摘要翻译:
我们考虑由近似矩条件定义的模型中的推理。我们证明了用广义矩法(GMM)估计量,加减标准误差乘以一个考虑了由于矩条件的不规范造成的潜在偏差的临界值,就可以形成近似最优置信区间(CIs)。为了在潜在的错误规范下优化性能,该GMM估计器的加权矩阵考虑了这种潜在的偏差,因此不同于在正确规范下的最优加权矩阵。为了形式化地证明这些CIs的近最优性,我们给出了在局部误指定GMM环境下推理的渐近效率界。这些界限可能是独立的兴趣,因为它们对在矩条件模型中进行推理时使用矩选择程序的可能性有影响。我们将我们的方法应用于汽车需求的实证应用中,表明调整加权矩阵可以使CIs收缩3倍或更多。
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英文标题:
《Sensitivity Analysis using Approximate Moment Condition Models》
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作者:
Timothy B. Armstrong and Michal Koles\'ar
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最新提交年份:
2020
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分类信息:
一级分类:Economics 经济学
二级分类:Econometrics 计量经济学
分类描述:Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论,微观计量经济学,宏观计量经济学,通过新方法发现的经济关系的实证内容,统计推论应用于经济数据的方法论方面。
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一级分类:Statistics 统计学
二级分类:Methodology 方法论
分类描述:Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计,调查,模型选择,多重检验,多元方法,信号和图像处理,时间序列,平滑,空间统计,生存分析,非参数和半参数方法
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英文摘要:
We consider inference in models defined by approximate moment conditions. We show that near-optimal confidence intervals (CIs) can be formed by taking a generalized method of moments (GMM) estimator, and adding and subtracting the standard error times a critical value that takes into account the potential bias from misspecification of the moment conditions. In order to optimize performance under potential misspecification, the weighting matrix for this GMM estimator takes into account this potential bias, and therefore differs from the one that is optimal under correct specification. To formally show the near-optimality of these CIs, we develop asymptotic efficiency bounds for inference in the locally misspecified GMM setting. These bounds may be of independent interest, due to their implications for the possibility of using moment selection procedures when conducting inference in moment condition models. We apply our methods in an empirical application to automobile demand, and show that adjusting the weighting matrix can shrink the CIs by a factor of 3 or more.
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PDF链接:
https://arxiv.org/pdf/1808.07387


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