Artikel
Equilibrium computation in discrete network games
Counterfactual policy evaluation often requires computation of game-theoretic equilibria. We provide new algorithms for computing pure-strategy Nash equilibria of games on networks with finite action spaces. The algorithms exploit the fact that many agents may be endowed with types such that a particular action is a dominant strategy. These agents can be used to partition the network into smaller subgames whose equilibrium sets may be more feasible to compute. We provide bounds on the complexity of our algorithms for models obeying certain restrictions on the strength of strategic interactions. These restrictions are analogous to the assumption in the widely used linear-in-means model of social interactions that the magnitude of the endogenous peer effect is bounded below one. For these models, our algorithms have complexity Op(nc), where the randomness is with respect to the data-generating process, n is the number of agents, and c depends on the strength of strategic interactions. We also provide algorithms for computing pairwise stable and directed Nash stable networks in network formation games.
- Sprache
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Englisch
- Erschienen in
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Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 11 ; Year: 2020 ; Issue: 4 ; Pages: 1325-1347 ; New Haven, CT: The Econometric Society
- Klassifikation
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Wirtschaft
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Econometrics of Games and Auctions
Computational Techniques; Simulation Modeling
Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
- Thema
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Multiple equilibria
graphical games
network formation
empiricalgames
- Ereignis
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Geistige Schöpfung
- (wer)
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Leung, Michael P.
- Ereignis
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Veröffentlichung
- (wer)
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The Econometric Society
- (wo)
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New Haven, CT
- (wann)
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2020
- DOI
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doi:10.3982/QE1386
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Leung, Michael P.
- The Econometric Society
Entstanden
- 2020