Semester

Spring

Date of Graduation

2013

Document Type

Dissertation

Degree Type

PhD

College

Chambers College of Business and Economics

Department

Economics

Committee Chair

Stratford M. Douglas

Committee Co-Chair

Tami Gurley-Calvez

Committee Member

Tim Phipps

Committee Member

Santiago Pinto

Committee Member

Andrew Young

Abstract

This dissertation is a collection of papers examining the relationship between resource intensity and economic growth in the Appalachian region of the United States. The first chapter develops a homogenous sample of counties within the Appalachian region and uses that sample to investigate how coal resources impact long-run per capita income growth. The Appalachian Regional Commission's definition of the Appalachian region is the one used most often by researchers, politicians, and the popular press. The uncritical use of this definition of Appalachia raises issues of both selection bias and excess heterogeneity in regression analysis of Appalachian income and growth. The ARC was created as part of President Johnson's war on poverty, and the geographical extent of its purview has been driven by politics and by the geography of poverty, neither of which is exogenous. It is well known that the use of endogenous variables to choose a sample creates bias and inconsistency in estimation of regression coefficients. To identify the counties that belong to the Appalachian region exogenously we use an algorithm based on three criteria: topography, contiguity, and prevalence of slavery in the 1860 census. We apply our sample to growth regressions using data from 1970 to 2008, addressing the question of the existence of a resource curse from coal extraction. For this model we find strong evidence of excess heterogeneity, but not bias.;In the second chapter, I extend the analysis by exploring different possible measures for coal resource abundance. I use both a geologic based measure of "abundance" and a flow based measure of "dependence", and find evidence that coal abundance significantly reduces growth of per capita income over the long run with both measures. In addition, I use a wide variety of alternative measures of resource abundance suggested by the literature, all which indicate a negative systematic effect of resources on income growth. I account for the endogeneity of the each flow measure with instruments, and when I also account for the endogeneity of initial income, results indicate that a one standard deviation increase in the measure of resource intensity results in a 0.43 percentage point drop in average annual growth.;In the third chapter, I investigate several of the causes for the under-performance by many resource rich counties in the Appalachian region. I examine the effect of coal abundance on educational attainment, local (county) level education expenditure decisions, and local level taxation decisions. I find evidence that the educational attainment channel accounts for a significant portion of the negative effect of resource abundance. Coal resource abundance tends to reduce educational attainment, reducing human capital in a county, which in turn reduces per capita income growth over the long run. When attainment is measured by the share of the population that dropped out of high school, a one standard deviation increase in the measure of resource abundance reduces average annual growth by an estimated 0.125 percentage points. When educational attainment is measured instead by the share of the population that completed a college degree, average annual growth is reduced by an estimated 0.037 percentage points. I find no evidence that resource abundance affects the education expenditure allocation decisions of local county governments, nor do I find evidence that resource rich counties test to under tax their populations.

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