Publications

  • What Can We Learn about the Low Income Housing Tax Credit Program by Looking at the Tenants?

    Using tenant-level data from fifteen states that represent more than thirty percent of all Low Income Housing Tax Credit (LIHTC) units, this paper examines tenant incomes, rental assistance and rent burdens to shed light on key questions about our largest federal supply-side affordable housing program. Specifically, what are the incomes of the tenants, and does this program reach those with extremely low incomes? What rent burdens are experienced, and is economic diversity within developments achieved? We find that more than forty percent of tenants have extremely low incomes, and the overwhelming majority of such tenants also receive some form of rental assistance. Rent burdens are generally higher than for HUD housing programs, but vary greatly by income level and are lowered by the sizable share of owners who charge below maximum rents. Finally, we find evidence of both economically diverse developments and those with concentrations of households with extremely low incomes.

  • Pathways After Default: What Happens to Distressed Mortgage Borrowers and Their Homes?

    We use a detailed dataset of seriously delinquent mortgages to examine the dynamic process of mortgage default – from initial delinquency and default to final resolution of the loan and disposition of the property. We estimate a two-stage competing risk hazard model to assess the factors associated with whether a borrower behind on mortgage payments receives a legal notice of foreclosure, and with what ultimately happens to the borrower and property. In particular, we focus on a borrower’s ability to avoid a foreclosure auction by getting a modification, by refinancing the loan, or by selling the property. We find that the outcomes of the foreclosure process are significantly related to: the terms of the loan; the borrower’s credit history; current loan-to-value and the presence of a junior lien; the borrower’s post-default payment behavior; the borrower’s participation in foreclosure counseling; neighborhood characteristics such as foreclosure rates, recent house price depreciation and median income; and the borrower’s race and ethnicity.

  • Pathways to Integration: Examining Changes in the Prevalence of Racially Integrated Neighborhoods

    Few researchers have studied integrated neighborhoods, yet these neighborhoods offer an important window into broader patterns of segregation.  We explore changes in racial integration in recent decades using decennial census tract data from 1990, 2000, and 2010.  We begin by examining changes in the prevalence of racially integrated neighborhoods and find significant growth in the presence of integrated neighborhoods during this time period, with the share of metropolitan neighborhoods that are integrated increasing from just under 20 percent to just over 30 percent.  We then shed light on the pathways through which these changes have occurred.  We find both a small increase in the number of neighborhoods becoming integrated for the first time during this period and a more sizable increase in the share of integrated neighborhoods that remained integrated.  Finally, we offer insights about which neighborhoods become integrated in the first place and which remain stably integrated over time.

  • American Murder Mystery Revisited: Do Housing Voucher Households Cause Crime?

    In recent years, the U.S. Department of Housing and Urban Development (HUD) has shifted resources from public housing to the Housing Choice Voucher (HCV or “voucher”) program. There were 2.2 million vouchers nationwide in 2008, compared to 1.2 million public housing units. Although the academic and policy communities have welcomed this shift, community opposition to vouchers can be fierce, due to perceptions that voucher-holders will both reduce property values and heighten crime. Despite the public concerns, however, there is virtually no research that systematically examines the link between the presence of voucher holders in a neighborhood and crime. Our paper uses longitudinal, neighborhood-level crime and voucher utilization data in 10 large U.S. cities over 12 years, and finds voucher-holders moving to a neighborhood does not, in fact, increase crime. We do see, on the other hand, that households with vouchers tend to move to communities when crime rates are rising.

  • Loan Modifications: What Works

    We use a unique dataset that combines data on loan, borrower, property, and neighborhood characteristics of modified mortgages on properties in New York City to examine the determinates of successful modifications. From November 2007 through March 2011, over 2.1 million mortgages were modified in the United States, and policymakers have heralded such modifications as a key to addressing the ongoing foreclosure crisis. This dataset includes both HAMP modifications and proprietary modifications. The analysis builds upon a prior paper in which the determinants of loan modifications were examined.

  • Determinants of the Incidence of Loan Modifications

    Loan modifications ensure that borrowers avoid foreclosure and save their credit record. These modifications are also beneficial to the neighborhoods in which these borrowers reside, preventing vacancies and high rates of turnover. This analysis looks at loan delinquency and repayment plan data from New York City borrowers to provide the strongest predictors of modifications or liquidation of property. In this paper, we answer key questions about loan modifications, including how the identity, property or neighborhood of the borrower affects the likelihood of receiving a modification. We also look at the role of residential segregation, as well as the identity of the loan’s servicer as an influence on variations in borrower access to loan modifications.

  • The Role of Neighborhood Characteristics in Mortgage Default Risk: Evidence from New York City

    We construct a database of non-prime hybrid adjustable and fixed rate mortgages from New York City that augments a rich set of loan and borrower risk characteristics with a variety of census tract level neighborhood characteristics. We find that these neighborhood characteristics are important for default behavior, even after an extensive set of controls. First, default rates increase with the rate of foreclosure notices and the number of lender-owned properties (REOs) in the tract. Second, default rates for home purchase mortgages are higher in predominantly black tracts, regardless of the borrower’s own race. We explore possible explanations for our findings.

  • The Low Income Housing Tax Credit and Racial Segregation

    This paper addresses a critical but almost unexamined aspect of the Low Income Housing Tax Credit (LIHTC) program—whether its use (and in particular, the siting of developments in high poverty/high minority neighborhoods), is associated with increased racial segregation. Using data from HUD and the census, supplemented with data on the racial composition of LIHTC tenants in three states, we examine three potential channels through which the LIHTC could affect segregation: where LIHTC units are built relative to where other low income households live, who lives in these tax credit developments, and changes in neighborhood racial composition in neighborhoods that receive tax credit projects. The evidence on each of these channels suggests that LIHTC projects do not contribute to increased segregation, even those in high poverty neighborhoods. On net, we find that increases in the use of tax credits are associated with declines in racial segregation at the metropolitan level.

  • Creating a Metric of Educational Opportunities for Assisted Households

    The U.S. Department of Housing and Urban Development’s strategic plan identifies the use of “housing as a platform for improving quality of life” as one of its five strategic goals. It further establishes a sub-goal to improve educational outcomes and early learning and development for children in HUD-assisted housing. This paper is intended to advise HUD about how to use readily available data to create a metric for school quality. This metric is the measure of success in providing “access to schools scores at or above the local average” for children in assisted households. The researchers recommend a ratio that compares the test scores of the elementary schools nearest subsidized households to the test scores of other schools in that same county or metropolitan area, with perhaps a comparison to the schools nearest other renters or low-income households. Using this local-comparison ratio can overcome differences in state methodologies for evaluating schools, differences in homeownership rates across metropolitan areas, and differences in income levels. This score will allow HUD to identify metropolitan areas to target for mobility efforts and to track progress over time.

  • Community Benefits Agreements: A New Local Government Tool or Another Variation on the Exactions Theme?

    Community benefits agreements (CBAs) are the latest in a long line of tools neighbors have used to protect their neighborhood from the burdens of development, and to try to secure benefits from the proposed development. This Article canvasses the benefits and drawbacks various stakeholders perceive CBAs to offer or to threaten, and reviews the legal and policy questions CBAs present. It recommends that local governments avoid the use of CBAs in land use approval processes unless the CBAs are negotiated through processes designed to ensure the transparency of the negotiations, the representativeness and accountability of the negotiators, and the legality and enforceability of the CBAs’ terms.