Gender wage gap in selected developing upper-middle income countries

The purpose of this paper is to examine the relationship between gender wage gap, productivity level of labor force and international trade for a sample of 13 developing upper-middle income countries over the period 2001 to 2015.

According to different statistical tests such as F-Limer test, the proper method for estimating this model is panel regression analysis. The Hausman test was handled to realize the fixed or random effect characteristics of this data. The final result of this test shows that the data follow some kind of random behavior which makes the panel regression model, random effect a suitable method for estimating this data.

The regression results showed that women’s (and men’s) employment in this sample has a positive relationship with their wages. Results showed that labor force’s productivity level affects their wage, and therefore, productivity difference between women and men is impressive on the gender wage gap. The significant finding is about international trade. While international trade has a positive effect on the wage rate of both genders, this effect is stronger for the female labor force. As a result of a stronger effect of international trade on the female labor force, a negative effect of international trade on the gender wage gap is observed.

Productivity variables are not available for this sample countries, so the author creates a new variable which is going to be used as a proxy for productivity. The author divides value added in each section (Agriculture, Manufacture, Industry, Service) by the total number of employees in that section; then for calculating the productivity rate of women, the author multiplies the result by the percentage of the employed women in that sector; for the productivity of men in that sector, the author multiplies the result by the percentage of men employed in that sector.

This paper contributes to the available studies by selecting a new sample of developing countries with upper-middle income level and also by introducing a new variable which is useful for measuring labor force productivity level.