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Does work-related training reduce the discrepancy between function requirements and competencies?

Author Info

  • Kappe, E.R.
  • Bijwaard, G.E.

Abstract

The issue of lifelong learning is high on the political agenda. However, despite this political interest and the large economic literature on human capital, the impact of work-related training on the discrepancy between function requirements and the skills of the employee has been ignored. In this paper we use an ordered probit model to analyze the perceived change in discrepancy. Based on the bi-annual OSA panel from 1998 till 2002 for The Netherlands, we show that taking a work-related course decreases the discrepancy significantly. We correct for the endogeneity between the decision to take a course and the change in discrepancy and we argue that ignoring the selective decision to take a course leads to misleading conclusions about the effect of these courses on the change in discrepancy. Some respondents of the OSA-panel drop out between two waves. To correct for the possibility of selective attrition we develop an Inverse Probability Weight (IPW) estimation method for the ordered probit with an endogenous binary regressor. From the implied marginal effects of the IPW estimation we conclude that taking a course increases the probability to change the fit between skills and function requirements from Bad to Good with 16~percent-point.

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File URL: http://repub.eur.nl/pub/7029/EI2005-42.pdf
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Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2005-42.

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Date of creation: 07 Nov 2005
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Handle: RePEc:ems:eureir:7029
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Keywords: endogenous regressor; inverse probability weighting; ordered probit; work-related training;

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  1. Schmid, Günther, 1998. "Transitional labour markets: A new European employment strategy," Discussion Papers, Research Unit: Labor Market Policy and Employment FS I 98-206, Social Science Research Center Berlin (WZB).
  2. Nicoletti, Cheti, 2006. "Nonresponse in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 461-489, June.
  3. Ann P. Bartel & Nachum Sicherman, 1999. "Technological Change and Wages: An Interindustry Analysis," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 285-325, April.
  4. Lisa M Lynch & Sandra E Black, 2002. "How to Compete: The Impact of Workplace Practices and Information Technology on Productivity," Working Papers 02-04, Center for Economic Studies, U.S. Census Bureau.
  5. John G. Cragg & Russell S. Uhler, 1970. "The Demand for Automobiles," Canadian Journal of Economics, Canadian Economics Association, vol. 3(3), pages 386-406, August.
  6. Andrea Bassanini & Alison Booth & Giorgio Brunello & Maria De Paola & Edwin Leuven, 2006. "Workplace training in Europe," Post-Print halshs-00120601, HAL.
  7. Booth, Alison L, 1993. "Private Sector Training and Graduate Earnings," The Review of Economics and Statistics, MIT Press, vol. 75(1), pages 164-70, February.
  8. Lynch, Lisa M, 1992. "Private-Sector Training and the Earnings of Young Workers," American Economic Review, American Economic Association, vol. 82(1), pages 299-312, March.
  9. Booth, Alison L, 1991. "Job-Related Formal Training: Who Receives It and What Is It Worth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 53(3), pages 281-94, August.
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