325 publications from this institution
This report charts the evolution of American urban policy since the 1960s to help readers understand attempts to make our cities more livable and what these attempts reveal about the policymaking process and policy research and how that research has influenced American urban policy. Nine core topics in the urban social agenda are analyzed. They are economic development, poverty, family support and social welfare, housing, land use and transportation, education, drug abuse, racial discrimination and segregation, and intergovernmental financial arrangements. A chapter describing the evolution of the Urban Institute and a chapter on managing urbanization in the developing world are also included.
The literature on urban sprawl confuses causes, consequences, and conditions. This article presents a conceptual definition of sprawl based on eight distinct dimensions of land use patterns: density, continuity, concentration, clustering, centrality, nuclearity mixed uses, and proximity. Sprawl is defined as a condition of land use that is represented by low values on one or more of these dimensions. Each dimension is operationally defined and tested in 13 urbanized areas. Results for six dimensions are reported for each area, and an initial comparison of the extent of sprawl in the 13 areas is provided. The test confirms the utility of the approach and suggests that a clearer conceptual and operational definition can facilitate research on the causes and consequences of sprawl. Keywords: Land use/zoningUrban environment
Removals of dams in the U.S have been growing exponentially, for reasons related to hazard mitigation, esthetic or recreational enhancements, and improved ecological and hydrological functions. We investigate whether these benefits from dam removal accrue disproportionately to neighborhoods inhabited primarily by non-Hispanic whites, thereby exploring a new frontier of environmental justice research. We analyzed dam removals since 2010 using national data on existing dams, removed dams, and demographics. The Northeast had almost half of the overall removals, while the South had the fewest. Nationally, dams were more likely to be removed if they were shorter, older, made of masonry or stone, and whose primary purpose was hydroelectric. Additionally, dams were removed from areas with more non-Hispanic whites compared to areas with existing dams. Regionally, we find that in the South, the probability of a dam being removed since 2010 is positively associated with the proportion of nearby white residents, even after controlling for dam purpose, construction type, age and height. This disparate racial impact can be traced to dams owned by local and state governments in the South, which we suggest is a consequence of the political power of white homeowners in the context of a permissive regulatory environment.
Since 1992, the federal government has established regulations encouraging the government-sponsored enterprises (GSEs) Fannie Mae and Freddie Mac to purchase home mortgages originated in neighborhoods traditionally underserved by financial institutions, with the aim of stimulating housing-market activity within such neighborhoods. This research tests this proposition empirically through an econometric analysis of variations in secondary mortgage market activity and single-family home prices across underserved census tracts in Cleveland, Ohio, from 1993 to 1999. We find no large or statistically significant relationship between variations in secondary-market purchasing rates of home-purchase mortgages in underserved neighborhoods and home prices one or two years hence, controlling for a rich variety of dwelling and neighborhood characteristics. These conclusions follow both for GSE and other sectors of the secondary market. We find some evidence that the secondary market was more responsive to changes in home prices than vice versa. We offer a possible explanation and draw policy implications.
This exploratory research probes the advertising practices in free real estate booklets distributed at retail outlets. Specifically, it analyzes the advertising of the five largest real estate companies operating in Memphis, Tennessee, as represented in the Real Estate News booklet during 1984–1986. Multiple regression analysis reveals that, compared to real estate areas having less than 5% black population, areas with 30–49.9% black population had: (1)a 90% lower rate of ads where the real estate company itself was marketed, (2) a 92% lower rate of school district notations in ads, and (3)a 42% lower rate of ads where a favorable adjective described the area. The authors conclude that such advertising practices render racially mixed areas less visible to white homeseekers, with grave economic and social consequences.
Background: Federal policy has increasingly sought to build financial capability, earnings, and assets of subsidized housing recipients. Objective: We conduct a benefit–cost analysis of the Denver Housing Authority’s (DHA) innovative Home Ownership Program (HOP), which incentivizes participants to increase earnings, build wealth, and purchase homes. Research design, subjects, and measures: In assessing HOP participant benefits (earnings, home-buying, and positive exits from DHA), we use parameter estimates from quasi-experimental methods (i.e., propensity score matching) that permit drawing causal inferences of program impacts. Impact estimates are robust to alternate model specification and mostly insensitive to omitted variable bias found in the social sciences. We deploy a comprehensive accounting framework, distinguishing benefits and costs accruing to program participants, nonparticipants (other citizens, taxpayers, and governments), and society as a whole. We use Monte Carlo simulation techniques to approximate distributions of benefit and cost parameters, thereby ascertaining how reliably participation in HOP yielded net benefits compared to if families had continued to receive housing assistance during the same period. Results: We estimate a net social benefit from HOP of US$6,015 per participant. The simulated standard deviation was only a third of this value and 99.9% of simulations returned positive net social benefits. Conclusion: We conclude with a high degree of statistical confidence that HOP produced substantial net benefits to society as a whole, program participants, and nonparticipants alike. HOP offers strong potential for poverty alleviation among housing subsidy recipients and should be replicated.
We advance scholarship about how macroeconomic forces differentially manifest themselves across local spaces by developing a holistic conceptual framework and empirical analyses involving multilevel change modeling. Unlike prior work, we examine differential rates of change in neighborhood indicators. We illustrate our approach with Chicago data measuring the crime, housing, and economic domains of neighborhood quality of life over the 2000–2009 period. We find that the local dynamic manifestations of macroeconomic cycles were far more nuanced than have been previously observed. Neighborhood indicators moved along distinct trajectories, sometimes but not necessarily tracking each other or the overall business cycle, and they changed with varied intensities. The Great Recession of 2006–2009 had disparate negative impacts on lower-income and minority-occupied neighborhoods' local job opportunities, home prices, and home foreclosures, though this was not true for credit or crime indicators. Credit indicators performed geographically much differently than in the prior Chicago recession. Key words: neighborhoodsmultilevel change modelsdisparate impactbusiness cycles Acknowledgements This research was supported from a grant from the MacArthur Foundation to MDRC related to the evaluation of the New Communities Program. The opinions expressed in this article are of the authors and do not necessarilyrepresent those of MDRC, the Foundation, or their respective Boards of Trustees. Notes 1 2The Census tract designations used for these transformations are the definitions created after the 2000 decennial Census; data collected or assembled using earlier designations was transformed to the 2000-era designations using the relational matrices published by the US Census Bureau. For most of the neighborhoods, the definitional boundaries align with tract boundaries such that the neighborhood-level measure is the aggregation of the tract-level measure. In cases where this is not true, the tract values were apportioned between multiple neighborhoods based on the distribution of the tract's population between the multiple neighborhoods. 2 3With multiple incidents, the report is classified in the UCR category of the most serious crime (generally, the crime with the highest potential penalty). Note that these are police reports and do not reflect later adjudication of the incident (e.g., an assault recorded on the initial report as a criminal act later adjudicated as justifiable self-defense is still included). 3 4HMDA data are used instead of sales price data due to the relatively long time series available; HMDA data was available starting in 1992 while the sales price data was only available as two incongruent time series that covered a more limited period. The HMDA and sales price data exhibited the same trends for the times in which we had overlapping coverage. Galster et al. (Citation2005) demonstrated the value of HMDA data as a source for constructing neighborhood indicators. 4 5Both filed and completions data exclude ownership transfers that occur as the result of financial distress (short sales or deed-in-lieu-of-foreclosure transactions). 5 6Details of the cluster analysis procedures, indicator variables employed, and allocations of particular neighborhood to cluster groups are available from the authors. 6 7This is a more refined way of dealing with "abnormal" spikes/troughs in longitudinal trajectories, which examination of our data indicates is focused on specific neighborhoods rather than across the entire sample. 7 8The multilevel model random effects are different from the random effects commonly used in econometric time series models. In the multilevel formulation, the random effects are equivalent to main effects, with the descriptor "random" referring to the nature of the neighborhoods (i.e., they are theoretically drawn at random from some larger population). In contrast, the econometric random effects describes the effect of individual differences (i.e., random disturbance), which is necessary to account for to generate unbiased estimates for the main effects. 8 9The trend and trajectory seen for Chicago and its neighborhoods is consistent with data reported by the FFIEC regarding national trends in these loans. An additional explanation for the results reported here is the cutoff point for reporting; that is, due to inflation and other trends in business capitalization, one million dollars may no longer reflect the high point for the types of loans the data collection program was intended was track. 9 10There are several potential explanations for this long-term decline, including reductions in the pool of teenagers, stabilization of local drug markets, mandatory prison sentencing requirements, and new policing strategies. 10 11This was the conclusion of Galster et al. (Citation2007) and Lim and Galster (Citation2009) in their analyses of neighborhood crime dynamics. Note that this argument cannot be made in the aforementioned case of foreclosures because in general there was a positive correlation between starting levels and rates of change: 0.80 for Chicago overall. 11 12Correlations are available upon request.
No abstract is provided for this article.
Federal programs have consistently encouraged ever-lower-income households to buy homes, despite concerns about the long-term sustainability and desirability of homeownership from the perspective of wealth-building, especially since the recent housing market collapse and the epidemic of mortgage foreclosures. We ask in this paper: can very low-income households build wealth through sustainable homeownership, with the aid of an innovative public program? We answer this question by examining 122 very low-income households who purchased their homes between 1996 and 2007 after completing an extensive asset-building and homeownership education/counseling program offered by the Housing Authority of the City and County of Denver (DHA), called HOP. We analyze our own longitudinal surveys and focus groups, as well as data compiled from administrative agency sources, real estate records, and longitudinal census data from the Neighborhood Change Database and the Piton Foundation's Neighborhood Facts Database. We find that homeownership attained through HOP typically did provide very low-income households with opportunities to build home equity (both absolutely and relative to generic homeowner cohorts in Denver) and net wealth, although this was contingent on time of purchase and ethnicity. Our multivariate analyses revealed that changes in annualized home equity appreciation were associated with the ethnic composition of the neighborhood and age of property. Annualized wealth accumulation was associated with annualized home equity appreciation, being married throughout the tenure of homeownership, and year of home purchase. HOP homebuyers received exceptionally favorable initial mortgage terms and conditions, often enhanced with down-payment assistance from their own DHA escrow account or from local housing and neighborhood development organizations, resulting in a dramatically low rate of default and foreclosure to date. Moreover, HOP homebuyers were not immune to financial stresses, and the continuing lack of wealth for many makes them vulnerable to future interruptions in primary wage earner's employment or health. We discuss the implications for low-income homeownership policy and argue that the goal of expanding homeownership opportunities should not be abandoned.
Neighborhood income segregation is a widespread phenomenon. We explore its origins by modeling neighborhood selection by native Norwegian households making inter–neighborhood moves, distinguishing influences of shares of three income groups and the discrepancy between the individual household's income and neighborhood median. We conduct a conditional logit analysis employing 2013–2014 population register data from the Oslo, Norway, metropolitan area. We find that status composition (shares of low– and high–income households) and status discrepancy (difference between individual household's and neighborhood median disposable incomes) critically shapes neighborhood selection, though heterogeneously across income groups. All income groups sort into neighborhoods that have more of their own status group in residence. Middle– or high–income households avoid neighborhoods with above–average shares of low–status households and median incomes that are higher than their own. High–income households are more attracted to a place the greater the superiority of their incomes compared to the neighborhood median. Our findings suggest that although the drivers of residential income segregation are powerful, public policies aimed at neighborhood diversification have potential efficacy nevertheless.
C. Institute of University of “-i.7 Business and California, ~ qA Economic Research Berkeley CENTER FOR REAL ESTATE AND URBAN ECONOMICS WORKING PAPER SERIES WORKING PAPER No, 87-331 SUBSIDIES FOR REHABILITATING SINGEE- FAMILY DWELLINGS: A BENEFIT-COST ANALYSIS ' ray GEORGE» C. 'GALs:'r=:ER Thes are Pfeiiminary in nat e; 'r purpose ' to stimulate discussion comment. Therefore. they are not to b ‘ted or quoted ' ny pub ' ‘on with t express permissio the author. GRADUATE SCHOOL OF BUSINESS ADMINISTRATION
This chapter aims at better understanding the cause and consequences of neighborhood segregation by class and race by developing a cumulative causation model. It has been conventional to view residential segregation by economic class and segregation by race or ethnicity as separate features of neighborhoods in America. Though both have evolved in distinctive ways, this chapter demonstrates that these aspects of neighborhoods are fundamentally linked. This is because they share several common proximate causes, influence each other directly, and are both key nodes in a complex web of mutually reinforcing causal links. This chapter's cumulative causation model of class and race segregation represents in the most powerful way the central theme of this book: we make our neighborhoods and then they make us. This holistic portrayal has a clear empirical implication: metropolitan areas that exhibit more class segregation should also exhibit more racial segregation, a result that has been borne out by recent empirical work.
My career-long intellectual project has been to understand how our human-built environments—at the dwelling, neighborhood, and metropolitan scales—serve as crucibles for human development, achievem...
Data from fair housing audits conducted in Cincinnati (1983-85) and Memphis (1985-87) are analyzed to discern whether and how racial steering occurs. The six real estate firms analyzed here engaged in some sort of steering during at least one-half of the audited transactions, on average. This steering did not limit the number of alternative areas shown to black auditors, nor their geographic concentration. Rarely were black auditors not shown dwellings in predominantly white areas, especially if they requested such. But of all the homes they saw, black auditors were shown significantly smaller fractions in predominantly white areas, and significantly larger fractions in mixed and predominantly black areas. These racial patterns persisted regardless of the geographic definition of area chosen: census block, census tract, school district, or community. In addition, blocks adjacent to the homes shown black auditors had higher percentages of black residents, on average, than those shown to white auditors. White auditors rarely were shown houses in racially mixed areas unless they requested them. Even then, after the requested home was shown the bulk of subsequent showings were located in predominantly white areas. This pattern of showings was buttressed by numerous favorable comments by agents about such predominantly white areas and school districts … comments that were rarely given to black auditors. The evidence was fully consistent with only one hypothesis about why real estate agents steer. They steer so as to perpetuate two segregated housing markets buffered by a zone of racially transitional neighborhoods, thereby maximizing housing turnover and agents’ commissions.
Currently, in many Western countries there are concerns that clustering of ethnic minorities in certain parts of cities will negatively affect integration processes. However, scholarly theory and evidence on this point is mixed. We use Swedish data and conduct a panel analysis quantifying the degree to which the ethnic composition of the neighbourhood affects the subsequent labour income of individuals for the 1991 to 2006 period. We employ a fixed effects model to reduce the potential bias arising from unmeasured individual characteristics leading to neighbourhood selection. We also control for a range of individual demographic and socioeconomic attributes. Based on gender-stratified analyses of eight immigrant categories (N = 110,000) in three Swedish metropolitan areas, we find that male immigrants (females less so) gain if they reside in neighbourhoods with higher shares of co-ethnics and (under most circumstances) other immigrants, though the impact depends on neighbourhood level of employment and trajectory of ethnic share. This, we argue, should not be seen as an argument for ethnic residential segregation, but it tells us that the high degree of exclusion from the labour market experienced by many immigrants in Sweden is not directly caused by the level of immigrant residential segregation.
We investigate the degree to which the ethnic group composition of “port-of-entry neighborhood” (PoE), the first permanent settlement after immigration, affects the employment prospects of refugees in Sweden during the subsequent 10 years. We use panel data on working-age adults from Iran, Iraq, and Somalia immigrating into Sweden from 1995 to 2004. We control for initial individual and labor market characteristics, use instrumental variable regression to avoid bias from geographic selection, and stratify models by gender and co-ethnic employment and education rates within the neighborhood. We find that the impact of co-ethnic neighbors in the PoE varies dramatically by gender.
Flood risks are forecast to rise significantly across many parts of Europe, USA, and Asia. As the climate warms, sea levels will continue to rise and the water holding capacity of the atmosphere will increase exponentially. At the same time, the cost of building flood barriers will increase disproportionately with every additional centimetre of height. For many countries, these flood risks will be highly localised, however, and with strong spatial spillovers. This paper uses a unique dataset for 5 boroughs in London to develop a spatial econometric simulation model of the impacts of current and future flood risks on house prices and the location of employment. We consider the broader socio-economic implications of our results.
This study tests the hypothesis that the acquisition of existing property by the public housing authority and its subsequent rehabilitation and occupancy by subsidized tenants significantly reduced the property values of surrounding single-family homes in Denver during the 1990s. This assessment examined pre- and post-occupancy sales, while controlling for the idiosyncratic neighborhood, local public service, and zoning characteristics of the areas in order to identify which sorts of neighborhoods, if any, experienced declining property values as a result of proximity to dispersed housing tenants. The analyses revealed that proximity to a subsidized housing site generally had an independent, positive effect on single-family home sales prices. The most notable exception to this pattern occurred in neighborhoods more than 20 percent of whose residents were black. Proximity to dispersed public housing sites in these neighborhoods resulted in slower growth in home sales prices in an other-wise booming housing market and suggest a threshold within "vulnerable" neighborhoods whereby any potential gains associated with rehabilitating existing units are offset by the increased concentration of poor residents. © 2001 by the Association for Public Policy Analysis and Management.
How will housing markets respond to increased frequency and severity of flooding expected with global climate change? Existing models yield poor predictions because they assume perfect information and rational decision-making processes in the housing market. This paper sets out a plausible alternative framework for analysing housing price responses to flood frequency and severity based on findings of behavioural economics and the sociology of risk, which emphasise myopic and amnesiac perceptions of risk. It utilises this framework to analyse graphically a variety of flood scenarios and their implications for housing prices and government intervention.
