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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).

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File URL: http://www.ifs.org.uk/wps/wp9801.pdf
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Bibliographic Info

Paper provided by Institute for Fiscal Studies in its series IFS Working Papers with number W98/01.

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Length: 12 pp.
Date of creation: Oct 1998
Date of revision:
Handle: RePEc:ifs:ifsewp:98/01

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  1. 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.
  2. 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.
  3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  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.
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Cited by:
  1. Gasmi, Farid & Noumba Um, Paul & Virto, Laura Recuero, 2006. "Political accountability and regulatory performance in infrastructure industries : an empirical analysis," Policy Research Working Paper Series 4101, The World Bank.
  2. Andersson, Martin & Lööf, Hans, 2009. "Agglomeration and Productivity - evidence from firm-level data," Working Paper Series in Economics and Institutions of Innovation 170, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
  3. Derek Jones & Panu Kalmi & Mikko Mäkinen, 2010. "The productivity effects of stock option schemes: evidence from Finnish panel data," Journal of Productivity Analysis, Springer, vol. 33(1), pages 67-80, February.
  4. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
  5. Angelica Gonzalez, 2007. "Empirical Likelihood Estimation in Dynamic Panel Models," ESE Discussion Papers 168, Edinburgh School of Economics, University of Edinburgh.
  6. Lalanne, Marie & Seabright, Paul, 2011. "The Old Boy Network: Gender Differences in the Impact of Social Networks on Remuneration in Top Executive Jobs," CEPR Discussion Papers 8623, C.E.P.R. Discussion Papers.

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