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<https://discovery.ucl.ac.uk/id/eprint/10177886> <http://purl.org/ontology/bibo/abstract> "We propose a semi-parametric test to evaluate (a) whether different instruments induce subpopulations of compliers with the same observable characteristics, on average; and (b) whether compliers have observable characteristics that are the same as the full population, treated subpopulation, or untreated subpopulation, on average. The test is a flexible robustness check for the external validity of instruments. To justify the test, we characterise the doubly robust moment for Abadie’s class of complier parameters, and we analyse a machine learning update to weighting that we call the automatic \r\n weight. We use the test to reinterpret Angrist and Evans' different local average treatment effect estimates obtained using different instrumental variables."^^<http://www.w3.org/2001/XMLSchema#string> .
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