Economic and social mobilities are cornerstones of modern democratic societies and known to be linked to prosperity and welfare. Cross-country empirical findings from the past several decades indicate that high levels of mobility are associated with low levels of income inequality. While deep understanding of these findings may lead to important policies for the benefit of the economy and society, standard neoclassical economic models offer them contradicting theoretical explanations without a clear consensus. In this talk we show how stochastic and network-based approaches can provide an original explanation to the empirical findings. We describe a mechanism for the effect the network structure – and in particular clustering – has on mobility and inequality. We find that increasing mobility can be achieved without reducing inequality, by declustering of the social structure and support our findings with additional empirical evidence. We also provide an explanation for the statistical association between inequality and immobility and show it is mechanically driven by the definition of mobility. This may hint that reducing income inequality will lead to higher mobility and vice versa. However, it questions the underlying economic significance of the empirical findings depicted in the Great Gatsby curve.