Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/103641
Authors: 
Sueishi, Naoya
Year of Publication: 
2013
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Publisher:] MDPI [Place:] Basel [Volume:] 1 [Year:] 2013 [Issue:] 2 [Pages:] 141-156
Abstract: 
This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.
Subjects: 
model selection
model averaging
focused information criterion
generalized empirical likelihood
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/3.0/
Document Type: 
Article
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