Addressing the gender pay gap: an application based on Object-Oriented Bayesian Networks to rethink gender composite indicators

A widely advocated approach for managing inequalities involves utilizing composite indexes, combining several indicators into a single numerical value such as the European Institute for Gender Equality (EIGE) index that permits European Countries ranking. Our proposal promotes a holistic approach using Object-Oriented Bayesian networks to capture the complexity of such a phenomenon. The paper delves into several discussion points, comparing the effectiveness of composite indicators with a hierarchical model, and explores the chance of integrating an interactive weighting system that applies to different decision contexts. Simulations are developed with the aim of tackling the gender pay gap. Preliminary results reveal interesting insights.