Türkiye’de Yenilenebilir Enerji Tüketimi, Tarım ve CO2 Emisyonu İlişkisi

Yıl 2020, , 21 - 34, 25.03.2019

İlyas Okumuş

https://doi.org/10.20979/ueyd.659092

Cited By: 14

Öz

Bu çalışmanın amacı, tarımsal katma değer, ekonomik büyüme, yenilenemez ve yenilenebilir enerji tüketimi, kentleşme oranı, dışa açıklık oranı ve CO2 emisyonunu ilişkisini Türkiye için 1968-2014 yıllarını kapsayan dönem için ARDL sınır testi kullanılarak açıklamaktır. Analiz sonuçları, modele dâhil edilen değişkenler arasında uzun dönemli bir ilişki olduğunu göstermiştir. Ayrıca, Türkiye’de ÇKE hipotezinin varlığı doğrulanmıştır. Ayrıca, tarımsal katma değerin, yenilenemez enerji tüketiminin, ticari serbestleşmenin ve kentleşmenin hem kısa hem de uzun dönemde CO2 emisyonunu artırdığı sonucuna ulaşılmıştır. Diğer yandan, yenilenebilir enerji tüketiminin kısa dönemde karbon emisyonunu azalttığı ancak uzun dönemde yenilenebilir enerji tüketiminin etkisinin istatistiksel olarak anlamsız olduğu görülmektedir.

Anahtar Kelimeler

Yenilenebilir Enerji Tüketimi, Tarımsal Katma Değer, CO2 emisyonu, Çevresel Kuznets Eğrisi Hipotezi, Türkiye

Renewable Energy Consumption, Agriculture and CO2 Emissions Nexus in Turkey

Öz

The purpose of this study is to explain the relationship between agricultural value added, economic growth, non-renewable and renewable energy consumption, urbanization rate, trade openness rate and CO2 emission in Turkey over the period 1968-2014 using ARDL bound test. Analysis results showed that there is a long-run relationship between the variables included in the model. In addition, it is confirmed the existence of the environmental Kuznets curve (EKC) hypothesis in Turkey. In addition, it is concluded that agricultural value added, non-renewable energy consumption, trade openness and urbanization increase CO2 emissions in both short and long-run. On the other hand, renewable energy consumption reduces carbon emissions in the short-run, but the impact of renewable energy consumption on CO2 emission in the long-run is statistically insignificant.

Anahtar Kelimeler

Renewable Energy Consumption, Agricultural Value Added

Kaynakça

• Bayrakcı, A. G. ve Koçar, G. (2012). Utilization of renewable energies in Turkey's agriculture. Renewable and Sustainable Energy Reviews, 16(1), 618-633.
• Ben Jebli, M. ve Ben Youssef, S. (2017). Renewable energy consumption and agriculture: evidence for cointegration and Granger causality for Tunisian economy. International Journal of Sustainable Development & World Ecology, 24(2), 149-158.
• Bento, J. P. C. ve Moutinho, V. (2016). CO2 emissions, non-renewable and renewable electricity production, economic growth, and international trade in Italy. Renewable and Sustainable Energy Reviews, 55, 142-155.
• Bhattacharya, M., Churchill, S. A. ve Paramati, S. R. (2017). The dynamic impact of renewable energy and institutions on economic output and CO2 emissions across regions. Renewable Energy, 111, 157-167.
• Bilgili, F., Koçak, E. ve Bulut, Ü. (2016). The dynamic impact of renewable energy consumption on CO2 emissions: a revisited Environmental Kuznets Curve approach. Renewable and Sustainable Energy Reviews, 54, 838-845.
• Bölük, G. ve Mert, M. (2014). Fossil & renewable energy consumption, GHGs (greenhouse gases) and economic growth: Evidence from a panel of EU (European Union) countries. Energy, 74, 439-446.
• Bölük, G. ve Mert, M. (2015). The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach. Renewable and Sustainable Energy Reviews, 52, 587-595.
• BP. (2018). Statistical Review of World Energy. London, UK.
• Chen, Y., Wang, Z. ve Zhong, Z. (2019). CO2 emissions, economic growth, renewable and non-renewable energy production and foreign trade in China. Renewable energy, 131, 208-216.
• Destek, M. A., Ulucak, R. ve Dogan, E. (2018). Analyzing the environmental Kuznets curve for the EU countries: the role of ecological footprint. Environmental Science and Pollution Research, 25(29), 29387-29396.
• Dogan, E. ve Ozturk, I. (2017). The influence of renewable and non-renewable energy consumption and real income on CO 2 emissions in the USA: evidence from structural break tests. Environmental Science and Pollution Research, 24(11), 10846-10854.
• Dong, K., Sun, R. ve Hochman, G. (2017). Do natural gas and renewable energy consumption lead to less CO2 emission? Empirical evidence from a panel of BRICS countries. Energy, 141, 1466-1478.
• Engle, R. F. ve Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
• Inglesi-Lotz, R. ve Dogan, E. (2018). The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub-Saharan Africa’s Βig 10 electricity generators. Renewable Energy, 123, 36-43.
• Invest in Turkey. (2019). Turkish Agri-Food Industry outlook. Erişim Adresi https://www.invest.gov.tr/en/publications/lists/investpublications/agrofood-industry.pdf
• IPCC. (2014). Working Group Ⅲcontribution to the IPCC Fifth Assessment Report. https://www.ipcc.ch/report/ar5/wg3/.
• Jebli, M. B. ve Youssef, S. B. (2017). The role of renewable energy and agriculture in reducing CO2 emissions: Evidence for North Africa countries. Ecological Indicators, 74, 295-301.
• Johansen, S. ve Juselius, K. (1990). Some structural hypotheses in a multivariate cointegration analysis of the purchasing power parity and the uncovered interest parity for UK (No. 90-05).
• Liu, X., Zhang, S. ve Bae, J. (2017). The impact of renewable energy and agriculture on carbon dioxide emissions: investigating the environmental Kuznets curve in four selected ASEAN countries. Journal of Cleaner Production, 164, 1239-1247.
• Paramati, S. R., Mo, D. ve Gupta, R. (2017). The effects of stock market growth and renewable energy use on CO2 emissions: evidence from G20 countries. Energy Economics, 66, 360-371.
• Pata, U. K. (2018). Renewable energy consumption, urbanization, financial development, income and CO2 emissions in Turkey: testing EKC hypothesis with structural breaks. Journal of Cleaner Production, 187, 770-779.
• Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica: Journal of the Econometric Society, 1361-1401.
• Pesaran, M. H., & Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31, 371-413.
• Pesaran, M. H., Shin, Y. ve Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326.
• Reynolds, L. ve Wenzlau, S. (2012). Climate-Friendly Agriculture and Renewable Energy: Working Hand-in-Hand toward Climate Mitigation. Worldwatch Institute. ed.
• Sinha, A. ve Shahbaz, M. (2018). Estimation of Environmental Kuznets Curve for CO2 emission: Role of renewable energy generation in India. Renewable energy, 119, 703-711.
• Waheed, R., Chang, D., Sarwar, S., & Chen, W. (2018). Forest, agriculture, renewable energy, and CO2 emission. Journal of Cleaner Production, 172, 4231-4238.
• WDI .(2018). World Development Indicators, World Bank.
• Zivot, E. ve Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of business & economic statistics, 20(1), 25-44.