Improving GMM efficiency in dynamic models for panel data with mean stationarity

Giorgio Calzolari and Laura Magazzini

No 12/2014, Working Papers from University of Verona, Department of Economics

Abstract: Within the framework of dynamic panel data models with mean stationarity, one additional moment condition may remarkably increase the efficiency of the system GMM estimator. This additional condition is essentially a condition of “homoskesdasticity” of the individual effects; it is “implicitly satisfied” in all the Monte Carlo simulations on dynamic panel data models available in the literature (including the experiments with heteroskedasticity, which is always confined to the idiosyncratic errors), but not “explicitly” exploited. Monte Carlo experiments show remarkable efficiency improvements when the distribution of individual effects, and thus of yi0, are skewed, thus including the very important cases in economic applications that include variables like individual wages, sizes of the firms, number of employees, etc.

Keywords: panel data; dynamic model; GMM estimation; mean stationarity; skewed individual effects (search for similar items in EconPapers)
JEL-codes: C13 C23 (search for similar items in EconPapers)
Date: 2014-07
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (1)

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