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Exponential class of dynamic binary choice panel data models with fixed effects

Author

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  • Majid M. Al-Sadoon
  • Tong Li
  • M. Hashem Pesaran

Abstract

This paper proposes an exponential class of dynamic binary choice panel data models for the analysis of short T (time dimension) large N (cross section dimension) panel data sets that allow for unobserved heterogeneity (fixed effects) to be arbitrarily correlated with the covariates. The paper derives moment conditions that are invariant to the fixed effects which are then used to identify and estimate the parameters of the model. Accordingly, generalized method of moments (GMM) estimators are proposed that are consistent and asymptotically normally distributed at the root-N rate. We also study the conditional likelihood approach and show that under exponential specification, it can identify the effect of state dependence but not the effects of other covariates. Monte Carlo experiments show satisfactory finite sample performance for the proposed estimators and investigate their robustness to misspecification.

Suggested Citation

  • Majid M. Al-Sadoon & Tong Li & M. Hashem Pesaran, 2017. "Exponential class of dynamic binary choice panel data models with fixed effects," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 898-927, October.
    • Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:898-927
    DOI: 10.1080/07474938.2017.1307597
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    Cited by:

    1. Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 471-496, September.
    2. Kitazawa, Yoshitsugu, 2022. "Transformations and moment conditions for dynamic fixed effects logit models," Journal of Econometrics, Elsevier, vol. 229(2), pages 350-362.
    3. Miranda, Alfonso & Trivedi, Pravin K., 2020. "Econometric Models of Fertility," GLO Discussion Paper Series 574, Global Labor Organization (GLO).
    4. St'ephane Bonhomme & Kevin Dano & Bryan S. Graham, 2023. "Identification in a Binary Choice Panel Data Model with a Predetermined Covariate," Papers 2301.05733, arXiv.org, revised Jul 2023.
    5. Bo E. Honoré & Martin Weidner, 2021. "Moment Conditions for Dynamic Panel Logit Models with Fixed Effects," Working Papers 2021-79, Princeton University. Economics Department..
    6. Bo E. Honoré & Martin Weidner, 2020. "Moment Conditions for Dynamic Panel Logit Models with Fixed Effects," CeMMAP working papers CWP38/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Stéphane Bonhomme & Kevin Dano & Bryan S. Graham, 2023. "Identification in a binary choice panel data model with a predetermined covariate," CeMMAP working papers 17/23, Institute for Fiscal Studies.
    8. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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