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Technology, Unemployment, and Inflation

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  • Jacob Mincer
  • Stephan Danninger

Abstract

We explore the response of employment (unemployment) skill differentials to skill-biased shifts in demand touched off by the new and spreading technologies. We find that skill differentials in unemployment follow at least in part the same pattern as skill differentials in wages: They widen initially but decline after a roughly 5-year lag, allowing time for training and learning to handle the new technologies. In the micro (PSID) cross-section the differentials show up as sectoral differences defined by technology. In the aggregate time series relative unemployment is defined by educational unemployment differentials. We find that the pace and turnaround in the unemployment gap' is twice as fast as in the wage gap'. Apparently, the hiring and training response is quicker than the wage response. We also observe in time series that the pace of technology has unclear effects on aggregate unemployment in the short run, but appears to reduce it in the longer run. In addition to technology, maturing of the workforce, and growth of international trade reduce unemployment in the longer run. The same variables also significantly reduce inflation in both the short and long run. Given the actual changes in these factors in the early 90's we are able to predict a little over a half of the decline in unemployment and about 70% of the reduction in inflation in the latter half of the last decade.

Suggested Citation

  • Jacob Mincer & Stephan Danninger, 2000. "Technology, Unemployment, and Inflation," NBER Working Papers 7817, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:7817
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    References listed on IDEAS

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    Cited by:

    1. Edward N. Wolff, 2005. "Computerization and Rising Unemployment Duration," Eastern Economic Journal, Eastern Economic Association, vol. 31(4), pages 507-536, Fall.
    2. Siena Daniele, & Zago Riccardo., 2021. "Job Polarization and the Flattening of the Price Phillips Curve," Working papers 819, Banque de France.
    3. Pablo Burriel-Llombart & Jonathan Thomas, 2001. "Skill imbalances in the UK labour market: 1979-99," Bank of England working papers 145, Bank of England.
    4. Bharat Trehan, 2003. "Productivity shocks and the unemployment rate," Economic Review, Federal Reserve Bank of San Francisco, pages 13-27.
    5. Rajarshi Majumder, 2018. "Technology and Labour Market: Insights from Indian Manufacturing Sector," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 61(2), pages 321-338, June.
    6. Jacob Mincer, 2006. "Technology and the Labor Market," Springer Books, in: Shoshana Grossbard (ed.), Jacob Mincer A Pioneer of Modern Labor Economics, chapter 8, pages 53-77, Springer.
    7. Mirzaei Abbasabadi, Hamed & Soleimani, Mohammad, 2021. "Examining the effects of digital technology expansion on Unemployment: A cross-sectional investigation," Technology in Society, Elsevier, vol. 64(C).
    8. José Alves & João Quental Gonçalves, 2022. "How Money relates to value? An empirical examination on Gold, Silver and Bitcoin," Working Papers REM 2022/0222, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    9. Dube, S. & Dube, M. & Turan, A., 2015. "Information technology in Turkey: Creating high-skill jobs along with more unemployed highly-educated workers?," Telecommunications Policy, Elsevier, vol. 39(10), pages 811-829.
    10. Wei Zou & Lan Liu & Ziyin Zhuang, 2009. "Skill Premium, Biased Technological Change and Income Differences," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 17(6), pages 64-87, November.

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