Analysis of Gender Discrimination in Employee Salary Payments in Iranian Governmental Organizations Using Simultaneous Equations Modeling, Weighted Least Squares (WLS), and Stepwise Regression
Keywords:
Gender discrimination, wages and salaries, education, WLS model, stepwise regressionAbstract
Gender discrimination in wage and salary payments remains one of the persistent challenges of the Iranian labor market. Despite the expansion of higher education among women and their increasing participation in professional occupations, income disparities between men and women remain substantial. The present study was conducted with the aim of examining the relationship between educational attainment and gender-based discrimination in salary payments among employees of Iranian governmental organizations. This applied research adopted a descriptive–analytical approach and employed simultaneous equations modeling, Stepwise Regression, and the Weighted Least Squares (WLS) estimation method. Research data were collected from 420 employees working in executive governmental agencies during the year 2024. The principal variables included the logarithm of monthly salary, gender, level of education, marital status, job tenure, and age. Data analysis was performed using EViews 8 and Microsoft Excel software. The findings indicated that the average rate of vulnerable employment among women was higher than that of men, and according to reports by the International Labour Organization (ILO), women’s unemployment rates were significantly higher than those of men. Educational attainment demonstrated a positive and statistically significant effect on wage levels; however, the interaction effect between gender and education showed a negative relationship with salary levels. This result indicates that increases in educational attainment lead to greater income growth for men compared to women. Furthermore, gender as an independent variable exerted a positive effect on wages, reflecting the existence of a gender pay gap in favor of men. The findings suggest that although education plays a significant role in improving income levels, it is not sufficient on its own to eliminate gender inequalities in compensation. The model’s coefficient of determination (R² = 0.915) indicates a high explanatory power in accounting for variations in the dependent variable. Finally, the study recommends the implementation of transparent pay policies, gender-sensitivity retraining workshops, and strengthened employment support mechanisms—such as parental leave policies and remote working opportunities—as practical strategies for reducing the wage gap between men and women.
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Copyright (c) 2026 Shahryar Hemmati Farahani (Author); Farzaneh Hajihassani; Kambiz Peykarjou (Author)
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