Inferring the Effect of a Confounded Treatment by Calibrating Resistant Population's Variance
通过校准处理抵抗人群的方差推断存在混杂的处理效应
In a general set-up that allows unmeasured confounding, we show that the conditional average treatment effect on the treated can be identified as one of two possible values. Unlike existing causal inference methods, we do not require an exogenous source of variability in the treatment, e.g., an instrument or another outcome unaffected by the treatment. Instead, we require (a) a nondeterministic treatment assignment, (b) that conditional variances of the two potential…