With data from the U.S. Bureau of the Census 1970 Public Use Samples and 1980 Public Use Microdata Sample tape files for 34 metropolitan statistical areas, the authors examine cross-metropolitan variations in Puerto Rican poverty, using an instrumental variables regression model. The analyses highlight the role of residential segregation and economic restructuring on Puerto Rican poverty in 1970 and 1980. Decomposition of changes during the 1970s revealed that the primary sources responsible for increased Puerto Rican poverty rates were structural: The effects of segregation on poverty grew stronger during the decade, and the ability of manufacturing employment and self-employment to attenuate poverty grew weaker.
This study estimates the size and characteristics of the potential homeowner market and examines the relative default risks associated with expanded homeownership among lower-income, underserved households.
No abstract is provided for this article.
An econometric model of 1970–1980 neighborhood racial changes is estimated for census tracts in Cuyahoga County (Cleveland), Ohio. Results indicate that 1970 tract percentage black, interacted with estimated segregationist sentiment for white residents, is the dominant explanatory variable, with its maximum marginal impact on loss of whites occurring at 35% black. Proximity to majority black tracts and intensity of white segregationist sentiments are also strongly associated with large variations in decadal racial changes. These racial contextual factors both abet white out-migration and deter white in-migration. “Affirmative marketing” policies conducted by the Shaker Heights and Cleveland Heights jurisdictions resulted in greater integration of initially all-white areas and less racial change in substantially integrated areas.
This article conducts the first contextual analysis of ethnic-based discrimination in an Australian rental housing market: metropolitan Sydney. Logistic regression is employed to investigate how the likelihood of five behaviors by rental agents that may favor Anglo home seekers varies according to characteristics of the agent, home seeker, dwelling, and neighborhood. We find that several forms of discrimination favoring Anglos are consistently more likely in neighborhoods characterized by lower crime rates and shares of renter households, regardless of the ethnicity of the agent. Other patterns are consistent with the hypothesis that, in general in the Sydney rental market, agents regardless of ethnicity are motivated to discriminate by statistical discrimination. Our result that profit, not prejudice, drives discrimination implies that it will prove resilient to unfettered housing market forces and changes in societal ethnic tolerance, but instead, must be addressed through enhanced civil rights enforcement strategies.
George Galster explains how children are harmed by growing up in predominantly poor neighborhoods. He also recommends ways to improve federal and state housing programs to avoid high concentrations of poverty. George Galster is an Urban Institute Affiliated Scholar and the Clarence B. Hilberry Professor of Urban Affairs at Wayne State University.
We advance scholarship related to home foreclosures and neighborhood crime by employing Granger causality tests and multilevel growth modeling with annual data from Chicago neighborhoods over the period 1998–2009. We find that completed foreclosures temporally lead property crime and not vice versa. More completed foreclosures during a year both increase the level of property crime and slow its decline subsequently. This relationship is strongest in higher income, predominantly renter-occupied neighborhoods, contrary to the conventional wisdom. We did not find unambiguous, unidirectional causation in the case of violent crime and when filed foreclosures were analyzed.
No abstract is provided for this article.
This paper estimates the life-cycle costs of housing for persons with mental illness using 5-year and 30-year holding periods and discount rates of 3.5, 5.75, and 8.0%. Life-cycle costs are between 5 and 7% higher in buildings occupied only by mentally ill tenants compared to buildings with no mentally ill tenants. However, the economies of scale in maintenance and repair that exist in buildings occupied by the non-mentally ill are not observed in buildings with mentally ill tenants. Additionally, buildings located in lower-quality neighborhoods have lower life-cycle costs when the tenants are mentally ill, just the reverse of the case for the general population.
Infill investments are argued to mitigate environmental footprints, regenerate places and accommodating population growth, but frequently generate local opposition. However, there is a dearth of knowledge around how different types of infill affect different segments of local property markets, how persistent effects are and how far they reach. Using detailed geocoded infill development activity and sales data, we test the price level and trajectory impacts of five infill types, distinguished by the net scale of additional dwellings, on property prices within five concentric 100-meter rings. Using an adjusted interrupted time-series estimation strategy with locality, property and neighborhood characteristic controls we find that developments that generate a net increase in dwellings of four or less, typically result in an appreciation in the average sales prices of proximate dwellings. Moderate and large-scale developments generate negative price effects, but these effects predominantly affect apartments and townhouses, not the dominant detached house submarket. Over time, amenity effects and local market potential may even have a further positive expectation effect on detached house prices. Infill type differentiation shows that urban densification may result in positive affordability outcome in the apartment submarket, but has the opposite effects in the detached house submarket. Divergent price trajectories also contribute to widening wealth disparities.
Every January, the US endeavors to count all of the individuals experiencing homelessness on a given night (General Definition of Homeless Individual, 1987).Local agencies called Continuums of Care tally up everyone residing in emergency shelters and transitional housing within their service areas, and send out volunteers to document people sheltering in cars or tents and other places "not designed for or ordinarily used as a regular sleeping accommodation for human beings" (42 USC § 11302).Last year, more than 580,000 people were experiencing homelessness according to this count-a record high (National Alliance to End Homelessness (NAEH), 2023).And yet this number is almost certainly an underestimate (people experiencing unsheltered homelessness might reasonably prefer to avoid public detection).Neither does it recognize forms of severe housing insecurity that might be considered homelessness under another definition (such as doubling up or sleeping in a motel).In countries around the world, there is much to learn about who experiences homelessness, in what way, and how best to serve them.As we embark on a new year of enumerating and fighting homelessness, this focus issue of Housing Policy Debate gathers nine articles shedding light on these efforts.The issue can be split roughly into two halves, beginning with a set of articles that try to better understand the experience of homelessness.
This article argues that interracial differentials in mortgage default rates are an unreliable indicator of racial discrimination in mortgage markets. First, minority applicants may be approved at nondiscriminatory institutions and thereby end up in the pool of mortgagors, even though they were first discriminated against at other institutions. Second, even with no mortgage discrimination, the expected default risk of minority mortgagors overall is probably higher than that of white mortgagors overall. Thus, even if discrimination eliminated some of the riskier minority applicants, it is not necessarily true that the default rate of minority mortgagors will be lower than that of whites.
:This article discusses the appropriate measurement of neighborhood racial integration and proposes a new operational definition. A neighborhood is integrated if currently (1) its stock of households may be classified as "mixed" (no single group comprises more than 75% of the neighborhood's population), and (2) the flow of households into and out of this stock is such that it will be so classified for a decade in the future. The article mathematically develops stability boundaries that researchers and policy makers can use to assess the degree to which contemporaneous flows of households into and out of mixed neighborhoods will render them integrated in the future.
This rejoinder addresses the response to articles by Berkovec, Canner, Gabriel, and Hannan. While our earlier comments emphasized the biases in the default approach, we focus here on the basic disagreement: whether, given those biases, the default approach provides a viable test for mortgage lending discrimination. We argue that the default approach does not provide such a test. The Berkovec, Canner, Gabriel, and Hannan research (BCGH, 1994 and in this issue) provides a careful empirical look at racial differences in loan default rates using data on Federal Housing Administration (FHA) mortgages. In this rejoinder, however, we focus on the key issues that separate us. First, we express our deep concerns about the basic conclusion of the BCGH article; then, with those concerns in mind, we suggest a change in future default specifications. In addition, we discuss the problems inherent in their suggestion that default rates may be useful for partitioning the observed incidence of racial discrimination into two different types: statistical and prejudiced based. Our fundamental disagreement with BCGH centers around the following statement, which is found in their article (in other words) and appears in their response to our critiques: “… FHA loan performance data do not support a finding of widespread systematic discrimination in mortgage lending due to lender prejudice.” Although they acknowledge that their approach may suffer from a variety of biases and cannot prove that discrimination does not exist, they argue that proof is too high a standard for any empirical test. In response, we propose an alternative standard: Performance analyses should not be used to identify discrimination in mortgage lending unless it is demonstrated that these analyses are at least as effective as relevant alternative analyses, such as traditional analyses based on loan approval data. We conclude that the default approach fails to meet this standard under virtually all circumstances. Consider the two key assumptions referred to by BCGH as no omitted variable bias and no statistical discrimination. The first assumption implies that all unobserved variables known to the lender are uncorrelated with race. If that is not so, the BCGH results are biased away from finding discrimination. In this case, BCGH point out—and we agree— loan application studies are also biased, and the bias is in favor of finding discrimination.
No abstract is provided for this article.
(2003). Neighbourhood effects on social opportunities: the European and American research and policy context. Housing Studies: Vol. 18, No. 6, pp. 797-806.
We conduct an impact analysis of the Denver, Colorado, Housing Authority's Home Ownership Program (HOP) employing quasi experimental methodologies (i.e., nearest-neighbor matching, inverse probability weighting with regression adjustment) that permit causal inferences of program impacts with substantial confidence. HOP is an unusual, enhanced variant of the Family Self-Sufficiency program that incentivizes and assists participants' purchase of a home. We analyze whether, compared with the control group, HOP participants exhibited significantly greater earnings growth during the program, enhanced economic security, and rates of home buying. We find that participants with a high intensity of treatment showed significant improvement in all outcomes. Results are robust to model specification and insensitive to omitted variable bias typically found in the social sciences. We conclude that a well-conceived and well-executed public housing authority program aimed at building the financial, human and social assets of low-income households receiving housing assistance can yield substantial benefits to participants.
