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Reducing Bias of MLE in a Dynamic Panel Model


  • Jinyong Hahn
  • Hyungsik Roger Moon


This paper investigates a simple dynamic linear panel regression model with both fixed effects and time effects. Using “large n and large T”asymptotics, we approximate the distribution of the fixed effect estimator of the autoregressive parameter in the dynamic linear panel model and derive its asymptotic bias. We find that the same higher order bias correction approach proposed by Hahn and Kuersteiner (2002) can be applied to the dynamic linear panel model even when time specific effects are present.

Suggested Citation

  • Jinyong Hahn & Hyungsik Roger Moon, 2005. "Reducing Bias of MLE in a Dynamic Panel Model," IEPR Working Papers 05.36, Institute of Economic Policy Research (IEPR).
  • Handle: RePEc:scp:wpaper:05-36

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    References listed on IDEAS

    1. Nerlove,Marc, 2005. "Essays in Panel Data Econometrics," Cambridge Books, Cambridge University Press, number 9780521022460, March.
    2. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, number 9780199267699.
    3. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
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    Cited by:

    1. Fernández-Val, Iván & Weidner, Martin, 2016. "Individual and time effects in nonlinear panel models with large N, T," Journal of Econometrics, Elsevier, vol. 192(1), pages 291-312.
    2. Chudik, Alexander & Pesaran, M. Hashem & Yang, Jui-Chung, 2016. "Half-panel jackknife fixed effects estimation of panels with weakly exogenous regressor," Globalization and Monetary Policy Institute Working Paper 281, Federal Reserve Bank of Dallas.
    3. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    4. Chudik, Alexander & Pesaran, M. Hashem, 2017. "A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels," Globalization and Monetary Policy Institute Working Paper 327, Federal Reserve Bank of Dallas.
    5. Moon, Hyungsik Roger & Weidner, Martin, 2017. "Dynamic Linear Panel Regression Models With Interactive Fixed Effects," Econometric Theory, Cambridge University Press, vol. 33(01), pages 158-195, February.
    6. Dhaene, Geert & Jochmans, Koen, 2016. "Bias-corrected estimation of panel vector autoregressions," Economics Letters, Elsevier, vol. 145(C), pages 98-103.
    7. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    8. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    9. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
    10. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    11. Okui, Ryo, 2011. "Asymptotically unbiased estimation of autocovariances and autocorrelations for panel data with incidental trends," Economics Letters, Elsevier, vol. 112(1), pages 49-52, July.
    12. Badi H. Baltagi, 2013. "Dynamic panel data models," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 10, pages 229-248 Edward Elgar Publishing.

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