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Tolerating defiance? Local average treatment effects without monotonicity

Author

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  • Chaisemartin, Clément de

    (The University of Warwick)

Abstract

We know that instrumental variable (IV) estimates a causal effect if the instrument satisfies a monotonicity condition. When this condition is not satisfied, we only know that IV estimates the difference between the effect of the treatment in two groups. This difference could be a very misleading measure of the treatment effect: it could be negative, even when the effect is positive in both groups. There are a large number of studies in which monotonicity is implausible. One might then question whether we should trust their estimates. I show that IV estimates a causal effect under a much weaker condition than monotonicity. I outline three criteria applied researchers can use to assess whether this condition is applicable in their studies. When this weaker condition is applicable, they can credibly interpret their estimates as causal effects. When it is not, they should interpret their results with caution.

Suggested Citation

  • Chaisemartin, Clément de, 2014. "Tolerating defiance? Local average treatment effects without monotonicity," CAGE Online Working Paper Series 197, Competitive Advantage in the Global Economy (CAGE).
    • Handle: RePEc:cge:wacage:197
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    File URL: http://www2.warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/197-2014_chaisemartin.pdf
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    References listed on IDEAS

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    Cited by:

    1. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    2. Ivan Zilic, 2018. "Effect of forced displacement on health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 889-906, June.
    3. Will Dobbie & Jae Song, 2015. "Debt Relief and Debtor Outcomes: Measuring the Effects of Consumer Bankruptcy Protection," American Economic Review, American Economic Association, vol. 105(3), pages 1272-1311, March.
    4. Sara Cools & Simen Markussen & Marte Strøm, 2017. "Children and Careers: How Family Size Affects Parents’ Labor Market Outcomes in the Long Run," Demography, Springer;Population Association of America (PAA), vol. 54(5), pages 1773-1793, October.

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    Keywords

    instrumental variable; two stage least squares; heterogeneous effects; monotonicity; deers; internal validity;
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