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Model averaging estimators for the stochastic frontier model
Parmeter, Christopher F.1; Wan, Alan T. K.2; Zhang, Xinyu3
2019-06-01
Source PublicationJOURNAL OF PRODUCTIVITY ANALYSIS
ISSN0895-562X
Volume51Issue:2-3Pages:91-103
AbstractModel uncertainty is a prominent feature in many applied settings. This is certainty true in the efficiency analysis realm where concerns over the proper distributional specification of the error components of a stochastic frontier model is, generally, still open along with which variables influence inefficiency. Given the concern over the impact that model uncertainty is likely to have on the stochastic frontier model in practice, the present research proposes two distinct model averaging estimators, one which averages over nested classes of inefficiency distributions and another that has the ability to average over distinct distributions of inefficiency. Both of these estimators are shown to produce optimal weights when the aim is to uncover conditional inefficiency at the firm level. We study the finite-sample performance of the model average estimator via Monte Carlo experiments and compare with traditional model averaging estimators based on weights constructed from model selection criteria and present a short empirical application.
KeywordOptimality J-fold cross-validation Efficiency Model selection
DOI10.1007/s11123-019-00547-8
Language英语
Funding ProjectNational Natural Science Foundation of China[71522004] ; National Natural Science Foundation of China[11471324] ; National Natural Science Foundation of China[71631008]
WOS Research AreaBusiness & Economics ; Mathematical Methods In Social Sciences
WOS SubjectBusiness ; Economics ; Social Sciences, Mathematical Methods
WOS IDWOS:000472216100001
PublisherSPRINGER
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/34932
Collection系统科学研究所
Affiliation1.Univ Miami, Dept Econ, Miami, FL 33136 USA
2.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Parmeter, Christopher F.,Wan, Alan T. K.,Zhang, Xinyu. Model averaging estimators for the stochastic frontier model[J]. JOURNAL OF PRODUCTIVITY ANALYSIS,2019,51(2-3):91-103.
APA Parmeter, Christopher F.,Wan, Alan T. K.,&Zhang, Xinyu.(2019).Model averaging estimators for the stochastic frontier model.JOURNAL OF PRODUCTIVITY ANALYSIS,51(2-3),91-103.
MLA Parmeter, Christopher F.,et al."Model averaging estimators for the stochastic frontier model".JOURNAL OF PRODUCTIVITY ANALYSIS 51.2-3(2019):91-103.
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