An Empirical Study On The Efficiency Of Basic Pension Insurance In Anhui Province Based On DEA

With the implementation of the family planning policy and the change of people's conception of birth,the birth rate of our country has been decreasing,and with the improvement of the modern material living standard,the population mortality of our country is also decreasing,and the problem of population aging is becoming more and more serious.On the one hand,the large population base,the rapid expansion of the elderly population,increased the requirements of the basic endowment insurance fund,and increased the pressure of the social endowment insurance fund.On the other hand,the phenomenon of "not getting rich before the old" and "not getting ready to get old" has made the related endowment insurance service demand increasing,and the government is facing a heavier pension burden.Under this macro background,the importance and severity of establishing a fair and efficient pension insurance system is prominent.The performance and efficiency of basic pension insurance directly affect the level of social welfare that the elderly can accept,and it is a key issue to improve the efficiency of social basic endowment insurance.In this paper,the DEA input-output efficiency evaluation model is built,and the collected data are analyzed statistically,and then the dynamic,spatial and other aspects of the in-depth study and analysis are carried out.Static,taking 2015 as the cross section,using CCR and BCC model,the basic endowment insurance efficiency of 31 provinces and cities in China is analyzed,and the ranking of Anhui province in China is obtained.Through comprehensive efficiency analysis,scale efficiency analysis,technical efficiency analysis and DEA effectiveness analysis,the gap between Anhui and other provinces is compared,and concrete and feasible countermeasures and suggestions are put forward.The efficiency value of the basic endowment insurance of 16 prefecture level cities under the jurisdiction of Anhui province in 2015 is calculated and analyzed,and the input-output redundancy analysis is carried out on 16 prefectural cities.The policy suggestions are put forward to the specific situation of the basic endowment insurance in Anhui Province,in order to optimize the investment mode of the old insurance fund and improve the fund.The ability of rational utilization.The Malmquist index was used to analyze the pension insurance of 2011-2016 years,and the interannual changes between the 2011-2016 years' pension insurance investment and the output index were analyzed.The full text is divided into six parts.The first part is the introduction,which introduces the background,significance and main research content,research ideas and frame structure of this paper.The second part is the theoretical analysis of the basic old-age insurance in China.In this part,the literature review and policy of basic endowment insurance at home and abroad and the basic old-age insurance are reviewed and reviewed.The third part mainly introduces the DEA method,introduces the model,the principle and the Malmquist index of the DEA method,and expounds the selection of the DEA evaluation index and the construction of the model of the endowment insurance system.The fourth part is an empirical analysis.Through the construction of DEA efficiency evaluation index system,this paper mainly evaluates and analyses the input-output efficiency.of basic pension insurance in 31 provinces and cities in China.The conclusion is that the DEA comprehensive efficiency value of Anhui province is the lowest,and it is ranked the last of the country.At the same time,the specific DEA value of the 16 cities in Anhui province is carried out in the microcosmic.Analysis?The fifth part is to analyze the 2011-2016 year endowment insurance with the Malmquist index dynamically,and analyze the interannual changes between the 2011-2016 years' pension insurance investment and the output indicators.The sixth part is targeted at the current situation of the basic pension insurance fund input and output in Anhui,and gives targeted and directional policy recommendations.