This paper proposes a structural non-equilibrium model of initial responses to incomplete-information games based on "level-k" thinking, which describes behavior in many experiments with complete-information games. We derive the model's implications in first-and second-price auctions with general information structures, compare them to equilibrium and Eyster and Rabin's (2005) "cursed equilibrium," and evaluate the model's potential to explain behavior in auction experiments. The level-k model generalizes many insights from equilibrium auction theory. It also allows a unified explanation of the winner's curse in common-value auctions and overbidding in those independent-private-value auctions without the uniform value distributions used in most experiments.
Most applications of game theory assume equilibrium, justified by presuming either that learning will have converged to one, or that equilibrium approximates people's strategic thinking even when a learning justification is implausible. Yet several recent experimental and empirical studies suggest that people's initial responses to games often deviate systematically from equilibrium, and that structural nonequilibrium “level-k” or “cognitive hierarchy” models often out-predict equilibrium. Even when learning is possible and converges to equilibrium, such models allow better predictions of history-dependent limiting outcomes. This paper surveys recent theory and evidence on strategic thinking and illustrates the applications of level-k models in economics. (JEL C70, D03, D82, D83)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.