Data-Driven Robust DEA Models for Measuring Operational Efficiency of Endowment Insurance System of Different Provinces in China
Shaojian Qu (),
Can Feng,
Shan Jiang,
Jinpeng Wei and
Yuting Xu
Additional contact information
Shaojian Qu: School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Can Feng: School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Shan Jiang: School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Jinpeng Wei: School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yuting Xu: School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Sustainability, 2022, vol. 14, issue 16, 1-21
Abstract:
China is facing an increasingly serious aging problem, which puts forward higher requirements for the smoothness of the endowment insurance system. Accurate evaluation of the efficiency of the system can help the government to find problems and improve the system. Some scholars have used data envelopment analysis (DEA) method to measure the efficiency of endowment insurance system. However, according to the literature, the impact of government policy adjustment and economic shocks on output of the data was ignored. In this study, a robust optimization method is applied to deal with uncertainty. Robust DEA models proposed in this paper are based on three kinds of uncertainty sets. A data-driven robust optimization method is also applied to resolve the over-conservative problem. Compared with the robust DEA method, based on analysis it is found that the data-driven robust DEA method is more flexible and reliable for efficiency estimating strategies. The results of data-driven robust DEA models illustrate that the government should increase its support for the endowment insurance system, especially for the underdeveloped regions.
Keywords: endowment insurance system; robust optimization; data envelopment analysis (DEA); uncertainty set; data-driven (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.mdpi.com/2071-1050/14/16/9954/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/16/9954/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:16:p:9954-:d:886109
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().