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2023, vol. 18, br. 1, str. 111-132
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Klimatske promene u EU - klaster analiza i regresija
Climate change in the EU: Analysis by clustering and regression
Projekat: Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije (institucija: Univerzitet u Nišu, Prirodno-matematički fakultet) (MPNTR - 451-03-68/2020-14/200124)
Sažetak
Klimatske promene se često posmatraju kao najglobalniji i najkompleksniji problem sa kojim se svet suočio u dosadašnjem razvoju. Emisije štetnih gasova, porast temperature, promenljive količine padavina, pojava ekstremnih vremenskih prilika utiču na sve zemlje nezavisno od njihove geografske pozicije i nivoa razvoja, determinišući njihove proizvodne potencijale i kvalitet životnih uslova stanovništva. Predmet i cilj ovog rada je da ispita uticaj ekonomskih, tehnoloških i demografskih determinanti na emisiju SO2 u 18 država Evropske Unije u vremenskom periodu od 2011. do 2020. godine. U istraživanju su korišćeni metoda klaster analize k-srednjih vrednosti i panel regresiona analiza. Primenom metoda k-srednjih vrednosti, izvršeno je grupisanje 18 zemalja Evropske unije u 2 klastera, prema visini emisija odabranih gasova staklene bašte (CO2 , CH4 , HFC, PFC, SF6 ) per capita. U "zelenom klasteru" nalaze se sledeće zemlje: Češka, Nemačka, Austrija, Poljska, Belgija, Irska i Holandija. "Crveni klaster" uključuje ostale analizirane zemlje Evropske unije. Rezultati panel regresionog modela u "zelenom klasteru" pokazali su da na emisiju SO2 statistički značajno i pozitivno utiču Energetska efikasnost i Proizvodnja električne energije iz neobnovljivih izvora. S druge strane, rezultati analize u "crvenom klasteru" sugerisali su da Troškovi istraživanja i razvoja predstavljaju najvažniji prediktor emisija SO2.
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.
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