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Testing Partial Instrument Monotonicity

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  • Hongyi Jiang
  • Zhenting Sun

Abstract

When multi-dimensional instruments are used to identify and estimate causal effects, the monotonicity condition may not hold due to heterogeneity in the population. Under a partial monotonicity condition, which only requires the monotonicity to hold for each instrument separately holding all the other instruments fixed, the 2SLS estimand can still be a positively weighted average of LATEs. In this paper, we provide a simple nonparametric test for partial instrument monotonicity. We demonstrate the good finite sample properties of the test through Monte Carlo simulations. We then apply the test to monetary incentives and distance from results centers as instruments for the knowledge of HIV status.

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  • Hongyi Jiang & Zhenting Sun, 2023. "Testing Partial Instrument Monotonicity," Papers 2308.08390, arXiv.org, revised Aug 2023.
    • Handle: RePEc:arx:papers:2308.08390
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    References listed on IDEAS

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    6. Rebecca L. Thornton, 2008. "The Demand for, and Impact of, Learning HIV Status," American Economic Review, American Economic Association, vol. 98(5), pages 1829-1863, December.
    7. Zhenting Sun & Brendan K. Beare, 2021. "Improved Nonparametric Bootstrap Tests of Lorenz Dominance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 189-199, January.
    8. Beare, Brendan K. & Shi, Xiaoxia, 2019. "An improved bootstrap test of density ratio ordering," Econometrics and Statistics, Elsevier, vol. 10(C), pages 9-26.
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    Cited by:

    1. Leonard Goff, 2024. "When does IV identification not restrict outcomes?," Papers 2406.02835, arXiv.org, revised Sep 2024.

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