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Technical Change, Learning, and Wages

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  • Ann P. Bartel
  • Frank R. Lichtenberg

Abstract

This paper examines the relationship between technological change and wages using pooled cross-sectional industry-level data and several alternative indicators of the rate of introduction of new technology. Our main finding is that industries with a high rate of technical change pay higher wages to workers of given age and education, compared to less technologically advanced industries. This is Consistent with the notion that the introduction of new technology creates a demand for learning, that learning is a function of employee ability and effort, and that increases in wages are required to elicit increases in ability and effort. A related finding is that the wages of highly educated workers (especially recent graduates) relative to those of less educated workers are highest in technologically advanced industries; this is consistent with the notion that educated workers are better learners.

Suggested Citation

  • Ann P. Bartel & Frank R. Lichtenberg, 1988. "Technical Change, Learning, and Wages," NBER Working Papers 2732, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:2732
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    Cited by:

    1. Stavrev, Emil, 2000. "A Comparative Analysis of the Czech Republic and Hungary. Using small Continuous-Time Macroeconometric Models," Transition Economics Series 19, Institute for Advanced Studies.
    2. Thushyanthan Baskaran & Zohal Hessami, 2012. "Public education spending in a globalized world:," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(5), pages 677-707, October.
    3. Thushyanthan Baskaran & Zohal Hessami, 2011. "Public Education Spending in a Globalized World: Is there a Shift in Priorities Across Educational Stages?," Working Paper Series of the Department of Economics, University of Konstanz 2011-42, Department of Economics, University of Konstanz.
    4. Lichtenberg, Frank R. & Siegel, Donald, 1990. "The effects of leveraged buyouts on productivity and related aspects of firm behavior," Journal of Financial Economics, Elsevier, vol. 27(1), pages 165-194, September.
    5. Grace Yuehan Wang, 2022. "Talent Migration in Knowledge Economy: The Case of China’s Silicon Valley, Shenzhen," Journal of International Migration and Integration, Springer, vol. 23(3), pages 1175-1196, September.
    6. Alice Civera & Davide Donina & Michele Meoli & Silvio Vismara, 2020. "Fostering the creation of academic spinoffs: does the international mobility of the academic leader matter?," International Entrepreneurship and Management Journal, Springer, vol. 16(2), pages 439-465, June.

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