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

有一个不断增长的文献集中在识别和估计的静态，战略相互作用模型。该建议侧重于一个同时离散选择模型，其中的行动集合由期望效用最大化代理决定。 的信念是他人选择空间上的主观概率函数。 这个项目获得的有效代理的概率的界限：（i）是否有完全的信息，在代理之间的回报;（ii）无论潜在的均衡选择机制的具体特征;（iii）对于满足非参数限制的任何支付函数集合，以及（iv）信念是否正确（例如，在纳什均衡中）只要它们是弱一致的。这一建议产生的文件将是第一个在文献中的相互作用模型的计量经济学分析，明确针对这一范围的鲁棒性。除了概率的特征边界，该建议还描述了涉及纳什均衡配置文件的非参数边界。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，以及给定配置文件被代理选择的概率的界限，因为它是纳什均衡。 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该建议对文献的贡献。在给定的一组假设条件下，提案中的所有概率界限都满足锐度条件。从这个建议产生的论文也将是第一个在离散的相互作用模型（纳什和更一般的行为）的均衡选择概率的非参数界的特点。更广泛的影响：该建议将创建一个先进的主题课程在博士第二年的水平上的稳健推断的主题在结构相互作用为基础的微观计量经济模型。本课程的目标受众是对微观计量经济学模型、实证产业组织感兴趣的学生，以及更广泛地对结构模型的应用微观经济学研究感兴趣的学生。 本课程旨在围绕经济互动结构模型中的稳健推理（参数和/或行为意义上的）撰写论文。该项目组织讲习班和研讨会，相关领域的主要作者介绍和讨论他们最近的工作及其与本提案的目标和目的的联系。

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.