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LATE with missing or mismeasured treatment

Rossella Calvi, Arthur Lewbel, Denni Tommasi

    Research output: Contribution to journalArticleResearchpeer-review

    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.

    Original languageEnglish
    Pages (from-to)1701-1717
    Number of pages17
    JournalJournal of Business and Economic Statistics
    Volume40
    Issue number4
    DOIs
    Publication statusPublished - 2022

    Keywords

    • Collective model
    • Health
    • LATE
    • Measurement error
    • Misclassification
    • Missing treatment
    • Resource shares

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