Trend AnalysisOther Social Sciences
Gender Wage Gap Analysis and Policy Interventions: Decomposition Evidence from Global South
The gender wage gap persists globally, but its drivers vary dramatically across contexts. Oaxaca-Blinder decomposition studies from Morocco, Senegal, and Indonesia reveal that 'unexplained' discrimination accounts for the majority of wage gaps, even where women are better educated.
By Sean K.S. Shin
This blog summarizes research trends based on published paper abstracts. Specific numbers or findings may contain inaccuracies. For scholarly rigor, always consult the original papers cited in each post.
Women earn less than men in virtually every country on Earth. The global gender pay gap stands at approximately 20%---women earn 80 cents for every dollar earned by men. But this aggregate figure masks enormous variation by country, sector, education level, and age group. Understanding what drives the gap---human capital differences, occupational segregation, discrimination, or labor market structure---is essential for designing effective policy interventions.
The Oaxaca-Blinder decomposition is the workhorse econometric technique: it separates the wage gap into an "explained" component (differences in education, experience, occupation) and an "unexplained" component (often interpreted as discrimination, though it captures all unobserved factors). Recent studies from the Global South provide fresh evidence on these dynamics in developing economies.
Why It Matters
Gender pay equity is not only a matter of justice but of economic efficiency. The IMF estimates that closing gender gaps in employment could increase GDP by 35% in some countries. Understanding the specific drivers of wage gaps in different contexts is essential for targeting interventions---equal pay legislation, parental leave policies, anti-discrimination enforcement, or educational access programs.
The Research Landscape
Morocco: Urban-Rural Disparities
Mounir and Soudi (2025) analyze gender pay gaps across Morocco's wage distribution, comparing urban and rural areas. Their quantile decomposition reveals that the gap is largest at the bottom of the distribution (low-wage workers) and narrower at the top---the opposite of the "glass ceiling" pattern observed in developed countries. In rural Morocco, the unexplained component dominates, suggesting pervasive discrimination in agricultural labor markets.
Senegal: Young Workers
Diallo (2025) studies labor market participation and the gender wage gap among young workers (18-35) in Senegal. The findings are striking: despite women's growing educational attainment, they face a 29% wage penalty. The Heckman selection model reveals significant selection bias---women who enter the labor market are not representative of all women, complicating simple gap estimates.
Indonesia: Java Island
Putri and Shidiq (2025) analyze the gender wage gap on Java Island using Oaxaca-Blinder decomposition within the Mincer human capital framework. Their results show that educational differences actually favor women (women are better educated on average), yet the wage gap persists---driven entirely by the unexplained component.
Indonesia: Riau Province
Maulida and Indrawati (2024) find a 29.56% gender wage gap in Riau Province, with women earning significantly less despite higher educational attainment. Their decomposition confirms the Java findings: the gap is not driven by human capital deficits but by labor market discrimination and occupational segregation.
Gender Wage Gap Components
<
| Country | Raw Gap | Explained (human capital) | Unexplained (discrimination+) |
|---|
| Morocco (urban) | ~25% | ~8% | ~17% |
| Senegal (youth) | ~29% | ~5% | ~24% |
| Indonesia (Java) | ~22% | Negative (women better educated) | >22% |
| Indonesia (Riau) | ~30% | ~4% | ~26% |
What To Watch
The interaction of gender wage gaps with the gig economy and remote work is reshaping the landscape. Platform-based work could reduce discrimination (algorithmic matching based on skills rather than gender) or amplify it (lower bargaining power, no labor protections). Research on how digital labor platforms affect gender pay equity is urgently needed, particularly in developing economies where platform work is growing fastest.
Women earn less than men in virtually every country on Earth. The global gender pay gap stands at approximately 20%---women earn 80 cents for every dollar earned by men. But this aggregate figure masks enormous variation by country, sector, education level, and age group. Understanding what drives the gap---human capital differences, occupational segregation, discrimination, or labor market structure---is essential for designing effective policy interventions.
The Oaxaca-Blinder decomposition is the workhorse econometric technique: it separates the wage gap into an "explained" component (differences in education, experience, occupation) and an "unexplained" component (often interpreted as discrimination, though it captures all unobserved factors). Recent studies from the Global South provide fresh evidence on these dynamics in developing economies.
Why It Matters
Gender pay equity is not only a matter of justice but of economic efficiency. The IMF estimates that closing gender gaps in employment could increase GDP by 35% in some countries. Understanding the specific drivers of wage gaps in different contexts is essential for targeting interventions---equal pay legislation, parental leave policies, anti-discrimination enforcement, or educational access programs.
The Research Landscape
Morocco: Urban-Rural Disparities
Mounir and Soudi (2025) analyze gender pay gaps across Morocco's wage distribution, comparing urban and rural areas. Their quantile decomposition reveals that the gap is largest at the bottom of the distribution (low-wage workers) and narrower at the top---the opposite of the "glass ceiling" pattern observed in developed countries. In rural Morocco, the unexplained component dominates, suggesting pervasive discrimination in agricultural labor markets.
Senegal: Young Workers
Diallo (2025) studies labor market participation and the gender wage gap among young workers (18-35) in Senegal. The findings are striking: despite women's growing educational attainment, they face a 29% wage penalty. The Heckman selection model reveals significant selection bias---women who enter the labor market are not representative of all women, complicating simple gap estimates.
Indonesia: Java Island
Putri and Shidiq (2025) analyze the gender wage gap on Java Island using Oaxaca-Blinder decomposition within the Mincer human capital framework. Their results show that educational differences actually favor women (women are better educated on average), yet the wage gap persists---driven entirely by the unexplained component.
Indonesia: Riau Province
Maulida and Indrawati (2024) find a 29.56% gender wage gap in Riau Province, with women earning significantly less despite higher educational attainment. Their decomposition confirms the Java findings: the gap is not driven by human capital deficits but by labor market discrimination and occupational segregation.
Gender Wage Gap Components
<
| Country | Raw Gap | Explained (human capital) | Unexplained (discrimination+) |
|---|
| Morocco (urban) | ~25% | ~8% | ~17% |
| Senegal (youth) | ~29% | ~5% | ~24% |
| Indonesia (Java) | ~22% | Negative (women better educated) | >22% |
| Indonesia (Riau) | ~30% | ~4% | ~26% |
What To Watch
The interaction of gender wage gaps with the gig economy and remote work is reshaping the landscape. Platform-based work could reduce discrimination (algorithmic matching based on skills rather than gender) or amplify it (lower bargaining power, no labor protections). Research on how digital labor platforms affect gender pay equity is urgently needed, particularly in developing economies where platform work is growing fastest.
References (7)
[1] Mounir, F., Hanchane, S., & Soudi, K. (2025). Gender pay gaps in Morocco. Middle East Development Journal.
[2] Diallo, M. A. (2025). Labor Market Participation and Gender Wage Gap in Senegal. Review of Development Economics.
[3] Putri, Q. N., Firmadhani, N. A., & Shidiq, F. A. (2025). Gender Wage Gap in Java. ICSEMA.
[4] Maulida, Y., Ningsih, R. B., & Indrawati, T. (2024). Gender Wage Gap in Riau Province. Journal of Economics.
Mounir, F., Hanchane, S., & Soudi, K. (2025). Gender pay gaps in Morocco: urban-rural disparities across the wage distribution. Development Studies Research, 12(1).
Putri, Q. N., Firmadhani, N. A., Shidiq, F. A., Islami, F. S., & Panjawa, J. L. (2025). DYNAMICS OF THE GENDER WAGE GAP IN JAVA ISLAND, 2024: AN OAXACAโBLINDER ANALYSIS WITHIN THE MINCER HUMANโCAPITAL FRAMEWORK. The International Conference on Sustainable Economics Management and Accounting Proceeding, 1, 2844-2852.
Maulida, Y., Ningsih, R. B., & Indrawati, T. (2024). Gender Wage Gap Analysis in Riau Province Using the Blinder-Oaxaca Decomposition Method. Journal of Ecohumanism, 3(8).