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Identification With Additively Separable Heterogeneity

Author

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  • Roy Allen
  • John Rehbeck

Abstract

This paper provides nonparametric identification results for a class of latent utility models with additively separable unobservable heterogeneity. These results apply to existing models of discrete choice, bundles, decisions under uncertainty, and matching. Under an independence assumption, such models admit a representative agent. As a result, we can identify how regressors alter the desirability of goods using only average demands. Moreover, average indirect utility (“welfare”) is identified without needing to specify or identify the distribution of unobservable heterogeneity.

Suggested Citation

  • Roy Allen & John Rehbeck, 2019. "Identification With Additively Separable Heterogeneity," Econometrica, Econometric Society, vol. 87(3), pages 1021-1054, May.
    • Handle: RePEc:wly:emetrp:v:87:y:2019:i:3:p:1021-1054
    DOI: 10.3982/ECTA15867
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    Citations

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    Cited by:

    1. Victor Aguirregabiria, 2021. "Identification of firms’ beliefs in structural models of market competition," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 5-33, February.
    2. Gu, Jiaying & Russell, Thomas M., 2023. "Partial identification in nonseparable binary response models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 235(2), pages 528-562.
    3. Mattsson, Lars-Göran & Weibull, Jörgen W., 2023. "An analytically solvable principal-agent model," Games and Economic Behavior, Elsevier, vol. 140(C), pages 33-49.
    4. Steven T. Berry & Philip A. Haile, 2020. "Nonparametric Identification of Differentiated Products Demand Using Micro Data," NBER Working Papers 27704, National Bureau of Economic Research, Inc.
    5. Mogens Fosgerau & Dennis Kristensen, 2021. "Identification of a class of index models: A topological approach," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 121-133.
    6. Nikhil Agarwal & Paulo J. Somaini, 2022. "Demand Analysis under Latent Choice Constraints," NBER Working Papers 29993, National Bureau of Economic Research, Inc.
    7. Martin Bustos, 2024. "Identification with Posterior-Separable Information Costs," Papers 2402.09789, arXiv.org.
    8. Mogens Fosgerau & Miroslawa Lukawska & Mads Paulsen & Thomas Kj{ae}r Rasmussen, 2022. "Bikeability and the induced demand for cycling," Papers 2210.02504, arXiv.org, revised Dec 2022.
    9. Roy Allen & John Rehbeck, 2021. "A Generalization of Quantal Response Equilibrium via Perturbed Utility," Games, MDPI, vol. 12(1), pages 1-16, March.
    10. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Discrete Choice Models for Bundles," Discussion Papers Series 625, School of Economics, University of Queensland, Australia.
    11. Paul Feldman & John Rehbeck, 2022. "Revealing a preference for mixtures: An experimental study of risk," Quantitative Economics, Econometric Society, vol. 13(2), pages 761-786, May.
    12. Aguiar, Victor H. & Kashaev, Nail & Allen, Roy, 2023. "Prices, profits, proxies, and production," Journal of Econometrics, Elsevier, vol. 235(2), pages 666-693.
    13. Alessandro Iaria, & Wang, Ao, 2021. "An Empirical Model of Quantity Discounts with Large Choice Sets," The Warwick Economics Research Paper Series (TWERPS) 1378, University of Warwick, Department of Economics.
    14. Mogens Fosgerau & Mads Paulsen & Thomas Kj{ae}r Rasmussen, 2021. "A perturbed utility route choice model," Papers 2103.13784, arXiv.org, revised Sep 2021.
    15. Wang, Ao, 2023. "Sieve BLP: A semi-nonparametric model of demand for differentiated products," Journal of Econometrics, Elsevier, vol. 235(2), pages 325-351.
    16. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," CRETA Online Discussion Paper Series 84, Centre for Research in Economic Theory and its Applications CRETA.
    17. Zhenzhen Yan & Karthik Natarajan & Chung Piaw Teo & Cong Cheng, 2022. "A Representative Consumer Model in Data-Driven Multiproduct Pricing Optimization," Management Science, INFORMS, vol. 68(8), pages 5798-5827, August.
    18. Sørensen, Jesper R.-V. & Fosgerau, Mogens, 2022. "How McFadden met Rockafellar and learned to do more with less," Journal of Mathematical Economics, Elsevier, vol. 100(C).
    19. Takeshi Fukasawa, 2022. "The Biases in Applying Static Demand Models under Dynamic Demand," Discussion Paper Series DP2022-18, Research Institute for Economics & Business Administration, Kobe University, revised Jul 2022.
    20. Wang, Ao, 2020. "Identifying the Distribution of Random Coefficients in BLP Demand Models Using One Single Variation in Product Characteristics," The Warwick Economics Research Paper Series (TWERPS) 1304, University of Warwick, Department of Economics.
    21. Fu Ouyang & Thomas T. Yang, 2023. "Semiparametric Discrete Choice Models for Bundles," Papers 2306.04135, arXiv.org, revised Nov 2023.
    22. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.
    23. Iaria, Alessandro & ,, 2020. "Identification and Estimation of Demand for Bundles," CEPR Discussion Papers 14363, C.E.P.R. Discussion Papers.
    24. Iaria, Alessandro & Wang, Ao, 2021. "A note on stochastic complementarity for the applied researcher," Economics Letters, Elsevier, vol. 199(C).
    25. Allen, Roy & Rehbeck, John, 2022. "Latent complementarity in bundles models," Journal of Econometrics, Elsevier, vol. 228(2), pages 322-341.

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