We analyse differences between the wage distributions in the USA and Germany in 2001 both for women and men. The empirical analysis is based on the decomposition of differences using Cox's marginal (partial) likelihood. The approach based on rank invariant estimators such as Cox's is borrowed from the literature on failure time data. Donald et al. (2000) pioneered this approach. However, they did not use the full power of the semi-parametric approach. Instead, they argued for using a piecewise constant hazard rate model. We improve on their work by showing that the semi-parametric features of Cox's marginal likelihood are as appropriate for the analysis of wage decompositions and as easy to interpret. Moreover, we extend their approach by allowing for nonlinear regression effects. We will show empirically that this formulation will both increase the flexibility of their approach and improve the discriminatory power between wage regimes.