Panel Data Study On Comprehensive Evaluation Of Sustainable Development Of G20 Countries Based On Time Weight And Index Weight

Under the situation of rapid economic development,the unsustainable situation between national economic development and social,technological,resource and environmental development becomes more and more serious.The sustainable development of a country is a complex system.It not only includes the dimensions of economic,social,technological,environmental and resource indicators,but also includes the time factor of present and future generations.With the transformation of the international political landscape in the 21 st century,the G20 has gradually become the backbone of world governance and the most influential economic cooperation organization in the world.Therefore,this organization has also become a popular choice for scholars to conduct research from a global perspective.Scientifically evaluate the level of sustainable and comprehensive development of the G20,and help governments of China and the world to make better national development decisions.First,based on previous research results,this paper introduces scientific and technological indicators into the National Sustainable Development Index(NSDI),and proposes a more complete and unified new index--the National Sustainable Development Composite Index(NSDCI).Then by making changes in the method of determining the index weight and time weight of the panel data,the corresponding optimal weight vectors are found respectively.In the index weighting,the entropy method,the coefficient of variation method and the CRITIC method are combined for weighting,and the least square method is used to construct the corresponding integrated model.With the help of MATLAB software,the Gauss Newton algorithm is used to search and solve the optimal Index weight;in the improvement of time weighting,the importance of the time dimension varies with time.For this reason,the arcsine function is introduced into the OWA operator,taking into account the particularity of the decision data that may appear,and then relying on the optimization of the decision data The OWA operator time weighting method based on the arc sine function is used to solve the time weight.Finally,the improved index weights and time weights are introduced into the comprehensive evaluation model of topsis--grey correlation analysis.Through the comprehensive evaluation model of dynamic topsis--grey correlation analysis of panel data,the comprehensive evaluation score and ranking of the G20 countries in2008--2016 are calculated.With the aid of R statistical software,this paper conducts a systematic cluster analysis on the scores of each country,and divides the sustainable comprehensive development of the G20 into three levels: high--upper middle--middle development.According to the evaluation results,it analyzes the general reasons for the country's sustainable high-level development and medium-level development,and puts forward corresponding policy recommendations and solutions for different levels of country.