Performance Evaluation Of Basic Pension Insurance For Urban And Rural Residents In China Under Uncertain Environmen

In the coming decades,China’s pension insurance system will face huge challenges.In order to reduce the pension risks caused by the aging of the population and solve the problem of providing for the elderly,China established a unified basic old-age insurance system for urban and rural residents in 2014,which makes China’s social security system cover all people.Today,nine years later,it is particularly important to evaluate the operational benefits of the basic old-age insurance system for urban and rural residents in China.Previous scholars have tried to measure the operational efficiency of basic old-age insurance for urban and rural residents in China using data envelopment analysis(DEA).However,no one considers the impact of uncertain factors such as economic impact and policy adjustment on the final performance.After the COVID-19 epidemic,the world entered the rhythm of political and economic order restructuring,and various risks impacted the government’s financial situation and national income,as well as the efficiency of the basic old-age insurance system for urban and rural residents.In this paper,the robust optimization method and data-driven robust optimization method are innovatively proposed to deal with the performance evaluation problem in uncertain environment.This paper takes the basic old-age insurance of urban and rural residents in 31 provinces as the research object,follows the principles of consistency,scientificity and feasibility in the selection of indicators,and our paper selects the number of policyholders,the number of people participating in basic old-age insurance,and the income of basic old-age insurance funds as the input indicators,and takes the accumulated balance and fund expenditure as the output indicators,and constructs a scientific evaluation system.Then,the DEA model is improved by robust optimization method and data-driven robust optimization method,and the robust DEA model and data-driven robust DEA model are constructed.In the construction of the model,we choose four kinds of uncertainty sets to describe different kinds of uncertainty.The results show that:(1)Both robust DEA model and data-driven robust DEA model can deal with uncertainty problems compared with traditional models,and data-driven robust DEA shows better optimality because it uses more available information.(2)The pension insurance performance rankings of 31 provinces,municipalities and autonomous regions have changed under uncertain circumstances,which is far from the conclusion of traditional methods.(3)Some uncertain set results show the strongest robustness and optimalityAt the last,based on the conclusion above,this paper puts forward three suggestions to improve the operational efficiency of the basic old-age insurance system for urban and rural residents.