John C. Chao, J. Hausman, Whitney Newey, Norman R. Swanson, Tiemen Woutersen
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引用次数: 4
摘要
本文展示了正向和反向Jackknife IV估计器(JIVE)的加权平均如何产生对异方差和许多工具具有鲁棒性的估计器。这些被称为HFUL(异方差鲁棒富勒)和HLIM(异方差鲁棒有限信息最大似然(LIML))的估计量是由Hausman等人(2012)引入的,但没有推导。组合一致估计量是与Jerry Hausman有关的主题,因此,我们在本卷中提出了这个推导。此外,为了进一步理解和解释在折刀型方差比估计器背景下的HFUL和HLIM,我们展示了HLIM的一个新变体,在特定的分组数据设置下,使用虚拟仪器,简化为Bekker和van der Ploeg (2005) MM(矩量法)估计器。
This paper shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited information maximum likelihood (LIML)) were introduced by Hausman et al. (2012), but without derivation. Combining consistent estimators is a theme that is associated with Jerry Hausman and, therefore, we present this derivation in this volume. Additionally, and in order to further understand and interpret HFUL and HLIM in the context of jackknife type variance ratio estimators, we show that a new variant of HLIM, under specific grouped data settings with dummy instruments, simplifies to the Bekker and van der Ploeg (2005) MM (method of moments) estimator.