YET MORE ON THE EXACT PROPERTIES OF IV ESTIMATORS
在高斯假设下，用条件化方法简化两阶段最小二乘和有限信息最大似然估计量的精确性质推导，澄清弱工具变量渐近理论中的结果。
We revisit the exact properties of two-stage least squares and limited information maximum likelihood estimators in a structural equation/instrumental variables regression under Gaussian assumptions. Simple derivations based on conditioning serve both to demystify the apparently complicated formulas, and to isolate the key quantities that determine the properties of the estimators. Some recent results obtained under weak-instrument asymptotics are sharpened and clarified by the exact analysis.Thanks to Peter Phillips and several anonymous referees for helpful comments that improved the paper considerably.