2018年-世界发展银行全球_The_Economics_of_the_Gender_Wage_Gap_in_Armenia_23页_1014kb

Summary of "The Economics of the Gender Wage Gap in Armenia"

Core Content

This paper examines the gender wage gap in Armenia using data from the 2015 Armenian Labor Force Survey (LFS). It analyzes how the wage gap varies across the distribution of earnings and identifies the main factors contributing to this gap.

Main Findings

• Gender Wage Gap: The average gender wage gap in Armenia is 20 percent, with women earning less than men at all percentiles.
• Inverted-U Shape: The wage gap is larger in the middle of the distribution (30th to 55th percentiles), while it is smaller at the top and bottom.
• Women's Earnings: Women earn 33 to 20 percent less than men on average, with the largest gap observed among young workers (15–30 years old).
• Education Level: The gender wage gap is around 28 percent for all education levels, but it decreases for those with tertiary or post-graduate education (18 percent).
• Occupational Segregation: Women are underrepresented in managerial and higher-paying occupations, such as finance and information and communication, where they face significant wage gaps.
• Sector Differences: Working in the public sector has a negative impact on earnings for women in the lower percentiles, but a positive effect for women in the 20th to 40th percentiles. The informal sector negatively affects earnings for both genders, especially at the lower end of the distribution.
• Marital Status: Being married reduces earnings for women at the top of the distribution but increases earnings for men at the bottom.
• Experience: The impact of experience is positive and more pronounced for women, especially at the lower percentiles.
• Demographic Trends: Despite progress in closing the gender wage gap, it remains one of the largest in the Europe and Central Asia region. Women's participation in the labor force is relatively high, but they still face significant wage disparities.

Key Factors Driving the Gap

• Wage Structure Effect: The wage gap is primarily driven by the wage structure effect, which accounts for most of the gap in the middle and upper parts of the distribution. This may be attributed to discrimination, occupational segregation, and differences in returns to characteristics.
• Composition Effect: At the lower end of the distribution, the composition effect is more significant, linked to lower human capital and skills among women.
• Human Capital: Women have lower educational attainment and fewer skills compared to men, contributing to the wage gap.
• Unpaid Work: Women are more likely to be involved in unpaid family work, which may affect their participation and earnings in the formal labor market.
• Labor Market Participation: Women are overrepresented in low-paying sectors and occupations, such as skilled agricultural and service roles, which contribute to the wage gap.

Methodology

• RIF Decomposition: The paper uses the reweighted, re-centered influence function (RIF) decomposition method, developed by Firpo, Fortin, and Lemieux (FFL), to analyze the wage gap across different percentiles.
• Quantile Treatment Effects: The methodology allows for the estimation of unconditional quantile treatment effects, providing a detailed understanding of how characteristics such as education, experience, and occupation affect wages differently for men and women at various points in the distribution.
• Empirical Analysis: The analysis is based on the most recent data from the Armenian LFS, covering a range of demographic and economic characteristics.

Policy Implications

• Gender Equality as Good Economics: The paper emphasizes that addressing gender gaps is not only a social issue but also a matter of economic efficiency and growth.
• Need for Intervention: Despite progress in education and labor force participation, the gender wage gap remains a challenge, indicating the need for targeted policies to address discrimination, occupational segregation, and unequal access to economic opportunities.
• Focus on Lower and Middle Earnings: Policies should focus on improving the returns to human capital for women, encouraging their participation in higher-paying sectors, and addressing the composition and structure effects that contribute to the wage gap.

Conclusion

• The paper provides a comprehensive analysis of the gender wage gap in Armenia, highlighting the importance of addressing both structural and compositional factors.
• It underscores the need for policies that ensure equal pay for equal work and promote women's access to better-paying jobs and sectors.
• The study contributes to the broader understanding of gender inequality in labor markets and highlights the economic benefits of closing these gaps.