I analyze a simple evolutionary model of residential segregation based on decentralized racism which extends Schelling's (1972) well-known tipping model by allowing for local interaction between residents. The richer set-up explains not only the persistence of ghettos, but also provides a mechanism for the rapid transition from an all-white to an all-black equilibrium. On one-dimensional streets segregation arises once a group becomes sufficiently dominant in the housing market. However, the resulting ghettos are not persistent, and periodic shifts in the market can give rise to "avenue waves". On two-dimensional inner-cities, on the other hand, ghettos can be persistent due to the \encircling phenomenon" if the majority ethnic group is sufficiently less tolerant than the minority. I review the history of residential segregation in the US and argue that my model can explain the rapid rise of almost exclusively black ghettos at the beginning of the 20th century. For the analysis of my model I introduce a new technique to characterize the medium and long-run stochastic dynamics. I show that clustering predicts the behavior of large-scale processes with many agents more accurately than standard stochastic stability analysis, because the latter concept overemphasizes the 'noisy' part of the stochastic dynamics.