A model averaging approach for the ordered probit and nested logit models with applications

doi:10.1080/02664763.2018.1450367

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	A model averaging approach for the ordered probit and nested logit models with applications
	Chen, Longmei 1; Wan, Alan T. K.1; Tso, Geoffrey 1; Zhang, Xinyu2
	2018
发表期刊	JOURNAL OF APPLIED STATISTICS
ISSN	0266-4763
卷号	45 期号:16 页码:3012-3052
摘要	This 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.
关键词	Hit rate model averaging model selection Monte Carlo nested logit ordered probit screening
DOI	10.1080/02664763.2018.1450367
语种	英语
资助项目	City 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研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000446217300008
出版者	TAYLOR & FRANCIS LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/31410
专题	系统科学研究所
通讯作者	Wan, Alan T. K.
作者单位	1.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
推荐引用方式 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.