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A bias-corrected fixed effects estimator in the dynamic panel data model

Author

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  • Chihwa Kao

    (University of Connecticut)

  • Long Liu

    (Florida Atlantic University)

  • Rui Sun

    (University of Connecticut)

Abstract

In this paper, we propose a biased-corrected FE estimator for the dynamic panel data model that works for the autoregressive coefficient $$\rho \in (-1,1]$$ ρ ∈ ( - 1 , 1 ] . We further derive the asymptotic result of the suggested bias-corrected FE estimator. We show that when $$\rho =1$$ ρ = 1 , the suggested estimator is super-consistent and is more efficient than the existing estimators that also work for $$\rho \in (-1,1]$$ ρ ∈ ( - 1 , 1 ] . In addition, when the initial condition is nonstationary, many of the existing dynamic estimators become inconsistent; however, the consistency of the bias-corrected FE estimator we propose does not depend on the stationarity of the initial condition. We also compare the finite sample performances of these estimators using Monte Carlo simulations.

Suggested Citation

  • Chihwa Kao & Long Liu & Rui Sun, 2021. "A bias-corrected fixed effects estimator in the dynamic panel data model," Empirical Economics, Springer, vol. 60(1), pages 205-225, January.
    • Handle: RePEc:spr:empeco:v:60:y:2021:i:1:d:10.1007_s00181-020-01995-0
    DOI: 10.1007/s00181-020-01995-0
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    2. Qi Li & Vasilis Sarafidis & Joakim Westerlund, 2021. "Essays in honor of Professor Badi H Baltagi," Empirical Economics, Springer, vol. 60(1), pages 1-11, January.
    3. Li, Qi & Sarafidis, Vasilis & Westerlund, Joakim, 2020. "Essays in Honor of Professor Badi H Baltagi: Editorial," MPRA Paper 104751, University Library of Munich, Germany.

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