Open AccessCombined with two-stage network DEA and DEa-Malmquist analysis of unemployment insurance efficiency.
Author(s) -
Yan Qing
Publication year - 2021
Publication title -
addaiyan journal of arts humanaties and social sciences
Language(s) - English
Resource type - Journals
ISSN - 2581-8783
DOI - 10.36099/ajahss.3.11.10
Subject(s) - unemployment , economics , malmquist index , index (typography) , productivity , labour economics , economic growth , total factor productivity , computer science , world wide web
Throughout history, unemployment has been a major national concern. Unemployment insurance is an important means to relieve unemployment pressure and promote re-employment and social stability, so it is very necessary to study the operating efficiency of unemployment insurance. As the number of unemployed continues to increase since the COVID-19 outbreak, it is urgent to give full play to the role of unemployment insurance and improve the efficiency of unemployment insurance. This paper intends to use two-stage network DEA and DEA- Malmquist to study the efficiency of unemployment insurance in Hunan Province and 8 provinces with different geographical locations and levels of economic development from 2015 to 2019. The results show that the efficiency of unemployment insurance in Hunan Province from 2015 to 2019 shows a declining trend in the M index model. The main reason is the lack of technological progress. In the two-stage network DEA model, it is the first stage that affects the overall efficiency. Therefore, to improve the efficiency of unemployment insurance, it is necessary to develop technological progress first, attract more insured people, and improve the relevant system of unemployment insurance.