Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/318549 
Year of Publication: 
2025
Series/Report no.: 
Center for Mathematical Economics Working Papers No. 706
Publisher: 
Bielefeld University, Center for Mathematical Economics (IMW), Bielefeld
Abstract: 
In this work, we study a class of stationary mean-field games of singular stochastic control under model uncertainty. The representative agent adjusts the dynamics of an Itô-diffusion via onesided singular stochastic control, aiming to maximize a long-term average expected profit criterion. The mean-field interaction is of scalar type through the stationary distribution of the population. Due to the presence of uncertainty, the problem involves the study of a stochastic (zero-sum) game, where the decision maker chooses the 'best' singular control policy, while the adversarial player selects the 'worst' probability measure. Using a constructive approach, we prove existence and uniqueness of a stationary mean-field equilibrium. Finally, we present an example of mean-field optimal extraction of natural resources under uncertainty and we analyze the impact of uncertainty on the mean-field equilibrium.
Subjects: 
stationary mean-field games
singular control
model uncertainty
ergodic criterion
free-boundary problem
shooting method
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

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