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The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey

Year 2024, Volume: 8 Issue: 2, 586 - 599, 31.05.2024
https://doi.org/10.29023/alanyaakademik.1407903

Abstract

Agricultural practices and renewable energy consumption have a major impact on the absorption of heat-trapping greenhouse gases and are closely linked to climate change. The impact of agriculture on climate change is due to the GHGs such as methane, nitrous oxide and carbon dioxide carbon dioxide that are released into the atmosphere during the agricultural practices. Therefore, to avoid undesirable effects of agriculture on climate change, it is important to understand the relationship between agricultural activities and greenhouse gases. In this study, we analyze the long-term effects of agricultural efficiency, fertilizer use, and renewable energy consumption on total carbon emissions in Turkey. The analysis is performed in two steps. In the first step, the values of agricultural efficiency are calculated using the CEE method. In the second step, ARDL and NARDL models are used to estimate the long-term effects of agricultural efficiency, fertilizer use, renewable energy consumption, GDP and population on CO2 emissions. The results show that improving agricultural efficiency and increasing the share of renewable energy would reduce carbon emissions, while fertilizer use, GDP, and population have negative long-term effects on CO2. In addition, the results of the Wald test indicate asymmetric long-term effects of renewable energy, agricultural efficiency, and fertilizer use on climate change.

References

  • Adams, R.M., Hurd, B.H., Lenhart, S., & Leary, N. (1998). Effects of global climate change on agriculture: an interpretative review. Climate Research, 11(1), 19-30.
  • Adger, W.N., Pettenella, D., & Whitby, M. (1997). Land use in Europe and the reduction of greenhouse-gas emissions. Climate-Change Mitigation and European Land-Use Policies, 1-22.
  • Anderson, T.R., Hollingsworth, K., & Inman, L. (2002). The fixed weighting nature of a cross-evaluation model. Journal of Productivity Analysis, 17, 249-255.
  • Arı Y. (2021). Using COGARCH-filtered volatility in modelling within ARDL framework. in: Adıgüzel Mercangöz B. (eds) handbook of research on emerging theories, models, and applications of financial econometrics. Springer, Cham. (SCOPUS) https://doi.org/10.1007/978-3-030-54108-8_13
  • Ari, Y. (2022). - ARDL sınır testi uygulamaları üzerine tartışmalar. In: Mehmet Özcan (Eds). 21. yüzyılda iktisadı anlamak: Güncel ekonometrik zaman serileri çalışmaları. ISBN: 9786258374858. Gazi Kitabevi. https://www.researchgate.net/publication/363116601
  • Arora, N.K. (2019). Impact of climate change on agriculture production and its sustainable solutions. Environmental Sustainability, 2(2), 95-96.
  • Aydinalp, C., & Cresser, M.S. (2008). The effects of global climate change on agriculture. American-Eurasian Journal of Agricultural & Environmental Sciences, 3(5), 672-676.
  • Çam, S., Karataş, A.S., & Lopcu, K. (2022). The puzzle of energy efficiency in Turkey: combining a multiple criteria decision making and the time series analysis. Energy Sources, Part B: Economics, Planning, and Policy, 17(1), 2136791.
  • Chen, S., Chen, X., & Xu, J. (2016). Impacts of climate change on agriculture: Evidence from China. Journal of Environmental Economics and Management, 76, 105-124.
  • Chen, Y., Miao, J., & Zhu, Z. (2021). Measuring green total factor productivity of China's agricultural sector: A three-stage SBM-DEA model with non-point source pollution and CO2 emissions. Journal of Cleaner Production, 318, 128543.
  • Closset, M., Dhehibi B.B.B., & Aw-Hassan, A.A. (2015). Measuring the economic impact of climate change on agriculture: a Ricardian analysis of farmlands in Tajikistan. Climate and Development 7(5): 454-468.
  • Cui, H., Zhao, T., & Shi, H. (2018). STIRPAT-based driving factor decomposition analysis of agricultural carbon emissions in Hebei, China. Polish Journal of Environmental Studies, 27(4).
  • Deng, X., & Gibson, J. (2019). Improving eco-efficiency for the sustainable agricultural production: A case study in Shandong, China. Technological Forecasting and Social Change, 144, 394-400.
  • Dumrul, Y., & Kilicaslan, Z. (2017). Economic impacts of climate change on agriculture: Empirical evidence from ARDL approach for Turkey. Journal of Business Economics and Finance, 6(4), 336-347.
  • EPA (United State Environmental Protection Agency). 2023. Greenhouse emissions/ Sources of greenhouse gas emissions. Access date: June 8, 2023. Available at: https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions
  • FAO (The Food and Agriculture Organization). 2018. Global, regional and country trends 2000–2018. Access date: June 8, 2023. Available at: https://www.fao.org/3/cb3808en/cb3808en.pdf
  • Flessa, H., Ruser, R., Dörsch, P., Kamp, T., Jimenez, M.A., Munch, J.C., & Beese, F. (2002). Integrated evaluation of greenhouse gas emissions (CO2, CH4, N2O) from two farming systems in southern Germany. Agriculture, Ecosystems & Environment, 91(1-3), 175-189.
  • Fróna, D., Szenderák, J., & Harangi-Rákos, M. (2019). The challenge of feeding the world. Sustainability, 11(20), 5816.
  • Guo, L., Zhao, S., Song, Y., Tang, M., & Li, H. (2022). Green finance, chemical fertilizer use and carbon emissions from agricultural production. Agriculture, 12(3), 313.
  • IAEA (International Atomic Energy Agency). 2023. Nuclear technology and applications/food and agriculture/climate-smart agriculture/greenhouse gas reduction. Access date: June 8, 2023. Available at: https://www.iaea.org/topics/greenhouse-gas-reduction
  • Lal, R. (2004). Carbon emission from farm operations. Environment International, 30(7), 981-990.
  • Liang, L., Wu, J., Cook, W.D., & Zhu, J. (2008). Alternative secondary goals in DEA cross-efficiency evaluation. International Journal of Production Economics, 113(2), 1025-1030.
  • Lovins, A. (2017). Energy efficiency. Energy Economics, 1, 234-258
  • Malhi, G.S., Kaur, M., & Kaushik, P. (2021). Impact of climate change on agriculture and its mitigation strategies: A review. Sustainability, 13(3), 1318.
  • Manogna R.L., & Mishra, A.K. (2022). Agricultural production efficiency of Indian states: Evidence from data envelopment analysis. International Journal of Finance & Economics, 27(4), 4244-4255.
  • Menegaki, A.N. (2019). The ARDL method in the energy-growth nexus field; best implementation strategies. Economies, 7(4), 105.
  • Namahoro, J.P., Wu, Q., Zhou, N., & Xue, S. (2021). Impact of energy intensity, renewable energy, and economic growth on CO2 emissions: Evidence from Africa across regions and income levels. Renewable and Sustainable Energy Reviews, 147, 111233.
  • Nandy, A., & Singh, P.K. (2020). Farm efficiency estimation using a hybrid approach of machine-learning and data envelopment analysis: Evidence from rural eastern India. Journal of Cleaner Production, 267, 122106.
  • Ogundari, K. (2014). The paradigm of agricultural efficiency and its implication on food security in Africa: what does meta-analysis reveal?. World Development, 64, 690-702.
  • Ojha, H.R., Sulaiman, V. R., Sultana, P., Dahal, K., Thapa, D., Mittal, N., ... & Aggarwal, P. (2014). Is South Asian agriculture adapting to climate change? Evidence from the Indo-Gangetic Plains. Agroecology and Sustainable Food Systems 38(5): 505-531.
  • Oliver, T.H., & Morecroft, M.D. (2014). Interactions between climate change and land use change on biodiversity: attribution problems, risks, and opportunities. Wiley Interdisciplinary Reviews: Climate Change, 5(3), 317-335.
  • Örkcü, H., & Örkcü, M. (2015). Data Envelopment Analysis cross efficiency evaluation approach to the technology selection. Gazi University Journal of Science Part A: Engineering and Innovation, 3(1), 1-14. Our World in Data. 2023. Emissions by sector. Access date: June 8, 2023. Available at: https://ourworldindata.org/emissions-by-sector
  • Ouraich, I., Dudu, H., Tyner, W.E., & Cakmak, E.H. (2019). Agriculture, trade, and climate change adaptation: a global CGE analysis for Morocco and Turkey. The Journal of North African Studies 24(6): 961-991.
  • Patterson, M.G. (1996). What is energy efficiency?: Concepts, indicators and methodological issues. Energy Policy, 24(5), 377-390.
  • Pesaran, M.H., Shin, Y., & Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16(3): 289-326.
  • Raihan, A., & Tuspekova, A. (2022). The nexus between economic growth, renewable energy use, agricultural land expansion, and carbon emissions: New insights from Peru. Energy Nexus, 6, 100067.
  • Ramírez, C.A., & Worrell, E. (2006). Feeding fossil fuels to the soil: An analysis of energy embedded and technological learning in the fertilizer industry. Resources, Conservation and Recycling, 46(1), 75-93.
  • Scialabba, N.E.H., & Müller-Lindenlauf, M. (2010). Organic agriculture and climate change. Renewable Agriculture and Food Systems, 25(2), 158-169.
  • Sexton, T.R., Silkman, R.H., & Hogan, A.J. (1986). Data envelopment analysis: Critique and extensions. New Directions for Program Evaluation, 1986(32), 73-105.
  • Shanmugam, K.R., & Venkataramani, A. (2006). Technical efficiency in agricultural production and its determinants: An exploratory study at the district level. Indian Journal of Agricultural Economics, 61(2).
  • Sharma, N., & Singhvi, R. (2017). Effects of chemical fertilizers and pesticides on human health and environment: a review. International Journal of Agriculture, Environment and Biotechnology, 10(6), 675-680.
  • Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in Honor of Peter Schmidt, ed. R.C. Sickles and W.C. Horrace, 281-314. New York: Springer.
  • Sun, X., Dong, Y., Wang, Y., & Ren, J. (2022). Sources of greenhouse gas emission reductions in OECD countries: Composition or technique effects. Ecological Economics, 193, 107288.
  • Talaei, A., Gemechu, E., & Kumar, A. (2020). Key factors affecting greenhouse gas emissions in the Canadian industrial sector: A decomposition analysis. Journal of Cleaner Production, 246, 119026.
  • Tilman, D., Balzer, C., Hill, J., & Befort, B.L. (2011). Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences, 108(50), 20260-20264.
  • Tongwane, M.I., & Moeletsi, M.E. (2018). A review of greenhouse gas emissions from the agriculture sector in Africa. Agricultural Systems, 166, 124-134.
  • Turhan, M.S., & Arı, Y. (2021) Örgütsel ekoloji ve kooperatif örgütlenmeleri: Türkiye’de tarım, ormancılık ve balıkçılık sektörü üzerine bir analiz. Üçüncü Sektör Sosyal Ekonomi Dergisi, 56(3), 1436-1454. doi: 10.15659/3.sektor-sosyal-ekonomi.21.08.1609
  • Uri, N.D. 2001. The potential impact of conservation practices in US agriculture on global climate change. Journal of Sustainable Agriculture 18(1): 109-131.
  • Wang, Z., & Wang, X. (2022). Research on the impact of green finance on energy efficiency in different regions of China based on the DEA-Tobit model. Resources Policy, 77, 102695.
  • World Bank. 2023. Climate-Smart Agriculture/Overview. Access date: June 8, 2023. Available at: https://www.worldbank.org/en/topic/climate-smart-agriculture
  • Yohannes, H. (2016). A review on relationship between climate change and agriculture. Journal of Earth Science & Climatic Change, 7(2).
  • Yurtkuran, S. (2021). The effect of agriculture, renewable energy production, and globalization on CO2 emissions in Turkey: A bootstrap ARDL approach. Renewable Energy, 171, 1236-1245.
  • Zhang, C., & Chen, P. (2022). Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries. Energy, 241, 122917.
  • Zhang, X., Davidson, E.A., Mauzerall, D.L., Searchinger, T.D., Dumas, P., & Shen, Y. (2015). Managing nitrogen for sustainable development. Nature, 528(7580), 51-59.
  • Zoundi, Z. (2017). CO₂ emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach. Renewable and Sustainable Energy Reviews, 72, 1067-1075.

The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey

Year 2024, Volume: 8 Issue: 2, 586 - 599, 31.05.2024
https://doi.org/10.29023/alanyaakademik.1407903

Abstract

Tarımsal uygulamalar ve yenilenebilir enerji tüketimi, ısıyı hapseden sera gazlarının emilimi üzerinde önemli bir etkiye sahiptir ve dolayısıyla iklim değişikliği ile yakından bağlantılıdır. Tarımın iklim değişikliği üzerindeki etkisi, tarımsal faaliyetler sırasında atmosfere salınan metan, azot oksit ve karbondioksit gibi gazlardan kaynaklanmaktadır. Dolayısıyla, tarımsal faaliyetlerin iklim değişikliği üzerindeki istenmeyen etkilerinden kaçınmak için tarımsal faaliyetlerin sera gazları üzerindeki etkisini ortaya koymak önemlidir. Bu çalışmada, Türkiye'de tarımsal etkinlik, gübre kullanımı ve yenilenebilir enerji tüketiminin toplam CO2 emisyonu üzerindeki uzun dönem etkileri analiz edilmektedir. Analiz iki aşamada gerçekleştirilmiştir. İlk aşamada CEE yöntemi kullanılarak Türkiye’nin tarımsal etkinlik değerleri hesaplanmıştır. İkinci aşamada ARDL ve NARDL modelleri yardımı ile tarımsal etkinlik, gübre kullanımı, yenilenebilir enerji tüketimi, GSYH ve nüfus gibi değişkenlerin CO2 üzerindeki uzun dönem etkileri tahmin edilmiştir. Sonuçlar, tarımsal etkinliğin iyileştirilmesinin ve yenilenebilir enerjinin payının artırılmasının sera gazı salınımı azaltacağını, gübre kullanımı, GSYH ve nüfusun ise sera gazı salınımı üzerinde olumsuz uzun vadeli etkileri olduğunu göstermektedir. Ek olarak, Wald testinin sonuçları yenilenebilir enerji, tarımsal etkinlik ve gübre kullanımının iklim değişikliği üzerindeki uzun vadeli etkilerinin asimetrik olduğunu göstermektedir.

References

  • Adams, R.M., Hurd, B.H., Lenhart, S., & Leary, N. (1998). Effects of global climate change on agriculture: an interpretative review. Climate Research, 11(1), 19-30.
  • Adger, W.N., Pettenella, D., & Whitby, M. (1997). Land use in Europe and the reduction of greenhouse-gas emissions. Climate-Change Mitigation and European Land-Use Policies, 1-22.
  • Anderson, T.R., Hollingsworth, K., & Inman, L. (2002). The fixed weighting nature of a cross-evaluation model. Journal of Productivity Analysis, 17, 249-255.
  • Arı Y. (2021). Using COGARCH-filtered volatility in modelling within ARDL framework. in: Adıgüzel Mercangöz B. (eds) handbook of research on emerging theories, models, and applications of financial econometrics. Springer, Cham. (SCOPUS) https://doi.org/10.1007/978-3-030-54108-8_13
  • Ari, Y. (2022). - ARDL sınır testi uygulamaları üzerine tartışmalar. In: Mehmet Özcan (Eds). 21. yüzyılda iktisadı anlamak: Güncel ekonometrik zaman serileri çalışmaları. ISBN: 9786258374858. Gazi Kitabevi. https://www.researchgate.net/publication/363116601
  • Arora, N.K. (2019). Impact of climate change on agriculture production and its sustainable solutions. Environmental Sustainability, 2(2), 95-96.
  • Aydinalp, C., & Cresser, M.S. (2008). The effects of global climate change on agriculture. American-Eurasian Journal of Agricultural & Environmental Sciences, 3(5), 672-676.
  • Çam, S., Karataş, A.S., & Lopcu, K. (2022). The puzzle of energy efficiency in Turkey: combining a multiple criteria decision making and the time series analysis. Energy Sources, Part B: Economics, Planning, and Policy, 17(1), 2136791.
  • Chen, S., Chen, X., & Xu, J. (2016). Impacts of climate change on agriculture: Evidence from China. Journal of Environmental Economics and Management, 76, 105-124.
  • Chen, Y., Miao, J., & Zhu, Z. (2021). Measuring green total factor productivity of China's agricultural sector: A three-stage SBM-DEA model with non-point source pollution and CO2 emissions. Journal of Cleaner Production, 318, 128543.
  • Closset, M., Dhehibi B.B.B., & Aw-Hassan, A.A. (2015). Measuring the economic impact of climate change on agriculture: a Ricardian analysis of farmlands in Tajikistan. Climate and Development 7(5): 454-468.
  • Cui, H., Zhao, T., & Shi, H. (2018). STIRPAT-based driving factor decomposition analysis of agricultural carbon emissions in Hebei, China. Polish Journal of Environmental Studies, 27(4).
  • Deng, X., & Gibson, J. (2019). Improving eco-efficiency for the sustainable agricultural production: A case study in Shandong, China. Technological Forecasting and Social Change, 144, 394-400.
  • Dumrul, Y., & Kilicaslan, Z. (2017). Economic impacts of climate change on agriculture: Empirical evidence from ARDL approach for Turkey. Journal of Business Economics and Finance, 6(4), 336-347.
  • EPA (United State Environmental Protection Agency). 2023. Greenhouse emissions/ Sources of greenhouse gas emissions. Access date: June 8, 2023. Available at: https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions
  • FAO (The Food and Agriculture Organization). 2018. Global, regional and country trends 2000–2018. Access date: June 8, 2023. Available at: https://www.fao.org/3/cb3808en/cb3808en.pdf
  • Flessa, H., Ruser, R., Dörsch, P., Kamp, T., Jimenez, M.A., Munch, J.C., & Beese, F. (2002). Integrated evaluation of greenhouse gas emissions (CO2, CH4, N2O) from two farming systems in southern Germany. Agriculture, Ecosystems & Environment, 91(1-3), 175-189.
  • Fróna, D., Szenderák, J., & Harangi-Rákos, M. (2019). The challenge of feeding the world. Sustainability, 11(20), 5816.
  • Guo, L., Zhao, S., Song, Y., Tang, M., & Li, H. (2022). Green finance, chemical fertilizer use and carbon emissions from agricultural production. Agriculture, 12(3), 313.
  • IAEA (International Atomic Energy Agency). 2023. Nuclear technology and applications/food and agriculture/climate-smart agriculture/greenhouse gas reduction. Access date: June 8, 2023. Available at: https://www.iaea.org/topics/greenhouse-gas-reduction
  • Lal, R. (2004). Carbon emission from farm operations. Environment International, 30(7), 981-990.
  • Liang, L., Wu, J., Cook, W.D., & Zhu, J. (2008). Alternative secondary goals in DEA cross-efficiency evaluation. International Journal of Production Economics, 113(2), 1025-1030.
  • Lovins, A. (2017). Energy efficiency. Energy Economics, 1, 234-258
  • Malhi, G.S., Kaur, M., & Kaushik, P. (2021). Impact of climate change on agriculture and its mitigation strategies: A review. Sustainability, 13(3), 1318.
  • Manogna R.L., & Mishra, A.K. (2022). Agricultural production efficiency of Indian states: Evidence from data envelopment analysis. International Journal of Finance & Economics, 27(4), 4244-4255.
  • Menegaki, A.N. (2019). The ARDL method in the energy-growth nexus field; best implementation strategies. Economies, 7(4), 105.
  • Namahoro, J.P., Wu, Q., Zhou, N., & Xue, S. (2021). Impact of energy intensity, renewable energy, and economic growth on CO2 emissions: Evidence from Africa across regions and income levels. Renewable and Sustainable Energy Reviews, 147, 111233.
  • Nandy, A., & Singh, P.K. (2020). Farm efficiency estimation using a hybrid approach of machine-learning and data envelopment analysis: Evidence from rural eastern India. Journal of Cleaner Production, 267, 122106.
  • Ogundari, K. (2014). The paradigm of agricultural efficiency and its implication on food security in Africa: what does meta-analysis reveal?. World Development, 64, 690-702.
  • Ojha, H.R., Sulaiman, V. R., Sultana, P., Dahal, K., Thapa, D., Mittal, N., ... & Aggarwal, P. (2014). Is South Asian agriculture adapting to climate change? Evidence from the Indo-Gangetic Plains. Agroecology and Sustainable Food Systems 38(5): 505-531.
  • Oliver, T.H., & Morecroft, M.D. (2014). Interactions between climate change and land use change on biodiversity: attribution problems, risks, and opportunities. Wiley Interdisciplinary Reviews: Climate Change, 5(3), 317-335.
  • Örkcü, H., & Örkcü, M. (2015). Data Envelopment Analysis cross efficiency evaluation approach to the technology selection. Gazi University Journal of Science Part A: Engineering and Innovation, 3(1), 1-14. Our World in Data. 2023. Emissions by sector. Access date: June 8, 2023. Available at: https://ourworldindata.org/emissions-by-sector
  • Ouraich, I., Dudu, H., Tyner, W.E., & Cakmak, E.H. (2019). Agriculture, trade, and climate change adaptation: a global CGE analysis for Morocco and Turkey. The Journal of North African Studies 24(6): 961-991.
  • Patterson, M.G. (1996). What is energy efficiency?: Concepts, indicators and methodological issues. Energy Policy, 24(5), 377-390.
  • Pesaran, M.H., Shin, Y., & Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16(3): 289-326.
  • Raihan, A., & Tuspekova, A. (2022). The nexus between economic growth, renewable energy use, agricultural land expansion, and carbon emissions: New insights from Peru. Energy Nexus, 6, 100067.
  • Ramírez, C.A., & Worrell, E. (2006). Feeding fossil fuels to the soil: An analysis of energy embedded and technological learning in the fertilizer industry. Resources, Conservation and Recycling, 46(1), 75-93.
  • Scialabba, N.E.H., & Müller-Lindenlauf, M. (2010). Organic agriculture and climate change. Renewable Agriculture and Food Systems, 25(2), 158-169.
  • Sexton, T.R., Silkman, R.H., & Hogan, A.J. (1986). Data envelopment analysis: Critique and extensions. New Directions for Program Evaluation, 1986(32), 73-105.
  • Shanmugam, K.R., & Venkataramani, A. (2006). Technical efficiency in agricultural production and its determinants: An exploratory study at the district level. Indian Journal of Agricultural Economics, 61(2).
  • Sharma, N., & Singhvi, R. (2017). Effects of chemical fertilizers and pesticides on human health and environment: a review. International Journal of Agriculture, Environment and Biotechnology, 10(6), 675-680.
  • Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in Honor of Peter Schmidt, ed. R.C. Sickles and W.C. Horrace, 281-314. New York: Springer.
  • Sun, X., Dong, Y., Wang, Y., & Ren, J. (2022). Sources of greenhouse gas emission reductions in OECD countries: Composition or technique effects. Ecological Economics, 193, 107288.
  • Talaei, A., Gemechu, E., & Kumar, A. (2020). Key factors affecting greenhouse gas emissions in the Canadian industrial sector: A decomposition analysis. Journal of Cleaner Production, 246, 119026.
  • Tilman, D., Balzer, C., Hill, J., & Befort, B.L. (2011). Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences, 108(50), 20260-20264.
  • Tongwane, M.I., & Moeletsi, M.E. (2018). A review of greenhouse gas emissions from the agriculture sector in Africa. Agricultural Systems, 166, 124-134.
  • Turhan, M.S., & Arı, Y. (2021) Örgütsel ekoloji ve kooperatif örgütlenmeleri: Türkiye’de tarım, ormancılık ve balıkçılık sektörü üzerine bir analiz. Üçüncü Sektör Sosyal Ekonomi Dergisi, 56(3), 1436-1454. doi: 10.15659/3.sektor-sosyal-ekonomi.21.08.1609
  • Uri, N.D. 2001. The potential impact of conservation practices in US agriculture on global climate change. Journal of Sustainable Agriculture 18(1): 109-131.
  • Wang, Z., & Wang, X. (2022). Research on the impact of green finance on energy efficiency in different regions of China based on the DEA-Tobit model. Resources Policy, 77, 102695.
  • World Bank. 2023. Climate-Smart Agriculture/Overview. Access date: June 8, 2023. Available at: https://www.worldbank.org/en/topic/climate-smart-agriculture
  • Yohannes, H. (2016). A review on relationship between climate change and agriculture. Journal of Earth Science & Climatic Change, 7(2).
  • Yurtkuran, S. (2021). The effect of agriculture, renewable energy production, and globalization on CO2 emissions in Turkey: A bootstrap ARDL approach. Renewable Energy, 171, 1236-1245.
  • Zhang, C., & Chen, P. (2022). Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries. Energy, 241, 122917.
  • Zhang, X., Davidson, E.A., Mauzerall, D.L., Searchinger, T.D., Dumas, P., & Shen, Y. (2015). Managing nitrogen for sustainable development. Nature, 528(7580), 51-59.
  • Zoundi, Z. (2017). CO₂ emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach. Renewable and Sustainable Energy Reviews, 72, 1067-1075.
There are 55 citations in total.

Details

Primary Language English
Subjects Econometric and Statistical Methods, Applied Macroeconometrics
Journal Section Makaleler
Authors

Salih Çam 0000-0002-3521-5728

Publication Date May 31, 2024
Submission Date December 21, 2023
Acceptance Date May 29, 2024
Published in Issue Year 2024 Volume: 8 Issue: 2

Cite

APA Çam, S. (2024). The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey. Alanya Akademik Bakış, 8(2), 586-599. https://doi.org/10.29023/alanyaakademik.1407903