Stochastic Generalized Method of Moments

Type
Article

Authors
Yin, Guosheng
Ma, Yanyuan
Liang, Faming
Yuan, Ying

KAUST Grant Number
KUS-C1-016-04

Online Publication Date
2011-08-16

Print Publication Date
2011-01

Date
2011-08-16

Abstract
The generalized method of moments (GMM) is a very popular estimation and inference procedure based on moment conditions. When likelihood-based methods are difficult to implement, one can often derive various moment conditions and construct the GMM objective function. However, minimization of the objective function in the GMM may be challenging, especially over a large parameter space. Due to the special structure of the GMM, we propose a new sampling-based algorithm, the stochastic GMM sampler, which replaces the multivariate minimization problem by a series of conditional sampling procedures. We develop the theoretical properties of the proposed iterative Monte Carlo method, and demonstrate its superior performance over other GMM estimation procedures in simulation studies. As an illustration, we apply the stochastic GMM sampler to a Medfly life longevity study. Supplemental materials for the article are available online. © 2011 American Statistical Association.

Citation
Yin G, Ma Y, Liang F, Yuan Y (2011) Stochastic Generalized Method of Moments. Journal of Computational and Graphical Statistics 20: 714–727. Available: http://dx.doi.org/10.1198/jcgs.2011.09210.

Acknowledgements
We thank the referees, associate editor, and editor for many insightful suggestions which strengthened the work immensely. Yin’s research was supported by a grant from the Research Grants Council of Hong Kong, Ma’s research was supported by a US NSF grant, Liang’s research was supported by grants from US NSF (DMS-1007457 and CMMI-0926803) and King Abdullah University of Science and Technology (KUS-C1-016-04), and Yuan’s research was supported by a U.S. National Cancer Institute R01 grant (R01CA154591-01A1).

Publisher
Informa UK Limited

Journal
Journal of Computational and Graphical Statistics

DOI
10.1198/jcgs.2011.09210

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