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Estimating dynamic panel models: backing out the Nickell Bias

Author

Listed:
  • Jerry Hausman

    (Institute for Fiscal Studies and MIT)

  • Maxim L. Pinkovskiy

    (Institute for Fiscal Studies)

Abstract

We propose a new estimator for the dynamic panel model, which solves the failure of strict exogeneity by calculating the bias in the first-order conditions as a function of the autoregressive parameter and solving the resulting equation. The estimator does well in a wide variety of situations where other estimators do not perform well: stationary initial condition, predetermined but not strictly exogenous regressors, and the presence of correlation between the error terms and the fixed effects. We also propose a general method for including predetermined variables infixed-effects panel regressions.

Suggested Citation

  • Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers CWP53/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:53/17
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    References listed on IDEAS

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    1. James H. Stock & Mark W. Watson, 2008. "Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression," Econometrica, Econometric Society, vol. 76(1), pages 155-174, January.
    2. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    3. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    4. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    5. Jushan Bai, 2013. "Fixed‐Effects Dynamic Panel Models, a Factor Analytical Method," Econometrica, Econometric Society, vol. 81(1), pages 285-314, January.
    6. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    7. Hahn, Jinyong, 1999. "How informative is the initial condition in the dynamic panel model with fixed effects?," Journal of Econometrics, Elsevier, vol. 93(2), pages 309-326, December.
    8. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    9. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
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    Cited by:

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    2. Atif Ellahie & Xiaoxia Peng, 2021. "Management forecasts of volatility," Review of Accounting Studies, Springer, vol. 26(2), pages 620-655, June.

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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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