Collaborative Research: Empirical Analysis of Static and Dynamic Strategic Interactions

战略互动模式对产业组织经济学有着深远的影响。 一个企业进入寡头垄断市场的行为通常取决于其他竞争企业的进入行为。 许多企业进入模式都有博弈论的基础。 理解博弈论模型的经验内容，其中竞争企业的战略选择是相互依赖的，对反垄断和监管的经济政策具有重要意义。 战略竞争模型的信息结构可以根据企业是否最大化静态或动态预期利润，以及每个竞争企业是否拥有其他市场参与者无法观察到的私人信息来区分。 由美国国家科学基金会资助的几个研究项目旨在研究战略互动的计量经济学模型，其中竞争企业在有限数量的互斥行为之间进行选择。第一个项目研究在私人信息假设下的静态版本的博弈论战略竞争模型的识别和估计。 一个算法来计算在这些模型中的整个平衡集。 应用这些估计和计算方法的股票分析师的建议市场发现同行的影响和多重均衡的重大影响的有力证据。 第二个项目将静态模型扩展到动态环境中，竞争企业在马尔可夫完美均衡中反复相互作用。 分析结果表明，这些模型的结构参数，可以确定从数据的进入行为的企业。 识别分析自然会导致一个灵活的非参数估计和一个实用的半参数估计的动态寡头模型的连续和离散的状态变量。 正在收集一套独特的石油勘探数据，以证明这些模型的经验预测。 第三个项目允许一个完整的信息设置，潜在的冲击，公司利润是共同观察到的所有公司和代理人。 一个可行的计算算法的开发，以方便估计这些模型与多个和混合策略的均衡。 应用该算法进入行为在加州公路采购拍卖恢复显着的进入成本投标公司和显着的多重均衡的进入行为的决定因素。这项研究的结果有潜在的重要经济应用超出了那些在产业组织领域。 在这些研究项目中开发的计量经济学方法将有助于解决应用微观经济学中的问题，其中代理商的效用是相互依赖的，代理商在战略上相互作用。 这方面的例子包括公共财政中的同行效应和城市经济学中的集聚效应。

Models of strategic interactions have a profound effect on the economics of industrial organization. The entry behavior of a firm into an oligopoly market typical depends on the entry behavior of other competing firms. Many firm entry models have a game theoretic foundation. Understanding the empirical contents of game theoretic models, in which the strategic choices of competing firms are mutually interdependent, has important implication on the economic policies of antitrust and regulation. The information structure of strategic competition models can be differentiated based whether firms maximize static or dynamic expected profits, and whether each competing firm possesses private information that can not be observed by other market participants. Several research projects supported by this NSF grant aim to study econometric models of strategic interactions where competing firms choose between a finite number of mutually exclusive actions. The first project studies identification and estimation of static versions of game theoretic strategic competition models under the private information assumption. An algorithm is developed to compute the entire set of equilibria in these models. Application of these estimation and computation methods to the market of stock analyst recommendations discovers strong evidence of peer influence and substantial impact of multiple equilibria. The second project extends the static models to a dynamic setting where competing firms interact repeatedly in a Markov perfect equilibrium. The results of the analysis show that the structural parameters of these models can be identified from data on the entry behavior of firms. The identification analysis naturally leads to a flexible nonparametric estimator and a practical semi-parametric estimator for dynamic oligopolistic models with both continuous and discrete state variables. A unique data set on oil exploration is being collected to demonstrate the empirical predictions of these models. The third project allows for a complete information setting where latent shocks to firm profits are commonly observable to all the firms and agents. A feasible computation algorithm is developed to facilitate estimating these models with multiple and mixed strategy equilibria. Application of this algorithm to entry behavior in California highway procurement auctions recovers significant entry costs by bidding firms and significant multiple equilibria determinants of entry behavior.Broader impacts. The results of this research have potentially important economic applications beyond those in the field of industrial organization. The econometric methods developed in these research projects will be useful for problems in applied microeconomics where the utilities of agents are interdependent and agents interact strategically. Examples include peer effects in public finance and agglomeration in urban economics.