AN ECONOMIC CLUSTER ANALYSIS OF THE UNITED STATES

Abstract

The United States is a large country that has many different areas. The cost of living combined with natural advantages for specific industries pose a difficult problem for individuals looking to find common ground across the United States at scale. Every area requires careful thought and planning by city planners relative to economic development. Past research has determined that economic clusters can be created in order to help decision makers in public office understand various economies; however, no open-source tool has been developed to aid decision makers think through public policy resolutions. Utilizing clustering models, we investigate what economic clusters form, the drivers of these clusters, and lay the ground work for more robust models. The goal of this thesis is to provide public policy decision makers with insights on other metropolitan statistical areas (MSA), encouraging further collaboration and resource sharing to aid in economic growth. Efforts were taken to keep the model simple yet robust, with the understanding that follow-on research can get much more specialized on specific issues. This thesis utilizes clustering techniques in order to determine what MSAs have similar economic outlooks. By identifying these clusters, we provide policymakers with insights on which MSA are comparable to other MSAs, shortening the research process for public policy decisions and promoting collaboration across the country.