The Oaxaca-Blinder decomposition is a widely used method to explain social disparities. However, assigning causal meaning to its estimated components requires strong assumptions that often lack explicit justification. This paper emphasizes the importance of clearly defined estimands and their identification when targeting mediating mechanisms of social disparities. Three approaches are distinguished based on their scientific questions and assumptions: a mediation approach and two interventional approaches. The Oaxaca-Blinder decomposition and Monte Carlo simulation-based g-computation are discussed for estimation in relation to these approaches. The latter method is used in an interventional effects analysis of the observed gender pay gap in West Germany, using data from the 2017 German Socio-Economic Panel. Ten mediators, including indicators of human capital and job characteristics, are considered. Key findings indicate that the gender pay gap in log hourly wages could be reduced by up to 86% if these mediators were evenly distributed between women and men. Substantial reductions could be achieved by aligning full-time employment and work experience.
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