Compilation And Analysis Of People's Livelihood Indexes In China

With the development of society,the theory of "GDP only" has been abandoned.The indicators for measuring human development are more aimed at the al-round development of human beings.The most influential human development indicator is the human development index issued by the United Nations Development Programme(UNDP)in 1990.However,the main contradiction of our society has changed into the contradiction between the growing needs of the people and the development of the unbalanced and inadequate.This means that China's human development research needs to be considered from many aspects of human development.As one of the important fields of human development in China,the field of people's livelihood has a strong research value.At present,there is a lack of research on people's Livelihood index in the study of Human Development index in China.On the one hand,it may be due to the wide coverage of the livelihood area.It is difficult to choose the index of People's livelihood index to inherit the concise thought of human Development index.On the other hand,it may be that the research around environmental sustainable development in recent years is a hot one,thus neglecting the field of people's livelihood.For whatever reason,in order to perfect China's human development Index,the People's Livelihood index all over China is worthy of further study.This paper is mainly composed of four parts.The first part combs the relevant theories of HDI and people's livelihood research.The second part,around China's policy objectives to improve and protect people's livelihood,selected two sub-indicators of the People's Livelihood Index: Social Security Index and Engel Index.The calculation of people's livelihood index inherits the calculation idea of HDI.Through the collection of data to calculate the 31 provinces and cities in China 1990-2017 years of People's Livelihood Index and forecast its 2018-2020 People's livelihood index.The third part.First of al,from the National People's Livelihood Index development trend analysis,concluded that China's People's livelihood index has a starting point of low growth and fast characteristics.Then the people's Livelihood index of all parts of our country is divided into the middle and northwest of China,and it is found that the people's livelihood index in northeastern China and the northeast shows the characteristics of the northeast > East > West.In order to better understand the regional differences of people's livelihood index all over China,cluster analysis is carried out by using panel data clustering analysis method.The results show that the people's Livelihood index can be divided into four categories in various parts of China.Based on the characteristics of the average and average annual growth rates of these four categories,they can be named as leading areas,medium zones,potential zones and backward areas.The leading areas are Beijing,Shanghai and Tianjin,the potential areas are Inner Mongolia,Qinghai,Chongqing and Ningxia,the backward areas are Tibet,and the rest are medium-sized areas.Then,the dynamic convergence of People's Livelihood Index is analyzed by using Geographically and Temporally Weighted Regression(GTWR).The conclusion is that the people's Livelihood index has significant conditional convergence,and the convergence speed of different provinces and cities has significant spatiotemporal heterogeneity.Improving the level of urbanization is beneficial to the convergence of people's livelihood index.Finally,through the comparative analysis of China's HDI and People's Livelihood index development trend and cluster analysis results found that: China's People's Livelihood Index is a short board relative to HDI,its growth rate and HDI difference is large,and the local people's Livelihood index and HDI clustering results are somewhat different.Thus,it confirms the correctness and necessity of adding people's Livelihood index to the study of HDI in various parts of China.The fourth part.The conclusions of this paper are summarized and policy recommendations are proposed for the influencing factors.