This paper studies identification of the marginal treatment effect (MTE) when a binary treatment variable is misclassified. We show under standard assumptions that the MTE is identified as the derivative of the conditional expectation of the observed outcome given the true propensity score, which is partially identified. We characterize the identified set for this propensity score, and then for the MTE. We use our MTE bounds to derive bounds on other commonly used parameters in the literature. We show that our bounds are tighter than the existing bounds for the local average treatment effect. We illustrate the practical relevance of our derived bounds through some numerical and empirical results.
C14, C31, C35, C36
Original Release Date: June 18, 2021
Department of Economics, Iowa State University
Acerenza, Santiago; Ban, Kyunghoon; and Kedagni, Desire, "Marginal Treatment Effects with Misclassified Treatment" (2021). Economics Working Papers: Department of Economics, Iowa State University. 21011.