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Identi?cation and estimation of dynamic structural models with unobserved choices

Author

Listed:
  • Yingyao Hu

    (Institute for Fiscal Studies and Johns Hopkins University)

  • Yi Xin

    (Institute for Fiscal Studies)

Abstract
This paper develops identi?cation and estimation methods for dynamic structural models when agents’ actions are unobserved by econometricians. We provide conditions under which choice probabilities and latent state transition rules are nonparametrically identi?ed with a continuous state variable in a single-agent dynamic discrete choice model. Our identi?cation results extend to (1) models with serially correlated unobserved heterogeneity and continuous choices, (2) cases in which only discrete state variables are available, and (3) dynamic discrete games. We apply our method to study moral hazard problems in US gubernatorial elections. We ?nd that the probabilities of shirking increase as the governors approach the end of their terms.

Suggested Citation

  • Yingyao Hu & Yi Xin, 2019. "Identi?cation and estimation of dynamic structural models with unobserved choices," CeMMAP working papers CWP35/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:35/19
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    File URL: https://www.ifs.org.uk/uploads/CW3519_Identification_and_Estimation_of_Dynamic_Structural_Models_with_Unobserved_Choices.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. Doug J. Chung & Byungyeon Kim & Byoung G. Park, 2021. "The Comprehensive Effects of Sales Force Management: A Dynamic Structural Analysis of Selection, Compensation, and Training," Management Science, INFORMS, vol. 67(11), pages 7046-7074, November.

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