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STIRPAT Modeli Özelinde Gelir Yoğunlaşması Ve Çevre Kirliliği İlişkisinin İncelenmesi: BRICS Ülkeleri Örneklemi

Yıl 2023, Cilt: 13 Sayı: 3, 2533 - 2550, 30.11.2023
https://doi.org/10.48146/odusobiad.1168622

Öz

Ülkelerarası artan ekonomik ilişkilerle birlikte küreselleşmenin etkisiyle artan ekonomik aktivitenin çevreye olan etkisi en çok tartışılan konulardan biri olmuştur. Bu bağlamda literatürde çevreye olumlu ve olumsuz etkisi olan birçok değişken kullanılarak analizler yapılmıştır. Bu çalışmada BRICS ülke örneklemi kullanılarak gelir eşitsizliğinin çevre üzerindeki etkisi kişi başına gelir, nüfus ve kentleşme kontrol değişkenleri kullanılarak incelenmektedir. STIRPAT modeli baz alınarak yaptığımız analizlerde, yatay kesit bağımlılığı ve homojenlik testlerinin ardından elde edilen sonuçlar ışığında ikinci nesil birim kök, panel eşbütünleşme ve uzun dönem katsayı tahmincisi testleri uygulanmıştır. Elde edilen panel eşbütünleşme testi sonuçlarına göre değişkenler uzun dönemde birlikte hareket ettiklerinde dolayı eşbütünleşme ilişkisine ulaşılmıştır. Ardından yapılan uzun dönem katsayı tahminci sonuçlarına göre ise panel genelinde gelir eşitsizliği ve kişi başına gelir değişkenlerinin uzun dönemde CO2 emisyonunu artırdığı sonucuna varılırken, nüfus değişkeninin CO2 emisyonunu azalttığı sonucuna varılmıştır. Panel geneli için kentleşme değişkeni ve çevre arasında anlamlı bir ilişkiye rastlanmamıştır. Ülkeler tek tek ele alındığında ise gelir eşitsizliğinin Hindistan’da CO2 emisyonunu artırdığı sonucuna ulaşılmıştır.

Kaynakça

  • Agostini, P. Botteon, M. & Carraro, C. (1992). A carbon tax to reduce CO2 emissions in Europe, Energy Economics, 14(4), 279-290.
  • Ahmed, Z., Zafar M.W., Ali, S. & Danish, (2020). Linking urbanization, human capital, and the ecological footprint in G7 countries: An empirical analysis, Sustainable Cities and Society, 55, 1-11. https://doi.org/10.1016/j.scs.2020.102064.
  • Ang, J. B. (2007). CO2 Emissions, energy consumption, and output in France, Energy Policy, 35, 4770-4778. Aslanidis, N. & Iranzo, S. (2009). Environment and development: is there a kuznets curve for CO2 emissions?, Applied Economics, 41(6), 803-810.
  • Aydin, M. (2019). The effect of biomass energy consumption on economic growth in brics countries: A country-specific panel data analysis, Renewable Energy, 138, 620-627, https://doi.org/10.1016/j.renene.2019.02.001.
  • Baloch, A., Shah, S.Z., Noor, Z.M. & Magsi, H.B. (2017). The nexus between income inequality, economic growth and environmental degradation in Pakistan, GeoJournal, 83, 207-222.
  • Barrett, S. & Graddy, K. (2000). Freedom, growth and the environment, Environment and Development Economics, 5, 433-456.
  • Boyce, J.K., (1994). Inequality as a cause of environmental degradation, Ecological Economics, 11, 169-178.
  • Branis, M., & Linhartova, M. (2012). Association between unemployment, income, education level, population size and air pollution in Czech cities: Evidence for environmental inequality? A Pilot National Scale Analysis, Health&Place, 18, 1110-1114.
  • Breusch, T. S., ve Pagan, A. R. (1980). The lagrange multiplier test and its applications to model specification in econometrics. The review of economic studies, 47(1), 239-253.
  • Cao, Q., Kang, W., Xu, S., Sajid, M.J. & Cao, M. (2019). Estimation and decomposition analysis of carbon emissions from the entire production cycle for Chinese household consumption, Journal of Environmental Management, 247, 525-537. https://doi.org/10.1016/j.jenvman.2019.06.044.
  • Chen, M. (2019). The impact of income gap on environmental pollution: Empirical evidence from china's energy producing regions, IOP Conference Series: Materials Science and Engineering. 592, 012201.
  • Cheng, Y. & Yao, X. (2021). carbon intensity reduction assessment of renewable energy technology innovation in China: A panel data model with cross-section dependence and slope heterogeneity, Renewable and Sustainable Energy Reviews, 135, 110157, https://doi.org/10.1016/j.rser.2020.110157.
  • Deitz, T., & Rosa, E.A. (1994). Rethinking the environmental impacts of population, affluence and technology, Human Ecology Review, 1(2), 277-300.
  • Demir, C., Cergibozan R. & Gök, A. (2018). Income inequality and CO2 emissions: Empirical evidence from Turkey, Energy and Environment, 1-18.
  • Eberhardt, M. & Teal, F. (2011). Econometrics for grumblers: a new look at the literature on cross-country growth empirics, Journal of Economic Surveys, 25(1), 109–155.
  • Eberhardt, M. & Teal, F. (2010). Productivity analysis in global manufacturing production, Economics Series Working Papers 515, University of Oxford, Department of Economics.
  • Eberhardt, M. & S. Bond. (2009). Cross-section dependence in nonstationary panel models: a novel estimator, MPRA Paper 17692, University Library of Munich.
  • Edmonds, J., & Reilly, J. (1983). A long-term global energy-economic model of carbon dioxide release from fossil fuel use, Energy Economics, 5(2), 74-88.
  • Ehlrich, P.R., & Holdren, J.P. (1971). Impact of population growth, American Association For The Advancement Of Science, 171(3977), 1212-1217.
  • Ekeocha, D.O., (2021). Urbanization, inequality, economic development and ecological footprint: searching for turning points and regional homogeneity in Africa, Journal of Cleaner Production, 291.
  • Grossman, G.M. & Krueger, A.B. (1995). Economic growth and environment, The Quarterly Journal of Economics, 110(2), 353-377.
  • Grunewald, N., Klasen, S., Martínez-Zarzoso I. & Muris, C. (2017). The trade-off between income inequality and carbon dioxide emissions, Ecological economics, 142.
  • Hashmi, R. & Alam, K. (2019). dynamic relationship among environmental regulation, innovation, CO2 emission, population, and economic growth in OECD countries: A panel investigation, Journal of Cleaner Production, 231, 1100-1109.
  • Huang, Z. & Duan, H. (2020). Estimating the threshold interaction between income inequality and carbon emissions. Journal of Environmental Management, 263, 1-11.
  • IEA, (2019). International Energy Outlook.
  • Jorgenson, A., Schor, J. & Huang, X. (2017). Income inequality and carbon emissions in the United States: A state-level analysis, 1997-2012, Ecological Economics, 134, 40-48.
  • Karabıçak, M. & Armağan, R. (2004). Çevre sorunlarının ortaya çıkış süreci, çevre yönetiminin temelleri ve ekonomik etkileri, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi, 9(2), 203-228.
  • Kusumawardani, D. & Dewi, A.K. (2020). The effect of income inequality on carbon dioxide emissions: A case study of Indonesia, Heliyon, 6(8), 1-8.
  • Le, H.P. & Ozturk, I. (2020). The impacts of globalization, financial development, government expenditures, and institutional quality on CO2 emissions in the presence of environmental kuznets curve, Environmental Science and Pollution Research, https://doi.org/10.1007/s11356-020-08812-2.
  • Mahallik, M.K., Mallick, H., Padhan, H. & Shaboo, B. (2018). Is skewed income distribution good for environmental quality? a comparative analysis among selected BRICS countries, Environmental Science And Pollution Research, 25, 23170-23194.
  • Mallick, H., Padhan, H. & Mahallik, M.K. (2019). Does skewed pattern of income distribution matter for the environmental quality? evidence from selected brics economies with an application of quantile-on-quantile regression (QQR) approach, Energy Policy, 129, 120-131.
  • Nordhaus, W.D. (1991). The economics of the greenhouse effect, The Economic Journal, 101(407), 920-937.
  • Olivier, J. G. J. & J. A. H. W. Peters, (2020). Trends in global CO2 and total greenhouse gas emissions, PBL Netherlands Environmental Assessment Agency.
  • Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure, Econometrica, 74(4), 967-1012.
  • Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence, Journal Of Applied Econometrics, 22(2), 265-312.
  • Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence, The Econometrics Journal, 11(1), 105-127.
  • Ravallion, M., Heil, M. & Jalan, J. (2000). Carbon emissions and income inequality, Oxford Economic Papers, 52, 651-669.
  • Wang, S., Wang, J., Fang C. & Li, S. (2019). Estimating the impact of urban form on CO2 emission efficiency in the pearl river delta, China, The International Journal of Urban Policy and Planning, 85, 117-129.
  • Westerlund, J., & Edgerton, D. L. (2007). A panel bootstrap cointegration test, Economics Letters, 97(3). 185–190.
  • Wolde-Rufael, Y. & Idowu, S. (2017). Income distribution and CO2 emission: A comperative analysis for China and India, Renewable and Sustainable Reviews, 74, 1336-1345.
  • World Development Indicators (WDI) (2021). World Development Indicators. www.data.worldbank.org/indicators, (Erişim Tarihi: 10.10.2021).
  • World Inequality Database (WID) (2021). World Wealth and Inequality Indicators. www.wid.world/data, (Erişim Tarihi: 10.10.2021).
  • Wu, R. & Xie, Z. (2020). Identifying the impact of income inequality on CO2 emissions: empirical evidence from OECD countries and non-OECD countries, 277, 2-16.
  • WUP, (2014). World Urbanisation Prospect: The 2014 Revision. ST/ESA/SER/366.
  • Yamaji, K., Matsuhashi, R., Nagata, Y. & Kaya, Y. (1993). A study on economic measures for CO2 reduction in Japan, Energy Policy, 21(2), 123-132.
  • York, R., Rosa, E.A. & Dietz, T. (2003). STIRPAT, IPAT and ImPACT: Analytic tools for unpacking the deriving forces of environmental impacts, Ecological Economics, 46, 351-365.
  • Zhou, A. & Li, J. (2020). Impact of income inequality and environmental regulation on environmental quality: evidence from China, Journal of Cleaner Production, 274, 1-14.

Examining The Relationship Between Income Concentration And Environmental Pollution In The Context Of The STIRPAT Model: The BRICS Countries

Yıl 2023, Cilt: 13 Sayı: 3, 2533 - 2550, 30.11.2023
https://doi.org/10.48146/odusobiad.1168622

Öz

The impact of rising economic activity, which increases with international economic relations and globalization, on environmental degradation has been subjected to many studies in the literature. Consequently, numerous factors that have both positive and negative impacts on the environment are included in a number of research. Using a sample of BRICS nations and controlling factors for income, population, and urbanization, our study examines the impact of economic disparity on the environment. In our study using the STIRPAT model, second-generation unit root, panel cointegration, and long-run coefficient tests were applied in light of the findings from the cross-sectional dependency and homogeneity tests. The variables behave jointly over the long term, which indicates that there is a cointegration link between the variables, according to the findings of the panel cointegration test that was conducted. Long-term coefficient estimate throughout the panel’s data reveals that while CO2 emissions are increased by income disparity and per capita income, they are decreased by population. No significant relationship was found for the whole panelbetween the urbanization variable and the environment. When individual nations are taken into account, it is determined that India's income disparity causes a rise in CO2 emissions.

Kaynakça

  • Agostini, P. Botteon, M. & Carraro, C. (1992). A carbon tax to reduce CO2 emissions in Europe, Energy Economics, 14(4), 279-290.
  • Ahmed, Z., Zafar M.W., Ali, S. & Danish, (2020). Linking urbanization, human capital, and the ecological footprint in G7 countries: An empirical analysis, Sustainable Cities and Society, 55, 1-11. https://doi.org/10.1016/j.scs.2020.102064.
  • Ang, J. B. (2007). CO2 Emissions, energy consumption, and output in France, Energy Policy, 35, 4770-4778. Aslanidis, N. & Iranzo, S. (2009). Environment and development: is there a kuznets curve for CO2 emissions?, Applied Economics, 41(6), 803-810.
  • Aydin, M. (2019). The effect of biomass energy consumption on economic growth in brics countries: A country-specific panel data analysis, Renewable Energy, 138, 620-627, https://doi.org/10.1016/j.renene.2019.02.001.
  • Baloch, A., Shah, S.Z., Noor, Z.M. & Magsi, H.B. (2017). The nexus between income inequality, economic growth and environmental degradation in Pakistan, GeoJournal, 83, 207-222.
  • Barrett, S. & Graddy, K. (2000). Freedom, growth and the environment, Environment and Development Economics, 5, 433-456.
  • Boyce, J.K., (1994). Inequality as a cause of environmental degradation, Ecological Economics, 11, 169-178.
  • Branis, M., & Linhartova, M. (2012). Association between unemployment, income, education level, population size and air pollution in Czech cities: Evidence for environmental inequality? A Pilot National Scale Analysis, Health&Place, 18, 1110-1114.
  • Breusch, T. S., ve Pagan, A. R. (1980). The lagrange multiplier test and its applications to model specification in econometrics. The review of economic studies, 47(1), 239-253.
  • Cao, Q., Kang, W., Xu, S., Sajid, M.J. & Cao, M. (2019). Estimation and decomposition analysis of carbon emissions from the entire production cycle for Chinese household consumption, Journal of Environmental Management, 247, 525-537. https://doi.org/10.1016/j.jenvman.2019.06.044.
  • Chen, M. (2019). The impact of income gap on environmental pollution: Empirical evidence from china's energy producing regions, IOP Conference Series: Materials Science and Engineering. 592, 012201.
  • Cheng, Y. & Yao, X. (2021). carbon intensity reduction assessment of renewable energy technology innovation in China: A panel data model with cross-section dependence and slope heterogeneity, Renewable and Sustainable Energy Reviews, 135, 110157, https://doi.org/10.1016/j.rser.2020.110157.
  • Deitz, T., & Rosa, E.A. (1994). Rethinking the environmental impacts of population, affluence and technology, Human Ecology Review, 1(2), 277-300.
  • Demir, C., Cergibozan R. & Gök, A. (2018). Income inequality and CO2 emissions: Empirical evidence from Turkey, Energy and Environment, 1-18.
  • Eberhardt, M. & Teal, F. (2011). Econometrics for grumblers: a new look at the literature on cross-country growth empirics, Journal of Economic Surveys, 25(1), 109–155.
  • Eberhardt, M. & Teal, F. (2010). Productivity analysis in global manufacturing production, Economics Series Working Papers 515, University of Oxford, Department of Economics.
  • Eberhardt, M. & S. Bond. (2009). Cross-section dependence in nonstationary panel models: a novel estimator, MPRA Paper 17692, University Library of Munich.
  • Edmonds, J., & Reilly, J. (1983). A long-term global energy-economic model of carbon dioxide release from fossil fuel use, Energy Economics, 5(2), 74-88.
  • Ehlrich, P.R., & Holdren, J.P. (1971). Impact of population growth, American Association For The Advancement Of Science, 171(3977), 1212-1217.
  • Ekeocha, D.O., (2021). Urbanization, inequality, economic development and ecological footprint: searching for turning points and regional homogeneity in Africa, Journal of Cleaner Production, 291.
  • Grossman, G.M. & Krueger, A.B. (1995). Economic growth and environment, The Quarterly Journal of Economics, 110(2), 353-377.
  • Grunewald, N., Klasen, S., Martínez-Zarzoso I. & Muris, C. (2017). The trade-off between income inequality and carbon dioxide emissions, Ecological economics, 142.
  • Hashmi, R. & Alam, K. (2019). dynamic relationship among environmental regulation, innovation, CO2 emission, population, and economic growth in OECD countries: A panel investigation, Journal of Cleaner Production, 231, 1100-1109.
  • Huang, Z. & Duan, H. (2020). Estimating the threshold interaction between income inequality and carbon emissions. Journal of Environmental Management, 263, 1-11.
  • IEA, (2019). International Energy Outlook.
  • Jorgenson, A., Schor, J. & Huang, X. (2017). Income inequality and carbon emissions in the United States: A state-level analysis, 1997-2012, Ecological Economics, 134, 40-48.
  • Karabıçak, M. & Armağan, R. (2004). Çevre sorunlarının ortaya çıkış süreci, çevre yönetiminin temelleri ve ekonomik etkileri, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi, 9(2), 203-228.
  • Kusumawardani, D. & Dewi, A.K. (2020). The effect of income inequality on carbon dioxide emissions: A case study of Indonesia, Heliyon, 6(8), 1-8.
  • Le, H.P. & Ozturk, I. (2020). The impacts of globalization, financial development, government expenditures, and institutional quality on CO2 emissions in the presence of environmental kuznets curve, Environmental Science and Pollution Research, https://doi.org/10.1007/s11356-020-08812-2.
  • Mahallik, M.K., Mallick, H., Padhan, H. & Shaboo, B. (2018). Is skewed income distribution good for environmental quality? a comparative analysis among selected BRICS countries, Environmental Science And Pollution Research, 25, 23170-23194.
  • Mallick, H., Padhan, H. & Mahallik, M.K. (2019). Does skewed pattern of income distribution matter for the environmental quality? evidence from selected brics economies with an application of quantile-on-quantile regression (QQR) approach, Energy Policy, 129, 120-131.
  • Nordhaus, W.D. (1991). The economics of the greenhouse effect, The Economic Journal, 101(407), 920-937.
  • Olivier, J. G. J. & J. A. H. W. Peters, (2020). Trends in global CO2 and total greenhouse gas emissions, PBL Netherlands Environmental Assessment Agency.
  • Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure, Econometrica, 74(4), 967-1012.
  • Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence, Journal Of Applied Econometrics, 22(2), 265-312.
  • Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence, The Econometrics Journal, 11(1), 105-127.
  • Ravallion, M., Heil, M. & Jalan, J. (2000). Carbon emissions and income inequality, Oxford Economic Papers, 52, 651-669.
  • Wang, S., Wang, J., Fang C. & Li, S. (2019). Estimating the impact of urban form on CO2 emission efficiency in the pearl river delta, China, The International Journal of Urban Policy and Planning, 85, 117-129.
  • Westerlund, J., & Edgerton, D. L. (2007). A panel bootstrap cointegration test, Economics Letters, 97(3). 185–190.
  • Wolde-Rufael, Y. & Idowu, S. (2017). Income distribution and CO2 emission: A comperative analysis for China and India, Renewable and Sustainable Reviews, 74, 1336-1345.
  • World Development Indicators (WDI) (2021). World Development Indicators. www.data.worldbank.org/indicators, (Erişim Tarihi: 10.10.2021).
  • World Inequality Database (WID) (2021). World Wealth and Inequality Indicators. www.wid.world/data, (Erişim Tarihi: 10.10.2021).
  • Wu, R. & Xie, Z. (2020). Identifying the impact of income inequality on CO2 emissions: empirical evidence from OECD countries and non-OECD countries, 277, 2-16.
  • WUP, (2014). World Urbanisation Prospect: The 2014 Revision. ST/ESA/SER/366.
  • Yamaji, K., Matsuhashi, R., Nagata, Y. & Kaya, Y. (1993). A study on economic measures for CO2 reduction in Japan, Energy Policy, 21(2), 123-132.
  • York, R., Rosa, E.A. & Dietz, T. (2003). STIRPAT, IPAT and ImPACT: Analytic tools for unpacking the deriving forces of environmental impacts, Ecological Economics, 46, 351-365.
  • Zhou, A. & Li, J. (2020). Impact of income inequality and environmental regulation on environmental quality: evidence from China, Journal of Cleaner Production, 274, 1-14.
Toplam 47 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ekonomi
Bölüm ARAŞTIRMA MAKALESİ
Yazarlar

İbrahim Tekiner 0000-0002-1185-5974

Aykut Yağlıkara 0000-0001-6728-2477

Erken Görünüm Tarihi 27 Ekim 2023
Yayımlanma Tarihi 30 Kasım 2023
Gönderilme Tarihi 30 Ağustos 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 13 Sayı: 3

Kaynak Göster

APA Tekiner, İ., & Yağlıkara, A. (2023). Examining The Relationship Between Income Concentration And Environmental Pollution In The Context Of The STIRPAT Model: The BRICS Countries. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 13(3), 2533-2550. https://doi.org/10.48146/odusobiad.1168622

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