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Identification analysis in models with unrestricted latent variables: Fixed effects and initial conditions

Author

Listed:
  • Andrew Chesher

    (Institute for Fiscal Studies)

  • Adam Rosen

    (Institute for Fiscal Studies)

  • Yuanqi Zhang

    (University College London)

Abstract
Many structural econometric models include latent variables on whose probability distributions one may wish to place minimal restrictions. Leading examples in panel data models are individual-specific variables sometimes treated as “fixed effects” and, in dynamic models, initial conditions. This paper presents a generally applicable method for characterizing sharp identified sets when models place no restrictions on the probability distribution of certain latent variables and no restrictions on their covariation with other variables. Endogenous explanatory variables can be easily accommodated. Examples of application to some static and dynamic binary, ordered and multiple discrete choice panel data models are presented.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Andrew Chesher & Adam Rosen & Yuanqi Zhang, 2023. "Identification analysis in models with unrestricted latent variables: Fixed effects and initial conditions," IFS Working Papers WCWP20/23, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:ifsewp:cwp20/23
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    File URL: https://ifs-staging2.sbx.so/sites/default/files/2023-10/CWP2023-Identification-analysis-in-models-with-unrestricted-latent-variables-fixed-effects-and-initial-conditions.pdf
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    References listed on IDEAS

    as
    1. Ariel Pakes & Jack R. Porter & Mark Shepard & Sophie Calder-Wang, 2021. "Unobserved Heterogeneity, State Dependence, and Health Plan Choices," NBER Working Papers 29025, National Bureau of Economic Research, Inc.
    2. 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.
    3. Aristodemou, Eleni, 2021. "Semiparametric identification in panel data discrete response models," Journal of Econometrics, Elsevier, vol. 220(2), pages 253-271.
    4. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    5. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
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    Cited by:

    1. Wayne Yuan Gao & Rui Wang, 2023. "Identification of Nonlinear Dynamic Panels under Partial Stationarity," Papers 2401.00264, arXiv.org, revised May 2024.

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