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The Cognitive Demands of Work and the Length of Working Life: The Case of Computerization

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  • Robert Willis

    (University of Michigan)

Abstract

This paper focuses on impact of computerization on the work and retirement decisions of the cohort of 51-61 year old individuals who entered the Health and Retirement Study in 1992 and have been followed for next 18 years through 2010. I use data on cognition and detailed occupations in the HRS linked to a measure of occupational computerization from the O*NET data assembled by the Bureau of Labor Statistics. Beginning with Autor et al. (2003), the labor economics literature suggests that advances in computers substitute for the tasks done by many middle-skilled workers and complement those done by high-skilled individuals. Advances in computer technology tend, therefore, to lower the productivity of the middle-skilled and raise the productivity of the high skilled. Older workers face a decision of whether to invest in keeping up with new technology, shifting to another occupation or exiting from full time work into partial or full retirement. I find strong evidence that women and many men retired earlier if they are in computer-intensive occupations while, for other men it appears that computerization does not have a significant effect on retirement. Higher cognition and being in a high wage occupation appears to partially offset retirement incentives of computerization.

Suggested Citation

  • Robert Willis, 2013. "The Cognitive Demands of Work and the Length of Working Life: The Case of Computerization," Discussion Papers 13-015, Stanford Institute for Economic Policy Research.
    • Handle: RePEc:sip:dpaper:13-015
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    References listed on IDEAS

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    1. Bonsang, Eric & Adam, Stéphane & Perelman, Sergio, 2012. "Does retirement affect cognitive functioning?," Journal of Health Economics, Elsevier, vol. 31(3), pages 490-501.
    2. Eli Berman & John Bound & Zvi Griliches, 1994. "Changes in the Demand for Skilled Labor within U. S. Manufacturing: Evidence from the Annual Survey of Manufactures," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(2), pages 367-397.
    3. Eileen M. Crimmins & Jung Ki Kim & Kenneth M. Langa & David R. Weir, 2011. "Assessment of Cognition Using Surveys and Neuropsychological Assessment: The Health and Retirement Study and the Aging, Demographics, and Memory Study," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 66(suppl_1), pages 162-171.
    4. Avner Ahituv & Joseph Zeira, 2011. "Technical Progress and Early Retirement," Economic Journal, Royal Economic Society, vol. 121(551), pages 171-193, March.
    5. 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.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
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    Cited by:

    1. 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.
    2. Brooke Helppie-McFall & Amanda Sonnega, 2018. "Feasibility and Reliability of Automated Coding of Occupation in the Health and Retirement Study," Working Papers wp392, University of Michigan, Michigan Retirement Research Center.

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