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Using Backward Means to Eliminate Individual Effects from Dynamic Panels

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  • G. EVERAERT

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Abstract

The within-groups estimator is inconsistent in dynamic panels with fixed T since the sample mean used to eliminate the individual effects from the lagged dependent variable is correlated with the error term. This paper suggests to eliminate individual effects from an AR(1) panel using backward means as an alternative to sample means. Using orthogonal deviations of the lagged dependent variable from its backward mean yields an estimator that is still inconsistent for fixed T but the inconsistency is shown to be negligibly small. A Monte Carlo simulation shows that this alternative estimator has superior small sample properties compared to conventional fixed effects, bias-corrected fixed effects and GMM estimators. Interestingly, it is also consistent for fixed T in the specific cases where (i) T = 2, (ii) the AR parameter is 0 or 1, (iii) the variance of the individual effects is zero.

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Bibliographic Info

Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 09/553.

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Length: 23 pages
Date of creation: Jan 2009
Date of revision:
Handle: RePEc:rug:rugwps:09/553

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Related research

Keywords: Dynamic panel; Individual effects; Backward mean; Orthogonal deviations; Monte Carlo simulation;

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  1. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  2. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
  3. 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.
  4. Maurice Bun, 2003. "Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 29-58.
  5. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  6. Bun,M.J.G. & Carree,M.A., 2002. "Bias-corrected estimation in dynamic panel data models," Research Memorandum 025, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  7. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  8. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
  9. Everaert, Gerdie & Pozzi, Lorenzo, 2007. "Bootstrap-based bias correction for dynamic panels," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1160-1184, April.
  10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  11. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, 07.
  12. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
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