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New Evidence about Skill-Biased Technological Change and Gender Wage Inequality

Author

Listed:
  • Manuel Carlos Nogueira

    (GOVCOPP—Research Unit in Governance, Competitiveness and Public Policy, ISPGAYA—Higher Polytechnic Institute of Gaya, Avenida dos Descobrimentos, 303, Santa Marinha, 4400-103 Vila Nova de Gaia, Portugal)

  • Mara Madaleno

    (GOVCOPP—Research Unit in Governance, Competitiveness and Public Policy, Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal)

Abstract
In recent decades, the wage gap between higher- and lower-skilled workers has steadily widened around the world, and this gap is widening. There are several approaches in the literature to understand the causes of this steady increase, with Skill-Biased Technological Change (SBTC) being the most used and the results more consistent. This paper aims to deepen the understanding of this wage gap among workers in Organisation for Economic Cooperation and Development (OECD) countries, using cluster analysis and then modeling through simultaneous equations for the period between 2007 and 2020. Albeit with varying intensity, we conclude that in all clusters, there is a strong influence of the wage gap of the less skilled on the widening of the wage gap of the more skilled, with this influence being even more intense in the case of women. The SBTC approach can also be detected in all clusters but with greater intensity in the case of countries that invest more in research and development (R&D). Education spending and gross domestic product (GDP) per capita also play a role in widening the wage gap as well as in reducing gender inequalities. We also conclude that each cluster has its specificities that justify the choice made and that a slow reduction in gender wage inequality is observed in all clusters.

Suggested Citation

  • Manuel Carlos Nogueira & Mara Madaleno, 2023. "New Evidence about Skill-Biased Technological Change and Gender Wage Inequality," Economies, MDPI, vol. 11(7), pages 1-22, July.
    • Handle: RePEc:gam:jecomi:v:11:y:2023:i:7:p:193-:d:1196063
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    References listed on IDEAS

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