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Technology Adoption and the Skill Mix of US Manufacturing Plants


Timothy Dunne


Federal Reserve Bank of Cleveland

Kenneth R. Troske


University of Kentucky - Department of Economics; University of Missouri at Columbia - Department of Economics; Institute for the Study of Labor (IZA)


Scottish Journal of Political Economy, Vol. 52, No. 3, pp. 387-405, July 2005

Abstract:     
This paper examines the relationship between technology adoption and the skill mix of the workforce in US manufacturing plants. Using information on the use and adoption of seven different information technologies, we find that the relationship between technology adoption and workforce skill varies across the technologies. The use and adoption of engineering and design tasks are associated with workplaces that have a relatively large share of nonproduction labor. When we examine the relationship between technology adoption and skill upgrading of workforces, we find little correlation between the use and/or adoption of technologies and changes in workforce skill at the plant level. However, we do find that plants adopting technologies related to engineering and design tasks grow faster over the period 1987-1997.

Number of Pages in PDF File: 19

Accepted Paper Series


Date posted: July 22, 2005  

Suggested Citation

Dunne, Timothy and Troske, Kenneth R., Technology Adoption and the Skill Mix of US Manufacturing Plants. Scottish Journal of Political Economy, Vol. 52, No. 3, pp. 387-405, July 2005. Available at SSRN: http://ssrn.com/abstract=758633

Contact Information

Timothy Dunne (Contact Author)
Federal Reserve Bank of Cleveland ( email )
PO Box 6387
Cleveland, OH 44101-1387
United States
Kenneth R. Troske
University of Kentucky - Department of Economics ( email )
Lexington, KY 40506
United States
University of Missouri at Columbia - Department of Economics ( email )
118 Professional Building
Columbia, MO 65211
United States
573-882-4229 (Phone)
573-882-2697 (Fax)
Institute for the Study of Labor (IZA)
P.O. Box 7240
Bonn, D-53072
Germany
Feedback to SSRN (Beta)


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