Projected increases in demand for postsecondary credentials in the labor market have exposed an immediate need for the United States to significantly increase its college attainment rate. The current growth rate of college tuition and fees, however, has been outstripping inflation for decades, and is limiting access for a growing number of would-be college students. Significant variance in college tuition and financial aid levels among states complicate the issue, having prevented researchers from finding the true indicators that govern college tuition levels. I posit that increased future earnings potential is one of these indicators causing tuition price variance throughout the U.S. Specifically, each state’s college wage premium – the amount a college graduate can expect to make over a high school graduate – causes its tuition prices through a supply/demand equilibrium. I hypothesize that the average public college tuition in a state is directly correlated with its college wage premium. Colleges in states with a high premium have a more valuable product and are able to charge more. I test this by collecting data from College Board and the U.S. Census Bureau on average college tuition and median-level college wage premium, and run a simple OLS regression to determine the strength of correlation. I then discuss my results in the context of the United States’ college attainment goals.
Despite the vast body of research surrounding mergers and acquisitions, there is little consensus as to what contributes to merger success or failure. One variable, target manager retention, has been found to have some explanatory power, but target managers experience a turnover rate significantly higher than average. Decreasing target manager turnover may be a key to improving the low merger success rate, and one possible method would be to provide incentives in the form of compensation increases. This study seeks to test the hypothesis that percent change in target manager compensation is positively and significantly correlated with the merger success rate. The statistical model used to test this hypothesis is logistic regression, and data were collected on multiple mergers, executive compensation, historical stock prices, historical S&P 500 Index prices, and several business return ratios to determine whether a merger succeeded. The findings are inconclusive but provide interesting insights into the nature of mergers and illuminate several areas of potential future research.