Identification Results in Interaction Models with Nonparametric Payoffs and Weakly Consistent Beliefs

有一种持续增长的文献专注于识别和估计静态的战略互动模型。这一建议集中在一个同时离散选择模型，其中一组行动由期望效用最大化的主体决定。的信念是关于他人选择空间的主观概率函数。这个项目得到了有效代理概率的界：(I)代理之间是否存在完全信息；(Ii)无论潜在均衡选择机制的特定特征；(Iii)满足非参数限制的任何支付函数集合；(Iv)只要弱一致，信念是否正确(例如，在纳什均衡中)。这一提议产生的论文将是关于相互作用模型的计量经济学分析的文献中第一批明确瞄准这一稳健性范围的论文。除了刻画概率的界外，该建议还描述了涉及纳什均衡分布的非参数界。这些包括任意选择配置文件是纳什均衡(混合或纯)的概率的界限，以及给定的配置文件被代理选择的概率的界限，假设它是纳什均衡。这些界限对于满足非参数假设的任何支付函数集合都是有效的。纳什均衡选择的非参数界也是对文献的一个贡献。在给定一组假设的情况下，建议中的所有概率界都满足锐度条件。这一提议产生的论文也将是第一批描述离散相互作用模型(包括NASH和更一般的行为)中均衡选择概率的非参数界限的论文。广泛影响：该提议将在博士二年级创建一门高级主题课程，主题是基于结构相互作用的微观计量经济学模型中的稳健推理主题。本课程的目标受众将是对微观计量经济学模型、经验产业组织感兴趣的学生，以及更广泛地说，所有对结构模型的应用微观经济学研究感兴趣的学生。本课程的目的是围绕经济相互作用的结构模型中的稳健推理(在参数和/或行为意义上)来撰写论文。该项目组织了讲习班和研讨会，相关领域的主要作者介绍并讨论了他们的最新工作及其与本提案的目的和目的的联系。

There exists a continuously growing literature focused on identification and estimation of static, strategic-interaction models. This proposal focuses on a simultaneous discrete choice model where a collection of actions are decided by expected-utility maximizing agents. The beliefs of are subjective probability functions over the space of others' choices. This project obtains bounds on the probabilities of agents that are valid: (i) Whether or not there is complete information in payoffs among agents; (ii) regardless of the specific features of the underlying equilibrium selection mechanism; (iii) for any collection of payoffs functions that satisfy the nonparametric restricts and (iv) whether or not beliefs are correct (e.g, as in Nash equilibrium) as long as they are weakly consistent. The papers produced by this proposal would be the first ones in the literature on econometric analysis of interaction models to explicitly aim for this range of robustness. Besides characterizing bounds for probabilities, this proposal also describes nonparametric bounds involving Nash equilibrium profiles. These include bounds for the probability that an arbitrary choice profile is a Nash equilibrium (either mixed or pure), as well as bounds for the probability that a given profile is selected by the agents given that it is a Nash equilibrium. These bounds are valid for any collection of payoff functions that satisfy the nonparametric assumptions. The nonparametric bounds for Nash equilibrium selection are also a contribution of this proposal to the literature. All probability bounds in the proposal satisfy sharpness conditions given the set of assumptions made. The papers resulting from this proposal would also be th first ones to characterize nonparametric bounds for equilibrium selection probabilities in discrete interaction models (both for Nash and the more general behavior).Broader Impact: The proposal would create an advanced topics course at the Ph.D second-year level on the subject of Robust Inference in Structural Interactions-Based Microeconometric Models. The target audience for this course would be students interested in microeconometric models, empirical industrial organization, and more generally all those interested in applied microeconomics research with structural models in general. This course is intended to produce dissertations centered around robust inference (both in the parametric and/or behavioral sense) in structural models of economic interaction. The project organizes workshops and seminars, where leading authors in related fields present and discuss their most recent work and their connection to the goals and objectives of this proposal.