Papers
Finding excluded (and exogenous) instruments is hard. We consider the situation where instruments are excluded only conditional on some unobserved common confounders, for which relevant proxies exist. Using insights from proximal learning, we can identify exogenous variation in the instruments to then identify a causal effect of a treament on an outcome. All our relevance assumptions are testable, while as usual in IV, the assumption of exclusion conditional on unobservables is not (up to specification tests). Importantly, exclusion conditional on unobservables for which proxies exist may be a weaker assumption than exclusion conditional on observables only.
