Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item NETWORK MODELS OF REGIONAL INNOVATION CLUSTERS AND THEIR IMPACT ON ECONOMIC GROWTH(2012) Dempwolf, Christopher Scott; Howland, Marie; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This research uses social network analysis to develop models of regional innovation clusters using data from patent applications and other sources. These new models are more detailed than current industry cluster models, and they reveal actual and potential relationships among firms that industry cluster models cannot. The network models can identify specific clusters of firms with high potential for manufacturing job growth where business retention and expansion efforts may be targeted. They can also identify dense clusters of talent where innovation and entrepreneurial efforts may be targeted. Finally, this research measures relationships between network structure at the time of patent application and manufacturing job growth in subsequent years. This will permit the translation of a wide range of network-building activities into the ubiquitous "jobs created" metric. These new tools will help economic developers focus resources on high-yield activities, and measure the results of networking activities more effectively. There are three parts to this research. First, it evaluates the uses of social network analysis (SNA) in planning, reviewing the literature and empirical research where SNA has been used in planning related studies. Second, it presents the construction if innovation network models, covering methodology, data, results and direct applications of the network models themselves. Models are constructed for Pennsylvania between 1990 and 2007. The methodology presents a significant innovation in how networks and geography are modeled, embedding counties in the network as place nodes. The resulting network models more accurately reflect the complex and multiple relationships that firms and inventors have with each other and the locations where they interact. This approach makes it possible to evaluate relationships between innovation and economic growth at a smaller geographic level (counties) than previous research. Third, this research presents an econometric model that evaluates the influence of network structure on county-level manufacturing employment and value added. Network structure is measured in the year of patent application, with manufacturing employment and value added being measured annually for each subsequent year. Differences in network structure generally reflect differences in the level of social capital embedded in different parts of the network. I find that network structure influences manufacturing employment within three years (longer for medical devices and pharmaceuticals) but does not influence value added.Item Empirical Essays in Comparative Institutional Economics(2007-05-02) Mukashev, Yerzhan Bulatovich; Murrell, Peter; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Essay 1 investigates an empirical link between institutional variables and the performance of firms based on cross-country firm-level survey data. Current empirical evidence based on this type of data is unsatisfactory because employing survey responses as direct measures of institutional concepts and using those to analyze the effects of institutions at the firm level would limit the researcher to findings only within countries effects. This happens at the expense of losing inherent cross-country variation in institutions. Essay 1 offers a simple conceptual framework that decomposes survey responses for each firm into the average of their country and a residual firm-specific component. Importantly, the estimation results indicate that both variations have clearly different effects on growth of sales of firms. Essay 2 estimates the causal effects of economic shocks on the incidence of politically destabilizing events. The estimation is difficult due to the joint endogeneity between economic growth and events related to the political environment, which is addressed by the instrumental variable method. The variation in oil prices is used as an instrument for economic growth in the sample of small oil importing economies during 1960 - 1999. In contrast to a common belief and OLS estimates, the most striking finding of the IV estimation is that higher economic growth has a strong and robust positive effect on the incidence of relatively peaceful unrest such as demonstrations, strikes and riots. Essay 3 studies the question of differences in economic growth rates between Democratic and Republican governorships in the United States. The question is difficult to answer by simply comparing growth rates because the party affiliation is not randomly selected during elections. The empirical analysis employs the Regression Discontinuity Method to address the endogeneity in the party control variable. Focusing on very close elections permits the generation of quasi-experimental estimates of the impact of a "randomized" change in party control at the 50 percent threshold. When comparing Democratic with Republican governorships, the results are suggestive about the possibility of slightly worse performance of Democratic governors but the lack of statistical significance does not fully support this evidence.