Nonparametric bounds on treatment effects with imperfect instruments

Instrument-based estimation with binarized treatments: Issues and tests for the exclusion restriction

Kyunghoon Ban and Désiré Kédagni
Authors registered in the RePEc Author Service: Desire Kedagni

The Econometrics Journal, 2022, vol. 25, issue 2, 477-493

Abstract: SummaryThis paper extends the identification results in Nevo and Rosen (2012) to nonparametric models. We derive nonparametric bounds on the average treatment effect when an imperfect instrument is available. As in Nevo and Rosen (2012), we assume that the correlation between the imperfect instrument and the unobserved latent variables has the same sign as the correlation between the endogenous variable and the latent variables. We show that the monotone treatment selection and monotone instrumental variable restrictions, introduced by Manski and Pepper (2000; 2009), jointly imply this assumption. Moreover, we show how the monotone treatment response assumption can help tighten the bounds. The identified set can be written in the form of intersection bounds, which is more conducive to inference. We illustrate our methodology using the National Longitudinal Survey of Young Men data to estimate returns to schooling.

Keywords: Imperfect instrumental variables; nonparametric bounds; average treatment effect; monotone treatment response (search for similar items in EconPapers)
Date: 2022
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Related works:
Working Paper: Nonparametric Bounds on Treatment Effects with Imperfect Instruments (2021)
Working Paper: Nonparametric Bounds on Treatment Effects with Imperfect Instruments (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:emjrnl:v:25:y:2022:i:2:p:477-493.

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