| Summary: | Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2005. === Includes bibliographical references (leaves 88-90). === Employment growth in the 1990s and its relationship with the initial industrial structure in 1990 are examined in the case of Appalachian counties, after controlling for labor-market conditions and other factors, such as labor mobility, natural amenities, and market size. Spatial exploratory data analysis of the competitive employment growth (CEG) in Appalachian region shows that strong spillover effect of CEG exists among 410 counties. Counties with higher employment growth rates are concentrated in the north side of Atlanta Metropolitan area around Interstate highway 1-75. Counties with lower growth rates concentrated in Central Appalachia, along the convergent border of three states, Kentucky, Virginia, and West Virginia. Another low growth rate concentration is in Northeast Pennsylvania. The existence of spatial autocorrelation affects my empirical model's explanatory power, the significance levels, and the values of coefficients of independent variables. There is no specific theoretical base for the county-interacting mechanism of this empirical model, whereas, the magnitude of each independent variable's impact on employment growth depends on the spatial-weight matrixes. To find a better match, I compare the parameters of the model by using two different weight matrixes, i.e., weights based on physical neighbor interaction and weights based on commuting ties. === (cont.) Based on the result of statistical comparison, the commuting tie is more likely the way by which counties interact with each other than physical proximity in the Appalachian Region. My empirical model is not able to explain completely the employment growth for all the counties in Appalachian Region, even after being adjusted for the spatial spillover effects, but it does provide some insight about what factors might matter for many places for their competitive employment growth from 1990 to 2000. Also, by analyzing the residuals of this model, analysts will be able to find some good candidates for case studies to understand what other determinants of economic growth might be. === by Zhijun (Jeanne) Tan. === M.C.P.
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