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Stationary Mean-Field Games of Singular Control under Knightian Uncertainty

Author

Listed:
  • Ferrari, Giorgio

    (Center for Mathematical Economics, Bielefeld University)

  • Tzouanas, Ioannis

    (Center for Mathematical Economics, Bielefeld University)

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.

Suggested Citation

  • Ferrari, Giorgio & Tzouanas, Ioannis, 2025. "Stationary Mean-Field Games of Singular Control under Knightian Uncertainty," Center for Mathematical Economics Working Papers 706, Center for Mathematical Economics, Bielefeld University.
  • Handle: RePEc:bie:wpaper:706
    as

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    File URL: https://pub.uni-bielefeld.de/download/3003604/3003605
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    References listed on IDEAS

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    Keywords

    stationary mean-field games; singular control; model uncertainty; ergodic criterion; freeboundary problem; shooting method;
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