Forecasting the Gender Wage Gap in Argentina from a Productivity-Based Approach

Abstract

This paper analyzes the association between the gender wage gap (GWG) and productivity at the industry level in Argentina from 2002 to 2022, drawing on gender studies and literature on structural change. Using dynamic OLS regression with random effects across the 1st to 4th quantiles, we examine the relationship between the GWG, female labor participation, and industry productivity. Results indicate that increased female participation is positively associated with reductions in the wage gap in the least productive industries. Additionally, female education rates contribute positively to reducing the GWG. The findings also reveal that productivity gains in the most productive sectors help narrow the gender wage gap, suggesting that structural shifts toward higher productivity levels may play a role in closing this gap.

Keywords

• gender wage gap
• productivity
• structural change