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New evidence about skill-biased technological change and gender wage inequality
by
Madaleno, Mara
, Nogueira, Manuel Carlos
in
Analysis
/ Cluster analysis
/ Education
/ Expenditures
/ Gender equality
/ gender wage inequality
/ Inequality
/ International trade
/ Labor market
/ Per capita
/ Qualifications
/ R&D
/ Research & development
/ Secondary schools
/ skill-biased technological change
/ Skilled labor
/ Skilled workers
/ Skills
/ Variables
/ Wage differential
/ Wage rates
/ Wages & salaries
2023
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New evidence about skill-biased technological change and gender wage inequality
by
Madaleno, Mara
, Nogueira, Manuel Carlos
in
Analysis
/ Cluster analysis
/ Education
/ Expenditures
/ Gender equality
/ gender wage inequality
/ Inequality
/ International trade
/ Labor market
/ Per capita
/ Qualifications
/ R&D
/ Research & development
/ Secondary schools
/ skill-biased technological change
/ Skilled labor
/ Skilled workers
/ Skills
/ Variables
/ Wage differential
/ Wage rates
/ Wages & salaries
2023
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New evidence about skill-biased technological change and gender wage inequality
by
Madaleno, Mara
, Nogueira, Manuel Carlos
in
Analysis
/ Cluster analysis
/ Education
/ Expenditures
/ Gender equality
/ gender wage inequality
/ Inequality
/ International trade
/ Labor market
/ Per capita
/ Qualifications
/ R&D
/ Research & development
/ Secondary schools
/ skill-biased technological change
/ Skilled labor
/ Skilled workers
/ Skills
/ Variables
/ Wage differential
/ Wage rates
/ Wages & salaries
2023
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New evidence about skill-biased technological change and gender wage inequality
Journal Article
New evidence about skill-biased technological change and gender wage inequality
2023
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Overview
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.
Publisher
MDPI,MDPI AG
Subject
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