Search

Racially unequal home mortgage loan patterns are alive and well today with many financial institutions. Efforts to change these trends are difficult when few question the 'reinvestment thesis'—an environment in which financial institutions are assumed to meet community needs, even when data suggest the opposite. In this article, we analyze thirteen years of financial institution lending data from 2007 to 2019 in Pittsburgh that show how the city's African American neighborhoods are starved for private capital as vastly more loans and loan dollars were approved in white neighborhoods. Conversely, an analysis of public expenditures for affordable housing between 2010 and 2020 demonstrate the majority of government dollars went to minority neighborhoods. These data provide a partial explanation as to why Pittsburgh lost > 10,000 Black residents over the past decade. These wide disparities are a significant barrier to building African American wealth and present challenges to community development efforts. [ABSTRACT FROM AUTHOR]

Surveys of Washington, D.C. households indicate that black households are twice as likely as white households to not get their first choice when moving into their current homes. More than one-fourth of black householders know someone who experienced discrimination during recent attempts to obtain housing or housing finance. Whites are over four times more likely than blacks to believe that equal opportunity exists in the housing market. (Contains references.) (SM)

'Linguistic profiling.' the identification of a person's race from the sound of their voice and the utilization of that information to discriminate on the basis of race, has been documented in the home rental market. This article examines this phenomenon in the home insurance industry. From an analysis of matched-paired tests conducted by fair-housing organizations, we find that home insurance agents are generally able to detect the race of someone who contacts them by telephone and that this information affects the services provided those who inquire about purchasing a home insurance policy. Keywords: linguistic profiling; insurance discrimination: redlining; segregation; housing

Racial profiling has emerged as a highly contentious practice in a range of social settings. This article examines the role of racial profiling in the property insurance industry and how such practices, grounded in negative racial stereotyping, have contributed to racial segregation and uneven metropolitan development. From a review of industry underwriting and marketing materials, court documents, and research by government agencies, industry and community groups, and academics, it is clear that race has long affected and continues to affect the policies and practices of this industry. Due to limitations in publicly available data, it is difficult to assess precisely the extent to which race shapes industry practices. Research and public policy initiatives are explored that can ameliorate the data problems, increase access to insurance, and foster more equitable community development.

Explicit considerations of race and unlawful racial discrimination persist as critical factors in the continuing segregation of urban housing markets. On the basis of a telephone survey of Washington, D.C. area households, the authors find that current black households were almost twice as likely as white households to not get their first choice when they moved into their current homes, more than one-fourth of black householders report that they or someone they know experienced discrimination in their efforts to obtain housing or housing finance within the past three years, and whites are more than four times as likely as blacks to believe that equal opportunity exists in the current housing market. These relationships persist after controlling on several socioeconomic characteristics (income, education, housing tenure) of households. Several policy options are recommended for ameliorating racial segregation in urban housing markets.

Check-cashing businesses constitute a growing industry, particularly in low-income and nonwhite neighborhoods. This case study of Milwaukee, Wisconsin, finds that check-cashing businesses are concentrated in the central city while conventional [...]

Objective. Debates over racial discrimination in mortgage lending have been contentious for decades. The objective of this paper is to examine the relationship between the racial composition of the workforce of financial institutions and the likelihood of approval of loans to black applicants. Methods. A binary logit analysis is performed on a data set on black and white mortgage applicants in the Milwaukee metropolitan area. The data set is based on HMDA data, EEO-1 data, and 1990 U.S. Census data. Results. This study finds that the likelihood of a black applicant being approved increases as the proportion of black employees increases when several applicant and institutional characteristics that influence loan review process are controlled. The effect of black professionals at thrift institutions is particularly significant. Conclusions. The results suggest that regulatory agencies could incorporate affirmative action and related issues in their enforcement activities and lenders could benefit from more aggressive voluntary affirmative action efforts.

Charles Leven and Michael Sykuta have a constricted idea of discriminatory attitudes and practices pertinent to lending. These two authors furthermore are not skillful in choosing the parameters and controls needed to enable their model to achieve validity. They have a way of making their assumptions and propositions hazy through the adoption of circuitous statistical techniques that the subject matter, which is discrimination, begins to escape their grasp. These are errors of methodology that impair the validity of their basic contentions.