EFFICIENCY GAINS OF SYSTEM GMM AND MDE OVER INDIVIDUAL EQUATION ESTIMATION*
The Japanese Economic Review, 2004, vol. 55, issue 4, 451-459
In the econometric literature it is known that, under certain conditions, estimating a system of equations together is more efficient than estimating each equation separately. This finding has been proved, however, only under the assumption of a known parametric form of heteroskedasticity (including homoskedasticity) or non‐random regressors/instruments. This note shows that an analogous finding holds for GMM under heteroskedasticity of unknown form and random regressors/instruments. Specifically, I provide a necessary condition for the efficiency gain of the system GMM over the single‐equation GMM. An analogous necessary condition for the efficiency gain is also shown to hold for minimum‐distance (or χ2) estimation (MDE).
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