{"title":"欧盟气候变化:聚类与回归分析","authors":"Krstić Miloš","doi":"10.5937/sjm18-43601","DOIUrl":null,"url":null,"abstract":"Climate change is often seen as the most global and complex problem the world has been facing during its current development. The emissions of harmful gases, rising temperatures, variable amounts of precipitation, the occurrence of extreme weather conditions affect all countries regardless of their geographical position and level of development. The subject and goal of this paper is to examine the impact of economic, technological and demographic determinants on CO2 emissions in 18 EU countries in the period from 2011 to 2020. In the research are used k-means clustering and panel regression analysis. By the application of k-means clustering, 18 EU countries were grouped into 2 clusters according to the level of emissions of selected greenhouse gases (CO2 , CH4 , HFC, PFC, SF6 ) per capita. In the \"green cluster\", there are the following countries: Czech Republic, Germany, Austria, Poland, Belgium, Ireland, and Netherlands. The \"red cluster\" includes the other analyzed EU countries. The results of the panel regression model in the \"green cluster\" showed that CO2 emissions are statistically significantly and positively influenced by Energy efficiency and Production of electricity by solid fossil fuels. On the other hand, the results of the analysis in the \"red cluster\" suggested that Research and developments costs turn out to be the most important predictor of CO2 emissions.","PeriodicalId":44603,"journal":{"name":"Serbian Journal of Management","volume":"1 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Climate change in the EU: Analysis by clustering and regression\",\"authors\":\"Krstić Miloš\",\"doi\":\"10.5937/sjm18-43601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Climate change is often seen as the most global and complex problem the world has been facing during its current development. The emissions of harmful gases, rising temperatures, variable amounts of precipitation, the occurrence of extreme weather conditions affect all countries regardless of their geographical position and level of development. The subject and goal of this paper is to examine the impact of economic, technological and demographic determinants on CO2 emissions in 18 EU countries in the period from 2011 to 2020. In the research are used k-means clustering and panel regression analysis. By the application of k-means clustering, 18 EU countries were grouped into 2 clusters according to the level of emissions of selected greenhouse gases (CO2 , CH4 , HFC, PFC, SF6 ) per capita. In the \\\"green cluster\\\", there are the following countries: Czech Republic, Germany, Austria, Poland, Belgium, Ireland, and Netherlands. The \\\"red cluster\\\" includes the other analyzed EU countries. The results of the panel regression model in the \\\"green cluster\\\" showed that CO2 emissions are statistically significantly and positively influenced by Energy efficiency and Production of electricity by solid fossil fuels. On the other hand, the results of the analysis in the \\\"red cluster\\\" suggested that Research and developments costs turn out to be the most important predictor of CO2 emissions.\",\"PeriodicalId\":44603,\"journal\":{\"name\":\"Serbian Journal of Management\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Serbian Journal of Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5937/sjm18-43601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Serbian Journal of Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5937/sjm18-43601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
Climate change in the EU: Analysis by clustering and regression
Climate change is often seen as the most global and complex problem the world has been facing during its current development. The emissions of harmful gases, rising temperatures, variable amounts of precipitation, the occurrence of extreme weather conditions affect all countries regardless of their geographical position and level of development. The subject and goal of this paper is to examine the impact of economic, technological and demographic determinants on CO2 emissions in 18 EU countries in the period from 2011 to 2020. In the research are used k-means clustering and panel regression analysis. By the application of k-means clustering, 18 EU countries were grouped into 2 clusters according to the level of emissions of selected greenhouse gases (CO2 , CH4 , HFC, PFC, SF6 ) per capita. In the "green cluster", there are the following countries: Czech Republic, Germany, Austria, Poland, Belgium, Ireland, and Netherlands. The "red cluster" includes the other analyzed EU countries. The results of the panel regression model in the "green cluster" showed that CO2 emissions are statistically significantly and positively influenced by Energy efficiency and Production of electricity by solid fossil fuels. On the other hand, the results of the analysis in the "red cluster" suggested that Research and developments costs turn out to be the most important predictor of CO2 emissions.
期刊介绍:
Technical Faculty in Bor, University of Belgrade has started publishing the journal called Serbian Journal of Management during the year 2006. This journal is an international medium for the publication of work on the theory and practice of management science.