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GMM Estimation of Empirical Growth Models

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  • Stephen Bond
  • Anke Hoeffler
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    Abstract

    This paper highlights a problem in using the first-differenced GMM panel data estimator to estimate cross-country growth regressions. When the time series are persistent, the first-differenced GMM estimator can be poorly behaved, since lagged levels of the series provide only weak instruments for subsequent first-differences. Revisiting the work of Caselli, Esquivel and Lefort (1996), we show that this problem may be serious in practice. We suggest using a more efficient GMM estimator that exploits stationarity restrictions, and this approach is shown to give more reasonable results than first-differenced GMM in our estimation of an empirical growth model.

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    File URL: http://www.nuff.ox.ac.uk/economics/papers/2001/w21/bht10.pdf
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    Bibliographic Info

    Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 2001-W21.

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    Date of creation: 01 Sep 2001
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    Handle: RePEc:oxf:wpaper:2001-w21

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    Related research

    Keywords: convergence; growth; generalized method of moments; weak instruments;

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    1. Alonso-Borrego, Cesar & Arellano, Manuel, 1999. "Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 36-49, January.
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