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GMM Estimation of Empirical Growth Models

Опубликовано на портале: 27-10-2004
CEPR Discussion Papers. 2001.  No. 3048.
This paper highlights a problem in using the first-difference GMM panel data estimator 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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