Effciency Gain of System GMM and MDE over Individual Equation Estimation
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?2) estimation (MDE).JEL Classification Number: C30. [ABSTRACT FROM AUTHOR]
Japanese Economic Review
Effciency Gain of System GMM and MDE over Individual Equation Estimation. (2004). Japanese Economic Review. 55, (4), 451-459. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/490
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