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

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  • 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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Bibliographic Info

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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Related research

Keywords: endogenous regressor; inverse probability weighting; ordered probit; work-related training;

References

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  1. 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.
  2. 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.
  3. S Black & L Lynch, 1997. "How to Compete: The Impact of Workplace Practices and Information Technology on Productivity," CEP Discussion Papers dp0376, Centre for Economic Performance, LSE.
  4. Ann P. Bartel & Nachum Sicherman, 1997. "Technological Change and Wages: An Inter-Industry Analysis," NBER Working Papers 5941, National Bureau of Economic Research, Inc.
  5. 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.
  6. Bassanini, Andrea & Booth, Alison L. & Brunello, Giorgio & De Paola, Maria & Leuven, Edwin, 2005. "Workplace Training in Europe," IZA Discussion Papers 1640, Institute for the Study of Labor (IZA).
  7. Cheti Nicoletti, 2002. "Non-Response in Dynamic Panel Data Models," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A5-4, International Conferences on Panel Data.
  8. Schmid, G√ľnther, 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).
  9. 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.
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