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GMM Estimation of Empirical Growth Models

  • Bond, Stephen Roy
  • Hoeffler, Anke
  • Temple, Jonathan

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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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 3048.

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Date of creation: Nov 2001
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Handle: RePEc:cpr:ceprdp:3048
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