社会福利的测度与比较——基于不平等厌恶系数的研究方法

Measurement and Comparison of Social Welfare——Based on the Research Method of Ineguality Aversion Coefficient

基于不平等厌恶系数构建测度社会福利水平的新方法,利用2010—2020年五期CGSS数据测度优势不平等厌恶系数和劣势不平等厌恶系数,冗余分析结果显示测度方法有较好的效度。使用机器学习算法对区域和城乡福利水平特征进行探究,结果发现:虽然社会福利水平总体在提高,但是存在发展不平衡的情况;城镇居民福利水平相对于农村而言,存在更为严重的阶层固化效应,并且马太指数、马太系数呈现均值回归特征;东部地区与中西部地区存在“福利鸿沟”,两者的福利水平差异随时间推移逐步扩大。

Based on the new construction method of using the inequality aversion coefficient measuring social welfare level,the paper adopted 5 periods of the CGSS data from 2010 to 2020 to measure the advantageous inequality aversion coefficient and disadvantageous inequality aversion coefficient.The results of redundancy analysis showed that the measuring method had a relatively better validity.Then the paper used the machine learning algorithm to explore both regional and urban-rural characteristics of welfare level.The results showed that,although the overall level of social welfare had an improving trend,there was still an unbalanced development status.The welfare level of urban residents had a more stronger hierarchical solidification effect than that of rural residents.Meanwhile,the Matthew index and Matthew coefficient exhibited the characteristics of mean regression.In addition,there was a“welfare gap”between the eastern region and the midwestern region,and the gap had a gradually enlarged trend.