IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/10752.html
   My bibliography  Save this paper

Experience-Biased Technical Change

Author

Listed:
  • Caselli, Francesco

Abstract

The baby-boom cycle has caused very large swings in the relative supply of experienced workers (first 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 confirm that older workers have a comparative disadvantage in occupations requiring physical strength.

Suggested Citation

  • Caselli, Francesco, 2015. "Experience-Biased Technical Change," CEPR Discussion Papers 10752, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10752
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP10752
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francesco Caselli, 2014. "Experience-biased Technical Change," Discussion Papers 1517, Centre for Macroeconomics (CFM), revised Jul 2015.
    2. Riccardo Leoncini, 2017. "Innovation, inequality and the skill premium," SPRU Working Paper Series 2017-16, SPRU - Science Policy Research Unit, University of Sussex Business School.
    3. Caselli, Francesco, 2015. "Experience-biased technical change," LSE Research Online Documents on Economics 86294, London School of Economics and Political Science, LSE Library.
    4. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    5. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    6. Daron Acemoglu & Gino Gancia & Fabrizio Zilibotti, 2015. "Offshoring and Directed Technical Change," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(3), pages 84-122, July.
    7. T. Gries & R. Grundmann & I. Palnau & M. Redlin, 2017. "Innovations, growth and participation in advanced economies - a review of major concepts and findings," International Economics and Economic Policy, Springer, vol. 14(2), pages 293-351, April.
    8. Silvia Vannutelli & Sergio Scicchitano & Marco Biagetti, 2022. "Routine-biased technological change and wage inequality: do workers’ perceptions matter?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 409-450, September.
    9. Jerzmanowski, Michal & Tamura, Robert, 2019. "Directed technological change & cross-country income differences: A quantitative analysis," Journal of Development Economics, Elsevier, vol. 141(C).
    10. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    11. Marin, Giovanni & Vona, Francesco, 2023. "Finance and the reallocation of scientific, engineering and mathematical talent," Research Policy, Elsevier, vol. 52(5).
    12. M. Battisti & M. Del Gatto & A. F. Gravina & C. F. Parmeter, 2021. "Robots versus labor skills: a complementarity/substitutability analysis," Working Paper CRENoS 202104, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    13. Pi, Jiancai & Zhang, Pengqing, 2018. "Skill-biased technological change and wage inequality in developing countries," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 347-362.
    14. Nicholas W Papageorge & Kevin Thom, 2020. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Journal of the European Economic Association, European Economic Association, vol. 18(3), pages 1351-1399.
    15. Guy Michaels & Ferdinand Rauch & Stephen J Redding, 2019. "Task Specialization in U.S. Cities from 1880 to 2000," Journal of the European Economic Association, European Economic Association, vol. 17(3), pages 754-798.
    16. Ariell Reshef, 2013. "Is Technological Change Biased Towards the Unskilled in Services? An Empirical Investigation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(2), pages 312-331, April.
    17. Paul Gaggl & Greg C. Wright, 2017. "A Short-Run View of What Computers Do: Evidence from a UK Tax Incentive," American Economic Journal: Applied Economics, American Economic Association, vol. 9(3), pages 262-294, July.
    18. Anton Korinek & Joseph E. Stiglitz, 2021. "Artificial Intelligence, Globalization, and Strategies for Economic Development," Working Papers Series inetwp146, Institute for New Economic Thinking.
    19. Gaetano Basso & Giovanni Peri & Ahmed S. Rahman, 2020. "Computerization and immigration: Theory and evidence from the United States," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(4), pages 1457-1494, November.
    20. Castex, Gonzalo & (Stanley) Cho, Sang-Wook & Dechter, Evgenia, 2022. "The decline in capital-skill complementarity," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).

    More about this item

    Keywords

    Baby boom; Experience premium; Technical change;
    All these keywords.

    JEL classification:

    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cpr:ceprdp:10752. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.