Efficiency gains of system GMM and MDE over individual equation estimation

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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 X2) estimation (MDE).

Original languageEnglish
Pages (from-to)451-459
Number of pages9
JournalJapanese Economic Review
Issue number4
Publication statusPublished - 2004 Dec
Externally publishedYes


ASJC Scopus subject areas

  • Economics and Econometrics

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