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The impact of training on productivity and wages : evidence from British panel data

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  • Dearden, Lorraine
  • Reed, Howard
  • Van Reenen, John

Abstract

It is standard in the literature on training to use wages as a sufficient statistic for productivity. But there are many reasons why wages and productivity may diverge. This paper is part of a smaller literature on the effects of work-related training on direct measures of productivity. We construct a panel of British industries between 1983 and 1996 containing training, productivity and wages. Using a variety of econometric estimation techniques (including system GMM) we find that training is associated with significantly higher productivity. Raising the proportion of workers trained in an industry by one percentage point (say from the average of 10% to 11%) is associated with an increase in value added per worker of about 0.6% and an increase in wages of about 0.3%. Furthermore, we find that the magnitude of the impact of training on wages is only half as large as the impact of training on productivity, implying that the existing literature has underestimated the importance of training. We also show evidence using complementary datasets (e.g. from individuals) that is suggestive of externalities of training and imperfect competition.

Suggested Citation

  • Dearden, Lorraine & Reed, Howard & Van Reenen, John, 2005. "The impact of training on productivity and wages : evidence from British panel data," Economic History Working Papers 779, London School of Economics and Political Science, Department of Economic History.
  • Handle: RePEc:ehl:wpaper:779
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    References listed on IDEAS

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    Cited by:

    1. Kristina Sisyuk, 2018. "Training, knowledge, competence, performance: what is the relationship?," Journal of Administrative and Business Studies, Professor Dr. Usman Raja, vol. 4(6), pages 297-312.
    2. Cuevas, Víctor M., 2010. "The dynamics of Mexican manufacturing exports," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    3. Lorraine Dearden & Howard Reed & John Van Reenen, 2006. "The Impact of Training on Productivity and Wages: Evidence from British Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(4), pages 397-421, August.
    4. Giuseppe Croce & Edoardo Di Porto & Emanuela Ghignoni & Andrea Ricci, 2013. "Employer education, agglomeration and workplace training: poaching vs knowledge spillovers," Working Papers in Public Economics 162, Department of Economics and Law, Sapienza University of Roma.
    5. Paul Vandenberg & Long Q. Trinh, 2016. "Small Firms, Human Capital, and Productivity in Asia," ADBI Working Papers 582, Asian Development Bank Institute.
    6. Andries De Grip & Jan Sauermann, 2012. "The Effects of Training on Own and Co‐worker Productivity: Evidence from a Field Experiment," Economic Journal, Royal Economic Society, vol. 122(560), pages 376-399, May.
    7. Sulieman Ibraheem Shelash Mohammad, 2011. "Human Resource Management Practices In Zain Cellular Communications Company Operating In Jordan," Perspectives of Innovation in Economics and Business (PIEB), Prague Development Center, vol. 8(2), pages 26-34, August.
    8. Maliranta, Mika & Asplund, Rita, 2007. "Training and Hiring Strategies to Improve Firm Performance," Discussion Papers 1105, The Research Institute of the Finnish Economy.
    9. Kevin J. Fox & Peter Goodridge & Jonathan Haskel & Gavin Wallis, 2017. "Spillovers from R&D and Other Intangible Investment: Evidence from UK Industries," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63, pages 22-48, February.
    10. Sousounis, Panos & Bladen-Hovell, Robin, 2010. "Persistence in the determination of work-related training participation: Evidence from the BHPS, 1991-1997," Economics of Education Review, Elsevier, vol. 29(6), pages 1005-1015, December.
    11. Picchio, Matteo & van Ours, Jan C., 2013. "Retaining through training even for older workers," Economics of Education Review, Elsevier, vol. 32(C), pages 29-48.
    12. Hector Sala & José Silva, 2013. "Labor productivity and vocational training: evidence from Europe," Journal of Productivity Analysis, Springer, vol. 40(1), pages 31-41, August.
    13. Benoit Mahy & Melanie Volral, 2008. "The effect of quantitative and qualitative training on labour demand in Belgium: a monopolistic competition approach," Economics of Education Working Paper Series 0021, University of Zurich, Department of Business Administration (IBW).
    14. Anna Vignoles & Augustin de Coulon, 2008. "An Analysis of the Benefit of NVQ2 Qualifications Acquired at Age 26-34," CEE Discussion Papers 0106, Centre for the Economics of Education, LSE.
    15. Gérard Ballot & Fathi Fakhfakh & Erol Taymaz, 2006. "Who Benefits from Training and R&D, the Firm or the Workers?," British Journal of Industrial Relations, London School of Economics, vol. 44(3), pages 473-495, September.
    16. Tan,Hong W. & Bashir,Sajitha & Tanaka,Nobuyuki, 2016. "Skill use, skill deficits, and firm performance in formal sector enterprises : evidence from the Tanzania enterprise skills survey, 2015," Policy Research Working Paper Series 7672, The World Bank.
    17. Mazzanti, Massimiliano & Mancinelli, Susanna, 2007. "SME Performance, Innovation and Networking Evidence on Complementarities for a Local Economic System," Knowledge, Technology, Human Capital Working Papers 9554, Fondazione Eni Enrico Mattei (FEEM).
    18. Harald U. Pfeifer, 2008. "Train to gain - The benefits of employee-financed training in Germany," Economics of Education Working Paper Series 0037, University of Zurich, Department of Business Administration (IBW).
    19. Giovannetti, Emanuele & Piga, Claudio A., 2017. "The contrasting effects of active and passive cooperation on innovation and productivity: Evidence from British local innovation networks," International Journal of Production Economics, Elsevier, vol. 187(C), pages 102-112.

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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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