Grigory Franguridi, Hyungsik Roger Moon
arXiv 27 Nov 2025 · Econometrics
arXiv:2511.21988 · PDF · DOI · OpenAlex · Extracted main text
We consider a generalized method of moments framework in which a part of the data vector is missing for some units in a completely unrestricted, potentially endogenous way. In this setup, the parameters of interest are usually only partially identified. We characterize the identified set for such parameters using the support function of the convex set of moment predictions consistent with the data. This identified set is sharp, valid for both continuous and discrete data, and straightforward to estimate. We also propose a statistic for testing hypotheses and constructing confidence regions for the true parameter, show that standard nonparametric bootstrap may not be valid, and suggest a fix using the bootstrap for directionally differentiable functionals of Fang and Santos (2019). A set of Monte Carlo simulations demonstrates that both our estimator and the confidence region perform well when samples are moderately large and the data have bounded supports.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Fang, Zheng and Santos, Andres (2019) Inference on directionally differentiable functions | 0.894 | 14 | 6 | 71% |
| 2 | Kaido, Hiroaki and Santos, Andres (2014) Asymptotically efficient estimation of models defined by convex moment inequalities | 0.644 | 2 | 2 | 100% |
| 3 | Franguridi, Grigory and Liu, Laura (2025) Inference in partially identified moment models via regularized optimal transport self | 0.511 | 2 | 2 | 50% |
| 4 | Beresteanu, Arie and Molchanov, Ilya and Molinari, Francesca (2011) Sharp identification regions in models with convex moment predictions | 0.405 | 1 | 1 | 100% |
| 5 | Chernozhukov, Victor and Lee, Sokbae and Rosen, Adam M (2013) Intersection bounds: Estimation and inference | 0.405 | 1 | 1 | 100% |
| 6 | Deng, Y. and Chang, C. and others (2016) Statistical Methods for Nonignorable Missing Longitudinal Data | 0.405 | 1 | 1 | 100% |
| 7 | Hausman, Jerry A. and Wise, David (1979) Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment | 0.405 | 1 | 1 | 100% |
| 8 | Manski, Charles F (1989) Anatomy of the selection problem | 0.405 | 1 | 1 | 100% |
| 9 | Manski, Charles F (2005) Partial identification with missing data: concepts and findings | 0.405 | 1 | 1 | 100% |
| 10 | Molinari, Francesca (2020) Microeconometrics with partial identification | 0.405 | 1 | 1 | 100% |
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