Neighborhood information and home mortgage lending.

An examination of how information about a neighborhood affects the level of lending activity in it--specifically, whether lenders deny mortgage applications at higher rates in neighborhoods where they have little experience in evaluating applications and/or where the lending community in general lacks such experience.Mortgages ; Discrimination in mortgage loans

Lender consistency in housing credit markets

An examination of how and why individual financial institutions vary in their propensity to attract and approve mortgage applications from minorities, using Home Mortgage Disclosure Act data.Mortgages ; Housing - Finance ; Home Mortgage Disclosure Act

Cross-lender variation in home mortgage lending

A lender-specific analysis of differences in minority and low-income mortgage loan originations using new applicant-level data gathered under the Home Mortgage Disclosure Act of 1975.Home Mortgage Disclosure Act ; Mortgages ; Discrimination in mortgage loans

Home mortgage lending by the numbers

A look at some of the issues associated with reports that minority applicants for home mortgage loans are far more likely than whites to be denied credit. The authors raise the concern that simple comparisons of denial rates are not sufficient for grasping the complexities surrounding community-oriented lending.Mortgages ; Community Reinvestment Act of 1977 ; Home Mortgage Disclosure Act

Accounting for racial differences in housing credit markets

A documentation of racial and neighborhood differences in home mortgage denial rates using data collected under the Home Mortgage Disclosure Act, exploring the extent to which objective lending criteria are responsible for observed differences. The authors find persistent variations in denial rates between white and minority applicants, but emphasize that the HMDA data do not contain enough relevant information to draw any firm conclusions regarding causation.Discrimination in mortgage loans ; Mortgages ; Home Mortgage Disclosure Act ; Community Reinvestment Act of 1977

Posted rates as signals in mortgage lending markets

A discussion of how mortgage lenders might use posted lending terms to signal both their eagerness to take new loan applications and their lending standards.Mortgages ; Interest rates

Diverse fossil epacrids (Styphelioideae; Ericaceae) from early Pleistocene sediments at Stony Creek Basin, Victoria, Australia

There is currently intense interest in the radiation of the scleromorphic groups that dominate the Australian flora, but at present, only Proteaceae and Casuarinaceae have fossil records detailed enough to provide useful evidence on the timing of these radiations. This article records a diverse assemblage of fossil leaves of another major scleromorphic group, the epacrids (subfamily Styphelioideae of Ericaceae, formerly known as Epacridaceae). The fossils are from Stony Creek Basin, in the western uplands of Victoria, Australia, and are of earliest Pleistocene age (ca. 1.6 million years old). They include 19 forms sufficiently distinct as to constitute different species. This diversity is considerably greater than the extant diversity of epacrids in the region. Published taphonomic data are used to argue that the actual diversity of the source vegetation of the fossil flora may have been significantly greater and comparable to the current local species richness of the centers of diversity. Ten of the fossil species are assigned to the largest extant tribe (Styphelieae), eight are assigned to Epacrideae or Archerieae, and one is assigned to Cosmelieae. This evidence is used to argue that substantial radiation of the epacrids had occurred by the beginning of the Pleistocene

Diabetes, Abdominal Adiposity, and Atherogenic Dyslipoproteinemia in Women Compared With Men

OBJECTIVE—To understand why atherogenic risk differs more between diabetic and nondiabetic women than between diabetic and nondiabetic men

Diabetes, Abdominal Adiposity, and Atherogenic Dyslipoproteinemia in Women Compared With Men

OBJECTIVE—To understand why atherogenic risk differs more between diabetic and nondiabetic women than between diabetic and nondiabetic men