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Sensitivity Analysis for Instrumental Variables Under Joint Relaxations of Monotonicity and Independence

Pedro Picchetti

arXiv 26 Mar 2026 · Econometrics

arXiv:2603.25529 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this paper I develop a breakdown frontier approach to assess the sensitivity of Local Average Treatment Effects (LATE) estimates to violations of monotonicity and independence of the instrument. I parametrize violations of independence using the concept of $c$-dependence from Masten & Poirier (2018) and allow for the share of defiers to be greater than zero but smaller than the share of compliers. I derive identified sets for the LATE and the Average Treatment Effect (ATE) in which the bounds are functions of these two sensitivity parameters. Using these bounds, I derive the breakdown frontier for the LATE, which is the weakest set of assumptions such that a conclusion regarding the LATE holds. I derive consistent sample analogue estimators for the breakdown frontiers and provide a valid bootstrap procedure for inference. Monte Carlo simulations show the desirable finite-sample properties of the estimators and an empirical application shows that the conclusions regarding the effect of family size on unemployment from Angrist & Evans (1998) are highly sensitive to violations of independence and monotonicity.

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appendix boundary found by appendix_titled_section at “Appendix A” · 49% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Joshua D. Angrist and William N. Evans (1998) Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size1.00064100%
2Masten, Matthew A. and Poirier, Alexandre (2020) Inference on breakdown frontiers0.9507486%
3Masten, Matthew A. and Poirier, Alexandre (2018) Identification of Treatment Effects Under Conditional Partial Independence0.9416683%
4Alexander Balke and Judea Pearl (1997) Bounds on Treatment Effects from Studies with Imperfect Compliance0.9285480%
5Chen, Xuan and Flores, Carlos A. and Flores-Lagunes, Alfonso (2017) Going beyond LATE: Bounding Average Treatment Effects of Job Corps Training0.9285380%
6Noack, Claudia (2026) Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption0.92843100%
7de Chaisemartin, Clément (2017) Tolerating defiance? Local average treatment effects without monotonicity0.84333100%
8Fang, Zheng and Santos, Andres (2018) Inference on Directionally Differentiable Functions0.79410350%
9Huber, Martin and Laffers, Lukas and Mellace, Giovanni (2017) Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance0.7373367%
10Han Hong and Jessie Li (2018) The numerical delta method0.64422100%

Showing the top 10 of 26 scored citations.