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Universal Inference for Incomplete Discrete Choice Models

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  • Hiroaki Kaido
  • Yi Zhang

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.

Suggested Citation

  • Hiroaki Kaido & Yi Zhang, 2025. "Universal Inference for Incomplete Discrete Choice Models," Papers 2501.17973, arXiv.org.
    • Handle: RePEc:arx:papers:2501.17973
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    References listed on IDEAS

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    6. Donald W. K. Andrews & Xiaoxia Shi, 2013. "Inference Based on Conditional Moment Inequalities," Econometrica, Econometric Society, vol. 81(2), pages 609-666, March.
    7. Bo E. Honoré & Elie Tamer, 2006. "Bounds on Parameters in Panel Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 74(3), pages 611-629, May.
    8. repec:spo:wpmain:info:hdl:2441/5rkqqmvrn4tl22s9mc4ao8ocg is not listed on IDEAS
    9. Michael J Dickstein & Eduardo Morales, 2018. "What do Exporters Know?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(4), pages 1753-1801.
    10. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 147-165.
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