Effciency Gain of System GMM and MDE over Individual Equation Estimation

Publication Type

Journal Article

Publication Date

2004

Abstract

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]

Discipline

Econometrics

Research Areas

Econometrics

Publication

Japanese Economic Review

Volume

55

Issue

4

First Page

451

Last Page

459

ISSN

1352-4739

Identifier

10.1111/j.1468-5876.2004.00312.x

Publisher

Wiley

Additional URL

https://doi.org/10.1111/j.1468-5876.2004.00312.x

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