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Efficiency comparisons for a system GMM estimator in dynamic panel data models

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  • Frank Windmeijer

    (Institute for Fiscal Studies and University of Bristol)

Abstract

The system GMM estimator in dynamic panel data models combines moment conditions for hte differenced equation with moment conditions for the model in levels. An initial optimal weight matrix under homoscedasticity and non-serial correlation is not known for this estimation procedure. It is common practice to use the inverse of the moment matrix of the instruments as the initial weight matrix. This paper assesses the potential efficiency loss from the use of this weight matrix using the efficiency bounds as derived by Liu and Neudecker (1997).

Suggested Citation

  • Frank Windmeijer, 1998. "Efficiency comparisons for a system GMM estimator in dynamic panel data models," IFS Working Papers W98/01, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:ifsewp:98/01
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    File URL: http://www.ifs.org.uk/wps/wp9801.pdf
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. 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.
    3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    4. 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.
    5. S. Liu & H. Neudecker, 1997. "Kantorovich inequalities and efficiency comparisons for several classes of estimators in linear models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 51(3), pages 345-355, November.
    6. 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.
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    Cited by:

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    3. Martin Andersson & Hans Lööf, 2011. "Agglomeration and productivity: evidence from firm-level data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(3), pages 601-620, June.
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    5. Angelica Gonzalez, 2007. "Angelica Gonzalez," Edinburgh School of Economics Discussion Paper Series 168, Edinburgh School of Economics, University of Edinburgh.
    6. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    7. Duguleană, Constantin & Duguleană, Liliana & Deszke, Klára-Dalma, 2024. "Financial performance and capital structure – an econometric approach for Romanian e-commerce companies during the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 786-812.

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