Efficiency Gains by Modifying GMM Estimation in Linear Models under Heteroskedasticity

Jan Kiviet and Qu Feng

No 14-06, UvA-Econometrics Working Papers from Universiteit van Amsterdam, Dept. of Econometrics

Abstract: While coping with nonsphericality of the disturbances, standard GMM suffers from a blind spot for exploiting the most effective instruments when these are obtained directly from unconditional rather than conditional moment assumptions. For instance, standard GMM counteracts that exogenous regressors are used as their own optimal instruments. This is easily seen after transmuting GMM for linear models into IV in terms of transformed variables. It is demonstrated that modified GMM (MGMM), exploiting straight-forward modifications of the instruments, can achieve substantial efficiency gains and bias reductions, even under mild heteroskedasticity. Feasible MGMM implementations and their standard error estimates are examined and compared with standard GMM and IV for a range of typical models for cross-section data, both by simulation and by empirical illustration.

Date: 2014-11-10
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://ase.uva.nl/binaries/content/assets/subsites ... ics/dp-2014/1406.pdf (application/pdf)

Related works:
Working Paper: Efficiency Gains by Modifying GMM Estimation in Linear Models under Heteroskedasticity (2014)
Working Paper: Efficiency Gains by Modifying GMM Estimation in Linear Models under Heteroskedasticity (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ame:wpaper:1406

Access Statistics for this paper

More papers in UvA-Econometrics Working Papers from Universiteit van Amsterdam, Dept. of Econometrics Dept. of Econometrics, Universiteit van Amsterdam, Valckenierstraat 65, NL - 1018 XE Amsterdam, The Netherlands. Contact information at EDIRC.
Bibliographic data for series maintained by Noud P.A. van Giersbergen (n.p.a.vangiersbergen@uva.nl).