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Universal Inference for Incomplete Discrete Choice Models

Hiroaki Kaido, Yi Zhang

arXiv 29 Jan 2025 · Econometrics

arXiv:2501.17973 · PDF · DOI · OpenAlex · Extracted main text

Abstract

A growing number of empirical models exhibit set-valued predictions. This paper develops a tractable inference method with finite-sample validity for such models. The proposed procedure uses a robust version of the universal inference framework by Wasserman et al. (2020) and avoids using moment selection tuning parameters, resampling, or simulations. The method is designed for constructing confidence intervals for counterfactual objects and other functionals of the underlying parameter. It can be used in applications that involve model incompleteness, discrete and continuous covariates, and parameters containing nuisance components.

Citation extraction

68
references
225
in-text mentions
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distinct cited
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self-citations
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main-text words

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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
1Wasserman, L., A. Ramdas, and S. Balakrishnan (2020) Universal inference0.97413692%
2Kaido, H. and Y. Zhang (2019) Robust Likelihood Ratio Tests for Incomplete Economic Models self0.9285380%
3Bugni, F., I. Canay, and X. Shi (2017) Inference for Subvectors and Other Functions of Partially Identified Parameters in Moment Inequality Models0.87472100%
4Philippe, F., G. Debs, and J.-Y. Jaffray (1999) Decision making with monotone lower probabilities of infinite order0.8434375%
5Bresnahan, T. F. and P. C. Reiss (1990) Entry in monopoly market0.7373367%
6Kaido, H. and F. Molinari (2024) Information Based Inference In Models With Set-Valued Predictions And Misspecification self0.73732100%
7Barseghyan, L., M. Coughlin, F. Molinari, and J. C. Teitelbaum (2021) Heterogeneous Choice Sets and Preferences0.73732100%
8Chernozhukov, V., S. Lee, and A. M. Rosen (2013) Intersection Bounds: Estimation and Inference0.73732100%
9Chesher, A., A. M. Rosen, and Y. Zhang (2024) Robust Analysis of Short Panels0.73732100%
10Andrews, D. W. and X. Shi (2013) Inference Based on Conditional Moment Inequalities0.64422100%

Showing the top 10 of 159 scored citations.