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Simulating the Lisbon skills targets in WorldScan

  • Bas Jacobs


This paper explains the theoretical background, the analytical methods, calibrations, assumptions and computations of the skill inputs for the WorldScan analysis on the skills targets of the Lisbon agenda. The Lisbon skills targets are implemented in WorldScan using most recent theoretical and empirical research in human capital theory. In particular, a satellite model for WorldScan is developed which disaggregates high skilled labour in S&E and non-S&E workers, and low skilled labour in workers with primary education (or less), lower secondary education, and higher secondary levels of education. In addition, workers can acquire skills through on-the-job training. The quality of the workforce may also increase by a higher quality of initial education. Finally, a stylised cohort model is developed to capture the time-lag between changes in policies and the eventual impact on the labour force. In implementing the skills targets we take heterogeneity between various EU countries into account with respect to the following skill variables: initial average levels of education, the returns to education, graduation rates in upper-secondary education, participation in on-the-job training, and the graduation shares in S&E education.

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Paper provided by CPB Netherlands Bureau for Economic Policy Analysis in its series CPB Memorandum with number 135.

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Date of creation: Dec 2005
Date of revision:
Handle: RePEc:cpb:memodm:135
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  1. Derek A. Neal & William R. Johnson, 1995. "The Role of Pre-Market Factors in Black-White Wage Differences," NBER Working Papers 5124, National Bureau of Economic Research, Inc.
  2. Heckman, James J, 1976. "A Life-Cycle Model of Earnings, Learning, and Consumption," Journal of Political Economy, University of Chicago Press, vol. 84(4), pages S11-44, August.
  3. James J. Heckman, 1999. "Policies to Foster Human Capital," NBER Working Papers 7288, National Bureau of Economic Research, Inc.
  4. Alan B. Krueger, 2003. "Economic Considerations and Class Size," Economic Journal, Royal Economic Society, vol. 113(485), pages F34-F63, February.
  5. Orley Ashenfelter & Colm Harmon & Hessel Oosterbeek, 2000. "A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias," NBER Working Papers 7457, National Bureau of Economic Research, Inc.
  6. Yoram Ben-Porath, 1967. "The Production of Human Capital and the Life Cycle of Earnings," Journal of Political Economy, University of Chicago Press, vol. 75, pages 352.
  7. Bas Jacobs, 2003. "The lost race between schooling and technology," CPB Discussion Paper 25, CPB Netherlands Bureau for Economic Policy Analysis.
  8. Richard J. Murnane & John B. Willett & Frank Levy, 1995. "The Growing Importance of Cognitive Skills in Wage Determination," NBER Working Papers 5076, National Bureau of Economic Research, Inc.
  9. James J. Heckman & Lance Lochner & Christopher Taber, 1998. "Explaining Rising Wage Inequality: Explorations with a Dynamic General Equilibrium Model of Labor Earnings with Heterogeneous Agents," NBER Working Papers 6384, National Bureau of Economic Research, Inc.
  10. Janet Currie & Duncan Thomas, 1999. "Early Test Scores, Socioeconomic Status and Future Outcomes," NBER Working Papers 6943, National Bureau of Economic Research, Inc.
  11. Colm Harmon & Hessel Oosterbeek & Ian Walker, 2003. "The Returns to Education: Microeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 17(2), pages 115-156, 04.
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