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«DiscoVeriNg HomelessNess Volume 13, Number 1 • 2011 U.S. Department of Housing and Urban Development | Office of Policy Development and Research ...»

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Cityscape 135 Cityscape: A Journal of Policy Development and Research • Volume 13, Number 1 • 2011 U.S. Department of Housing and Urban Development • Office of Policy Development and Research Joice In July 2008, Congress passed the Housing and Economic Recovery Act (HERA). Although better known for placing Fannie Mae and Freddie Mac into government conservatorship, HERA also provided $3.92 billion in funding for “emergency assistance for the redevelopment of abandoned and foreclosed homes”2 through a program called the Neighborhood Stabilization Program (NSP)—hereafter, NSP1. In January 2009, Congress appropriated an additional $2 billion— NSP2—through the American Recovery and Reinvestment Act (the Recovery Act).3 Most recently, the Wall Street Reform and Consumer Protection Act provided $1 billion for NSP3, which the U.S. Department of Housing and Urban Development (HUD) allocated in September 2010.4 When referring to a program element common to all three rounds, this article uses the acronym NSP.

The next section discusses the challenges in the housing market leading up to the passage of HERA and presents a justification for the general idea behind NSP. The remainder of this article discusses some of the more specific ideas HUD built into NSP and identifies some questions for continued examination of the program.

Policy Justification A justification for NSP rests on the premise that the foreclosure crisis was both caused and exacerbated partially by a failure in the housing market. Between 2000 and 2006, home prices soared by 90 percent. Shiller (2008) argued that this increase was not justified by market fundamentals and was substantially influenced by market psychology. As prices increase, people develop an expectation that prices should increase; this feedback mechanism pushes prices higher and creates a bubble. Feedback, or contagion, can also occur in the opposite direction; as the housing bubble burst in 2006 and broader economic conditions worsened in 2008, consumer confidence and home builder confidence both began to plummet, ultimately reaching record lows in early 2009 (NAHB, 2009; Short, 2010). Expectations were no longer of home-price increases but of flat home prices and increasing foreclosures.

In the midst of this turmoil and uncertainty, policymakers believed that government action was necessary to stabilize housing markets and instill confidence. The homebuyer tax credit, support for Fannie Mae and Freddie Mac, and the Federal Reserve’s efforts to keep interest rates low all were macroeconomic policies intended to broadly stimulate demand for housing. All applied nationwide, across cities and regions with substantially different housing markets, and were not restricted based on the current condition or ownership of the unit being purchased. Policymakers also considered the idea of a more targeted intervention—a program that would soak up the emerging glut of foreclosed units and help neighborhoods where foreclosures and vacancies were causing particularly severe problems.

Critics of these recent efforts argue that the housing market needs to settle at a new equilibrium point. Such a position assumes that the housing market operates fairly efficiently, that the recent price declines were a necessary correction, and that the foreclosure process is (or should be) a

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mechanism for determining the appropriate price for a property. The consequences of this process are either irrelevant, or considered to be commensurate with the risk that homebuyers and mortgage lenders should anticipate and be responsible for. Policymakers may also worry, however, that declining property values and increasing foreclosures have consequences for the larger community.

Negative externalities resulting from increasing foreclosures could develop through several channels. First, a foreclosed unit may sit vacant and attract crime or vandalism. Second, a foreclosed unit may remain occupied, but occupied by someone with less long-term interest in the neighborhood. This person may be a homeowner demoralized by the prospect of foreclosure, or a renter living there on a temporary basis. Such households may let the property deteriorate. Third, foreclosed properties may be sold at a discount, and then be used as comparables that drive down values for nearby homes.

A substantial body of research on such externalities began to emerge early in the foreclosure crisis.

Immergluck and Smith (2006a) found that the foreclosure rate of a census tract has a statistically significant effect on the amount of violent crime in the neighborhood; an increase of 1 percentage point in the foreclosure rate corresponds to an increase of 2.33 percent in violent crime. They did not find, however, a statistically significant effect of foreclosures on property crime or total crime.

Immergluck and Smith (2006b) analyzed the effect of foreclosures on property values, using a cross-section of foreclosures and single-family home sales in Chicago. The authors acknowledged the potential for reverse causation, because lower property values (negative equity in particular) affect the likelihood of foreclosure, but they included a variable for the neighborhood’s median property value in an attempt to control for this effect. They found that each additional foreclosure within one-eighth of a mile from a house decreases the value of that house by 0.9 percent. When the model is run on only transactions in low- and moderate-income census tracts, the effect is a decrease of 1.4 percent.





Schuetz, Been, and Ellen (2008) also studied the effect of foreclosures on property values, and are better able to address the issue of reverse causation thanks to rich longitudinal dataset. This data set enabled them to more effectively control for pre-existing differences across neighborhoods, which affect both foreclosures and property values. Schuetz, Been, and Ellen used subsequent foreclosures (those that occurred after the transaction that provided the dependent variable observation) to proxy for these unobserved neighborhood conditions, and found that the negative effect of foreclosures on property values is robust to this specification. Schuetz, Been, and Ellen also examined whether foreclosures have a nonlinear effect on property values—whether a threshold effect exists. They found that being near a small number of foreclosures does not depress property values, but beyond a threshold there is a statistically significant negative effect of foreclosures on property values.5 This emerging research suggests that foreclosures have an adverse effect on neighborhood quality, and that effect is amplified in poor neighborhoods and when foreclosures are highly concentrated.

The significant thresholds: more than two foreclosures between 250 and 500 feet away or more than five foreclosures between 500 and 1,000 feet away. Both are limited to foreclosures within 18 months before the dependent variable property transaction.

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Evidence also indicates that the subprime loans that initiated the first wave of foreclosures were concentrated in poor, predominantly minority neighborhoods. As policymakers considered the need for a neighborhood-based housing program, they were also concerned that the neighborhoods likely to be hit hardest by the foreclosure crisis were those least equipped to respond. This environment was the context within which HERA was passed and NSP was authorized.

Program Design

The basic program framework established by the respective statutes was as follows:

• Method of allocation: NSP1 and NSP3 were distributed by formula. HERA specified that the formula be based on the number and percentage of home foreclosures, mortgage defaults, and subprime loans. NSP2 was a competitive grant with some general criteria specified by the Recovery Act that provided considerable flexibility for HUD.

• Eligible uses of funds (mostly the same for NSP1, NSP2, and NSP3):

Financing mechanisms, such as downpayment assistance or shared-equity loans.

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• Property eligibility: Properties targeted by the program generally must be foreclosed, abandoned, or vacant, although these criteria vary subtly by eligible use and across the three rounds of NSP.

• Household eligibility: Households or individuals assisted through the program must make less than 120 percent of the Area Median Income (AMI). A subset of funds must be used for households making less than 50 percent of AMI.

• Community Development Block Grants (CDBG) program rules: Unless otherwise specified, the provisions of Title I of the Housing and Community Development Act of 1974, which governs the CDBG program, apply to NSP as well.

More than 1,200 state and local governments around the country receive CDBG funds and are familiar with the activities that can be funded through the program. This framework made NSP easier to administer than it would have been if HUD had established a new program from scratch.

However, CDBG is a highly decentralized program. Decisions about program design and targeting of funding are all made by grantees, with substantial deference from HUD. Like CDBG, NSP does not prescribe particular strategies and will result in a wide variety of interventions across a wide variety of market conditions. HUD expects (and has already seen in NSP1) substantial variation in the effectiveness of the different grantees; studying this variation should provide lessons for future neighborhood stabilization efforts.

HUD’s role was particularly limited in implementing NSP1 and NSP3. HUD was responsible for developing the funding allocation formulas, interpreting statutory requirements, providing guidance for grantees, and ensuring compliance with laws and regulations.

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In implementing NSP2, HUD had more flexibility and discretion. In many ways, NSP2 was designed to correct perceived flaws in NSP1. NSP1 was distributed by a need-based formula that funded a number of grantees with limited capacity to carry out the program. The scoring criteria specified by the Recovery Act included need, capacity, leveraging potential, and concentration of investment to achieve stabilization. Simply having a foreclosure or vacancy problem was not sufficient to win NSP2 funding; an applicant had to understand its particular problems, describe an appropriate stabilization strategy, and demonstrate the capacity to carry out that strategy.

The reference in the Recovery Act to “concentration of investment to achieve stabilization” is evidence of another important change from NSP1 to NSP2. Some senior HUD staff believe that local officials have a tendency to spread community development funding across a town like peanut butter on bread—a nice even coverage, to ensure that everyone gets a taste and everyone is happy. In the case of NSP, HUD believed that such a geographically dispersed strategy would be extremely inappropriate. HUD wanted NSP to be used like a defibrillator—a forceful government intervention to brace a neighborhood before its heart stops for good. The hope was that such an intervention would restore confidence and allow the market to find an equilibrium and resume functioning. HERA provided some support for this strategy by requiring that grantees give priority emphasis to the “areas of greatest need” (which HUD also refers to as target areas). Some grantees argued, however, that their entire city, county, or state was an area of greatest need, while many others identified a target area covering one-third or more of their jurisdiction. HUD struggled to determine an adequate level of geographic targeting and did not consistently require NSP1 grantees to concentrate on only a few neighborhoods.

With the explicit mandate from the Recovery Act, HUD increased the emphasis on geographic targeting for NSP2. To help grantees identify where to target their funds, HUD created a web-based Geographic Information System (GIS) platform that enabled applicants to research, identify, and submit their target area on line.6 This GIS tool also presented census tract level foreclosure risk scores and abandonment risk scores. To ensure that NSP2 funds were targeted to the areas of greatest need, HUD decided that a target area could be eligible only if the average risk score for the area was at least 18 points out of 20.

These risk scores and targeting requirements have elicited a small amount of controversy. Some NSP participants have suggested that the risk scores understate the problems they face—that the neighborhoods identified by HUD are not actually those with the greatest needs. Others have argued the opposite—that the neighborhoods with the highest risk scores are in such bad shape that they are past the point where a stabilization strategy could be effective. HUD’s response was that the risk scores were estimates, and HUD recognized that both of these critiques could be true in different places. To build in a cushion, HUD required that the average risk score in an applicant’s target area be 18; not every census tract had to have a score of 18. Furthermore, the abandonment risk score and foreclosure risk score offer two different assessments of a neighborhood’s condition, and either could be used to qualify. The targeting requirement is being continued for NSP3, with two additional modifications to increase flexibility. First, the threshold has been lowered from 18 to 17.

Second, because some states have few, if any, areas with a risk score of 17, an area can also qualify if its average risk score is greater than the risk score for 80 percent of the census tracts in that state.

http://www.huduser.org/nspgis/nsp.html.

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Some NSP participants have expressed a more general opposition to the requirement of targeting funds. For a period of time from mid-2009 to late 2009, NSP1 grantees were having great difficulty getting their programs off the ground. Some grantees believed that the targeting requirement was part of the problem, because it limited opportunities for REO (Real Estate Owned) acquisition and hindered opportunities for bulk purchases. HUD has responded to this challenge by using the target areas that grantees have submitted to develop a First Look program for Federal Housing Administration REOs. HUD is also working to extend this program to other institutions, potentially streamlining the process for grantees to purchase REOs.



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