On the effect of mean-nonstationarity in dynamic panel data models
AbstractIn this paper, we investigate the effect of mean-nonstationarity on the first-difference generalized method of moments (FD-GMM) estimator in dynamic panel data models. We find that when data is mean-nonstationary and the variance of individual effects is significantly larger than that of disturbances, the FD-GMM estimator performs quite well. We demonstrate that this is because the correlation between the lagged dependent variable and instruments gets larger owing to the unremoved individual effects, i.e.,Â instruments become strong. This implies that, under mean-nonstationarity, the FD-GMM estimator does not always suffer from the weak instruments problem even when data is persistent.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 153 (2009)
Issue (Month): 2 (December)
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Web page: http://www.elsevier.com/locate/jeconom
Dynamic panel data models Strength of instruments Generalized method of moments estimator Mean-nonstationarity;
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