Supporters of urban revitalization have relied on community development corporations (CDCs) to carry a major share of the front-line burden. This research presents new evidence that these community-controlled, market-responsive organizations can indeed spark a chain reaction of investment. Advanced econometric analysis shows that CDC residential and commercial investments have led to increases in property values--the single-best measure of neighborhood improvement--as great as 69 percent higher than they would have been otherwise. To achieve these results, CDCs did more than just develop projects; they also brought business people, civic organizations, and public agencies into the neighborhood improvement process.
The elimination of racial discrimination has long been a dominant American social concern. Laudably, economists have contributed many studies which have attempted to identify and quantify such discrimination, particularly in the area of the housing market. The research reported here, while following in this tradition, employs a new approach in attempting to discover not only the magnitude of housing price discrimination, but how its burden is incident upon different types of nonwhite households. A model of urban housing markets will be developed from the bid-rent theory which allows one to isolate empirically the distinct contributions to interracial housing price differentials made by variations in households' preferences, incomes, and housing packages versus those made by discriminatory actions. Bid-rent functions will be econometrically estimated for individual household observations stratified into groups of comparable age, family size, education, socioeconomic class, and race. These functions will be used to estimate what the various nonwhite strata would be willing to bid for typical white-occupied units. The divergencies between such bids and prices actually paid by whites will provide a measure of the existence and magnitude of discrimination confronting nonwhite groups.
Regression analysis of Community Development Block Grant (CDBG) spending in 17 large cities reveals strong statistical associations between spending from 1994 to 1996 and changes in three indicators of neighborhood conditions: the home purchase mortgage approval rate, the median amount of the home purchase loans originated, and the number of businesses. However, there is no consistent association between spending and indicators of subsequent neighborhood change unless CDBG spending is sufficiently spatially targeted that it exceeds a threshold of the sample mean expenditure and is measured relative to the number of poor residents. In addition, associations vary according to neighborhood trajectories before investment and changes in the local economy. Nevertheless, even in the least hospitable contexts—highly concentrated neighborhood poverty, preexisting declines in home values, weak city job growth—our estimates are consistent with the hypothesis that above‐threshold CDBG spending produces significant neighborhood improvements. We discuss the implications for such spatially targeted spending and connections between our work and the emerging literature on the dynamics of poor neighborhoods.
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.
Comprehensive data on 153 properties offering independent living for persons with mental illness are used to examine the effects on repair and maintenance (RM) costs of building quality, neighborhood quality, building size, proportion of tenants with mental illness, and management experience with mentally ill tenants. We find an inverted U‐shaped relationship between the proportion of mentally ill tenants in a building and its RM costs, which suggests favorable behavioral effects on mentally ill tenants of living in the same building with others who are mentally ill. We also find amenity features are associated with higher RM costs in properties where more tenants are mentally ill.
Differences in immigrant economic trajectories have been attributed to a wide variety of factors. One of these is the local spatial context where immigrants reside. This spatial context assumes special salience in light of expanding public exposure to and scholarly interest in the potential impacts of spatial concentrations of immigrants. A crucial question is whether immigrants' opportunities are influenced by their neighbours. In this paper we contribute statistical evidence relevant to answering this vital question. We develop multiple measures of the spatial context in which immigrants reside and assess their contribution to the average earnings of immigrant individuals in the three large Swedish metropolitan areas, controlling for individual and regional labour-market characteristics. We use unusually rich longitudinal information about Swedish immigrants during the 1995–2002 period. We find evidence that immigrant men and women paid a substantial penalty during 1999–2002 if in 1999 they resided in areas where a substantial number of their neighbours were members of the same ethnic group. The evidence suggests that own-group concentrations can initially pay dividends for immigrants, but these benefits quickly turn into net disadvantages over time.
There is long-standing interest in predicting if and when less advantaged urban neighborhoods will experience upsurges in their housing prices, yet little research has investigated year-to-year neighborhood price dynamics. The authors advance knowledge in this realm by employing anually updated, readily available indicators created from the Home Mortgage Disclosure Act and assessor’s data from Washington, D.C., census tracts for 1995 to 2005 to estimate a hazard model of the year when consistent, substantial, and sustained housing price appreciation starts in disadvantaged neighborhoods, based on predictors measured one and two years in advance. The results suggest that proximity to stronger neighborhoods, a robust metropolitan housing market, and inflows of higher-status home buyers are key predictors of appreciation onset in disadvantaged neighborhoods, but replications and refinements are needed before firm generalizations about this process can be made.
No abstract is provided for this article.
This chapter applies the metropolitan housing submarket model developed in the prior chapter to demonstrate its power as a diagnostic framework for comprehending the origins, dynamic processes and consequences of neighborhood decline and revitalization. It considers neighborhood downgrading (a combination of physical erosion of the housing stock and downward income succession of households) and upgrading (the opposite combination) separately, though both are subsumed under the common housing submarket analytical framework. After these theoretical expositions, it demonstrates how the predictions of the model comport well with empirical reality, using as archetypes of decline and revitalization of Detroit and Los Angeles. The chapter closes with a discussion of limitations of the housing submarket model as a bridge to forthcoming chapters wherein the model's simplifying assumptions are progressively relaxed.
No abstract is provided for this article.
No abstract is provided for this article.
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.
This chapter is structured around three interrelated questions. How should neighborhood be defined? Does a neighborhood have unambiguous and consensual boundaries? Should neighborhood be thought of as a variable? The chapter provides a definition of the neighborhood as externality space. Instead of conceptualizing neighborhood as a place, the chapter advances the idea that congruence, generality and accordance represent three distinct dimensions over which the degree of neighborhood varies across space. In one extreme case, the values assumed by these three dimensions could signal an archetypical neighborhood commanding distinct, clear boundaries from the viewpoints of all decision-makers of relevance for all the important spatial attributes. In the opposite extreme case, the values assumed by these three dimensions signal that no meaningful neighborhood exists in this geographic space beyond that idiosyncratic one which an individual resident might perceive. Finally, this chapter suggests how these measures of the neighborhood could be empirically tested and reflects on how the concept of neighborhood as externality space overarches and advances conventional views on the neighborhood.
This chapter considers the degree to which the processes of neighborhood change and the outcomes they yield are socially desirable. It investigates whether the primarily market-driven processes that neighborhoods undergo as they transition between states, and the population and housing stock characteristics that neighborhoods exhibit at any moment are the best we can hope for from a society-wide perspective. Based on a theoretical analysis and review of the evidence, the chapter advances three propositions of inefficiency, inequity, and unequal opportunity. Private, market-oriented decision-makers governing resource flows among neighborhoods usually arrive at an inefficient allocation due to externalities, strategic gaming, and self-fulfilling prophecies, systematically producing too-little investment in housing and too much segregation by race and economic standing. Lower socioeconomic status, black and Hispanic households and property owners typically bear a disproportionate share of the financial and social costs associated with segregation, under-investment and neighborhood transition processes, while reaping comparatively little of their social benefits. Because neighborhood context powerfully affects children, youth, and adults—yet neighborhood contexts are very unequal across economic and racial groups—space becomes a way of perpetuating unequal opportunities for social advancement.
No abstract is provided for this article.
:This article develops a conceptual framework of neighborhood crime dynamics based on a synthesis of criminology and neighborhood change literatures which suggests that neighborhood decline can produce a nonlinear response in crime rates. The authors probe this relationship using a rich Detroit data set containing detailed, block-level information about housing, land, abandonment, population, schools, liquor outlets, and crime reports of various categories. Negative binomial models reveal that several neighborhood attributes are consistently associated with all types of crime (renter occupancy, population density, establishments with liquor licenses) while other attributes are only associated with particular types of crime. A simulation using estimated parameters suggests that processes of disinvestment and abandonment can generate a nonlinear pattern in the rate of growth in neighborhood crimes that vary in intensity by crime type. The authors explore the implications of their findings for anticrime strategies focusing on demolishing abandoned housing, "right-sizing" urban footprints, and regulating liquor-selling establishments. NotesFor additional references, see Miethe and Meier (Citation).One of the few consensual findings in the criminological literature is the positive correlation between neighborhood poverty rates and crime rates (Crutchfield, Glusker, and Bridges, Citation; Hannon, Citation, Citation; Hipp, 2007; Warner & Pierce, Citation; Warner & Rountree, Citation), although recently Hipp and Yates (Citation) found that crime rates were highest in tracts with 35% poverty rates and lower in tracts with even greater poverty concentrations.The vacant lot designation used for this study includes both "unimproved" (74%) and "improved" (24%) vacant lots (n = 91,488) as recorded by the Detroit Residential Parcel Survey. Both types are defined as parcels without residential structures, and "improved" parcels are those with some visible improvement, such as a paved lot, accessory structure, fence, or park.The Herfindahl index of ethnic heterogeneity is expressed as , where G represents the proportion of the population of race/ethnic group j out of J groups. In this instance, the index includes Hispanic or Latino, non-Hispanic white alone, non-Hispanic black or African American alone, non- Hispanic American Indian and Alaska Native alone, non-Hispanic Asian alone, non-Hispanic Native Hawaiian and Other Pacific Islander alone, non-Hispanic some other race alone, and non-Hispanic two or more races. The index takes on a value of zero with a homogenous composition and a limiting value of one with many groups identically represented.Alternatively, we employed the conventional poverty rate available from ACS but found it less predictive.Our Herfindahl index of earning heterogeneity uses four groups: residents who have not worked in the past 12 months and are assumed to have zero earnings (from ACS), employed residents earning $1,250 per month or less, employed residents earning $1,251 to $3,333 per month, and employed residents earning $3,333 per month or more. The inclusion of ACS data for this measure required aggregation of OTM data to block group–level, and application of the calculated values to blocks comprising each block group.All these lags employ a distance-to-block centroid within cutoff threshold of 2,232 feet. These spatial lags assume that the relationship between crime in the focal block and vacancy/blighting influences in proximate blocks is linear and symmetric regardless of whether nearby blocks are more or less blighted than the focal block.The spatial lag for burglary and drug crime was based on queen's-based contiguity; for vandalism, robbery, and all property crime it used distance within a threshold of 2,232 feet; for all other crimes it used distance within threshold of 4,680 feet.This variable was positively associated with rates of violent crime in all three categories analyzed, but in no case did the relationship approach statistical significance.Of 11,289 blocks in the sample, 4,673 (41.4%) have at least one DFV, and 2,574 (22.8%) have two or more DFVs.For the simulation we are forced to switch to the census tract scale because the variable distributions at the block scale were so positively skewed that distinct quintile breaks often could not be identified. Note all the zero medians for crime in Table and appendix table.For tractability we excluded spatial interactions in this simulation, both endogenously among blocks within our hypothetical tract and from other blocks nearby.The first proportional change was based on the number of crimes at the 10th percentile of the distribution, assuming this would appertain to the neighborhood in Stage 1; thereafter in the simulation the proportional change was based on the prior stage's simulated level of crime. In the simulation we assumed that all blocks within the stylized census tract changed uniformly, since our coefficients are based on underlying block, not tract, data. We also assume that the negative binomial regression parameters estimated cross-sectionally appertain to this implicitly longitudinal process being simulated.Additional informationNotes on contributorsErica RaleighErica Raleigh is the Acting Director of Data Driven Detroit, a nonprofit organization committed to the equitable access of information for data-driven decision making. She holds a Master of Urban Planning from Wayne State University, and a Bachelor of Arts in Hispanic Studies from the University of Michigan. Her research explores neighborhood quality-of-life issues, especially the interplay between neighborhood change and crime dynamics.George GalsterGeorge Galster is the Clarence Hilberry Professor of Urban Affairs at Wayne State University. His research has focused on urban neighborhoods and housing markets, exploring how they change and how they change the people who live within them. This has resulted in over 130 peer-reviewed articles, 30 book chapters, and seven books. His latest book is Driving Detroit: The Quest for Respect in the Motor City (2012). He earned his PhD in Economics from the Massachusetts Institute of Technology.
We review the longstanding dialectic that has characterized theorizing, evidence-gathering, and policy-making in the realm of neighborhood social mix, take stock of where the debate now stands, and offer suggestions of where next steps in scholarship might be most fruitful. The preponderance of plausibly causal evidence from Europe and North America indicates that disadvantaged individuals are (1) harmed by the presence of sizable disadvantaged groups concentrated in their neighborhood and (2) helped by the presence of more advantaged groups in their neighborhood, probably due to positive role modeling, stronger collective control over disorder, and violence and elimination of geographic stigma, not cross-class social ties. Thus, there is a sufficient evidentiary base to justify the goal of social mix on grounds of improving the absolute well-being of the disadvantaged. This goal should be achieved by voluntary, gradualist, housing option-enhancing strategies that over the longer term expand opportunities for lower income families to live in communities with households of greater economic means. We advocate for these approaches because they impose fewer hardships on the disadvantaged and, hopefully, are also more effective over time.
This paper analyses the degree to which the mixture of low-, middle- and high-income males in the neighbourhood affects the subsequent earnings of individuals, and aims to test explicitly the degree to which these impacts vary across gender, age, presence of children, employment status or income at the start of the analysis period. An intertemporal differences specification of an econometric model is employed to eliminate the potential selection bias arising from unmeasured individual characteristics, utilising data on 1.67 million adults living in Swedish metropolitan areas 1991—99. It is found that there are important differences in the nature and magnitude of neighbourhood income mix effects in several dimensions, but many are statistically and economically significant. Neighbourhood mix effects are consistently stronger for parents and those who do not work full-time, independently of other individual dimensions, although a combination of personal attributes typically governs the vulnerability of the individual to the neighbourhood.
Costs for severely mentally disabled persons receiving housing subsidies and/or case management services or who are in a state hospital were compared in two suburban and rural Ohio counties. Costs assessed included housing, mental health services, medical services, dental services, personal consumption, and total costs. Costs for groups consisting of 16 clients with subsidized housing and intensive case management, 24 with subsidized housing and nonintensive case management, 11 with nonsubsidized/intensive, 11 with nonsubsidized/nonintensive, and 20 with subsidized/treatment team clients were compared with aggregate costs for state hospital patients. Costs were adjusted for differences in client characteristics between groups. Results indicated that in the areas of housing costs, mental health costs, personal-consumption costs, and total costs, there were statistically significant differences among the five community-based groups. More dramatic, total operating costs for the state hospital were at least three times as high.
