Semiparametric Estimation of a Dynamic Game of Incomplete Information
Semiparametric Estimation of a Dynamic Game of Incomplete Information
复制标题
不完全信息动态博弈的半参数估计
DOI：
10.3386/t0320
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
H. Hong
中科院分区：
文献类型：
--
作者：
Patrick Bajari;H. Hong
近年来，实证产业组织经济学家提出了不完全信息动态博弈的估计方法。在这些模型中，代理人从有限数量的行动中进行选择，并在马尔可夫完美均衡中最大化期望的折扣效用。先前的计量经济学方法估计第一阶段中代理人动作的概率分布。在第二步骤中，估计周期返回函数的参数的有限向量。在本文中，我们开发了半参数估计的动态游戏允许连续的状态变量和非参数的第一阶段。尽管第一阶段是非参数估计的，但结构参数的估计值是T1/2一致的（其中T是样本量）并且渐进正态。我们还提出了充分条件的模型识别。
Recently, empirical industrial organization economists have proposed estimators for dynamic games of incomplete information. In these models, agents choose from a finite number actions and maximize expected discounted utility in a Markov perfect equilibrium. Previous econometric methods estimate the probability distribution of agents%u2019 actions in a first stage. In a second step, a finite vector of parameters of the period return function are estimated. In this paper, we develop semiparametric estimators for dynamic games allowing for continuous state variables and a nonparametric first stage. The estimates of the structural parameters are T1/2 consistent (where T is the sample size) and asymptotically normal even though the first stage is estimated nonparametrically. We also propose sufficient conditions for identification of the model.