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Essays on Bounded Rationality in Games and Markets

Abstract

In economics, players are assumed to be rational: they exhibit self interested behavior and play equilibrium strategies. However, in laboratory games or actual markets, players often manifest behavior that is rather consistent with bounded rationality. This thesis consists of two chapters, which relax the standard assumptions on rationality and allow for bounded rationality of players.

The first essay weakens the assumption that players are self interested. In this essay, a retail market is empirically investigated under the relaxed assumption that firms may not be purely self interested or profit maximizing. Standard models of price competition stipulate that firms are pure profit maximizers; this assumption can be sensible and empirically useful in inferring product markups in a market with no direct government intervention. However, in markets for essential goods such as food and healthcare, a government may wish to address its consumer surplus concerns by imposing regulatory constraints or actively participating as a player in the market. As a consequence, some firms may have objectives beyond profit maximization and standard models may induce systematic biases in empirical estimation. This essay develops the structural model of price competition where some firms have consumer surplus concerns. Our model is applied in order to understand demand and supply behaviors in a retail grocery market where the dominant retailer publicly declares its consumer surplus objective. Our estimation results show that the observed low prices of this retailer arise indeed as a consequence of its consumer surplus concerns instead of its low marginal costs. The estimated degree of consumer surplus concerns suggests that the dominant retailer weighs consumer surplus to profit in a 1 to 7 ratio. The counterfactual analysis reveals that if the dominant retailer were to be profit maximizing as in the standard model, its prices would increase by 6.09% on average. As a consequence, its profit would increase by 1.16% and total consumer surplus would decrease by 7.18%. To the contrary, competitors lower their prices in response to the dominant retailer's increased prices, i.e., become less aggressive as if they are strategic substitutes. Interestingly, even though profit of all firms increases, total social surplus would decrease by 3.21% suggesting that profit maximization by all firms induces an inefficient outcome for the market.

The second essay relaxes the rationality assumption that players exhibit equilibrium behavior, and develops a model that explains nonequilibrium behavior of players in laboratory games. In standard nonequilibrium models of iterative thinking, there is a fixed rule hierarchy and every player chooses a fixed rule level; nonequilibrium behavior emerges when some players do not perform enough thinking steps. Existing approaches however are inherently static. In this essay, we generalize models of iterative thinking to incorporate adaptive and sophisticated learning. Our model has three key features. First, the rule hierarchy is dynamic, i.e., the action that corresponds to each rule level can evolve over time depending on historical game plays. Second, players' rule levels are dynamic. Specifically, players update beliefs about opponents' rule levels in each round and change their rule level in order to maximize payoff. Third, our model accommodates a continuous rule hierarchy, so that every possible observed action can be directly interpreted as a real-numbered rule level r. The proposed model unifies and generalizes two seemingly distinct streams of nonequilibrium models (level-k and belief learning models) and as a consequence nests several well-known nonequilibrium models as special cases. When both the rule hierarchy and players' rule levels are fixed, we have a static level-r model (which generalizes the standard level-k model). When only players' rule levels are fixed, our model reduces to a static level-r model with dynamic rule hierarchy and captures adaptive learning. When only the rule hierarchy is fixed, our model reduces to a dynamic level-r model and captures sophisticated learning. Since our model always converges to the iterative dominance solution, it can serve as a model of the equilibration process. Using experimental data on p-beauty contests, we show that our model describes subjects' dynamic behavior better than all its special cases. In addition, we collect new experimental data on a generalized price matching game. The estimation results show that it is crucial to allow for both adaptive and sophisticated learning in predicting dynamic choice behaviors across games.

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