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Modeling Work-Related Training And Training Effects Using Count Data Techniques

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  • Arulampalam, Wiji
  • Booth, Alison L.
  • Elias, Peter

Abstract

This paper estimates the determinants of the number of work-related training courses, and their impact on expected wages growth, using longitudinal data from the British National Child Development Study. The analysis covers a crucial decade in the working lives of a cohort of young men – from the age of 23 to 33. We use hurdle negative binomial models to estimate the number of work-related training events. This approach allows us to account for the fact that half of all sample members experienced no work-related training over the period from 1981 to 1991. We then estimate a wages growth model where the returns from the first training experience are allowed to differ from subsequent training experiences. The results generated from the hurdle count model are used to control for training endogeneity in the wages growth equation. This has not been done before in the training literature. The sensitivity of the wage growth estimates to alternative modelling strategies is also examined. Since we find a strong correlation between education and subsequent training experiences, we experiment with estimating the joint impact of previous education and subsequent training on wages growth, in order to tease out the combined effect of these variables. We find that the biggest returns to training are to highly educated men.
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Suggested Citation

  • Arulampalam, Wiji & Booth, Alison L. & Elias, Peter, 1996. "Modeling Work-Related Training And Training Effects Using Count Data Techniques," Economic Research Papers 268697, University of Warwick - Department of Economics.
    • Handle: RePEc:ags:uwarer:268697
    DOI: 10.22004/ag.econ.268697
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    Cited by:

    1. J. M. Tomkins & J. Twomey, 2000. "Occupational mobility in England," Applied Economics, Taylor & Francis Journals, vol. 32(2), pages 193-209.
    2. O'Neill, Donal & Sweetman, Olive, 1998. "Intergenerational Mobility in Britain: Evidence from Unemployment Patterns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 60(4), pages 431-447, November.
    3. Eli Haim HANI, 2021. "The Effect Of Key Business Success Factors On Start-Up Performance," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 18, pages 117-129, December.
    4. Groot, Wim & van den Brink, Henriette Maassen, 2003. "Firm-related training tracks: a random effects ordered probit model," Economics of Education Review, Elsevier, vol. 22(6), pages 581-589, December.

    More about this item

    Keywords

    Labor and Human Capital; Teaching/Communication/Extension/Profession;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets

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