Theoretical Studies in Unawareness and Discovery Process

中央大学博士(経済学)【学位授与の要件】中央大学学位規則第4条第1項 【論文審査委員主査】瀧澤　弘和(中央大学経済学部教授) 【論文審査委員副査】浅田　統一郎(中央大学経済学部教授),谷口　洋志(中央大学経済学部教授),石川　竜一郎(早稲田大学国際学術院教授)application/pdfdoctoral thesi

Learning to Play Bayesian Games

This paper discusses the implications of learning theory for the analysis of games with a move by Nature. One goal is to illuminate the issues that arise when modeling situations where players are learning about the distribution of Nature's move as well as learning about the opponents' strategies. A second goal is to argue that quite restrictive assumptions are necessary to justify the concept of Nash equilibrium without a common prior as a steady state of a learning process.Economic

The algebraic geometry of perfect and sequential equilibrium: an extension

We extend the generic equivalence result of Blume and Zame (Econometrica 62: 783-794, 1994) to a broader context of perfectly and sequentially rational strategic behavior (including equilibrium and nonequilibrium behavior) through a unifying solution concept of "mutually acceptable course of action" (MACA) proposed by Greenberg et al. (2009). As a by-product, we show, in the affirmative, Dekel et al.'s (1999) conjecture on the generic equivalence between the sequential and perfect versions of rationalizable self-confirming equilibrium. JEL Classification: C70, C7

Robust Model Misspecification and Paradigm Shifts

This paper studies the forms of model misspecification that are likely to persist when compared with competing models. I consider an agent using a subjective model to learn about an action-dependent outcome distribution. Aware of potential model misspecification, she uses a threshold rule to switch between models according to how well they fit the data. A model is globally robust if it can persist against every finite set of competing models and is locally robust if it can persist against every finite set of nearby competing models. The main result provides simple characterizations of globally robust and locally robust models based on the set of Berk-Nash equilibria they induce. I then apply the results to examples including risk underestimation, overconfidence, and incorrect beliefs about market demand