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A model averaging approach for the ordered probit and nested logit models with applications
Chen, Longmei1; Wan, Alan T. K.1; Tso, Geoffrey1; Zhang, Xinyu2
2018
Source PublicationJOURNAL OF APPLIED STATISTICS
ISSN0266-4763
Volume45Issue:16Pages:3012-3052
AbstractThis paper considers model averaging for the ordered probit and nested logit models, which are widely used in empirical research. Within the frameworks of these models, we examine a range of model averaging methods, including the jackknife method, which is proved to have an optimal asymptotic property in this paper. We conduct a large-scale simulation study to examine the behaviour of these model averaging estimators in finite samples, and draw comparisons with model selection estimators. Our results show that while neither averaging nor selection is a consistently better strategy, model selection results in the poorest estimates far more frequently than averaging, and more often than not, averaging yields superior estimates. Among the averaging methods considered, the one based on a smoothed version of the Bayesian Information criterion frequently produces the most accurate estimates. In three real data applications, we demonstrate the usefulness of model averaging in mitigating problems associated with the replication crisis' that commonly arises with model selection.
KeywordHit rate model averaging model selection Monte Carlo nested logit ordered probit screening
DOI10.1080/02664763.2018.1450367
Language英语
Funding ProjectCity University of Hong Kong[7004985] ; National Science Foundation of China[71522004] ; National Science Foundation of China[71463012] ; National Science Foundation of China[71631008] ; National Science Foundation of China[11471324] ; Ministry of Education of China[17YJC910011]
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000446217300008
PublisherTAYLOR & FRANCIS LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/31410
Collection系统科学研究所
Affiliation1.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Chen, Longmei,Wan, Alan T. K.,Tso, Geoffrey,et al. A model averaging approach for the ordered probit and nested logit models with applications[J]. JOURNAL OF APPLIED STATISTICS,2018,45(16):3012-3052.
APA Chen, Longmei,Wan, Alan T. K.,Tso, Geoffrey,&Zhang, Xinyu.(2018).A model averaging approach for the ordered probit and nested logit models with applications.JOURNAL OF APPLIED STATISTICS,45(16),3012-3052.
MLA Chen, Longmei,et al."A model averaging approach for the ordered probit and nested logit models with applications".JOURNAL OF APPLIED STATISTICS 45.16(2018):3012-3052.
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