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The tests for the level moment conditions: GMM estimation in a linear dynamic panel data model

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  • Takuya Hasebe

    (Graduate Center, City University of New York)

Abstract

This paper compares the power of alternative tests for the level moment conditions in GMM estimation of a linear dynamic panel data model. The test statistic calculated conventionally can take on a negative value in finite samples even though it cannot be asymptotically. A straightforward modification makes the test statistic nonnegative. Monte Carlo simulations show that the test can gain power from the modification.

Suggested Citation

  • Takuya Hasebe, 2012. "The tests for the level moment conditions: GMM estimation in a linear dynamic panel data model," Economics Bulletin, AccessEcon, vol. 32(1), pages 412-420.
    • Handle: RePEc:ebl:ecbull:eb-11-00706
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    References listed on IDEAS

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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. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
    3. Matz Dahlberg & Eva Mork & Per Tovmo, 2008. "Power properties of the Sargan test in the presence of measurement errors in dynamic panels," Applied Economics Letters, Taylor & Francis Journals, vol. 15(5), pages 349-353.
    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. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    6. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    7. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    8. Hayakawa, Kazuhiko, 2009. "On the effect of mean-nonstationarity in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 153(2), pages 133-135, December.
    9. 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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    More about this item

    Keywords

    GMM; Dynamic panel data; Overidentifying restrictions test;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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