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Skill Bias Magnified: Intersectoral Linkages and White-Collar Labor Demand in U.S. Manufacturing

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  • Nico Voigtländer

    (UCLA and NBER)

Abstract

This paper presents a novel stylized fact and analyzes its contribution to the skill bias of technical change in U.S. manufacturing. The share of skilled labor embedded in intermediate inputs correlates strongly with the skill share employed in final production. This finding points toward an intersectoral technology-skill complementarity (ITSC). Together with input-output linkages, the observed complementarity delivers a multiplier that reinforces skill demand along the production chain. Reduced-form estimates suggest that the effect is quantitatively important, explaining about as much skill upgrading as outsourcing. Empirical evidence suggests that one channel through which this complementarity works is product innovation. I also analyze the importance of different drivers of skill upgrading over time. While foreign outsourcing and IT capital are associated with skill demand particularly strongly from the 1980s on (a period of rapidly increasing skill premiums), R&D contributed stably throughout the period 1958 to 2005. The same is true for ITSC, which augmented within-sector skill bias in a stable fashion throughout the past five decades. © 2014 The President and Fellows of Harvard College and the Massachusetts Institute of Technology

Suggested Citation

  • Nico Voigtländer, 2014. "Skill Bias Magnified: Intersectoral Linkages and White-Collar Labor Demand in U.S. Manufacturing," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 495-513, July.
  • Handle: RePEc:tpr:restat:v:96:y:2014:i:3:p:495-513
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    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00390
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    Citations

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    Cited by:

    1. Atolia, Manoj & Kurokawa, Yoshinori, 2016. "The impact of trade margins on the skill premium: Evidence from Mexico," Journal of Policy Modeling, Elsevier, vol. 38(5), pages 895-915.
    2. Marcela Eslava & Ana Cecília Fieler & Daniel Yi Xu, 2015. "(Indirect) Input Linkages," American Economic Review, American Economic Association, vol. 105(5), pages 662-666, May.
    3. Schulte, Patrick, 2021. "Skill Bias magnified: Identifying the role of international technology diffusion," Journal of International Economics, Elsevier, vol. 129(C).
    4. Justin Caron & Thibault Fally & James Markusen, 2021. "Per capita income and the demand for skills," World Scientific Book Chapters, in: BROADENING TRADE THEORY Incorporating Market Realities into Traditional Models, chapter 12, pages 251-268, World Scientific Publishing Co. Pte. Ltd..
    5. Robert C. Feenstra, 2017. "Statistics to Measure Offshoring and its Impact," NBER Working Papers 23067, National Bureau of Economic Research, Inc.
    6. Óscar Afonso & Tiago Neves Sequeira & Marcelo Santos & Pedro Cunha Neves, 2023. "Global Firms, (de)unionization and Wage Inequality," Open Economies Review, Springer, vol. 34(5), pages 979-1013, November.

    More about this item

    Keywords

    U.S. Income Inequality; Skill-Biased Technical Change; Intermediate Linkages; Input-Output; Complementarity;
    All these keywords.

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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