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Ergodic Mean-Field Games of Singular Control with Regime-Switching (Extended Version)
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abstract
This paper studies a class of stationary mean-field games of singular stochastic control with regime-switching. The representative agent adjusts the dynamics of a Markov-modulated It\^o-diffusion via a two-sided singular stochastic control and faces a long-time-average expected profit criterion. The mean-field interaction is of scalar type and it is given through the stationary distribution of the population. Via a constructive approach, we prove the existence and uniqueness of the stationary mean-field equilibrium. Furthermore, we show that this realizes a symmetric $\varepsilon_N$-Nash equilibrium for a suitable ergodic $N$-player game with singular controls. The proof hinges on the characterization of the optimal solution to the representative player's ergodic singular stochastic control problem with regime switching in terms of an auxiliary Dynkin game, which is of independent interest and appears here for the first time.
Forward citations
Cited by 2 Pith papers
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On Mean-field Singular Stochastic Control Problems
Under convexity, potential MFG equilibria solve mean-field singular control; for the mean-field monotone follower with strategic complementarities the optimum is a free boundary uniquely solving a nonlinear integral equation.
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Optimal Policy Characterization for a Class of Multi-Dimensional Ergodic Singular Stochastic Control Problems
Optimal policy in multi-dimensional ergodic singular control is characterized via Skorokhod reflection at free boundaries of an auxiliary Dynkin game, with two fully solved 2D inventory models.
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