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引用次数: 0
摘要
本研究探讨了与经济、社会和环境相互联系相关的各种指标的主要构成部分。数据主要来自世界银行的世界发展指数(WDI)、联合国开发计划署的人类发展指数(HDI)和 "数据中的世界"(Our World in Data)指标。利用 2000 年至 2021 年 32 个欧洲国家的横截面面板数据,通过主成分分析生成了大量因素。分析结果显示,农业部门增加值占国内生产总值的百分比、人均一次能源消费总量、使用互联网的人口比例、失业人口比例、人口密度、总抚养比、工业部门增加值占国内生产总值的百分比以及至少接受过中等教育的女性人口比例等因素在更大程度上描述了三维相互关联性。为了观察经济增长与经济、社会和环境相互关联性之间的现存相关性,我们对所获得的因素以及国内生产总值进行了统计分析。根据皮尔逊相关性的结果,经济增长与涉及三维互联性的因素之间存在强度适中的正负关系。此外,还为今后的研究提出了建议,即根据先前获得的各因素的构成要素创建一个指数。
THE INTERCONNECTIONS BETWEEN ECONOMIC, SOCIAL AND ENVIRONMENT RELATED INDIDCATORS AND THEIR RELATIONSHIP WITH ECONOMIC GROWTH
This study examines the principal components that are characteristic to a varied number of indicators specific to the economic, social and environmental interconnectivity. The data are drawn primarily from the World Bank’s WDI, the UNDP’s HDI and Our World in Data’s Indicators. Using cross-section panel data from 2000 to 2021, for a number of 32 European countries, a considerable number of factors are generated by conducting the principal component analysis. The results of the analysis depict an image where the three-dimensional interconnectivity is described to a greater extent by components such as: the agricultural sector’s value added as a percentage of the GDP, the total quantity of primary energy consumed per capita, the percentage of the population that has access to internet, the percentage of individuals that are unemployed, the population density, the total dependency ratio, the industrial sector’s value added as a percentage of the GDP and the percentage of the female population that has attained at least secondary education. Together with the GDP, the obtained factors are statistically analysed in order to observe the existing correlations between economic growth and the economic, social and environmental interconnectivity. According to the results of the Pearson correlation, both positive and negative relationships of moderate intensities exist between economic growth and the factors that address the three-dimensional interconnectivity. Furthermore, recommendations are made for future research regarding the creation of an index based on the components that form the factors previously obtained.