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Partial Identification in Nonseparable Binary Response Models with Endogenous Regressors

Jiaying Gu, Thomas M. Russell

arXiv 4 Jan 2021 · Econometrics · publishedJournal of Econometrics (2022) · 7 citations (OpenAlex)

arXiv:2101.01254 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper considers (partial) identification of a variety of counterfactual parameters in binary response models with possibly endogenous regressors. Our framework allows for nonseparable index functions with multi-dimensional latent variables, and does not require parametric distributional assumptions. We leverage results on hyperplane arrangements and cell enumeration from the literature on computational geometry in order to provide a tractable means of computing the identified set. We demonstrate how various functional form, independence, and monotonicity assumptions can be imposed as constraints in our optimization procedure to tighten the identified set. Finally, we apply our method to study the effects of health insurance on the decision to seek medical treatment.

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76
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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
1Cho, J. and Russell, T. M (2021) Simple inference on functionals of set-identified parameters defined by linear moments self1.000214100%
2Chesher, A. and Rosen, A. M (2014) An instrumental variable random-coefficients model for binary outcomes1.000205100%
3Chesher, A., Rosen, A. M., and Smolinski, K (2013) An instrumental variable model of multiple discrete choice1.000104100%
4Chesher, A. and Rosen, A. M (2017) Generalized instrumental variable models1.00074100%
5Heckman, J. J. and Pinto, R (2018) Unordered monotonicity1.00053100%
6Galichon, A. and Henry, M (2011) Set identification in models with multiple equilibria0.92843100%
7Gu, J. and Koenker, R (2020) Nonparametric maximum likelihood methods for binary response models with random coefficients self0.874102100%
8Fukuda, K. and Prodon, A (1995) Double description method revisited0.73732100%
9Molchanov, I. S (1998) A limit theorem for solutions of inequalities0.73732100%
10Rada, M. and Cerný, M (2018) A new algorithm for enumeration of cells of hyperplane arrangements and a comparison with avis and fukuda's reverse search0.73732100%

Showing the top 10 of 80 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 for Linear Systems with Unknown Coefficients0.64422
2Simple Inference on Functionals of Set-Identified Parameters Defined by Linear MomentsA previous version of this paper was circulated under the title “Inference on Functionals of Set-Identified Parameters Defined by Convex Moments." We are grateful to Ivan Canay, the associate editor, and two referees for excellent feedback that greatly improved the paper. We thank Victor Aguirregabiria, Bulat Gafarov, Christian Gourieroux, Jiaying Gu, Ismael Mourifie, Jeffrey Negrea, Adam Rosen, Brennan Thompson, Stanislav Volgushev and Yuanyuan Wan for helpful comments and discussion. We are also grateful to participants at the 7th Annual Doctoral Workshop in Applied Econometrics at the University of Toronto, as well as participants at the 2019 North America Summer Meeting of the Econometric Society at the University of Washington. This research was supported by the Social Sciences and Humanities Research Council of Canada. All errors are our own0.51121
3A Computational Approach to Identification of Treatment Effects for Policy Evaluation0.40511