Stochastic Dynamics and Equilibrium Selection in Core-Periphery Model

In this paper, we study a perfect foresight dynamics in the Core-Periphery(CP) model with taste heterogeneity of agents, that has multiple equilibria. We introduce stochastic fluctuations into the model and describe the state of the model by a Markov process. By solving the master equation and the value function, we show that equilibrium agglomeration patterns can be obtained as probability distributions around the stationary states of the mean dynamics and that this provides a basis for equilibrium selection in CP models.