Masters Theses

Date of Award

12-2008

Degree Type

Thesis

Degree Name

Master of Science

Major

Agricultural Economics

Major Professor

Dayton M. Lambert

Committee Members

Daniel De La Torre Ugarte, Burton English, Kim Jensen

Abstract

As rural areas struggle to adjust to the changing U.S. economy with increasing unemployment, falling wages, and constrained capital markets, economic developers look for strategies to promote economic expansion. Development strategies identifying and evaluating county comparative advantage may offer the promise of economic growth in rural areas. This thesis develops two models whereby county comparative advantage can be empirically identified and evaluated. The study first examines ethanol plant location determinants at the county level, in the contiguous forty-eight United States, the second identified industry clusters within Tennessee at the county level and estimated the extent to which these clusters contributed to growth in labor productivity.

In the first study, the location of grain-based ethanol plants is determined by infrastructure, product and input markets, fiscal attributes of local communities, and state and federal incentives. Bivariate probit regression along with spatial clustering methods are used to analyze investment activity of ethanol plants at the county level for the contiguous 48 United States from 2000-2007. The ability of a county to supply feedstock, and the absence of previously established ethanol plants, dominated the site selection decision between 2000 and 2007. Other factors, such as access to railroads or navigable rivers, product markets, low worker wages, producer credit and excise tax incentives, and methyl tertiary-butyl ether bans gave some counties comparative advantage with respect to attracting grain-based ethanol plant investment.

The second study identified industry clusters or economic linkages between purchasers and suppliers, at the county and regional level for 447 economic sectors in Tennessee. Information about value-added activities or innovative potential is possible by determining the sector composition of the value chains defining an industry cluster. The cluster analysis was extended to estimate the extent to which specific value chains contributed to economic growth between 2001 and 2006 across Tennessee’s 95 counties using an econometric model. County and regional comparative advantage was determined by testing whether the presence of a particular value chain in a given county increased labor productivity during this period.

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