{"title":"THE INTERCONNECTIONS BETWEEN ECONOMIC, SOCIAL AND ENVIRONMENT RELATED INDIDCATORS AND THEIR RELATIONSHIP WITH ECONOMIC GROWTH","authors":"Radu Rusu","doi":"10.56043/reveco-2023-0021","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":85430,"journal":{"name":"Revista economica","volume":"56 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista economica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56043/reveco-2023-0021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.