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Asymptotic properties of estimators for the linear panel regression model with random individual effects and serially correlated errors: the case of stationary and non-stationary regressors and residuals

Author

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  • Badi H. Baltagi
  • Chihwa Kao
  • Long Liu

Abstract

This paper studies the asymptotic properties of standard panel data estimators in a simple panel regression model with random error component disturbances. Both the regressor and the remainder disturbance term are assumed to be autoregressive and possibly non-stationary. Asymptotic distributions are derived for the standard panel data estimators including ordinary least squares (OLS), fixed effects (FE), first-difference (FD) and generalized least squares (GLS) estimators when both T and n are large. We show that all the estimators have asymptotic normal distributions and have different convergence rates dependent on the non-stationarity of the regressors and the remainder disturbances. We show using Monte Carlo experiments that the loss in efficiency of the OLS, FE and FD estimators relative to true GLS can be substantial. Copyright The Author(s). Journal compilation Royal Economic Society 2008

Suggested Citation

  • Badi H. Baltagi & Chihwa Kao & Long Liu, 2008. "Asymptotic properties of estimators for the linear panel regression model with random individual effects and serially correlated errors: the case of stationary and non-stationary regressors and residu," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 554-572, November.
    • Handle: RePEc:ect:emjrnl:v:11:y:2008:i:3:p:554-572
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    Cited by:

    1. Badi Baltagi & Chihwa Kao & Sanggon Na, 2011. "Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 329-350, December.
    2. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    3. Trapani, Lorenzo, 2021. "Inferential theory for heterogeneity and cointegration in large panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 474-503.
    4. Todd Gabe & Andrew Crawley, 2021. "Effects of the COVID-related stay-at-home order on hospitality sales and automobile traffic counts: evidence from the State of Maine, USA," Economics and Business Letters, Oviedo University Press, vol. 10(4), pages 336-341.
    5. Badi H. Baltagi & Chihwa Kao & Long Liu, 2017. "Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 85-102, March.
    6. Badi H. Baltagi & Chihwa Kao & Long Liu, 2014. "Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 347-394, Emerald Group Publishing Limited.
    7. Raffaela Giordano & Marcello Pericoli & Pietro Tommasino, 2013. "Pure or Wake-up-Call Contagion? Another Look at the EMU Sovereign Debt Crisis," International Finance, Wiley Blackwell, vol. 16(2), pages 131-160, June.
    8. Badi H. Baltagi & Chihwa Kao & Long Liu, 2013. "The Estimation and Testing of a Linear Regression with Near Unit Root in the Spatial Autoregressive Error Term," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 241-270, September.
    9. 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.
    10. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Testing for Breaks in Cointegrated Panels," Center for Policy Research Working Papers 135, Center for Policy Research, Maxwell School, Syracuse University.
    11. Trapani, Lorenzo, 2012. "On the asymptotic t-test for large nonstationary panel models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3286-3306.
    12. Xiaowen Dai & Shidan Huang & Libin Jin & Maozai Tian, 2023. "Wild Bootstrap-Based Bias Correction for Spatial Quantile Panel Data Models with Varying Coefficients," Mathematics, MDPI, vol. 11(9), pages 1-16, April.

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