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Model averaging with averaging covariance matrix
Zhao, Shangwei1; Zhang, Xinyu2; Gao, Yichen3
AbstractThis article studies optimal model averaging for linear models with heteroscedasticity. We choose weights by minimizing Mallows-type criterion. Because the covariance matrix of random error in the criterion is unknown, an averaging estimator of covariance matrix is plugged into the criterion. The resulting model averaging estimator is proved to be asymptotically optimal under some regularity conditions. Simulation experiments show that the proposed model averaging method is superior to its competitors. (C) 2016 Elsevier B.V. All rights reserved.
KeywordAsymptotic optimality Heteroscedasticity Model averaging
Funding ProjectNational Natural Science Foundation of China[71522004] ; National Natural Science Foundation of China[11471324] ; National Natural Science Foundation of China[11271355] ; National Natural Science Foundation of China[71501133] ; special talent grant from AMSS, CAS
WOS Research AreaBusiness & Economics
WOS SubjectEconomics
WOS IDWOS:000381834600050
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Document Type期刊论文
Corresponding AuthorZhang, Xinyu
Affiliation1.Minzu Univ China, Coll Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100864, Peoples R China
3.Capital Univ Econ & Business, ISEM, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Shangwei,Zhang, Xinyu,Gao, Yichen. Model averaging with averaging covariance matrix[J]. ECONOMICS LETTERS,2016,145:214-217.
APA Zhao, Shangwei,Zhang, Xinyu,&Gao, Yichen.(2016).Model averaging with averaging covariance matrix.ECONOMICS LETTERS,145,214-217.
MLA Zhao, Shangwei,et al."Model averaging with averaging covariance matrix".ECONOMICS LETTERS 145(2016):214-217.
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