BRICS Ekonomilerinin Birincil Enerji Tüketimi için Trend Analiziyle Türetilen Tahmin Modelleri
Yıl 2026,
Cilt: 9 Sayı: 1, 86 - 104, 14.01.2026
Imene Rogai
,
İzzet Karakurt
,
Gökhan Aydın
Öz
Bu çalışmada, dünya çapında BRICS olarak bilinen Brezilya, Rusya Federasyonu, Hindistan, Çin ve Güney Afrika ekonomilerinin birincil enerji tüketimleri (PEC) için 1985'ten 2023'e kadarki toplam nüfus (TP) ve birincil enerji tüketimleri (PEC) bağımsız ve bağımlı değişkenler olarak kullanılarak trend analizi tabanlı tahmin modelleri türetilmiştir. Türetilen modeller daha sonra çeşitli indisler ile istatistiksel olarak doğrulanmıştır. Aynı zamanda, türetilen modellerin tahmin doğrulukları da çeşitli hata göstergeleri kullanılarak ölçülmüştür. Ek olarak, BRICS ekonomilerinin PEC’leri önerilen modeller kullanılarak 2025'ten 2035'e kadar tahmin edilmiştir. Sonuçlar, ilgili ekonomilerin gelecekteki PEC’lerinin önerilen modellerle başarılı bir şekilde tahmin edilebileceğini ortaya koymuştur. Ayrıca, tahmin sonuçları ilgili ekonomilerin gelecekteki PEC’lerinde önemli artışların beklendiğini açıkça göstermiştir.
Kaynakça
-
Aydin G., Kaya S., Karakurt I. Modeling of energy consumption based on population: The case of Turkey. 24th International Mining Congress and Exhibition of Turkey, 14-17 April 2015, Antalya, pp. 88-92.
-
Aydin G. Production modeling in the oil and natural gas industry: An application of trend analysis. Petroleum Science and Technology 2014; 32(5): 555-564.
-
Aydin G. Forecasting natural gas production using various regression models. Petroleum Science and Technology 2015; 33: 1486–1492.
-
Azadeh A., Saberi M., Asadzadeh SM., Khakestani M. A hybrid fuzzy mathematical programming-design of experiment framework for improvement of energy consumption estimation with small data sets and uncertainty: The cases of USA, Canada, Singapore, Pakistan and Iran. Energy 2011; 36(12): 6981-6992.
-
Azevedo VG., Sartori S., Campos LMS. CO2 emissions: A quantitative analysis among the BRICS nations. Renewable and Sustainable Energy Reviews 2018, 81: 107–115.
-
Bianco V., Manca O., Nardini S. Electricity consumption forecasting in Italy using linear regression models. Energy 2009; 34(9): 1413-1421.
-
Bianco V., Manca O., Nardini S., Mine AA. Analysis and forecasting of nonresidential electricity consumption in Romania. Applied Energy 2010; 87(11): 3584–3590.
-
Bianco V., Scarpa F., Tagliafico LA. Analysis and future outlook of natural gas consumption in the Italian residential sector. Energy Conversion and Management 2014; 87: 754–764.
-
BP. 2020. Technical report on BP energy outlook 2035. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy, (accessed on 15 February 2025).
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BP. 2023. British Petroleum Energy Outlook – 2022, Insights from the Accelerated, Net Zero and New Momentum scenarios – Brazil. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2022-country-insight-brazil.pdf (2024, accessed on 10 March 2025).
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BP. 2023a. Statistical review of world energy 2022. Retrieved from https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html (accessed on 10 February 2025).
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BP. 2023b. British Petroleum Energy Outlook – 2022, Insights from the Accelerated, Net Zero and New Momentum scenarios – China. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2022-country-insight-china.pdf (accessed on 5 March 2025).
-
BP. 2023c. British Petroleum Energy Outlook – 2022, Insights from the Accelerated, Net Zero and New Momentum scenarios – India. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2022-country-insight-india.pdf (accessed on 1 January 2025).
-
Byrne RF. Beyond traditional time-series: Using demand sensing to improve forecasts in volatile times. Journal of Business Forecasting 2012; 31(2): 13-20.
-
Cambazogu B. Comparative macroeconomic analysis of CIVETS Countries. Turkish Studies - Social Sciences 2021; 15(2): 77-91.
-
Celiker M., Yukseler U., Dursun UF. Trend analyses for discharge-recharge of Tacin karstic spring (Kayseri, Türkiye). Journal of African Earth Sciences 2021; 184: 104344.
-
Chang CL., Fang M. Renewable energy-led growth hypothesis: New insights from BRICS and N-11 economies. Renewable Energy 2022; 188: 788-800.
-
Chiu YB., Lee CC. Effects of financial development on energy consumption: The role of country risks. Energy Economics 2020; 90: 104833.
-
Demircioglu M., Esiyok S. Energy consumption forecast of Turkey using artificial neural networks from a sustainability perspective. International Journal of Sustainable Energy 2022; 41(8): 1127–1141.
-
Despotovic M., Nedic V., Despotovic D., Cvetanovic S. Review and statistical analysis of different global solar radiation sunshine models. Renewable and Sustainable Energy Reviews 2015; 52: 1869–1880.
-
Ehigiamusoe KU., Dogan E. The role of interaction effect between renewable energy consumption and real income in carbon emissions: Evidence from low-income countries. Renewable and Sustainable Energy Reviews 2022; 154: 111883.
-
EI. 2024. Statistical review of world energy 2024. Retrieved from https://www.energyinst.org/statistical-review (accessed on 12 December 2024).
-
Erba S., Beydoğan HO. Attitudes of educators towards educational research. Kırsehir Journal of the Faculty of Education 2017; 18(3): 246-260.
-
Ergezer EC. 2025. BRICS expansion and the rising voice of the global south. Turkish Economic Policy Research Foundation, an evaluation note, https://www.tepav.org.tr/upload/files/1705388852BRICS_genislemesi_ve_kuresel_Guney___in_yukselen_sesi.pdf (accessed 10 January 2025).
-
Fareed Z., Pata UK. Renewable, non-renewable energy consumption and income in top ten renewable energy-consuming countries: Advanced Fourier based panel data approaches. Renewable Energy 2022; 194: 805-821.
-
Gazder U. Energy consumption trends in energy scarce and rich countries: comparative study for Pakistan and Saudi Arabia. World Renewable Energy Congress-17, 4-8 December 2016, Bahrain, pp. 1 – 8.
-
Gusarove S. Role of China in the development of trade and FDI cooperation with BRICS countries. China Economic Review 2019; 101271.
-
Hartono D., Yusuf AA., Hastuti SH., Saputri NK., Syaifudin N. Effect of COVID-19 on energy consumption and carbon dioxide emissions in Indonesia. Sustainable Production and Consumption 2021; 28: 391–404.
-
IEA. 2021. World energy outlook 2021. Retrieved from https://www.iea.org/reports/world-energy-outlook-2021 (accessed on 12 December 2024).
-
IPCC. 2013. The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge (UK), NY (USA): Cambridge University Press.
-
Islam MM., Irfan M., Shahbaz M., Vo XV. Renewable and non-renewable energy consumption in Bangladesh: The relative influencing profiles of economic factors, urbanization, physical infrastructure and institutional quality. Renewable Energy 2022; 84: 1130-1149.
-
Kankal M., Akpınar A., Komurcu IM., Ozsahin ST. Modeling and forecasting of Turkey’s energy consumption using socio-economic and demographic variables. Applied Energy 2011; 88: 1927–1939.
-
Karakurt I. Energy consumption modelling using socio-economic indicators: Evidence from the BRICS-T countries. Journal of the Southern African Institute of Mining and Metallurgy 2020; 120(7): 425-43.
-
Karakurt I. Modelling and forecasting the oil consumptions of the BRICS-T countries. Energy 2021; 220: 119720.
-
Kartal MT. The role of consumption of energy, fossil sources, nuclear energy, and renewable energy on environmental degradation in top-five carbon producing countries. Renewable Energy 2022; 184: 871-880.
-
Kavaklıoğlu K., Ceylan H., Ozturk KH., Canyurt EO. Modeling and prediction of Turkey’s electricity consumption using artificial neural networks. Energy Conversion and Management 2009; 50: 2719–2727.
-
Khan AM., Osinska M. How to predict energy consumption in BRICS countries?. Energies 2021; 14: 2749.
-
Kim S., Kim H. A new metric of absolute percentage error for intermittent demand forecasts. International Journal of Forecasting 2016, 32(3): 669–679.
-
Kok B., Benli H. Energy diversity and nuclear energy for sustainable development in Turkey. Renewable Energy 2017; 111: 870-877.
-
Kone CA., Buke T. Forecasting of CO2 emissions from fuel combustion using trend analysis. Renewable and Sustainable Energy Reviews 2010; 14: 2906–2915.
-
Konuk F., Zeren F., Akpınar S., Yıldız S. Biomass energy consumption and economic growth: Further evidence from Next-11 countries. Energy Reports 2021; 7: 4825–4832.
-
Li MF., Tang XP., Wu W., Liu HB. General models for estimating daily global solar radiation for different solar radiation zones in mainland China. Energy Conversion and Management 2013; 70: 139–148.
-
Lorente DB., Driha OM., Halkos G., Mishra S. Influence of growth and urbanization on CO2 emissions: The moderating effect of foreign direct investment on energy use in BRICS. Sustainable Development 2022; 30: 227–240.
-
Mensah IA., Sun M., Gao C., Omari-Sasu AY., Zhu D., Ampimah BC., Quarcoo A. Analysis on the nexus of economic growth, fossil fuel energy consumption, CO2 emissions and oil price in Africa based on a PMG panel ARDL approach. Journal of Cleaner Production 2019; 228: 161-174.
-
Ostrom CW. Time Series Analysis - Regression Techniques. The USA: Sage Publications, 1978.
-
Paiva H., Afonso RJM., Caldeira FMSLA., Velasquez EA. A computational tool for trend analysis and forecast of the COVID-19 pandemic. Applied Soft Computing 2021; 105: 107289.
-
Pao HT., Tsai CM. Multivariate granger causality between CO2 emissions, energy consumption, FDI and GDP: Evidence from a panel of BRIC (Brazil, Russian Federation, India, and China) countries. Energy 2021; 36(1): 685-693.
-
PwC. The world in 2050. https://www.pwc.com/gx/en/world-2050/assets/pwc-the-world-in-2050-full-report-feb-2017.pdf. 2024.
-
Simba AHM., Oztek MF. Empirical analysis of energy consumption and economic growth in Tanzania: based on Engel and Granger test. Journal of Economics, Finance and Accounting 2021; 7(3): 250-262.
-
Somoye OA., Ozdeser H., Seraj M. Modeling the determinants of renewable energy consumption in Nigeria: Evidence from Autoregressive Distributed Lagged in error correction approach. Renewable Energy 2022; 190: 606-616.
-
Tabachnick BG., Fidell LS. Using multivariate statistics. Boston: Pearson, 2013.
-
Tuzemen OB., Tuzemen S. The impact of foreign direct investment and biomass energy consumption on pollution in BRICS countries: A panel data analysis. Global Journal of Emerging Market Economies 2022; 14(1): 76–92.
-
Uma J., Yun H., Jeong CS., Heo JH. Factor analysis and multiple regression between topography and precipitation on Jeju Island Korea. Journal of Hydrology 2011; 410: 189–203.
-
UN. 2018. United Nations, Department of Economic and Social Affairs, Population Division, World Urbanization Prospects: The 2018 Revision. https://population.un.org/wup/Download/ (accessed on 20 March 2025).
-
Wang M., Wang M., Wu L. Application of a new grey multivariate forecasting model in the forecasting of energy consumption in 7 regions of China. Energy 2022a; 243: 123024.
-
Wang Z., Pham TLH., Sun K., Wang B., Bui O., Hashemizadeh A. The moderating role of financial development in the renewable energy consumption - CO2 emissions linkage: The case study of Next-11 countries. Energy 2022b; 254: 124386.
-
WBI. 2025. Worldbank indicators on total population, https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS (accessed on 20 March 2025).
Yildirim DC., Yildirim S., Demirtas I. Investigating energy consumption and economic growth for BRICS-T countries. World Journal of Science, Technology and Sustainable Development 2019; 16(4): 84-195.
-
Zafar MV., Zaidi AH., Sinha A., Gedikli A., Hou F. The role of stock market and banking sector development, and renewable energy consumption in carbon emissions: Insights from G-7 and N-11 countries. Resources Policy 2019; 62: 427–436.
-
Zakarya G.Y., Mostefa B., Abbes SM., Seghir GM. Factors affecting CO2 emissions in the BRICS countries: A panel data analysis. Procedia Economics and Finance 2015; 26: 114 – 125.
-
Zeeshan M., Han J., Rehman A., Ullah I., Afridi FEA., Fareed Z. Comparative analysis of trade liberalization, CO2 emissions, energy consumption and economic growth in Southeast Asian and Latin American regions: A structural equation modeling approach. Frontiers in Environmental Science 2022; 10: 854590.
Forecast Models Derived by Trend Analysis for the BRICS Economies' Primary Energy Consumption
Yıl 2026,
Cilt: 9 Sayı: 1, 86 - 104, 14.01.2026
Imene Rogai
,
İzzet Karakurt
,
Gökhan Aydın
Öz
In this study, trend analysis-based forecast models were derived for the primary energy consumptions (PECs) of Brazil, the Russian Federation, India, China and South Africa economies, known as the BRICS worldwide using total population (TP) and PECs as independent and dependent variables from 1985 to 2023. The derived models were then statistically verified by several indices. Forecasting accuracies of the derived models were also measured using various error indicators. Additionally, the PECs of the BRICS economies were projected from 2025 to 2035 using the proposed models. The results reveal that the future PECs of the related economies can be successfully projected with the proposed models. Moreover, the forecasting results make it abundantly evident that substantial rises are anticipated for the related economies' future PECs. It is thought that the study's results will allow the way for the proposal and establishment of sustainable strategies for controlling the PECs of the BRICS economies using the proposed methodology.
Kaynakça
-
Aydin G., Kaya S., Karakurt I. Modeling of energy consumption based on population: The case of Turkey. 24th International Mining Congress and Exhibition of Turkey, 14-17 April 2015, Antalya, pp. 88-92.
-
Aydin G. Production modeling in the oil and natural gas industry: An application of trend analysis. Petroleum Science and Technology 2014; 32(5): 555-564.
-
Aydin G. Forecasting natural gas production using various regression models. Petroleum Science and Technology 2015; 33: 1486–1492.
-
Azadeh A., Saberi M., Asadzadeh SM., Khakestani M. A hybrid fuzzy mathematical programming-design of experiment framework for improvement of energy consumption estimation with small data sets and uncertainty: The cases of USA, Canada, Singapore, Pakistan and Iran. Energy 2011; 36(12): 6981-6992.
-
Azevedo VG., Sartori S., Campos LMS. CO2 emissions: A quantitative analysis among the BRICS nations. Renewable and Sustainable Energy Reviews 2018, 81: 107–115.
-
Bianco V., Manca O., Nardini S. Electricity consumption forecasting in Italy using linear regression models. Energy 2009; 34(9): 1413-1421.
-
Bianco V., Manca O., Nardini S., Mine AA. Analysis and forecasting of nonresidential electricity consumption in Romania. Applied Energy 2010; 87(11): 3584–3590.
-
Bianco V., Scarpa F., Tagliafico LA. Analysis and future outlook of natural gas consumption in the Italian residential sector. Energy Conversion and Management 2014; 87: 754–764.
-
BP. 2020. Technical report on BP energy outlook 2035. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy, (accessed on 15 February 2025).
-
BP. 2023. British Petroleum Energy Outlook – 2022, Insights from the Accelerated, Net Zero and New Momentum scenarios – Brazil. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2022-country-insight-brazil.pdf (2024, accessed on 10 March 2025).
-
BP. 2023a. Statistical review of world energy 2022. Retrieved from https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html (accessed on 10 February 2025).
-
BP. 2023b. British Petroleum Energy Outlook – 2022, Insights from the Accelerated, Net Zero and New Momentum scenarios – China. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2022-country-insight-china.pdf (accessed on 5 March 2025).
-
BP. 2023c. British Petroleum Energy Outlook – 2022, Insights from the Accelerated, Net Zero and New Momentum scenarios – India. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2022-country-insight-india.pdf (accessed on 1 January 2025).
-
Byrne RF. Beyond traditional time-series: Using demand sensing to improve forecasts in volatile times. Journal of Business Forecasting 2012; 31(2): 13-20.
-
Cambazogu B. Comparative macroeconomic analysis of CIVETS Countries. Turkish Studies - Social Sciences 2021; 15(2): 77-91.
-
Celiker M., Yukseler U., Dursun UF. Trend analyses for discharge-recharge of Tacin karstic spring (Kayseri, Türkiye). Journal of African Earth Sciences 2021; 184: 104344.
-
Chang CL., Fang M. Renewable energy-led growth hypothesis: New insights from BRICS and N-11 economies. Renewable Energy 2022; 188: 788-800.
-
Chiu YB., Lee CC. Effects of financial development on energy consumption: The role of country risks. Energy Economics 2020; 90: 104833.
-
Demircioglu M., Esiyok S. Energy consumption forecast of Turkey using artificial neural networks from a sustainability perspective. International Journal of Sustainable Energy 2022; 41(8): 1127–1141.
-
Despotovic M., Nedic V., Despotovic D., Cvetanovic S. Review and statistical analysis of different global solar radiation sunshine models. Renewable and Sustainable Energy Reviews 2015; 52: 1869–1880.
-
Ehigiamusoe KU., Dogan E. The role of interaction effect between renewable energy consumption and real income in carbon emissions: Evidence from low-income countries. Renewable and Sustainable Energy Reviews 2022; 154: 111883.
-
EI. 2024. Statistical review of world energy 2024. Retrieved from https://www.energyinst.org/statistical-review (accessed on 12 December 2024).
-
Erba S., Beydoğan HO. Attitudes of educators towards educational research. Kırsehir Journal of the Faculty of Education 2017; 18(3): 246-260.
-
Ergezer EC. 2025. BRICS expansion and the rising voice of the global south. Turkish Economic Policy Research Foundation, an evaluation note, https://www.tepav.org.tr/upload/files/1705388852BRICS_genislemesi_ve_kuresel_Guney___in_yukselen_sesi.pdf (accessed 10 January 2025).
-
Fareed Z., Pata UK. Renewable, non-renewable energy consumption and income in top ten renewable energy-consuming countries: Advanced Fourier based panel data approaches. Renewable Energy 2022; 194: 805-821.
-
Gazder U. Energy consumption trends in energy scarce and rich countries: comparative study for Pakistan and Saudi Arabia. World Renewable Energy Congress-17, 4-8 December 2016, Bahrain, pp. 1 – 8.
-
Gusarove S. Role of China in the development of trade and FDI cooperation with BRICS countries. China Economic Review 2019; 101271.
-
Hartono D., Yusuf AA., Hastuti SH., Saputri NK., Syaifudin N. Effect of COVID-19 on energy consumption and carbon dioxide emissions in Indonesia. Sustainable Production and Consumption 2021; 28: 391–404.
-
IEA. 2021. World energy outlook 2021. Retrieved from https://www.iea.org/reports/world-energy-outlook-2021 (accessed on 12 December 2024).
-
IPCC. 2013. The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge (UK), NY (USA): Cambridge University Press.
-
Islam MM., Irfan M., Shahbaz M., Vo XV. Renewable and non-renewable energy consumption in Bangladesh: The relative influencing profiles of economic factors, urbanization, physical infrastructure and institutional quality. Renewable Energy 2022; 84: 1130-1149.
-
Kankal M., Akpınar A., Komurcu IM., Ozsahin ST. Modeling and forecasting of Turkey’s energy consumption using socio-economic and demographic variables. Applied Energy 2011; 88: 1927–1939.
-
Karakurt I. Energy consumption modelling using socio-economic indicators: Evidence from the BRICS-T countries. Journal of the Southern African Institute of Mining and Metallurgy 2020; 120(7): 425-43.
-
Karakurt I. Modelling and forecasting the oil consumptions of the BRICS-T countries. Energy 2021; 220: 119720.
-
Kartal MT. The role of consumption of energy, fossil sources, nuclear energy, and renewable energy on environmental degradation in top-five carbon producing countries. Renewable Energy 2022; 184: 871-880.
-
Kavaklıoğlu K., Ceylan H., Ozturk KH., Canyurt EO. Modeling and prediction of Turkey’s electricity consumption using artificial neural networks. Energy Conversion and Management 2009; 50: 2719–2727.
-
Khan AM., Osinska M. How to predict energy consumption in BRICS countries?. Energies 2021; 14: 2749.
-
Kim S., Kim H. A new metric of absolute percentage error for intermittent demand forecasts. International Journal of Forecasting 2016, 32(3): 669–679.
-
Kok B., Benli H. Energy diversity and nuclear energy for sustainable development in Turkey. Renewable Energy 2017; 111: 870-877.
-
Kone CA., Buke T. Forecasting of CO2 emissions from fuel combustion using trend analysis. Renewable and Sustainable Energy Reviews 2010; 14: 2906–2915.
-
Konuk F., Zeren F., Akpınar S., Yıldız S. Biomass energy consumption and economic growth: Further evidence from Next-11 countries. Energy Reports 2021; 7: 4825–4832.
-
Li MF., Tang XP., Wu W., Liu HB. General models for estimating daily global solar radiation for different solar radiation zones in mainland China. Energy Conversion and Management 2013; 70: 139–148.
-
Lorente DB., Driha OM., Halkos G., Mishra S. Influence of growth and urbanization on CO2 emissions: The moderating effect of foreign direct investment on energy use in BRICS. Sustainable Development 2022; 30: 227–240.
-
Mensah IA., Sun M., Gao C., Omari-Sasu AY., Zhu D., Ampimah BC., Quarcoo A. Analysis on the nexus of economic growth, fossil fuel energy consumption, CO2 emissions and oil price in Africa based on a PMG panel ARDL approach. Journal of Cleaner Production 2019; 228: 161-174.
-
Ostrom CW. Time Series Analysis - Regression Techniques. The USA: Sage Publications, 1978.
-
Paiva H., Afonso RJM., Caldeira FMSLA., Velasquez EA. A computational tool for trend analysis and forecast of the COVID-19 pandemic. Applied Soft Computing 2021; 105: 107289.
-
Pao HT., Tsai CM. Multivariate granger causality between CO2 emissions, energy consumption, FDI and GDP: Evidence from a panel of BRIC (Brazil, Russian Federation, India, and China) countries. Energy 2021; 36(1): 685-693.
-
PwC. The world in 2050. https://www.pwc.com/gx/en/world-2050/assets/pwc-the-world-in-2050-full-report-feb-2017.pdf. 2024.
-
Simba AHM., Oztek MF. Empirical analysis of energy consumption and economic growth in Tanzania: based on Engel and Granger test. Journal of Economics, Finance and Accounting 2021; 7(3): 250-262.
-
Somoye OA., Ozdeser H., Seraj M. Modeling the determinants of renewable energy consumption in Nigeria: Evidence from Autoregressive Distributed Lagged in error correction approach. Renewable Energy 2022; 190: 606-616.
-
Tabachnick BG., Fidell LS. Using multivariate statistics. Boston: Pearson, 2013.
-
Tuzemen OB., Tuzemen S. The impact of foreign direct investment and biomass energy consumption on pollution in BRICS countries: A panel data analysis. Global Journal of Emerging Market Economies 2022; 14(1): 76–92.
-
Uma J., Yun H., Jeong CS., Heo JH. Factor analysis and multiple regression between topography and precipitation on Jeju Island Korea. Journal of Hydrology 2011; 410: 189–203.
-
UN. 2018. United Nations, Department of Economic and Social Affairs, Population Division, World Urbanization Prospects: The 2018 Revision. https://population.un.org/wup/Download/ (accessed on 20 March 2025).
-
Wang M., Wang M., Wu L. Application of a new grey multivariate forecasting model in the forecasting of energy consumption in 7 regions of China. Energy 2022a; 243: 123024.
-
Wang Z., Pham TLH., Sun K., Wang B., Bui O., Hashemizadeh A. The moderating role of financial development in the renewable energy consumption - CO2 emissions linkage: The case study of Next-11 countries. Energy 2022b; 254: 124386.
-
WBI. 2025. Worldbank indicators on total population, https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS (accessed on 20 March 2025).
Yildirim DC., Yildirim S., Demirtas I. Investigating energy consumption and economic growth for BRICS-T countries. World Journal of Science, Technology and Sustainable Development 2019; 16(4): 84-195.
-
Zafar MV., Zaidi AH., Sinha A., Gedikli A., Hou F. The role of stock market and banking sector development, and renewable energy consumption in carbon emissions: Insights from G-7 and N-11 countries. Resources Policy 2019; 62: 427–436.
-
Zakarya G.Y., Mostefa B., Abbes SM., Seghir GM. Factors affecting CO2 emissions in the BRICS countries: A panel data analysis. Procedia Economics and Finance 2015; 26: 114 – 125.
-
Zeeshan M., Han J., Rehman A., Ullah I., Afridi FEA., Fareed Z. Comparative analysis of trade liberalization, CO2 emissions, energy consumption and economic growth in Southeast Asian and Latin American regions: A structural equation modeling approach. Frontiers in Environmental Science 2022; 10: 854590.