Assrnxcr The relationship between social interaction and college attendance is examined across varying types of communities. Structural arrangements and interaction patterns that foster positive relationships are regarded as social capital and are conceptualized as investments that can yield human capital returns in terms of higher educational attainment. Logistic regression procedures are employed to analyze data from the High School and Beyond Longitudinal Study. The social capital model of college attendance is estimated for the full sample and separately for high school students living in urban, suburban, and rural communities. Predicted probabilities of attending college for students with high and low social capital are obtained. Results of these analyses indicate that parental expectation of college attendance is the most powerful predictor of subsequent college attendance among variables examined. Measures of community social capital and parental human capital also strongly predict attendance. AnSTRACf Rising fiscal pressure on local governments in rural areas of the United States is documented in this study. The level of fiscal burden on taxpayers to support local governments in nonmetropolitan areas is found to be higher than that in metropolitan areas between 1977 and 1987. Using a model from the urban fiscal literature, the level of fiscal burden in nonmetropolitan areas is found to be influenced by a combination of demographic, socioeconomic, intergovernmental, and historical factors. Intergovernmental revenue transfers from the state and federal government play a critical role in determining the level of fiscal burden rural taxpayers bear. These findings have implications for rural economic development and for understanding how rural areas are influenced by the larger society.
Previous research on rural and urban differences in risk of mortality has been inconclusive. This article used data from the National Longitudinal Mortality Study to establish whether all-cause mortality risk among persons 55 years and older varies by degree of urbanization, controlling for the potential sociodemographic confounders of age, gender, race/ethnicity, education, income, and marital status. Using the Cox Proportional Hazards Regression Procedure, the authors found that persons living in the most rural locales and those living in rural communities in standard metropolitan statistical areas (SMSAs) have the lowest risk of mortality, while those living in SMSA central cities had the highest risk of dying during the study period. The protective effect of rural residence declines in older age cohorts.
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