  We consider a model of urban spatial structure proposed by Harris and Wilson
(Environment and Planning A, 1978). The model consists of fast dynamics, which
represent spatial interactions between locations by the entropy-maximizing
principle, and slow dynamics, which represent the evolution of the spatial
distribution of local factors that facilitate such spatial interactions. One
known limitation of the Harris and Wilson model is that it can have multiple
locally stable equilibria, leading to a dependence of predictions on the
initial state. To overcome this, we employ equilibrium refinement by stochastic
stability. We build on the fact that the model is a large-population potential
game and that stochastically stable states in a potential game correspond to
global potential maximizers. Unlike local stability under deterministic
dynamics, the stochastic stability approach allows a unique and unambiguous
prediction for urban spatial configurations. We show that, in the most likely
spatial configuration, the number of retail agglomerations decreases either
when shopping costs for consumers decrease or when the strength of
agglomerative effects increases.
