LATE With Missing or Mismeasured Treatment

Rossella Calvi, Arthur Lewbel and Denni Tommasi

Journal of Business & Economic Statistics, 2022, vol. 40, issue 4, 1701-1717

Abstract: We provide a new estimator, MR-LATE, that consistently estimates local average treatment effects when treatment is missing for some observations, not at random. If instead treatment is mismeasured for some observations, then MR-LATE usually has less bias than the standard LATE estimator. We discuss potential applications where an endogenous binary treatment may be unobserved or mismeasured. We apply MR-LATE to study the impact of women’s control over household resources on health outcomes in Indian families. This application illustrates the use of MR-LATE when treatment is estimated rather than observed. In these situations, treatment mismeasurement may arise from model misspecification and estimation errors.

Date: 2022
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DOI: 10.1080/07350015.2021.1970573

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