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On the plausibility of the latent ignorability assumption

Martin Huber

arXiv 2 Jun 2020 · Econometrics · publishedEconometrics (2021)

arXiv:2006.01703 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The estimation of the causal effect of an endogenous treatment based on an instrumental variable (IV) is often complicated by attrition, sample selection, or non-response in the outcome of interest. To tackle the latter problem, the latent ignorability (LI) assumption imposes that attrition/sample selection is independent of the outcome conditional on the treatment compliance type (i.e. how the treatment behaves as a function of the instrument), the instrument, and possibly further observed covariates. As a word of caution, this note formally discusses the strong behavioral implications of LI in rather standard IV models. We also provide an empirical illustration based on the Job Corps experimental study, in which the sensitivity of the estimated program effect to LI and alternative assumptions about outcome attrition is investigated.

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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
1Fricke, Frölich, Huber, and Lechner (2020) Endogeneity and Non-Response Bias in Treatment Evaluation - Nonparametric Identification of Causal Effects by Instruments0.64441100%
2Frölich and Huber (2014) Treatment evaluation with multiple outcome periods under endogeneity and attrition0.64441100%
3Angrist, Imbens, and Rubin (1996) Identification of Causal Effects using Instrumental Variables0.64422100%
4Frangakis and Rubin (1999) Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subs…0.64422100%
5Barnard, Frangakis, Hill, and Rubin (2003) A Principal Stratification Approach to Broken Randomized Experiments: A Case Study of School Choice Vouchers in New York City0.40511100%
6Mealli, Imbens, Ferro, and Biggeri (2004) Analyzing a randomized trial on breast self-examination with noncompliance and missing outcomes0.40511100%
7Rubin (1976) Inference and Missing Data0.40511100%
8Schochet, Burghardt, and Glazerman (2001) National Job Corps Study: The Impacts of Job Corps on Participants' Employment and Related Outcomes0.40511100%

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