Date of Award
Master of Science
Dayton M. Lambert
Burton C. English, Kimberly L. Jensen, Michael D. Wilcox
A number of renewable, or so-called “green energy” products have emerged in response to the environmental, national security, and economic risks posed by the consumption of fossil fuels. The development of the renewable fuels sector, including ethanol, biodiesel, landfill and dairy methane gas, and solar and wind energy have also been considered potential sources of economic growth. But continuously changing market and policy conditions put at risk recent accomplishments in green energy sector development, thus placing a greater emphasis on efficient coordination between producers and suppliers.
Recent advances in firm location theory have produced a variety of analytical tools to determine the effects of geographical proximity on industry upstream and downstream linkages. Locations exhibiting a comparative advantage with respect to attracting green energy business establishments can also be statistically identified with these new approaches. These analytical developments are used to analyze the uneven spatial distribution of businesses and employment, generally described as “concentration”. Findings may supplement more effective policy design and recommendations, and could provide investors with additional information about which locations may be associated with cost savings.
The US County Business Patterns (CBP) database organizes employment and establishment data into a hierarchy by county and has been among the primary data sources for industry concentration analysis. Until recently, studies at finer levels of the geographic and industry hierarchy have been difficult due to suppression of employment data. Several procedures have been developed that use information contained in the CBP databases to impute missing employment records.
This two-paper thesis contributes to the analysis of firm location by: (1) providing a discussion of existing methods of missing employment data imputation and contributing a new imputation procedure, and (2) developing a two-stage method to analyze the geographic distribution of firms and employment, which is applied to ten value chains in the renewable energy sector. Full, accurate datasets and richer analytical methods can be applied to analyze industry concentration patterns and their potential impact on rural economies in future research. The findings and analytical contributions of this thesis may benefit policy makers and investors in green energy, regional scientists and economic geographers.
Register, David Lane, "Data Anti-Suppression Methods and an Application of Spatial Concentration Measures to Evaluate Green Energy Value Chain Concentration. " Master's Thesis, University of Tennessee, 2012.