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A note on bounding average treatment effects

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  • Lafférs, Lukáš

Abstract

Imposing the monotone treatment selection (MTS) assumption and the monotone instrumental variable (MIV) assumption implies bounds on average treatment effect that differ from those commonly reported in the applied literature. Instead, for the bounds to be correct, we should use an MTS assumption conditional on the value of a monotone instrument (cMTS). In this paper, we present an empirical example of bounding the effect of the mother’s education on her children’s education, in which the MTS and cMTS assumptions lead to considerably different bounds on the treatment effects.

Suggested Citation

  • Lafférs, Lukáš, 2013. "A note on bounding average treatment effects," Economics Letters, Elsevier, vol. 120(3), pages 424-428.
    • Handle: RePEc:eee:ecolet:v:120:y:2013:i:3:p:424-428
    DOI: 10.1016/j.econlet.2013.05.029
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    References listed on IDEAS

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    11. Brent Kreider & John V. Pepper & Craig Gundersen & Dean Jolliffe, 2012. "Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation Is Endogenous and Misreported," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 958-975, September.
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    Cited by:

    1. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.

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    More about this item

    Keywords

    Partial identification; Bounds; Average treatment effect;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • I2 - Health, Education, and Welfare - - Education

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