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Intelligent Machine Technology And Productivity Growth

Author

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  • David Leech
  • John Scott

Abstract

This paper provides preliminary estimates of the productivity impact of intelligent machine technology (IMT) and the rate of return to IMT research and development (R&D) over the next two decades. The paper adapts economists' traditional productivity growth model to enable the use of industrial experts' forecasts of a few key parameters of the model to form the estimates of productivity growth and rate of return. Respondents - from a sample of firms operating in IMT development and applications in the automotive, aerospace, and capital construction industries - anticipate that IMT will generate substantial productivity growth over the next two decades, and the estimated social rates of return to IMT R&D are substantial.

Suggested Citation

  • David Leech & John Scott, 2008. "Intelligent Machine Technology And Productivity Growth," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 17(7-8), pages 677-687.
  • Handle: RePEc:taf:ecinnt:v:17:y:2008:i:7-8:p:677-687
    DOI: 10.1080/10438590701785637
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    Cited by:

    1. Albert N. Link & John T. Scott, 2013. "The theory and practice of public-sector R&D economic impact analysis," Chapters, in: Albert N. Link & Nicholas S. Vonortas (ed.), Handbook on the Theory and Practice of Program Evaluation, chapter 2, pages 15-55, Edward Elgar Publishing.
    2. Link, Albert N. & Scott, John T., 2011. "The Theory and Practice of Public-Sector R&D Economic Impact Analysis: The Case of the National Institute of Standards and Technology," UNCG Economics Working Papers 11-16, University of North Carolina at Greensboro, Department of Economics.

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