We study the properties of “shock-exposure instruments,” constructed from a set of quasi-experimental shocks and endogenous measures of heterogeneous exposure. Validity of these instruments generally requires a simple but non-standard correction, derived from knowledge of counterfactual shocks that might have been realized. Such design knowledge can also be used for exact randomization inference and specification tests that are valid in finite samples. We further characterize the shock-exposure instruments that are asymptotically efficient. This framework has practical implications for the use of shift-share instruments, simulated eligibility instruments, model-implied instruments, and for other designs. We illustrate these implications in two applications.
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