This research focuses on developing innovative statistical methods to better analyze the gender pay gap, in line with the EU Pay Transparency Directive. Starting in 2027, employers with more than 150 employees will be required to report on their gender pay gap. If the adjusted pay gap exceeds 5%, employers must investigate the issue and, if necessary, take corrective actions. The gender pay gap will be studied not only at the company level but also at the individual level.

Current methods primarily use simple linear regression models to analyze the pay gap within companies. In collaboration with private partners providing wage data, this project explores new approaches. The main objectives include:

• Applying causal techniques and machine learning to gain deeper insights into the gender pay gap.
• Investigating the feasibility of predicting the pay gap at the individual level.
• Developing alternative rank-based methods to quantify the pay gap, which are less sensitive to outliers.

This project contributes to improving statistical tools for more accurate and fair analysis of wage discrimination.