论文标题
关于仪器变量估计，许多弱和无效的仪器
On the instrumental variable estimation with many weak and invalid instruments
论文作者
论文摘要
我们讨论了具有未知IV有效性的线性仪器变量（IV）模型中识别的基本问题。通过假设“最稀少的规则”，该规则等同于复数规则，但在计算算法中起作用，我们研究并证明了基于两步选择的其他IV估计器的非convex惩罚方法的优势，就选择性和适应性而言，基于两步的选择。此外，我们提出了一种替代较少的惩罚，该罚款与识别条件保持一致，并同时提供甲骨文稀疏的结构。与先前的文献相比，针对静脉强度较弱的估计仪得出了理想的理论特性。使用模拟证明了有限样本特性，并且选择和估计方法应用于有关BMI对舒张压的影响的经验研究。
We discuss the fundamental issue of identification in linear instrumental variable (IV) models with unknown IV validity. With the assumption of the "sparsest rule", which is equivalent to the plurality rule but becomes operational in computation algorithms, we investigate and prove the advantages of non-convex penalized approaches over other IV estimators based on two-step selections, in terms of selection consistency and accommodation for individually weak IVs. Furthermore, we propose a surrogate sparsest penalty that aligns with the identification condition and provides oracle sparse structure simultaneously. Desirable theoretical properties are derived for the proposed estimator with weaker IV strength conditions compared to the previous literature. Finite sample properties are demonstrated using simulations and the selection and estimation method is applied to an empirical study concerning the effect of BMI on diastolic blood pressure.
