing market characteristics, minorities are equally likely to receive a loan modification that involves lowered interest rates or principal balances. When we examine the amount of change in monthly payments, we find that Black, Hispanic, and Asian borrowers are all more likely to receive a slightly larger reduction than White borrowers, although the amount is small. In terms of the effectiveness of loan modifications, we find that modifications reduce the likelihood of subsequent redefault and foreclosure, and that the terms of the modification influence its effectiveness, even after controlling for a wide range of variables. We do not find significant differences in redefault rates across racial or ethnic groups.
This study proceeds as follows. The first section following this introduction provides a brief background on the evolution of federal loan modification policies, including the federal Home Affordable Modification Program (HAMP). The second section reviews the existing literature on loan modifications, focusing on studies that have examined modification outcomes by race and ethnicity. The third section describes our data and methodology and provides descriptive statistics for our sample. The fourth section presents our findings. The article concludes with the implications of this research for public policy and suggests avenues for future research.
Evolution of Loan Modification Efforts Since the start of the foreclosure crisis in 2007, mortgage servicing has garnered increased attention for its role in processing mortgage delinquencies. As the interface between borrowers and investors, servicers are often the ones that make the decision to either grant a loan modification or start foreclosure proceedings. Mortgage loan servicers2 have a number of options open to them in response to a borrower in default: approve a loan modification, offer an alternative such as a short sale, or pursue a foreclosure. Servicers may pursue these options simultaneously, or even encourage borrowers to submit modification applications and then fail to act on the application, request extensions and more data, or require that the borrower initiate the entire process again sometime down the road.
Although a mortgage loan may be serviced by a third party or by a lender, we use the term “servicer” to indicate the party responsible for reporting to lenders and investors in a security about the status of each loan each month.
In addition to significant variation in the loan modification process, loans can be modified in multiple ways, and not always in ways that are favorable to the borrower. A common form of loan modification occurs when a servicer adds payment arrears to the total loan balance and then calculates a new monthly payment that will amortize the increased balance during the life of the loan. This type of modification generally increases the monthly payment amount and the overall amount of debt (White, 2009a, 2009b). A second type of modification—generally used on adjustable rate mortgages (ARMs)—is to freeze the interest rate and not permit it to reset at a higher rate. With a third type, a servicer can permanently reduce the interest rate on a loan to reduce the monthly payment, while leaving the balance of the mortgage the same. Finally, a servicer can choose to reduce the loan balance or principal, which reduces the overall amount of the loan. A principal reduction is believed to be particularly beneficial to homeowners whose house values are significantly lower than the amount of their mortgage, commonly referred to as being “under water.” Recent research has suggested significant heterogeneity among servicers in terms of the types of resolutions they offer to borrowers (Agarwal et al., 2012). Early loan modification efforts were solely proprietary and voluntary in nature, and they did little to help delinquent borrowers. As the foreclosure crisis extended into 2008, prompting a large-scale recession and high rates of unemployment, pressure mounted on the federal government to scale up efforts to modify loans and prevent foreclosures. In February 2009, the U.S. Department of the Treasury (hereafter, Treasury) rolled out the federal government’s landmark foreclosure prevention initiative, the Making Home Affordable (MHA) program, which included the Home Affordable Modification Program (HAMP). HAMP was designed to overcome barriers to loan modification by encouraging servicers to bring loan payments in line with borrowers’ incomes (GAO, 2014). Under the program, eligible borrowers work with the servicer to reduce their monthly payment to 38 percent of their income, and then HAMP provides a government subsidy to further reduce the payment to 31 percent. Servicers also receive an upfront fee of $1,000 for each modification, plus “pay for success” fees on performing modified loans of $1,000 per year for up to 5 years, thus providing servicers a financial incentive to initiate modifications that help keep borrowers in their homes.3 Borrowers are eligible for a HAMP modification on first lien loans for owner-occupied properties with an unpaid principal balance of less than $729,750, originated on or before January 1, 2009.
Since its launch, HAMP has been revised several times to extend its reach and effectiveness.