Effects of Environmental Innovations, Renewable Energy Consumption and Economic Growth on CO2 Emission: Panel Data Analysis for Select G-20 Countries

Abstract

Environmental problems are becoming more visible and this detrimental situation, negatively affecting the national economies. Therefore, the economic effects and costs of environmental problems have become an important research topic in the field of economics. In the literature, carbon dioxide (CO2) emission is generally used as an environmental pollution indicator. It is thought that renewable energy investments and innovative approaches to the environment can overcome environmental problems in the long run. In this study, the effect of environmental innovations (ETI), renewable energy (REC) and growth (GDP) on CO2 emission examined for 8 countries, listed according to the IMF's classification in the G-20 country group between 1993 and 2018. Durbin-H cointegration and FMOLS tests are used in the analysis, considering the cross-sectional dependency and heterogeneity. According to the analysis results, there is a long-term relationship between the variables. The effects of the variables considered on CO2 emission differ by country, the change in REC and GDP for the panel generally reduces CO2 emission, while the increase in ETI increases CO2 emission.

Keywords

• Environmental Innovations
• Renewable Energy
• Growth
• CO2 Emission

Çevresel İnovasyonlar, Yenilenebilir Enerji Tüketimi ve Ekonomik Büyümenin CO2 Emisyonu Üzerine Etkileri: Seçilmiş G-20 Ülkeleri için Panel Veri Analizi

Öz

Çevresel problemler her geçen gün katlanarak artmaktadır ve bu durum doğrudan ve dolaylı olarak ülke ekonomilerini de olumsuz yönde etkilemektedir. Bu nedenle çevresel problemlerin ekonomik etkileri ve maliyeti iktisat alanında önemli bir araştırma konusu haline gelmiştir. Çevresel kirlilik göstergesi olarak literatürde genellikle karbondioksit (CO2) emisyonu kullanılmaktadır. Yenilenebilir enerji yatırımları ve çevreye yönelik inovatif yaklaşımların uzun dönemde çevresel problemlerin üstesinden gelebileceği düşünülmektedir. Bu çalışmada çevresel inovasyonlar (ETI), yenilenebilir enerjinin (REC) ve büyümenin (GDP) CO2 emisyonu üzerindeki etkisi 1993-2018 yılları arasında G-20 ülke grubunda IMF’nin sınıflandırmasına göre gelişen statüsündeki 8 ülke için incelenmiştir. Analizde yatay kesit bağımlılığı ve heterojenliği dikkate alan Durbin-H eşbütünleşme ve FMOLS testleri kullanılmıştır. Analiz sonuçlarına göre değişkenler arasında uzun dönemli bir ilişki vardır. Ele alınan değişkenlerin CO2 emisyonu üzerindeki etkileri ülkeden ülkeye farklılık göstermektedir fakat panelin geneli için REC ve GDP’deki artışın CO2 emisyonu üzerindeki etkisi negatifken ETI’daki artışın etkisi beklenenin aksine pozitiftir.

Anahtar Kelimeler

• Çevresel İnovasyonlar
• Yenilenebilir Enerji
• Büyüme
• CO2 emisyonu

References

1. Alper, A., & Oguz, O. (2016). The role of renewable energy consumption in economic growth: Evidence from asymmetric causality. Renewable and Sustainable Energy Reviews, 60, 953-959.
2. Altıntaş, H., & Mercan, M. (2015). Ar-Ge Harcamaları ve Ekonomik Büyüme İlişkisi: OECD Ülkeleri Üzerine Yatay Kesit Bağımlılığı Altında Panel Eşbütünleşme Analizi. Ankara Üniversitesi SBF Dergisi, 70(2), 345-376.
3. Bai, C., Feng, C., Yan, H., Yi, X., Chen, Z., & Wei, W. (2020). Will income inequality influence the abatement effect of renewable energy technological innovation on carbon dioxide emissions?. Journal of environmental management, 264, 110482.
4. Bai, J., & Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica, 72(4), 1127-1177.
5. Bai, J., & Ng, S. (2010). Panel unit root tests with cross-section dependence: a further investigation. Econometric Theory, 1088-1114.
6. Cheng, C., Ren, X., & Wang, Z. (2019a). The impact of renewable energy and innovation on carbon emission: An empirical analysis for OECD countries. Energy Procedia, 158, 3506-3512.
7. Cheng, C., Ren, X., Wang, Z., & Yan, C. (2019b). Heterogeneous impacts of renewable energy and environmental patents on CO2 emission-Evidence from the BRIICS. Science of the total environment, 668, 1328-1338.
8. Demez S. (2021) OECD Ülkelerinde Çevresel Kuznets Eğrisi Hiptezinin Geçerliliği: Panel GMM Analizi. 10. Uluslararası Bilimsel Araştırmalar Kongresi, Nisan 2021 Ankara, 109-117. ISBN:978-625-7813-68-6.

9. Emrullah, M (2020). Sürdürülebilir Kalkınma Kapsamında Yeşil Lojistik: Avrupa Birliği ve Türkiye Örneği. Karadeniz Sosyal Bilimler Dergisi, 12(23), 101-114.
10. Erdoğan, S., Yıldırım, S., Yıldırım, D. Ç., & Gedikli, A. (2019) G20 Ülkelerinde İnovasyon ve CO2 Emisyonu. In International Congress of Energy Economy and Security (p. 193).
11. Esso LJ, Keho Y (2016) Energy consumption, economic growth and carbon emissions: cointegration and causality evidence from selected African countries. Energy Econ 114:492–497.
12. Fernández, Y. F., López, M. F., & Blanco, B. O. (2018). Innovation for sustainability: the impact of R&D spending on CO2 emissions. Journal of cleaner production, 172, 3459-3467.
13. Ganda, F. (2019). The impact of innovation and technology investments on carbon emissions in selected organisation for economic Co-operation and development countries. Journal of cleaner production, 217, 469-483.
14. Gormus, S., & Aydin, M. (2020). Revisiting the environmental Kuznets curve hypothesis using innovation: new evidence from the top 10 innovative economies. Environmental Science and Pollution Research, 27, 27904-27913. Hasanov, F. J., Khan, Z., Hussain, M., & Tufail, M. (2021). Theoretical framework for the carbon emissions effects of technological progress and renewable energy consumption. Sustainable Development.
15. Lin, B., & Zhu, J. (2019). The role of renewable energy technological innovation on climate change: empirical evidence from China. Science of the Total Environment, 659, 1505-1512.
16. Mensah, C. N., Long, X., Boamah, K. B., Bediako, I. A., Dauda, L., & Salman, M. (2018). The effect of innovation on CO 2 emissions of OCED countries from 1990 to 2014. Environmental Science and Pollution Research, 25(29), 29678-29698.
17. Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels (IZA Discussion Paper No. 1240). Institute for the Study of Labor (IZA).
18. 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.
19. 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.
20. Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of econometrics, 142(1), 50-93.
21. Pesaran, M. H., Smith, L. V., & Yamagata, T. (2013). Panel unit root tests in the presence of a multifactor error structure. Journal of Econometrics, 175(2), 94-115.
22. Reese, S., & Westerlund, J. (2016). Panicca: Panic on cross‐section averages. Journal of Applied Econometrics, 31(6), 961-981.
23. Roberts, J. T., & Grımes, P. E. (1997). Carbon intensity and economic development 1962–1991: a brief exploration of the environmental Kuznets curve. World development, 25(2), 191-198.
24. San Cristóbal, J. R. (2011). Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method. Renewable energy, 36(2), 498-502.
25. Santra, S. (2017). The effect of technological innovation on production-based energy and CO2 emission productivity: evidence from BRICS countries. African Journal of Science, Technology, Innovation and Development, 9(5), 503-512.
26. Saudi, M. H. M., Sinago, O., Jabarullah, H., N. (2019). The role of renewable, non-renewable energy consumption and technology innovation in testing environmental Kuznets curve in Malaysia.
27. Schumpeter, J., & Backhaus, U. (2003). The theory of economic development. In Joseph Alois Schumpeter (pp. 61-116). Springer, Boston, MA.
28. Temelli, F., & Şahin, D. (2019). Yükselen Piyasa Ekonomilerinde Finansal Gelişme, Ekonomik Büyüme ve Teknolojik Gelişmenin Çevresel Kalite Üzerine Etkisinin Analizi. Karabük Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9(2), 577-593.
29. Wang, L., Chang, H. L., Rizvi, S. K. A., & Sari, A. (2020). Are eco-innovation and export diversification mutually exclusive to control carbon emissions in G-7 countries?. Journal of Environmental Management, 270, 110829.
30. Wang, Z., & Zhu, Y. (2020). Do energy technology innovations contribute to CO2 emissions abatement? A spatial perspective. Science of the Total Environment, 726, 138574.
31. Westerlund, J. (2008). Panel cointegration tests of the Fisher effect. Journal of Applied Econometrics, 23(2), 193-233.
32. Yerdelen Tatoğlu, F. (2017). Panel Zaman Serileri Analizi Stata Uygulamalı (1. Baskı). Beta yayınevi, İstanbul.
33. Yerdelen Tatoğlu, F., & İçen, H. (2019). Çevresel Kuznets Eğrisinin Çok Boyutlu Panel Veri Modelleri ile Analizi. Anadolu İktisat ve İşletme Dergisi, 3(1), 26-38.
34. Yilanci, V., & Ozgur, O. (2019). Testing the environmental Kuznets curve for G7 countries: evidence from a bootstrap panel causality test in rolling windows. Environmental Science and Pollution Research, 26(24), 24795-24805.