The war on poverty started in America in the early 1960s, and the poverty rate of 22.4 percent in the year 1959 decreased to 11.1 percent in 1973. Regrettably, this war did not last long enough, as poverty rate increased to 15.1 percent in 1993. In the year 2000 the US poverty rate declined, but always stayed above 11.1 percent. Kentucky also did not achieve success in this poverty war, and it resulted in growing numbers of poor people. Analysis of poverty has always aroused the interest of economists, sociologists and policy makers. Goal of this paper is to intricate appropriate strategies and invent effective prevention efforts to eradicate the young adult poverty. Estimation of Gini coefficients for various age groups indicates that the young adult population of Kentucky is at risk. The purpose of this paper is to determine the factors of young adult poverty, employing ZIP Code data in Kentucky. Data analysis reveals that rural young adults are more vulnerable than urban young adults in Kentucky. Some significant factors such as; male and female educational level, presence of minorities and type of employment are the primary determinants of poverty for this age group. Analysis of outcomes leaves suggestions for the policy makers to exterminate young adult poverty from Kentucky.

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The goal of this research was to examine the potential predictive ability of socioeconomic and demographic data for drivers on Kentucky crash occurrence. Identifying unique background characteristics of at-fault drivers that contribute to crash rates and crash severity may lead to improved and more specific interventions to reduce the negative impacts of motor vehicle crashes. The driver-residence zip code was used as a spatial unit to connect five years of Kentucky crash data with socioeconomic factors from the U.S. Census, such as income, employment, education, age, and others, along with terrain and vehicle age. At-fault driver crash counts, normalized over the driving population, were used as the dependent variable in a multivariate linear regression to model socioeconomic variables and their relationship with motor vehicle crashes. The final model consisted of nine socioeconomic and demographic variables and resulted in a R-square of 0.279, which indicates linear correlation but a lack of strong predicting power. The model resulted in both positive and negative correlations of socioeconomic variables with crash rates. Positive associations were found with the terrain index (a composite measure of road curviness), travel time, high school graduation and vehicle age. Negative associations were found with younger drivers, unemployment, college education, and terrain difference, which considers the terrain index at the driver residence and crash location. Further research seems to be warranted to fully understand the role that socioeconomic and demographic characteristics play in driving behavior and crash risk.

This study looks at the relationship between charter school presence and neighborhood quality in Los Angeles. Using data from the Los Angeles Department of Education, Zillow Real Estate, and the Los Angeles Sheriff, this paper attempts to find whether changes in charter presence influence the price of surrounding real estate or the occurrence of serious and petty crimes. The results find that charter schools tend to be associated with a decrease in home sale prices. The results on crime imply that crime increases upon the opening of charter schools, however they are statistically insignificant.

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