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The optimal choice of moments in dynamic panel data models

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  • Okui, Ryo
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Abstract

This paper derives an approximation of the mean square error (MSE) of the GMM estimator in dynamic panel data models. The approximation is based on higher-order asymptotic theory under double asymptotics. While first-order theory under double asymptotics provides information about the bias, it does not provide enough information about the variance of the estimator. Higher-order theory enables us to obtain information about the variance. From this result, a procedure for choosing the number of instruments is proposed. The simulations confirm that the proposed procedure improves the precision of the estimator.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 151 (2009)
Issue (Month): 1 (July)
Pages: 1-16

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Handle: RePEc:eee:econom:v:151:y:2009:i:1:p:1-16

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: GMM Dynamic panel data model Higher-order expansion Moment selection;

References

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Citations

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Cited by:
  1. Mariangela Bonasia, 2012. "Twenty years of internal migration in Italy. Answers from some economic and non-economic determinants," Discussion Papers, CRISEI, University of Naples "Parthenope", Italy 6_2012, CRISEI, University of Naples "Parthenope", Italy.
  2. Kazuhiko Hayakawa, 2008. "On the Effect of Nonstationary Initial Conditions in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series, Institute of Economic Research, Hitotsubashi University d07-245, Institute of Economic Research, Hitotsubashi University.
  3. Lee, Nayoung & Moon, Hyungsik Roger & Weidner, Martin, 2012. "Analysis of interactive fixed effects dynamic linear panel regression with measurement error," Economics Letters, Elsevier, vol. 117(1), pages 239-242.
  4. Ziesemer, Thomas, 2012. "The impact of development aid on education and health: Survey and new evidence from dynamic models," MERIT Working Papers 057, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  5. Salima Bouayad-Agha & Nadine Turpin & Lionel Védrine, 2010. "Fostering the potential endogenous development of European regions: a spatial dynamic panel data analysis of the Cohesion Policy on regional convergence over the period 1980-2005," TEPP Working Paper, TEPP 2010-17, TEPP.
  6. Ivan Savin & Peter Winker, 2010. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection. Application on the Russian Innovative Performance," Working Papers, COMISEF 027, COMISEF.
  7. Magnac, Thierry & Pistolesi, Nicolas & Roux, Sébastien, 2013. "Post Schooling Human Capital Investments and the Life Cycle Variance of Earnings," IZA Discussion Papers 7407, Institute for the Study of Labor (IZA).
  8. Bohdan Yu. Kyshakevych & Anatoliy K. Prykarpatsky & Denis Blackmore & Ivan P. Tverdokhlib, 2010. "Statistically Optimal Strategy Analysis of a Competing Portfolio Market with a Polyvariant Profit Function," Papers 1005.2661, arXiv.org.
  9. Reinhard Hujer & Paulo J.M. Rodrigues & Katja Wolf, 2008. "Dynamic Panel Data Models with Spatial Correlation," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 228(5+6), pages 612-629, December.
  10. Miyazaki, Tomomi, 2013. "Fiscal Policy and Regional Business Cycle Fluctuations in Japan," Discussion Paper Series, Institute of Economic Research, Hitotsubashi University 583, Institute of Economic Research, Hitotsubashi University.

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