Identification and Estimation in Structural Econometric Models

结构计量经济学模型是产业组织、劳动和公共经济学、发展经济学等领域许多实证研究的基本工具。识别分析是任何此类研究的第一个必要步骤。在许多这些模型中，如那些涉及多维优化或平衡条件的模型，感兴趣的变量同时确定。Benkard和Berry（2004）最近的一个结果表明，长期以来用于确定身份的身份识别结果，在身份识别模型中，是不正确的。因此，除了几十年前研究的具有加性不可观测随机项的限制性线性规范模型外，目前对结构联立方程模型的识别条件知之甚少。在本项目中，PI将为具有加性和非加性不可观测变量的参数和非参数模型中的结构联立方程系统的识别提供正确的条件。由于以前的大量计量经济学工作依赖于以前的不正确条件，PI还将分析在结构模型中的哪些附加条件下，以前的结果仍然成立。将开发的识别条件将用于指导发现非参数联立方程的新估计方法，这些方法将是一致的，渐近正态的，并且易于计算。由于在经济学应用领域中遇到的许多结构计量经济学模型中，人们遇到对内生变量（例如利润或效用值）的实际值的观察有限的情况，因此识别和估计结果将扩展到这种情况，在内生变量为联立方程的情况下，模型是潜在的。为了指导PI开发新方法，并促进新方法的采用和理解，她将考虑应用于应用经济学中的几个主要模型，如消费者需求模型，离散选择模型，快乐均衡模型，纳什均衡，调查响应误差模型。建议ActivityThe的智力优点有关识别的联立方程，PI将开发的结果将允许应用计量经济学家，以确定可以识别的元素在econometricmodel，给定他们的可用数据。结果将适用于非常一般的模型，这并不指定参数结构的未知函数或分布的不可观测的随机项，以及更严格的，参数模型。非参数模型估计的结果将使研究者能够在不施加参数限制的情况下估计这类模型，由于同时确定感兴趣变量的值的结构计量经济模型在经济学的大多数应用领域中广泛存在，因此这些结果预计将产生非常广泛的影响。此外，通过开辟新的方法来分析identificationand估计在非参数联立方程模型，预计一波新的理论成果将遵循，作为本项目的研究结果。更广泛的影响模型，其中几个变量的兴趣，同时确定广泛的，除其他外，工程和社会科学。在这个项目中开发的方法将适用于这些科学的应用，并通过它们造福于整个社会。为此，将广泛传播该项目的成果。通过让研究生参与本研究，期望他/她将新的结果应用于他/她的论文和/或开发新的相关结果。

Structural econometric models are essential tools for many empirical studies in fields such asindustrial organization, labor and public economics, and development economics. The analysisof identification is a first necessary step in any such studies. In many of these models, such asthose involving multidimensional optimization or equilibrium conditions, the variables of interestare determined simultaneously. A recent result by Benkard and Berry (2004) has shown thatidentification results that were used for a long time to determine identification, in simultaneousequations models, are incorrect. Hence, other than in the restrictive linear specification modelswith additive unobservable random terms, studied decades ago, little is known at present aboutthe conditions for identification in structural simultaneous equation models.In this project, the PI will develop correct conditions for identification of systems of simultaneousequations, in parametric and nonparametric models, with additive and nonadditive unobservablevariables. Since a large body of previous work in econometrics has relied on the previous incorrectconditions, the PI will also analyze under what additional conditions in the structural models, thoseprevious results still hold.The identification conditions that will be developed will be used to guide the discovery ofnew methods for estimation in nonparametric simultaneous equations, which will be consistent,asymptotically normal, and easy to compute.Since in many of the structural econometric models encountered in applied fields in economics,one encounters situations where observations on the actual values of endogenous variables, such as profits or utility values, is limited, the identification and estimation results will be extended to such situations, where the endogenous variables is simultaneous equations models are latent.To guide the PI in the development of the new methods, and to facilitate the adoption andunderstanding of the new methods, she will consider applications to several leading models inapplied economics, such as models of consumer demand, discrete choice models, hedonic equilibrium models, Nash equilibrium, and models of survey response errors.Intellectual Merit of the Proposed ActivityThe results about identification of simultaneous equations that the PI will develop will allowapplied econometricians to determine the elements that can be identified in an econometricmodel, given their available data. The results will be applicable to very general models, whichdo not specify parametric structures either for the unknown functions or for the distributions ofthe unobservable random terms, as well as to more restrictive, parametric models. The resultsabout estimation of nonparametric models will allow researchers to estimate such models withoutimposing parametric restrictions.Since structural econometric models where the values of the variables of interest are determinedsimultaneously is widespread in most applied fields in economics, these results are predicted tohave a very wide impact. Moreover, by opening the road to new ways of analyzing identificationand estimation in nonparametric simultaneous equation models, it is expected that a wave of newtheoretical results will follow, as a result of the research in this project.Broader ImpactsModels where several variables of interest are determined simultaneously are widespread in,among others, engineering and the social sciences. The methods that will be developed in thisproject will be suitable for applications in these sciences, and through them, they will benefit societyat large. With this aim, the results of the project will be disseminated widely. By involving agraduate student in this research, it is expected that he/she will apply the new results in his/herdissertation and/or develop new related results.