- citations in SCIndeks: 0
- citations in CrossRef:0
- citations in Google Scholar:[
 ]
- visits in previous 30 days:0
- full-text downloads in 30 days:0
|
|
|
2023, vol. 18, iss. 1, pp. 111-132
|
|
Climate change in the EU: Analysis by clustering and regression
Klimatske promene u EU - klaster analiza i regresija
Project: Ministry of Education, Science and Technological Development, Republic of Serbia (Institution: Univeristy of Niš, Faculty of Science) (MESTD - 451-03-68/2020-14/200124)
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.
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.
|
|
|
|
References
|
|
|
*** (2008) Energy technology perspective 2008: Scenarios and strategies to 2050. Paris: International Energy Agency (IEA)
|
|
|
*** (2008) CO2 capture and storage: A key abatement option. Paris: International Energy Agency
|
|
|
*** (2010) Development and climate change. Washington: World Bank
|
|
|
*** (1992) United Nations framework convention on climate change. New York: United Nations
|
|
|
*** (2014) Programme of action. New York: United Nation Population Food (UNPF)
|
|
  
|
Auffhammer, M., Hsiang, S.M., Schlenker, W., Sobel, A. (2013) Using weather data and climate model output in economic analyses of climate change. Review of Environmental Economics and Policy, 7(2): 181-198
|
|
|
Banuri, T., Opschoor, H. (2007) Climate change and sustainable development. DESA Working Paper No. 56
|
|
|
Barnett, J., Evans, L.S., Gross, C., Kiem, A.S., Kingsford, R.T., Palutikof, J.P., Pickering, C.M., Smithers, S.G. (2015) From barriers to limits to climate change adaptation: Path dependency and the speed of change. Ecology and Society, 20(3): 5-16
|
|
|
Bergquist, P., Mildenberger, M., Stokes, L.C. (2020) Combining climate, economic, and social policy builds public support for climate action in the US. Environmental Research Letters, 15(5): 1-10
|
|
|
Bierbaum, R., Holdrend, J.P., Maccracken, M., Moss, R.H., Raven, P.H., Nakicenovic, N. (2007) Confronting climate change: Avoiding the unmanageable and managing the unavoidable. New York: United Nations Foundation
|
|
|
Bok, H. (2018) Baron de Montesquieu, Charles-Louis de Secondat. Retrieved from http://plato.stanford.edu/archives/win2018/e ntries/montesquieu
|
|
|
Cole, M.A., Neumayer, E. (2004) Examining the impact of demographic factors on air pollution. Population and Environment, 26(1): 5-21
|
|
|
Dietz, T., Rosa, E.A. (1997) Effects of population and affluence on CO2 emissions. Proceedings of the National Academy of Sciences, 94(1): 175-179
|
|
|
Dosio, A., Panitz, H.J. (2016) Climate change projections for CORDEX-Africa with COSMO-CLM regional climate model and differences with the driving global climate models. Climate Dynamics, 46(5-6): 1599-1625
|
|
|
Đokić, D., Novaković, T., Tekić, D., Matkovski, B., Zekić, S., Milić, D. (2022) Technical efficiency of agriculture in the European Union and western Balkans: SFA method. Agriculture, 12(12): 1992-1992
|
|
|
Eloriaga, J., producer (1992) Panel data models (Pooled OLS, FE, RE, LSDVs) in STATA. Retrieved from https://www.youtube.com/watch?v=b02s2D dRvzM
|
|
|
Franta, B. (2022) Weaponizing economics: Big oil, economic consultants, and climate policy delay. Environmental Politics, 31(4): 555-575
|
|
|
Gaweł, A., Krstić, M. (2021) Gender gaps in entrepreneurship and education levels from the perspective of clusters of European countries. Journal of Developmental Entrepreneurship, 26(04): 2150024
|
|
|
Giddens, A. (2009) Politics of climate change. London: Policy Network
|
|
14
|
Greene, W.H. (2018) Econometric analysis. New York: Pearson
|
|
|
Hashmi, R., Alam, K. (2019) Dynamic relationship among environmental regulation, innovation, CO2 emissions, population, and economic growth in OECD countries: A panel investigation. Journal of Cleaner Production, 231: 1100-1109
|
|
|
Hoegh-Guldberg, O., Jacob, D., Taylor, M., Guillén, B.T., Bindi, M., Brown, S., Camilloni, I.A., Diedhiou, A., Djalante, R., Ebi, K., Engelbrecht, F., Guiot, J., Hijioka, Y., Mehrotra, S., Hope, C.W., Payne, A.J., Pörtner, H.-.O., Seneviratne, S.I., Thomas, A. (2019) The human imperative of stabilizing global climate change at 1.5 C. Science, 365(6459): eaaw6974-eaaw6974
|
|
|
IPCC (2007) Climate change 2007: The physical science basis. Cambridge: Cambridge University Press, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
|
|
|
Iqbal, U., Rabrenovic, M., Li, Y.C. (2019) Health care quality challenges in low-and middle-income countries. International Journal for Quality in Health Care, 31(3): 165-165
|
|
1
|
Kilian, L., Vigfusson, R.J. (2017) The role of oil price shocks in causing U.S. recessions. Journal of Money, Credit and Banking, 49(8): 1747-1776
|
|
|
Kukla-Gryz, A. (2009) Economic growth, international trade and air pollution: A decomposition analysis. Ecological Economics, 68(5): 1329-1339
|
|
|
Nemet, G.F., Kammen, D.M. (2007) Asymmetric impacts of energy efficiency on carbon emissions: A comparative analysis between developed and developing economies. Energy, 227: 120485-120485
|
|
|
Nemet, G.F., Kammen, D.M. (2007) US energy research and development: Declining investment, increasing need, and the feasibility of expansion. Energy Policy, 35(1): 746-755
|
|
5
|
Newey, W.K., West, K.D. (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3): 703-708
|
|
|
Petrović, P., Nikolić, G., Ostojić, I. (2018) Emissions of CO2 in the European Union: Empirical analysis of demographic, economic and technological factors. Stanovništvo, 56(1): 63-82; in Serbian
|
|
|
Schmidheniy, K. (2018) Panel data: Fixed and random effects: Short guides to microeconometrics. Basel: University of Basel
|
|
|
Shalizi, Z., Lecocq, F. (2009) Climate change and the economics of targeted mitigation in sectors with long-lived capital stock. Policy Research Working Paper, 5063; Retrieved from: http://hdl.handle.net/10986/4254
|
|
|
Stern, N. (1992) The economics of climate change. Retrieved from http://www.hmtreasury.gov.uk/independent_ reviews/stern_review_economics_climate_c hange/stern_review_report.cfm
|
|
|
Tijanić, L. (2010) Regional (un)competitiveness in the Republic of Croatia. Ekonomski pregled, 61(7-8): 419-454;i n Croatian
|
|
|
Voumik, L.C., Islam, M.A., Rahaman, A., Rahman, M.M. (2002) Emissions of carbon dioxide from electricity production in ASEAN countries: GMM and quantile regression analysis. SN Business & Economics, 2(9): 133-133
|
|
|
Wisniak, J. (2002) Svante Arrhenius and the greenhouse effect. Indian Journal of Chemical Technology, 9(3): 165-173
|
|
5
|
Wooldridge, J.M. (2015) Introductory econometrics: A modern approach. Boulevard Mason: South-Western Cengage Learning
|
|
|
York, R., Rosa, E.A., Dietz, T. (2003) STIRPAT, IPAT, and ImPACT: Analytic tools for unpacking the driving forces of environmental impacts. Ecological Economics, 46(3): 351-365
|
|
|
Zhou, Y., Chen, X., Tan, X., Liu, C., Zhang, S., Yang, F., Zhou, W., Huang, H. (2018) Mechanism of CO2 emission reduction by global energy interconnection. Global Energy Interconnection, 1(4): 409-419
|
|
|
|
|