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An Empirical Model of the Sources of Innovation in the U.S. Manufacturing Sector

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  • Jeremy A Leonard
  • Cliff Waldman

Abstract

This paper estimates a simple model of innovation in the U.S. manufacturing sector and derives summary indicators of product and process innovation. Our empirical work reveals that the drivers of innovation extend well beyond business research and development (R&D) spending. Capital investment, cutting-edge scientific output from academic institutions, and the growth of the science and engineering workforce all matter. The dynamic structure of our model suggests that policymakers must look beyond the short-term when developing and evaluating innovation initiatives because there can be lags of several years before inputs are fully realized in innovative performance. But simple simulations conducted with our equations indicate that even a modest increase in key innovation inputs reaps significant benefits.Business Economics (2007) 42, 33–45; doi:10.2145/20070404

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  • Jeremy A Leonard & Cliff Waldman, 2007. "An Empirical Model of the Sources of Innovation in the U.S. Manufacturing Sector," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 42(4), pages 33-45, October.
    • Handle: RePEc:pal:buseco:v:42:y:2007:i:4:p:33-45
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    Cited by:

    1. Cliff Waldman, 2016. "The Evolving Contours of Productivity Performance and Automation Investment in U.S. Manufacturing," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 51(4), pages 213-238, October.
    2. Abdul Waheed & Xiaoming Miao & Salma Waheed & Naveed Ahmad & Abdul Majeed, 2019. "How New HRM Practices, Organizational Innovation, and Innovative Climate Affect the Innovation Performance in the IT Industry: A Moderated-Mediation Analysis," Sustainability, MDPI, vol. 11(3), pages 1-21, January.

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