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On the falsification of instrumental variable models for heterogeneous treatment effects

Ricardo E. Miranda

arXiv 20 Jan 2026 · Econometrics

arXiv:2601.14464 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this paper I derive a set of testable implications for econometric models defined by three assumptions: (i) the existence of strictly exogenous discrete instruments, (ii) restrictions on how the instruments affect adoption of a finite number of treatment types (such as monotonicity), and (iii) the assumption that the instruments only affect outcomes through their effect on treatment adoption (i.e. an exclusion restriction). The testable implications aggregate (via integration) an otherwise potentially infinite set of inequalities that must hold for every measurable subset of the outcome's support. For binary instruments the testable implications are sharp. Furthermore, I propose an implementation that links restrictions on latent response types to a generalization of first-order stochastic dominance and random utility models, allowing to distinguish violations of the exclusion restriction from violations of monotonicity-type assumptions. The testable implications extend naturally to the many instruments case.

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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
1Guido W. Imbens and Joshua D. Angrist (1994) Identification and Estimation of Local Average Treatment Effects0.9507586%
2Kitagawa, Toru (2015) A test for instrument validity0.9416383%
3Sun, Zhenting (2023) Instrument validity for heterogeneous causal effects0.92843100%
4Heckman, James J and Pinto, Rodrigo (2018) Unordered monotonicity0.8746467%
5Kwon, Soonwoo and Roth, Jonathan (2024) Testing Mechanisms0.87452100%
6Kaido, Hiroaki and Ponomarev, Kirill (2025) Testing Exclusion and Shape Restrictions in Potential Outcomes Models0.81142100%
7Navjeevan, Manu and Pinto, Rodrigo (2022) Ordered, Unordered and Minimal Monotonicity Criteria0.81142100%
8Lee, Sokbae and Salanié, Bernard (2020) Treatment effects with targeting instruments0.7946550%
9Bai, Yuehao and Huang, Shunzhuang and Tabord-Meehan, Max (2024) Sharp Testable Implications of Encouragement Designs0.7375440%
10Goff, Leonard (2024) When does IV identification not restrict outcomes?0.7375340%

Showing the top 10 of 44 scored citations.