This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an asymptotic distribution theory, which allows for mild misspecification. Moment misspecification causes bias in conventional GMM variance estimators, which can lead to severely oversized hypothesis tests. We show how to consistently estimate the correct asymptotic variance matrix. Our simulation results show that our methods are properly sized under both correct specification and mild to moderate misspecification. We illustrate the method with an application to the model of Acemoglu, Johnson, Robinson, and Yared (2008).

中文翻译：

---

错误规范下的迭代GMM推论

本文为迭代的过度识别广义矩（GMM）估计器开发了推理方法。我们为迭代估计量和渐进分布理论的存在提供了条件，该理论允许轻度错误指定。瞬间错误指定会导致传统GMM方差估算器产生偏差，从而可能导致假设检验严重过大。我们展示了如何一致地估计正确的渐近方差矩阵。我们的模拟结果表明，我们的方法在正确的规格和轻度到中度的错误规格下都具有适当的大小。我们将其应用到Acemoglu，Johnson，Robinson和Yared（2008）的模型中进行说明。