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Does Education Raise Productivity and Wages Equally ?The Moderating Roles of Age, Gender and Industry

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  • François Rycx
  • Yves Saks
  • Ilan Tojerow

Abstract

The labour market situation of low-educated people is particularly critical in most advanced economies, especially among youngsters and women. Policies aiming to increase their employability either try to foster their productivity and/or to decrease their wage cost. Yet, the evidence on the misalignment between education-induced productivity gains and corresponding wage cost differentials is surprisingly thin, inconclusive and subject to various econometric biases. We estimate the impact of education on productivity, wage costs and productivity-wage gaps (i.e. profits) using rich Belgian linked employer-employee panel data. Findings, based on the generalised method of moments (GMM) and Levinsohn and Petrin (2003) estimators, show a significant upward-sloping profile between education and wage costs, on the one hand, and education and productivity, on the other. They also systematically highlight that educational credentials have a stronger impact on productivity than on wage costs. This ‘wage compression effect’, robust across industries, is found to disappear among older cohorts of workers and to be more pronounced among women than men. Overall, findings suggest that particular attention should be devoted to the productivity to wage cost ratio of low-educated workers, especially when they are young and female, but also to policies favouring gender equality in terms of remuneration and career advancement.

Suggested Citation

  • François Rycx & Yves Saks & Ilan Tojerow, 2015. "Does Education Raise Productivity and Wages Equally ?The Moderating Roles of Age, Gender and Industry," DULBEA Working Papers 15-02, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:dul:wpaper:2013/199632
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    2. Anneleen Vandeplas & Anna Thum-Thysen, 2019. "Skills Mismatch and Productivity in the EU," European Economy - Discussion Papers 100, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    3. Abdul Azeez Oluwanisola Abdul Wahab, 2017. "Modeling the Effect of Healthcare Expenditure and Education Expenditure on Labour Productivity: A Study on OIC Countries," GATR Journals jber134, Global Academy of Training and Research (GATR) Enterprise.
    4. María Delgado Gómez-Flors & Maite Alguacil, 2018. "The Impact of Immigrant Diversity on Wages. The Spanish Experience," Sustainability, MDPI, vol. 10(9), pages 1-29, September.
    5. MORIKAWA Masayuki, 2017. "Are Part-time Employees Underpaid or Overpaid? Productivity–wage gaps in Japan," Discussion papers 17077, Research Institute of Economy, Trade and Industry (RIETI).

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    More about this item

    Keywords

    Education; labour costs; productivity; linked panel data;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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