Degree Type


Date of Award


Degree Name

Master of Science




This thesis examines whether industry clustering results in higher manufacturing wages for Iowa counties. The industry for any given plant is defined to be the set of 3-digit SIC codes that use unusually large proportions of the same occupations as it's own 3-digit SIC code, as measured by key-occupation elasticities. Industry clustering is captured by measures of industry density (the number and relative size of plants in the industry) and industry size. A model is used which includes controls for workforce size (urbanization), plant size, mix of 4-digit industries, workforce education, and other relevant variables that predict county manufacturing earnings per worker. Weighted least squares regressions were performed for ten manufacturing sectors. The combined effect of industry size and industry density on manufacturing earnings is negative in half of the ten sectors.;The four sectors where clustering has the largest negative effects on wages are sectors where a significant share of rural plants serve local markets. Increases in industry size raise earnings in metals, industrial equipment and transportation equipment by a modest amount. Workforce size has a substantial positive effect on earnings in most manufacturing sectors, as does plant size. Urbanization is estimated to have the strongest effect on earnings in printing & publishing, electronics & instruments, and chemicals. The only two sectors where it has virtually no positive effect on wages are textile & leather products and meatpacking. The coefficients estimated by the model accurately predict differences between metro and non-metro counties earnings in general, but are not able to fully account for wide differences in earnings among non-metro county types.



Digital Repository @ Iowa State University,

Copyright Owner

Lee Edwin Hill



OCLC Number


File Format


File Size

171 pages

Included in

Economics Commons