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Experience-biased technical change

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  • Caselli, Francesco

Abstract

The baby-boom cycle has caused very large swings in the relative supply of experienced workers (Örst a large decline, and then a large increase). Yet, the experience premium has failed to decline markedly in the period where the supply of experience has increased. I develop a methodology to estimate the increase in the relative demand for experience that is required to reconcile the behavor of prices and quantities, and show this to have been large - a phenomenon I dub experience-biased technical change. I conjecture that one of the drivers of experience-biased technical change is a decline in the relative demand for physical strength. In support this conjecture, I show that occupations requiring high or moderate physical strength have accounted for a declining share of weeks worked in the economy, with sedentary occupations experiencing a corresponding increase. I also conÖrm that older workers have a comparative disadvantage in occupations requiring physical strength.

Suggested Citation

  • Caselli, Francesco, 2015. "Experience-biased technical change," LSE Research Online Documents on Economics 86294, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:86294
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    File URL: http://eprints.lse.ac.uk/86294/
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    References listed on IDEAS

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    1. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    2. Daron Acemoglu, 1998. "Why Do New Technologies Complement Skills? Directed Technical Change and Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1055-1089.
    3. Galor, Oded & Weil, David N, 1996. "The Gender Gap, Fertility, and Growth," American Economic Review, American Economic Association, vol. 86(3), pages 374-387, June.
    4. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    5. Francesco Caselli & Wilbur John Coleman II, 2002. "The U.S. Technology Frontier," American Economic Review, American Economic Association, vol. 92(2), pages 148-152, May.
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    Cited by:

    1. Nir Jaimovich & Henry E. Siu, 2017. "High-Skilled Immigration, STEM Employment, and Nonroutine-Biased Technical Change," NBER Chapters, in: High-Skilled Migration to the United States and Its Economic Consequences, pages 177-204, National Bureau of Economic Research, Inc.
    2. Michael J. Böhm & Christian Siegel, 2021. "Make Yourselves Scarce: The Effect Of Demographic Change On The Relative Wages And Employment Rates Of Experienced Workers," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(4), pages 1537-1568, November.
    3. Rainer Kotschy & Uwe Sunde & Tommaso MonacelliManaging Editor, 2018. "Can education compensate the effect of population ageing on macroeconomic performance?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 33(96), pages 587-634.
    4. Orhun Sevinc, 2017. "Skill-Biased Technical Change and Labor Market Polarization: The Role of Skill Heterogeneity Within Occupations," Discussion Papers 1728, Centre for Macroeconomics (CFM).

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    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics

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