Research Article
BibTex RIS Cite

Yenilenebilir Enerji - Ekonomik Büyüme İlişkisi Açısından Türkiye ve AB Ülkelerinin Malmquist Endeksi ile Performans İncelemesi

Year 2022, Volume: 11 Issue: 2, 1022 - 1044, 30.06.2022
https://doi.org/10.15869/itobiad.937202

Abstract

Nüfus artışı, teknolojik gelişmeler vb. birçok faktör dünyadaki enerji ihtiyacını ve tüketimini hızla artırmaktadır. Son dönemlerde kişi başına düşen enerji tüketiminin artması ciddi boyutlara ulaşmış, enerji üretiminde dışa bağımlığı azaltma ve küresel ekonomik rekabette belirleyici bir aktör olma hususları enerji üretiminin önemini artırmıştır. Bu sebeple, enerji kaynaklarına sahip olan ülkeler, ekonomik olarak diğer ülkelerden farklı bir konuma geçmiştir. Bununla birlikte, günümüzdeki çevre sorunları, fosil kaynakların tükenebilir olması veya fosil kaynaklara sahip olunmaması vb. sebepler yenilenebilir enerji kaynaklarına ilgiyi artırmıştır. AB’ye üyelik sürecinde, Türkiye ve AB ülkelerinin yenilenebilir enerji performanslarının zaman içinde değerlendirilmesi literatüre ve yapılacak çalışmalara da katkı sağlayacaktır. Bu çalışmanın amacı, yenilenebilir enerji ve ekonomik büyüme ilişkisi açısından Türkiye ve AB ülkelerinin verimlilikleri değerlendirmektir. Çalışma kapsamında yapılan literatür incelemesi sonucu yenilenebilir enerji göstergeleri ile ilgili 5 değişken belirlenmiştir. Girdi değişkenleri; CO2 Salınımı, Toplam Enerji Tüketimindeki Yenilenebilir Enerji kullanımı (YEK), İşgücü (EMP) çıktı değişkenleri; Kişi Başına GSYİH ve Toplam Enerji Arzının İçindeki Yenilenebilir Enerji Oranı (TEAYEO)’dır. Çalışmada, bahsi geçen ekonomik ve yenilenebilir enerji göstergeleri yardımıyla 2008-2015 döneminde AB ülkeleri ve Türkiye’nin performanslarındaki değişimler değerlendirilmiştir. Zaman içindeki verimliliğin gelişimini değerlendirebilmek için Malmquist Toplam Faktör Verimliliği (TFV) endeksi kullanılmıştır. Malmquist Endeksi, Veri zarflama analizi (VZA) temelli bir endeks olduğundan karar verme birimleri (KVB) arasında homojeniteyi sağlayabilmek amacıyla kümeleme analizi yapılmış ve benzer ülkeler gruplandırılmıştır. Çalışma sonucunda, 2008-2015 dönemdeki TFV ortalama değerlerine göre ülkeleri sıraladığımızda, Lüksemburg’un diğer ülkelerden kayda değer bir farkla birinci sırada yer aldığı görülmektedir. Lüksemburg’u sırasıyla Belçika, Türkiye, Bulgaristan, Hırvatistan Slovenya, Kıbrıs vd. ülkeler takip etmektedir. Türkiye’nin de ortalama TFVG değerine göre başarılı ülkelerden olduğu görülmektedir.

References

  • Aydoğan, S., Şahin, M., & Söylemez, İ. (2017). Avrupa Ülkelerinin Çevre ve Enerji Performansına Yönelik Etkinlik Değerlendirmesi: Veri Zarflama Analizi Uygulaması. The International New Issues in Social Sciences, 5(5), 267-282.
  • Chen, W., ve Geng, W. (2017). Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input. Energy, 120, 283-292. https://doi.org/10.1016/j.energy.2016.11.080
  • Chien, T., ve Hu, J. L. (2007). Renewable energy and macroeconomic efficiency of OECD and non-OECD economies. Energy Policy, 35(7), 3606-3615.
  • Chiu, Y. H., Lin, J. C., Hsu, C. C., & Lee, J. W. (2013). Carbon Emission Allowances of Efficiency Analysis: Application of Super SBM ZSG-DEA Model. Polish Journal of Environmental Studies, 22(3).
  • Cicea, C., Marinescu, C., Popa, I., ve Dobrin, C. (2014). Environmental efficiency of investments in renewable energy: Comparative analysis at macroeconomic level. Renewable and Sustainable Energy Reviews, 30, 555-564.
  • Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik. SPSS ve lisrel uygulamaları. Ankara: Pegem Akademi.
  • De Paoli L., Maura S. ve Nicola P., (2010). Evaluating Security of Energy Supply in the EU: Implications for Project Appraisal, European Investment Bank.
  • Doğanay, H., ve Coşkun, O. (2017). Enerji kaynakları. Pegem Atıf İndeksi, 1-328.
  • Eskin, M. C. (2018). Yenilenebilir Enerji Kaynaklarının Çevreye ve Ekonomiye Etkisi. [Mali Hizmetler Uzmanlığı uzmanlık tezi]. Çevre ve Şehircilik Bakanlığı Strateji Geliştirme Başkanlığı.
  • Färe, R., Grosskopf, S., & Hernandez-Sancho, F. (2004). Environmental performance: an index number approach. Resource and Energy economics, 26(4), 343-352.
  • Fulginity, L. E. Ve Perrin L. K. (1997). LDC agriculture: non-parametric malmquist indexes, Journal of Development Economics, 53(2), 373-390.
  • Gökgöz, F., ve Güvercin, M. T. (2018). Energy security and renewable energy efficiency in EU. Renewable and Sustainable Energy Reviews, 96, 226-239. https://doi.org/10.1016/j.rser.2018.07.046
  • Guo, J., Zhu, D., Wu, X., & Yan, Y. (2017). Study on environment performance evaluation and regional differences of strictly-environmental-monitored cities in China. Sustainability, 9(12), 2094.
  • Halkos, G. E., & Tzeremes, N. G. (2012). Analyzing the Greek renewable energy sector: A Data Envelopment Analysis approach. Renewable and sustainable energy reviews, 16(5), 2884-2893.
  • Halkos, G. E., ve Tzeremes, N. G. (2014). Measuring the effect of Kyoto protocol agreement on countries’ environmental efficiency in CO 2 emissions: an application of conditional full frontiers. Journal of Productivity Analysis, 41(3), 367-382.
  • Hansen, P. ve Jaumard, B. (1997). Cluster analysis and mathematical programming, Mathematical Programming, 79(1-3), 191-215.
  • Hermoso-Orzáez, M. J., García-Alguacil, M., Terrados-Cepeda, J., & Brito, P. (2020). Measurement of environmental efficiency in the countries of the European Union with the enhanced data envelopment analysis method (DEA) during the period 2005–2012. Environmental Science and Pollution Research, 27(13), 15691-15715.
  • Jin, J., Zhou, D., & Zhou, P. (2014). Measuring environmental performance with stochastic environmental DEA: The case of APEC economies. Economic Modelling, 38, 80-86.
  • Kalaycı, Ş. (2005). SPSS Uygulamalı çok değişkenli istatistik teknikleri. Asil Yayın Dağıtım LTD.ŞTİ. 3. Baskı, s.350–369.
  • Kangallı, S. G., Uyar, U. ve Buyrukoğlu, S. (2014). OECD ülkelerinde ekonomik özgürlük: bir kümeleme analizi, Journal of Alanya Faculty of Business/Alanya İşletme Fakültesi Dergisi, 6(3), 95-109.
  • Karagöz, Y. (2016). SPSS 23 ve AMOS 23 uygulamalı istatistiksel analizler. Nobel Akademik Yayıncılık.
  • Kortelainen, M. (2008). Dynamic environmental performance analysis: A Malmquist index approach. Ecological Economics, 64(4), 701-715.
  • Kumar, S. (2006). Environmentally sensitive productivity growth: a global analysis using Malmquist–Luenberger index. Ecological Economics, 56(2), 280-293.
  • Mahadevan, R. (2002). A DEA approach to understanding the productivity growth of Malaysia’s manufacturing ındusteries, Asia Pasific Journal of Management, 19(4), 587-600.
  • Matsumoto, K. I., Makridou, G., & Doumpos, M. (2020). Evaluating environmental performance using data envelopment analysis: The case of European countries. Journal of cleaner production, 272, 122637.
  • Mavi, N. K., & Mavi, R. K. (2019). Energy and environmental efficiency of OECD countries in the context of the circular economy: Common weight analysis for malmquist productivity index. Journal Of Environmental Management, 247, 651-661. https://doi.org/10.1016/j.jenvman.2019.06.069
  • Menegaki, A. N. (2013). Growth and renewable energy in Europe: Benchmarking with data envelopment analysis. Renewable Energy, 60, 363-369. https://doi.org/10.1016/j.renene.2013.05.042
  • Oh, D. H. (2010). A global Malmquist-Luenberger productivity index. Journal of productivity analysis, 34(3), 183-197.
  • Sanz-Díaz, M. T., Velasco-Morente, F., Yñiguez, R., & Díaz-Calleja, E. (2017). An analysis of Spain's global and environmental efficiency from a European Union perspective. Energy Policy, 104, 183-193.
  • Seyhan, N., & Tolun Tayalı, S. (2019). Türkiye’nin Avrupa Birliği ülkelerine makroekonomik olarak yakınsaması üzerine. Turkish Studies-Economics, Finance, Politics, 14(3), 995-1010. http://dx.doi.org/10.29228/TurkishStudies.36852
  • Sueyoshi, T., ve Goto, M. (2013). DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations. Energy Economics, 40, 370-382. https://doi.org/10.1016/j.eneco.2013.07.013
  • Şimşek, N. (2011). Türkiye'nin Çevresel Enerji Etkinliği ve Toplam Faktör Verimliliği: Karşılaştırmalı Bir Analiz. Ege Academic Review, 11(3), 379-396.
  • Tinsley, H. E., ve Brown, S. D. (Eds.). (2000). Handbook of applied multivariate statistics and mathematical modeling. Academic press.
  • Topçuoğlu, Ö. (2016). Özelleştirmenin etkinlik ve verimliliğe yansıması: çimento sektörü üzerine bir uygulama, [Yayımlanmamış doktora tezi].Atatürk Üniversitesi Sosyal Bilimler Enstitüsü.
  • Wang, K., Wei, Y. M., & Zhang, X. (2013). Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. Applied Energy, 104, 105-116.
  • Wei, C., Löschel, A., & Liu, B. (2015). Energy-saving and emission-abatement potential of Chinese coal-fired power enterprise: A non-parametric analysis. Energy Economics, 49, 33-43
  • Woo, C., Chung, Y., Chun, D., Seo, H. ve Hong, S. (2015). The Static and Dynamic Environmental Efficiency of Renewable Energy: A Malmquist Index Analysis of OECD Countries. Renewable and Sustainable Energy Reviews, 47, 367-376.
  • Woo, C., Chung, Y., Chun, D., Seo, H., ve Hong, S. (2015). The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries. Renewable and Sustainable Energy Reviews, 47, 367-376. https://doi.org/10.1016/j.rser.2015.03.070
  • Wu, J., Zhu, Q., Yin, P., & Song, M. (2017). Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices. Operational Research, 17(3), 715-735.
  • Xie, B. C., Shang, L. F., Yang, S. B., ve Yi, B. W. (2014). Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countries. Energy, 74, 147-157. https://doi.org/10.1016/j.energy.2014.04.109
  • Yang, L., & Zhang, X. (2018). Assessing regional eco-efficiency from the perspective of resource, environmental and economic performance in China: A bootstrapping approach in global data envelopment analysis. Journal of cleaner production, 173, 100-111.
  • Yapar, M., (2020). Yenilenebilir enerji kaynakları kullanımı-iktisadi büyüme ilişkisi: gelişmekte olan ülkeler ve türkiye örneği. [Yayımlanmamış doktora tezi]. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü.
  • Yörük, B. K., & Zaim, O. (2005). Productivity growth in OECD countries: A comparison with Malmquist indices. Journal of Comparative Economics, 33(2), 401-420.
  • Zaim, O., ve Taşkın, F. (2000). Environmental efficiency in carbon dioxide emissions in the OECD: A non-parametric approach. Journal of Environmental Management, 58(2), 95-107.
  • Zhou, P. A. B. W., Ang, B. W., & Poh, K. L. (2006). Slacks-based efficiency measures for modeling environmental performance. Ecological Economics, 60(1), 111-118.
  • Zhou, P., Ang, B. W., ve Han, J. Y. (2010). Total factor carbon emission performance: a Malmquist index analysis. Energy Economics, 32(1), 194-201. https://doi.org/10.1016/j.eneco.2009.10.003
  • Zofı́o, J. L., & Prieto, A. M. (2001). Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries. Resource and Energy Economics, 23(1), 63-83. https://doi.org/10.1016/S0928-7655(00)00030
  • Zurano-Cervelló, P., Pozo, C., Mateo-Sanz, J. M., Jiménez, L., & Guillén-Gosálbez, G. (2019). Sustainability efficiency assessment of the electricity mix of the 28 EU member countries combining data envelopment analysis and optimized projections. Energy Policy, 134, 110921.

The Performance Analysis of Turkey and EU Countries with Malmquist Index in terms of Renewable Energy – Economic Growth Relationship

Year 2022, Volume: 11 Issue: 2, 1022 - 1044, 30.06.2022
https://doi.org/10.15869/itobiad.937202

Abstract

The need and consumption of energy in the world is increasing rapidly because of factors such as population growth and technological developments. In recent years, the increase in per capita energy consumption has reached remarkable levels, the purpose of reducing foreign dependency in energy production and being a determinant actor in global economic competition have increased the importance of energy production. For this reason, countries that have energy resources have moved to an economically different position than other countries. However, the reasons such as today's environmental problems, the exhaustion of fossil resources or the lack of fossil resources have increased the interest in renewable energy sources. In the EU membership process, evaluating the performances of Turkey and EU countries in context of renewable energy will contribute to the literature and studies. The aim of this study was to evaluate the efficiency of Turkey and EU countries in terms of renewable energy and economic growth relationship. As a result of the literature review conducted within the scope of the study, 5 variables related to renewable energy indicators were determined. CO2 Emission, Percentage of Renewable Electricity Output in Total Electric Output, Labor are input variables; GDP per capita and the Percentage of Renewable Energy in Total Energy Supply are output variables. In this study, changes in performances of EU countries and Turkey during the period 2008-2015 are evaluated with the help of aforementioned economic and renewable energy indicators. The Malmquist Total Factor Productivity (TFP) index was used to evaluate the development of productivity over time. Since the Malmquist Index is an index based on Data Envelopment Analysis (DEA), a cluster analysis has been performed and similar countries have been grouped in order to ensure homogeneity among decision-making units. Since the Malmquist Index is an index based on DEA, a cluster analysis has been performed and similar countries have been grouped in order to ensure homogeneity among decision-making units. As a result of the study, when the countries have been ranked according to TFP average values in the period 2008-2015, it is seen that Luxembourg ranks first with a significant difference from other countries. Belgium, Turkey, Bulgaria, Slovenia, Croatia, Cyprus follow Luxembourg respectively and Turkey also appears to be one of the successful countries according to the average value TFPD.

References

  • Aydoğan, S., Şahin, M., & Söylemez, İ. (2017). Avrupa Ülkelerinin Çevre ve Enerji Performansına Yönelik Etkinlik Değerlendirmesi: Veri Zarflama Analizi Uygulaması. The International New Issues in Social Sciences, 5(5), 267-282.
  • Chen, W., ve Geng, W. (2017). Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input. Energy, 120, 283-292. https://doi.org/10.1016/j.energy.2016.11.080
  • Chien, T., ve Hu, J. L. (2007). Renewable energy and macroeconomic efficiency of OECD and non-OECD economies. Energy Policy, 35(7), 3606-3615.
  • Chiu, Y. H., Lin, J. C., Hsu, C. C., & Lee, J. W. (2013). Carbon Emission Allowances of Efficiency Analysis: Application of Super SBM ZSG-DEA Model. Polish Journal of Environmental Studies, 22(3).
  • Cicea, C., Marinescu, C., Popa, I., ve Dobrin, C. (2014). Environmental efficiency of investments in renewable energy: Comparative analysis at macroeconomic level. Renewable and Sustainable Energy Reviews, 30, 555-564.
  • Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik. SPSS ve lisrel uygulamaları. Ankara: Pegem Akademi.
  • De Paoli L., Maura S. ve Nicola P., (2010). Evaluating Security of Energy Supply in the EU: Implications for Project Appraisal, European Investment Bank.
  • Doğanay, H., ve Coşkun, O. (2017). Enerji kaynakları. Pegem Atıf İndeksi, 1-328.
  • Eskin, M. C. (2018). Yenilenebilir Enerji Kaynaklarının Çevreye ve Ekonomiye Etkisi. [Mali Hizmetler Uzmanlığı uzmanlık tezi]. Çevre ve Şehircilik Bakanlığı Strateji Geliştirme Başkanlığı.
  • Färe, R., Grosskopf, S., & Hernandez-Sancho, F. (2004). Environmental performance: an index number approach. Resource and Energy economics, 26(4), 343-352.
  • Fulginity, L. E. Ve Perrin L. K. (1997). LDC agriculture: non-parametric malmquist indexes, Journal of Development Economics, 53(2), 373-390.
  • Gökgöz, F., ve Güvercin, M. T. (2018). Energy security and renewable energy efficiency in EU. Renewable and Sustainable Energy Reviews, 96, 226-239. https://doi.org/10.1016/j.rser.2018.07.046
  • Guo, J., Zhu, D., Wu, X., & Yan, Y. (2017). Study on environment performance evaluation and regional differences of strictly-environmental-monitored cities in China. Sustainability, 9(12), 2094.
  • Halkos, G. E., & Tzeremes, N. G. (2012). Analyzing the Greek renewable energy sector: A Data Envelopment Analysis approach. Renewable and sustainable energy reviews, 16(5), 2884-2893.
  • Halkos, G. E., ve Tzeremes, N. G. (2014). Measuring the effect of Kyoto protocol agreement on countries’ environmental efficiency in CO 2 emissions: an application of conditional full frontiers. Journal of Productivity Analysis, 41(3), 367-382.
  • Hansen, P. ve Jaumard, B. (1997). Cluster analysis and mathematical programming, Mathematical Programming, 79(1-3), 191-215.
  • Hermoso-Orzáez, M. J., García-Alguacil, M., Terrados-Cepeda, J., & Brito, P. (2020). Measurement of environmental efficiency in the countries of the European Union with the enhanced data envelopment analysis method (DEA) during the period 2005–2012. Environmental Science and Pollution Research, 27(13), 15691-15715.
  • Jin, J., Zhou, D., & Zhou, P. (2014). Measuring environmental performance with stochastic environmental DEA: The case of APEC economies. Economic Modelling, 38, 80-86.
  • Kalaycı, Ş. (2005). SPSS Uygulamalı çok değişkenli istatistik teknikleri. Asil Yayın Dağıtım LTD.ŞTİ. 3. Baskı, s.350–369.
  • Kangallı, S. G., Uyar, U. ve Buyrukoğlu, S. (2014). OECD ülkelerinde ekonomik özgürlük: bir kümeleme analizi, Journal of Alanya Faculty of Business/Alanya İşletme Fakültesi Dergisi, 6(3), 95-109.
  • Karagöz, Y. (2016). SPSS 23 ve AMOS 23 uygulamalı istatistiksel analizler. Nobel Akademik Yayıncılık.
  • Kortelainen, M. (2008). Dynamic environmental performance analysis: A Malmquist index approach. Ecological Economics, 64(4), 701-715.
  • Kumar, S. (2006). Environmentally sensitive productivity growth: a global analysis using Malmquist–Luenberger index. Ecological Economics, 56(2), 280-293.
  • Mahadevan, R. (2002). A DEA approach to understanding the productivity growth of Malaysia’s manufacturing ındusteries, Asia Pasific Journal of Management, 19(4), 587-600.
  • Matsumoto, K. I., Makridou, G., & Doumpos, M. (2020). Evaluating environmental performance using data envelopment analysis: The case of European countries. Journal of cleaner production, 272, 122637.
  • Mavi, N. K., & Mavi, R. K. (2019). Energy and environmental efficiency of OECD countries in the context of the circular economy: Common weight analysis for malmquist productivity index. Journal Of Environmental Management, 247, 651-661. https://doi.org/10.1016/j.jenvman.2019.06.069
  • Menegaki, A. N. (2013). Growth and renewable energy in Europe: Benchmarking with data envelopment analysis. Renewable Energy, 60, 363-369. https://doi.org/10.1016/j.renene.2013.05.042
  • Oh, D. H. (2010). A global Malmquist-Luenberger productivity index. Journal of productivity analysis, 34(3), 183-197.
  • Sanz-Díaz, M. T., Velasco-Morente, F., Yñiguez, R., & Díaz-Calleja, E. (2017). An analysis of Spain's global and environmental efficiency from a European Union perspective. Energy Policy, 104, 183-193.
  • Seyhan, N., & Tolun Tayalı, S. (2019). Türkiye’nin Avrupa Birliği ülkelerine makroekonomik olarak yakınsaması üzerine. Turkish Studies-Economics, Finance, Politics, 14(3), 995-1010. http://dx.doi.org/10.29228/TurkishStudies.36852
  • Sueyoshi, T., ve Goto, M. (2013). DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations. Energy Economics, 40, 370-382. https://doi.org/10.1016/j.eneco.2013.07.013
  • Şimşek, N. (2011). Türkiye'nin Çevresel Enerji Etkinliği ve Toplam Faktör Verimliliği: Karşılaştırmalı Bir Analiz. Ege Academic Review, 11(3), 379-396.
  • Tinsley, H. E., ve Brown, S. D. (Eds.). (2000). Handbook of applied multivariate statistics and mathematical modeling. Academic press.
  • Topçuoğlu, Ö. (2016). Özelleştirmenin etkinlik ve verimliliğe yansıması: çimento sektörü üzerine bir uygulama, [Yayımlanmamış doktora tezi].Atatürk Üniversitesi Sosyal Bilimler Enstitüsü.
  • Wang, K., Wei, Y. M., & Zhang, X. (2013). Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. Applied Energy, 104, 105-116.
  • Wei, C., Löschel, A., & Liu, B. (2015). Energy-saving and emission-abatement potential of Chinese coal-fired power enterprise: A non-parametric analysis. Energy Economics, 49, 33-43
  • Woo, C., Chung, Y., Chun, D., Seo, H. ve Hong, S. (2015). The Static and Dynamic Environmental Efficiency of Renewable Energy: A Malmquist Index Analysis of OECD Countries. Renewable and Sustainable Energy Reviews, 47, 367-376.
  • Woo, C., Chung, Y., Chun, D., Seo, H., ve Hong, S. (2015). The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries. Renewable and Sustainable Energy Reviews, 47, 367-376. https://doi.org/10.1016/j.rser.2015.03.070
  • Wu, J., Zhu, Q., Yin, P., & Song, M. (2017). Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices. Operational Research, 17(3), 715-735.
  • Xie, B. C., Shang, L. F., Yang, S. B., ve Yi, B. W. (2014). Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countries. Energy, 74, 147-157. https://doi.org/10.1016/j.energy.2014.04.109
  • Yang, L., & Zhang, X. (2018). Assessing regional eco-efficiency from the perspective of resource, environmental and economic performance in China: A bootstrapping approach in global data envelopment analysis. Journal of cleaner production, 173, 100-111.
  • Yapar, M., (2020). Yenilenebilir enerji kaynakları kullanımı-iktisadi büyüme ilişkisi: gelişmekte olan ülkeler ve türkiye örneği. [Yayımlanmamış doktora tezi]. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü.
  • Yörük, B. K., & Zaim, O. (2005). Productivity growth in OECD countries: A comparison with Malmquist indices. Journal of Comparative Economics, 33(2), 401-420.
  • Zaim, O., ve Taşkın, F. (2000). Environmental efficiency in carbon dioxide emissions in the OECD: A non-parametric approach. Journal of Environmental Management, 58(2), 95-107.
  • Zhou, P. A. B. W., Ang, B. W., & Poh, K. L. (2006). Slacks-based efficiency measures for modeling environmental performance. Ecological Economics, 60(1), 111-118.
  • Zhou, P., Ang, B. W., ve Han, J. Y. (2010). Total factor carbon emission performance: a Malmquist index analysis. Energy Economics, 32(1), 194-201. https://doi.org/10.1016/j.eneco.2009.10.003
  • Zofı́o, J. L., & Prieto, A. M. (2001). Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries. Resource and Energy Economics, 23(1), 63-83. https://doi.org/10.1016/S0928-7655(00)00030
  • Zurano-Cervelló, P., Pozo, C., Mateo-Sanz, J. M., Jiménez, L., & Guillén-Gosálbez, G. (2019). Sustainability efficiency assessment of the electricity mix of the 28 EU member countries combining data envelopment analysis and optimized projections. Energy Policy, 134, 110921.
There are 48 citations in total.

Details

Primary Language Turkish
Subjects Economics
Journal Section Articles
Authors

Nazlı Seyhan 0000-0003-0759-9119

Burak Seyhan 0000-0003-1026-1805

Publication Date June 30, 2022
Published in Issue Year 2022 Volume: 11 Issue: 2

Cite

APA Seyhan, N., & Seyhan, B. (2022). Yenilenebilir Enerji - Ekonomik Büyüme İlişkisi Açısından Türkiye ve AB Ülkelerinin Malmquist Endeksi ile Performans İncelemesi. İnsan Ve Toplum Bilimleri Araştırmaları Dergisi, 11(2), 1022-1044. https://doi.org/10.15869/itobiad.937202

Journal of the Human and Social Science Researches is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY NC).