Identification robust Inference in GMM Models Using Stability Restrictions

结构变化通常由政策体制转变引起，是动态经济模型的一个共同特征。所提出的研究表明，这种变化可以建设性地用于改善随着时间的推移是稳定的结构参数的识别。这一见解被用来开发新的计量经济学方法，推广广泛使用的广义矩量法（GMM）。所提出的方法产生用于分析宏观经济政策的模型的改进的推理，因此，他们有可能被广泛地应用于practice.The拟议的研究重点是时间序列模型，艾德的一组矩条件。一个主要的例子是欧拉方程模型，其参数被假定为在面对政策制度转变或经济冲击波动变化时保持稳定。然而，所提出的推理方法的范围超出了这个具体的例子。所提出的研究的贡献是双重的。首先，它提出了使用稳定性限制的正式理由（例如，免疫卢卡斯批评）作为一个来源的稳定结构参数的经济模型中的识别，或者说，不同的是，使用结构变化来识别稳定的动态因果效应。关键的见解是，在数据的分布变化引起的，例如，政策制度的转变，提供额外的外源性变化，可以有效地利用推理。通常的GMM方法只依赖于全样本排除或交叉方程限制来识别模型的结构参数，而忽略了这些信息。第二个贡献是开发新的结构推断计量经济学方法，利用稳定性限制中的信息，只需要对数据分布的不稳定性进行温和的假设。具体而言，它们不需要事先了解中断的发生率、次数和时间。因为不需要任何关于识别的假设，所以主要的正则性条件严格地弱于那些用于证明在应用工作中广泛使用的稳定性检验的条件。 因此，所提出的方法的范围非常广。应用所提出的方法，一个广泛使用的新凯恩斯主义宏观经济模型表明，这些方法是非常有用的practice.Intellectual优点：这项研究，这是在与Leandro Magnusson（杜兰大学）合作，是重要的，以推进经济学领域的知识，通过发展必要的新的定量方法与变革的潜力。更广泛的影响：㈠该项目将为评价经济政策所用模型提供基本工具。(ii)将通过在会议上介绍和在同行评审的学术期刊上发表，广泛传播研究结果，以提高科学认识。

Structural change, typically induced by policy regime shifts, is a common feature of dynamic economic models. The proposed research shows that such changes can be used constructively to improve the identification of structural parameters that are stable over time. This insight is used to develop novel econometric methods that generalize the widely used generalized method of moments (GMM). The proposed methods yield improved inference in models that are used for the analysis of macroeconomic policy, so they have the potential to be widely used in practice.The proposed reseach focuses on time series models that are speci…ed in terms of a set of moment conditions. A leading example is Euler equation models whose parameters are assumed to be stable in the face of policy regime shifts or changes in the volatility of economic shocks. However, the scope of the proposed methods of inference extends beyond this specific example.The contribution of the proposed research is twofold. First, it makes a formal case for using stability restrictions (e.g., immunity to the Lucas critique) as a source of identification of the stable structural parameters in economic models, or put di¤erently, for using structural change to identify stable dynamic causal e¤ects. The key insight is that changes in the distribution of the data induced by, for example, policy regime shifts, provide additional exogenous variation that can be usefully exploited for inference. This information is ignored by the usual GMM approach that relies only on full-sample exclusion or cross-equation restrictions to identify the structural parameters of the model.The second contribution is to develop new econometric methods for structural inference that exploit the information in stability restrictions and require only mild assumptions about the nature of instability in the distribution of the data. Specifically, they do not require any prior knowledge about the incidence, number and timing of breaks. Because no assumptions about identification are required, the main regularity conditions are strictly weaker than those used to justify the stability tests that are widely used in applied work. Therefore, the scope of the proposed methods is very wide. Application of the proposed methods to a widely used new Keynesian macroeconomic model shows that these methods are very useful in practice.Intellectual Merit: This research, which is in collaboration with Leandro Magnusson (Tulane U), is important to advancing knowledge in the field of economics by developing essential new quantitative methods with transformative potential. Broader Impact: (i) The project will provide essential tools for the evaluation of models used for economic policy. (ii) the results will be broadly disseminated to enhance scientific understanding through presentations in conferences, and publication in peer-reviewed academic journals.