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Does Factor-Biased Technological Change Stifle International Covergence? Evidence from Manufacturing

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  • Eli Berman

Abstract

Factor-biased technological change implies divergent productivity growth across countries with different amounts of skill and capital per worker. I estimate the extent of factor bias within industries and countries using a 19-country panel of manufacturing data covering the 1980s. Estimates using both production functions and total factor productivity functions show that technological change is strongly biased against less-skilled workers and toward both skilled workers and capital. An industry or country with twice the capital and skill per less-skilled worker enjoys 1.4%-1.8% faster total factor productivity growth annually due to the effects of factor-bias. These results are consistent with the empirical literature on skill-biased technological change. They may well explain why conditional convergence' of per capita income across countries is so slow.

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  • Eli Berman, 2000. "Does Factor-Biased Technological Change Stifle International Covergence? Evidence from Manufacturing," NBER Working Papers 7964, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:7964
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    3. Anders Akerman & Ingvil Gaarder & Magne Mogstad, 2015. "The Skill Complementarity of Broadband Internet," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1781-1824.
    4. Eli Berman & Rohini Somanathan & Hong W. Tan, 2010. "Is Skill-Biased Technological Change Here Yet? Evidence from Indian Manufacturing in the 1990s," NBER Chapters, in: Contributions in Memory of Zvi Griliches, pages 299-321, National Bureau of Economic Research, Inc.
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    6. Pawlik, Konrad, 2005. "How knowledge transfer and absorption impact on the profitability of foreign affiliates in Transition Economy? The case of Poland: 1993-2002," Working Papers 2005-5, University of Aarhus, Aarhus School of Business, Department of Management.
    7. Betcherman, Gordon, 2002. "An overview of labor markets world-wide : key trends and major policy issues," Social Protection Discussion Papers and Notes 25510, The World Bank.
    8. Vinoj Abraham, 2010. "The Effect of Information Technology on Wage Inequality: Evidence from Indian Manufacturing Sector," Working Papers id:3180, eSocialSciences.
    9. Swati Virmani, 2019. "Are Technology Transfers Skill Biased?," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 62(2), pages 239-263, June.

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    More about this item

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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