▼ "Development" is a ubiquitous term that at one turn refers purely to regional or national economic growth, and at another refers to achieving a basic standard of living for all the people of the world. The dearth of reflection on these multiple meanings in the literature is further overshadowed by the absence of empirical study into the different implications of development, when considered through these various lenses.In this thesis, I strive to provide some analysis into the prevailing trends in two separate measures among the 48 contiguous United States over the period 1997-2006: real Gross State Product per capita (GSP) representing the "economic growth" paradigm, and the Human Development Index (HDI) representing a more holistic "quality of life" conception. Using the standard convergence equation popularized and rigorously defined by Barro and Sala-i-Martin (2004), I analyze whether there is convergence, divergence or stability in the distribution of GSP and HDI over this time period. I also experiment with three different model specifications: the standard non-linear model, a random effects panel model, and a spatial error panel model with random effects. Each specification, by relaxing some of the assumptions of the previous model, is found to provide a more realistic and nuanced picture of the true data generating process. I find that, over the study period, there is stability in GSP among the states, and that HDI is converging rapidly. I find further that all of the components of HDI are converging with the exception of the "command over resources" component, which is based on real GSP per capita. This implies that if prevailing trends continue, the quality of life experienced by the states in terms of health and education will rapidly approach equality, but that inequality in income is persistent, and should be the focus of policy aimed to increase equity among U.S. residents. I also find that there are significant spatial relationships among the states, and that controlling for these spatial effects greatly improves a model’s explanatory power. Advisors/Committee Members: Ajilore, Olugbenga.

▼ We examine the relationship between fourth grade student proficiency scores, various educational spending categories, student and teacher characteristics as well as population socioeconomic characteristics using a building-level database containing 1,965 Ohio elementary schools. While most economic studies of the relationship between student performance and educational resources show a weak link, we find a strong link between student performance and resources. We argue that use of the appropriate spatial scale is an overlooked issue in previous economic studies. Furthermore, we provide an alternative method of capturing variation over geographical space through the estimation of locally linear models. By estimating a separate model for each individual building, we see that the global estimates provided by previous estimation methodologies may not be provide valid inferences. The locally linear estimates and inferences suggest that location-special forces exist in the relationship between resources and student performance. Advisors/Committee Members: LeSage, James P.

▼ Two costs are associated with visiting a recreational site: the opportunity cost of time and the travel cost. This research examines the robustness of various estimates of the opportunity cost of time in order to more accurately estimate the willingness to pay for wetland restoration at Maumee Bay State Park. Samples are drawn from the Northwest Ohio Wetland Survey, which was conducted in 2008. Because employment classification reveals information about the individual's opportunity cost of time, respondents were split into subgroups based on their employment classification. An individual can be out of the labor market, work a fixed schedule and be underemployed, work a fixed schedule and be overemployed, or an individual can be free to choose their work hours. I also allow for the possibility that an individual working a fixed schedule is content working their current hours. Models using different discount rates, k, were used to estimate the sensitivity of the willingness to pay estimate to various measures of the opportunity cost of time. Using estimates from a bivariate Poisson lognormal model, the willingness to pay estimates varied significantly, from $14.91 per person per year when k=0 to $56.42 per person per year when k=1, depending on the opportunity cost of time. Allowing k to vary by employment subgroup leads to a willingness to pay estimate of $26.40, which was similar to the estimate calculated when k was 1/3. Advisors/Committee Members: Egan, Kevin.

▼ We examine the spatial autoregressive relationship between county-level voting outcomes in the 2000 Presidential election and a host of candidate explanatory variables taken from the year 2000 census. These include: measures of past voting behavior, indicators of socioeconomic demographic status of the population, and economic variables that reflect recent economic conditions. Using a recently developed spatial econometric extension of least-squares regression-based Markov Chain Monte Carlo model composition methodology (often labelled MC3) by LeSage and Parent(2004), we present evidence on which explanatory variables are important in explaining voting outcomes. The LeSage and Parent (2004) methodology deals with cases where the number of possible models based on different combinations of candidate explanatory variables is large enough that calculation of posterior probabilities for all models is difficult or infeasible. In addition, we produce estimates using a spatial autoregressive seemingly unrelated regression methodology developed in LeSage and Pace (2005), that takes into account cross-equation error covariance between the Bush and Gore equations in the model. Advisors/Committee Members: LeSage, James Paul.