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Optimal transportation and the falsifiability of incompletely specified economic models

Author

Listed:
  • Ivar Ekeland

    (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Alfred Galichon
  • Marc Henry

    (CIRANO - Centre interuniversitaire de recherche en analyse des organisations - UQAM - Université du Québec à Montréal = University of Québec in Montréal, CIREQ - Centre interuniversitaire de recherche en économie quantitative)

Abstract

A general framework is given to analyze the falsifiability of economic models based on a sample of their observable components. It is shown that, when the restrictions implied by the economic theory are insufficient to identify the unknown quantities of the structure, the duality of optimal transportation with zero–one cost function delivers interpretable and operational formulations of the hypothesis of specification correctness from which tests can be constructed to falsify the model.

Suggested Citation

  • Ivar Ekeland & Alfred Galichon & Marc Henry, 2010. "Optimal transportation and the falsifiability of incompletely specified economic models," Post-Print hal-03417660, HAL.
    • Handle: RePEc:hal:journl:hal-03417660
    DOI: 10.1007/s00199-008-0432-y
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    References listed on IDEAS

    as
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    Cited by:

    1. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    3. Ivar Ekeland & Alfred Galichon, 2013. "The housing problem and revealed preference theory: duality and an application," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 54(3), pages 425-441, November.
    4. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
    5. Andrew Chesher & Adam M. Rosen & Konrad Smolinski, 2013. "An instrumental variable model of multiple discrete choice," Quantitative Economics, Econometric Society, vol. 4(2), pages 157-196, July.
    6. Lixiong Li & Marc Henry, 2022. "Finite Sample Inference in Incomplete Models," Papers 2204.00473, arXiv.org, revised Apr 2024.
    7. Marc Henry & Ismael Mourifié, 2013. "Set inference in latent variables models," Econometrics Journal, Royal Economic Society, vol. 16(1), pages 93-105, February.
    8. V. Chernozhukov & C. Hansen, 2013. "Quantile Models with Endogeneity," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 57-81, May.
    9. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
    10. Victor H Aguiar & Nail Kashaev, 2021. "Stochastic Revealed Preferences with Measurement Error [Consistency between Household-level Consumption Data from Registers and Surveys]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 2042-2093.
    11. Thomas Demuynck & Tom Potoms, 2022. "Testing revealed preference models with unobserved randomness: a column generation approach," Working Papers ECARES 2022-42, ULB -- Universite Libre de Bruxelles.
    12. Victor Chernozhukov & Pierre-André Chiappori & Marc Henry, 2010. "Introduction," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 42(2), pages 271-273, February.
    13. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.
    14. Timothy Christensen & Benjamin Connault, 2023. "Counterfactual Sensitivity and Robustness," Econometrica, Econometric Society, vol. 91(1), pages 263-298, January.

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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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