Building a knowledge economy index for southern metropolitan areas

The purpose of this thesis is to determine if the methodology used to build the South Carolina Research Authority Knowledge Economy Index (KEI) for states can be replicated and applied to Southern Metropolitan Statistical Areas (MSAs). Data to imitate the KEI measures for workforce education and fast growth firms were available at the MSA-level; however, academic R&D was used as a proxy for industrial R&D in this index because data was not available for MSAs. An index for Southern MSAs was built based on the coefficients from the OLS results. Workforce education was the most important factor for increasing mean per capita income. The fast growth firms variable was not significant in the regression. Academic R&D had a negative coefficient, the opposite sign of industrial R&D in the KEI. The residual analysis and the high rankings of university cities revealed this type of MSA to be critical to the index. Further analysis was performed on the education variable to determine the source of the high coefficient in the OLS results. Finally, this index was compared to other relevant indices. The thesis offers research-based suggestions for improving MSA-based Knowledge Economy indices. Other research is also recommended that focuses on university cities and the relationship between MSAs and the states in which they are located.