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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 examines the impact of work-related training 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 - the years from the age of 23 to the age of 33. We use hurdle negative binominal models to estimate the number of work-related training events. This approach, which has not been used for training before, allows us to account for the fact that more than 50% of sample members experienced no work-related training over the period 1981 to 1991. We find evidence of strong complementaries between past general education and training, suggesting that reliance on job-related training to increase the skills of the British workforce will result in an increase in the skills of the already-educated, but will not improve the skills of individuals entering the labor market with a low level of education. The results generated from the hurdle count model are subsequently used in estimation of the wages growth model. We find that each additional training event is estimated to increase wages growth by 0.7 per cent, for young men experiencing at least one training occurrence over the decade.

Suggested Citation

  • Arulampalam, Wiji & Booth, Alison L & Elias, Peter, 1996. "Modeling Work-related Training and Training Effects Using Count Data Techniques," The Warwick Economics Research Paper Series (TWERPS) 448, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:448
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    File URL: https://warwick.ac.uk/fac/soc/economics/research/workingpapers/1995-1998/twerp448.pdf
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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

    Count data models ; hurdle ; training ; skills segmentation ; wages growth;
    All these keywords.

    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
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets

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