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Robustness to Missing Data: Breakdown Point Analysis

Daniel Ober-Reynolds

arXiv 10 Jun 2024 · Econometrics · publishedJournal of Econometrics (2025)

arXiv:2406.06804 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Missing data is pervasive in econometric applications, and rarely is it plausible that the data are missing (completely) at random. This paper proposes a methodology for studying the robustness of results drawn from incomplete datasets. Selection is measured as the squared Hellinger divergence between the distributions of complete and incomplete observations, which has a natural interpretation. The breakdown point is defined as the minimal amount of selection needed to overturn a given result. Reporting point estimates and lower confidence intervals of the breakdown point is a simple, concise way to communicate the robustness of a result. An estimator of the breakdown point of a result drawn from a generalized method of moments model is proposed and shown root-n consistent and asymptotically normal under mild assumptions. Lower confidence intervals of the breakdown point are simple to construct. The paper concludes with a simulation study illustrating the finite sample performance of the estimators in several common models.

Citation extraction

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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
1Bandiera, Oriana and Buehren, Niklas and Burgess, Robin and Goldstei… (2020) Women’s empowerment in action: evidence from a randomized control trial in Africa0.87462100%
2Giacobino, Hélène and Huillery, Elise and Michel, Bastien and Sage,… (2024) Schoolgirls, not brides: Education as a shield against child marriage0.87462100%
3Kline, Patrick and Santos, Andres (2013) Sensitivity to missing data assumptions: Theory and an evaluation of the US wage structure0.8434375%
4Csiszár, Imre and Gamgoa, F and Gassiat, Elisabeth (1999) MEM pixel correlated solutions for generalized moment and interpolation problems0.8435360%
5Barham, Tania and Macours, Karen and Maluccio, John A (2024) Experimental evidence from a conditional cash transfer program: schooling, learning, fertility, and labor market outcomes after…0.81142100%
6Borwein, Jonathan M and Lewis, Adrian S (1991) Duality relationships for entropy-like minimization problems0.81142100%
7Diegert, Paul and Masten, Matthew A and Poirier, Alexandre (2025) Assessing Omitted Variable Bias when the Controls are Endogenous0.7373367%
8Masten, Matthew A and Poirier, Alexandre (2020) Inference on breakdown frontiers0.7373367%
9Manski, Charles F (2005) Partial identification with missing data: concepts and findings0.73732100%
10Fang, Zheng and Santos, Andres (2019) Inference on directionally differentiable functions0.64410240%

Showing the top 10 of 48 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Inference under First-Order Degeneracy0.40511