Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/22094
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dc.contributor.authorBandhu, Sarvesh
dc.contributor.authorLahkar, Ratul
dc.date.accessioned2024-02-20T05:54:33Z-
dc.date.available2024-02-20T05:54:33Z-
dc.date.issued2023
dc.identifier.issn0938-2259
dc.identifier.issn1432-0479
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/22094-
dc.description.abstractWe consider dominant strategy implementation in a large population aggregative game. The model has strategic complementarities which generates multiple Nash equilibria. Moreover, externalities are positive due to which, all equilibria are socially inefficient. The planner, therefore, constructs a direct mechanism and assigns efficient strategies and transfer levels to agents. Truthful revelation then becomes strictly dominant, which implements efficiency. In our new evolutionary approach to this mechanism, the reported type distribution evolves under dynamics satisfying monotone percentage growth. Such dynamics eliminate dominated strategies thereby ensuring convergence to truthful revelation by all agents. Dominant strategy implementation is, therefore, robust under such evolutionary dynamics. Our evolutionary approach differs from existing models of evolutionary implementation based on potential games. That approach may fail to implement efficiency under strategic complementarities as a Pareto inferior Nash equilibrium can remain asymptotically stable under evolutionary dynamics. Our evolutionary approach is effective even under such strategic complementarities. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
dc.publisherSpringer
dc.subjectAggregative games
dc.subjectEvolutionary game theory
dc.subjectImplementation
dc.subjectPotential games
dc.titleEvolutionary robustness of dominant strategy implementation
dc.typeJournal Article
dc.identifier.doi10.1007/s00199-022-01474-w
dc.pages685-721p.
dc.vol.noVol.76
dc.issue.noIss.2
dc.journal.nameEconomic Theory
Appears in Collections:2020-2029 C
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