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Estimating Dynamic Binary Panel Data Model with Random Effects: A Computational Note

Author

Listed:
  • Gang Yu

    (Dongbei University of Finance and Economics)

  • Wei Gao

    (Northeast Normal University)

  • Weiguo Wang

    (Dongbei University of Finance and Economics)

  • Shaoping Wang

    (Huazhong University of Science and Technology)

Abstract

Recently, Gao et al. (J Time Ser Anal, 2016 doi: 10.1111/jtsa.12178 ) propose a new estimation method for dynamic panel probit model with random effects, where the theoretical properties of estimator are derived. In this paper, we extend their estimation method to the $$T\ge 3$$ T ≥ 3 case, and some Monte Carlo simulations are presented to illustrate the extended estimator.

Suggested Citation

  • Gang Yu & Wei Gao & Weiguo Wang & Shaoping Wang, 2018. "Estimating Dynamic Binary Panel Data Model with Random Effects: A Computational Note," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 535-539, March.
    • Handle: RePEc:kap:compec:v:51:y:2018:i:3:d:10.1007_s10614-016-9620-1
    DOI: 10.1007/s10614-016-9620-1
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    References listed on IDEAS

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    1. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
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    3. Arellano, Manuel & Carrasco, Raquel, 2003. "Binary choice panel data models with predetermined variables," Journal of Econometrics, Elsevier, vol. 115(1), pages 125-157, July.
    4. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    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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