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We propose exact tests and confidence sets for various structural models typically estimated by IV methods, such as models with unobserved regressors, which remain valid despite the presence of identification problems or weak instruments. Two approaches are considered: (1) an instrument substitution method, which generalizes the Anderson-Rubin procedure, and (2) a samplesplit method, that allows the use of "generated regressors." Projection techniques are also proposed for inference on general parameter transformations. The asymptotic theory of the tests under weaker assumptions is discussed. Simulation results are presented. The suggested techniques are applied to a model of Tobin's q and to a model of academic performance.

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