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GMM Estimation of Empirical Growth Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Stephen Bond (Nuffield College and Institute for Fiscal Studies )
Anke Hoeffler (St Antony's College and Centre for the Study of African Economics)
Jonathan Temple () (Department of Economics, University of Bristol)
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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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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number
2001-W21.
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Length: 35 pages
Date of creation: 12 Sep 2001Date of revision:
Handle: RePEc:nuf:econwp:0121Contact details of provider: Web page: http://www.nuff.ox.ac.uk/economics/
For technical questions regarding this item, or to correct its listing, contact: (Catherine McNeill).
Keywords: convergence growth generalised method of moments weak instruments. Other versions of this item:
Find related papers by JEL classification: O41 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
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