KOORDİNELİ PİYASA EKONOMİLERİNDE TARIM, ORMAN ALANLARI VE ENERJİ TÜKETİMİNİN ÇEVRESEL KALİTE ÜZERİNDEKİ ETKİSİ: AMPİRİK BİR ANALİZ

Year 2022, Volume: 9 Issue: 1, 319 - 337, 23.03.2022

Hüseyin Ünal , Oğuz Yusuf Atasel

https://doi.org/10.30798/makuiibf.863178

Abstract

Bu çalışma, 1990-2016 döneminde koordineli piyasa ekonomileri için tarımsal katma değerin, orman alanlarının, ekonomik büyümenin ve yenilenebilir ve yenilenemez enerji tüketiminin çevresel kalite üzerindeki etkisini panel Common Corelated Effects (CCE) modelini kullanarak incelemeyi amaçlamaktadır. Panel CCE modelinden elde edilen uzun dönem katsayılara göre orman alanlarının çevre kalitesini arttırdığı, başka bir ifadeyle karbondioksit emisyonunu azalttığı, yenilenemez enerji tüketiminin ve ekonomik büyümenin ise çevre kalitesi üzerinde negatif bir etki oluşturduğu tespit edilmiştir. Ayrıca, incelenen dönemde tarımsal katma değerin ve yenilenebilir enerji tüketiminin çevre kalitesi üzerinde bir etki oluşturmadığı görülmüştür. Son olarak değişkenler arasındaki nedensellik ilişkisi Dumitrescu–Hurlin testi ile araştırılmıştır. Uygulanan nedensellik testi ile tarım ile karbondioksit emisyonları, tarım ile yenilenemez enerji tüketimi, yenilenebilir enerji tüketimi ile yenilenemez enerji tüketimi arasında çift yönlü nedensellik ilişkisi elde edilmiştir.

Keywords

Tarımsal Katma Değer, Orman Alanı, Yenilenebilir-Yenilenemez Enerji Tüketimi, Çevresel Kalite, Panel ARDL Modeli

THE IMPACT OF AGRICULTURE, FOREST AREAS AND ENERGY CONSUMPTION ON THE ENVIRONMENTAL QUALITY IN COORDINATED MARKET ECONOMIES: AN EMPIRICAL ANALYSIS

Abstract

This study aims to investigate the impact of agricultural added value, forest areas, economic growth, renewable and non-renewable energy consumption (REC-NREC) on environmental quality using panel Common Corelated Effects (CCE) model for coordinated market economies for the period 1990-2016. According to the long-term coefficients obtained from the panel CCE model, it has been determined that the forest areas increase the environmental quality, in other words, it reduces the carbon dioxide (CO2) emissions, and the NREC and economic growth have a negative effect on the environment quality. Moreover, It has been observed that agricultural added value and REC do not have an effect on environmental quality. Finally, the causality relationship between variables is investigated with Dumitrescu – Hurlin test. With the applied causality test, there is bidirectional causality relationship between agriculture and CO2 emissions; agriculture and NREC; REC and NREC.

Keywords

Agriculture Value Added, Forest Areas, Renewable-Non-renewable Energy Consumption, Environmental Quality, Panel ARDL Model

References

• Abas, N., Kalair, A., Khan, N. ve Kalair, A. R. (2017). Review of GHG emissions in Pakistan compared to SAARC countries. Renewable and Sustainable Energy Reviews, 80, 990–1016. doi: 10.1016/j.rser.2017.04.022
• Agboola, M. O. ve Bekun, F. V. (2019). Does Agricultural value added ınduce environmental degradation? Empirical evidence from an Agrarian country. Environmental Science and Pollution Research, 26, 27660–27676. doi: 10.1007/s11356-019-05943-z
• Ang, J. B. (2007). CO2 emissions, energy consumption, and output in France. Energy Policy, 35(10), 4772–4778. doi: 10.1016/j.enpol.2007.03.032
• Apergis, N., Ben Jebli, M. ve Ben Youssef, S. (2018). Does renewable energy consumption and health expenditures decrease carbon dioxide emissions? Evidence for Sub-Saharan Africa countries. Renewable Energy, 127, 1011–1016. doi: 10.1016/j.renene.2018.05.043
• Aydoğan, B. ve Vardar, G. (2020). Evaluating The role of renewable energy, economic growth and agriculture on CO2 emission in E7 countries. International Journal of Sustainable Energy, 39(4), 335-348. doi: 10.1080/14786451.2019.1686380
• Aytun, C., ve Akın, C. S. (2014), OECD Ülkelerinde Telekomünikasyon Altyapısı ve Ekonomik Büyüme: Yatay Kesit Bağımlı Heterojen Panel Nedensellik Analizi. İktisat, İşletme ve Finans, 29(340), 69-94.
• Aziz, N., Sharif, A., Raza, A. ve Rong, K. (2020). Revisiting the role of forestry, agriculture, and renewable energy in testing environment Kuznets curve in Pakistan: Evidence from quantile ARDL approach. Environmental Science and Pollution Research, 27, 10115–10128. doi: 10.1007/s11356-020-07798-1
• Başoğlu, A. ve Üzar, U. (2019). An empirical evaluation about the effects of environmental expenditures on environmental quality in coordinated market economies. Environmental Science and Pollution Research, 26, 23108–23118. doi: 10.1007/s11356-019-05567-3
• Ben Jebli, M. ve Ben Youssef, S. (2017a). 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. doi: 10.1080/13504509.2016.1196467
• Ben Jebli, M. ve Ben Youssef, S. (2017b). The Role of renewable energy and agriculture in reducing co2 emissions: Evidence for North Africa countries. Ecoogical Indicators, 74, 295-301. doi: 10.1016/j.ecolind.2016.11.032
• Ben Jebli, M., Ben Youssef, S. ve Öztürk, I. (2013). The environmental Kuznets curve: The role of renewable and non-renewable energy consumption and trade openness. MPRA paper 51672 University Library of Munich,Germany. Erişim adresi https://econpapers.repec.org/paper/pramprapa/51672.htm
• Bildirici, M. ve Özaksoy, F. (2016). Woody biomass energy consumption and economic growth in Sub-Saharan Africa. Procedia Economics and Finance, 38, 287-293. doi: 10.1016/S2212-5671(16)30202-7
• Bilgili, F., Koçak, E. ve Bulut, Ü. (2016). The dynamic ımpact of renewable energy consumption on CO2 emissions: A revisited environmental Kuznets curve approach. Renewable & Sustainable Energy Reviews, 54, 838–845. doi: 10.1016/j.rser.2015.10.080
• 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. doi: 10.1016/j.rser.2015.07.138
• Breitung, J. (2005). A parametric approach to the estimation of cointegration vectors in panel data. Econometric Reviews, 24(2), 151-173. doi: 10.1081/ETC-200067895
• Breusch, T. S., ve Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253. doi: 10.2307/2297111
• Cherni, A. ve Jouini, S.E. (2017). An ARDL approach to the CO2 emissions, renewable energy and economic growth nexus: Tunisian evidence. International Journal of Hydrogen Energy, 42(48), 29056-29066. doi: 10.1016/j.ijhydene.2017.08.072
• Dogan, N. (2019). The impact of agriculture on CO2 emissions in China. Panoeconomicus, 66(2), 257-271. doi: 10.2298/PAN160504030D
• Dumitrescu, E. I. ve Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29, 1450–1460. doi: 10.1016/j.econmod.2012.02.014
• Emir, F. ve Bekun, F. V. (2019). Energy ıntensity, carbon emissions, renewable energy, and economic growth nexus: New insights from Romania. Energy & Environment, 30(3), 427-443. doi: 10.1177/0958305X18793108
• Eren, E. (2020). Neoklasik iktisada çoğulcu yaklaşmak. İktisat ve Toplum, 114, 53-64.
• Food and Agriculture Organization of the United Nations [FAO] (2016). The State of food and agriculture climate change, agriculture and food security. Rome. Erişim adresi http://www.fao.org/3/a-i6030e.pdf
• Fuglie, K. (2010). Total factor productivity in the global agricultural economy: Evidence from FAO data. J. M. Alston, B. A. Babcock, ve P. G. Pardey (Ed.) The Shifting patterns of agricultural production and productivity worldwide içinde (63-95). Ames, Iowa: The Midwest Agribusiness Trade Research and Information Center Iowa State University. Erişim adresi https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1001&context=card_books#page=92
• Gökmenoğlu, K. K., Taşpınar, N. ve Kaakeh, M. (2019). Agriculture-induced environmental Kuznets curve: The case of China. Environmental Science and Pollution Research, 26, 37137–37151. doi: 10.1007/s11356-019-06685-8
• Gökmenoğlu, K.K., ve Taşpınar, N. (2018). Testing the agriculture-induced EKC hypothesis: The case of Pakistan. Environmental Science and Pollution Research, 25(23), 22829-22841. doi: 10.1007/s11356-018-2330-6
• Hamit-Haggar, M. (2012). Greenhouse gas emissions, energy consumption and economic growth: A panel cointegration analysis from Canadian ındustrial sector perspective. Energy Economics, 34(1), 358–364. doi: 10.1016/j.eneco.2011.06.005
• Im, K. S., Pesaran, M. H. ve Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74. doi: 10.1016/S0304-4076(03)00092-7
• Intergovernmental Panel on Climate Change [IPCC] (2013). Climate change 2013 the physical science basis. Erişim adresi https://www.ipcc.ch/site/assets/uploads/2018/03/WG1AR5_SummaryVolume_FINAL.pdf
• Karl, T. R. ve Trenberth, K. E. (2003). Modern global climate change. Science, 302(5651), 1719–1724. doi: 10.1126/science.1090228
• Köseoğlu, M. ve Ünal, H. (2019). Türkiye’nin sürdürülebilir ekonomik büyümesinde tarım, kentleşme ve yenilenebilir enerjinin etkisi: ARDL sınır testi yaklaşımı. Hitit Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 12(2), 400-415. doi: 10.17218/hititsosbil.590338
• Lean, H. H. ve Smyth, R. (2010). CO2 emissions, electricity consumption and output in ASEAN. Applied Energy, 87(6), 1858–1864. doi: 10.1016/j.apenergy.2010.02.003
• Li, D. ve Yang, D. (2016) Does non-fossil energy usage lower CO2 emissions? Empirical evidence from China. Sustainability, 8(9), 1–11. doi: 10.3390/su8090874
• 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. doi: 10.1016/j.jclepro.2017.07.086
• Nathaniel, S. P. ve Iheonu, C. O. (2019). Carbon dioxide abatement in Africa: The role of renewable and non-renewable energy consumption. Science of the Total Environment, 679, 337–345. doi: 10.1016/j.scitotenv.2019.05.011
• Pao, H. T. ve Tsai, C. M. (2010). CO2 emissions, energy consumption and economic growth in BRIC countries. Energy Policy, 38(12), 7850–7860. doi: 10.1016/j.enpol.2010.08.045
• 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. doi: 10.1016/j.eneco.2017.06.025
• Pata, U. K. (2018). The Effect of urbanization and industrialization on carbon emissions in Turkey: Evidence from ARDL bounds testing procedure. Environmental Science and Pollution Research, 25(8), 7740-7747. doi: 10.1007/s11356-017-1088-6
• Pata, U. K. (2021). Renewable and non-renewable energy consumption, economic complexity, CO 2 emissions, and ecological footprint in the USA: Testing the EKC hypothesis with a structural break. Environmental Science and Pollution Research, 28, 846–861. doi: 10.1007/s11356-020-10446-3
• Pesaran, H. M. (2004). General diagnostic tests for cross-sectional dependence in panels. University of Cambridge, Cambridge Working Papers in Economics, 435.
• Pesaran, M. H. (2006). Estimation and ınference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967-1012. doi: 10.1111/j.1468-0262.2006.00692.x
• 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. doi: 10.1002/jae.951
• Pesaran, M. H. ve Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics 142(1), 50–93. https://doi.org/10.1016/j.jeconom.2007.05.010
• Phillips, P. C. ve Sul, D. (2003). Dynamic panel estimation and homogeneity testing under cross section dependence. The Econometrics Journal, 6(1), 217-259. doi: 10.1111/1368-423X.00108
• Prastiyo S. E., Irham, Hardyastuti, S. ve Jamhari (2020). How agriculture, manufacture, and urbanization ınduced carbon emission? The case of Indonesia. Environmental Science and Pollution Research, 27, 42092–42103. doi: 10.1007/s11356-020-10148-w
• Qiao, H., Zheng, F., Jiang, H. ve Dong, K. (2019). The Greenhouse effect of the agriculture-economic growth-renewable energy nexus: evidence from G20 countries. Science of the Total Environment, 671, 722-731. doi: 10.1016/j.scitotenv.2019.03.336
• Reynolds, L. ve S. Wenzlau. (2012). Climate-friendly agriculture and renewable energy: Working hand-in-hand toward climate mitigation. Worldwatch Institute. Erişim adresi https://www.renewableenergyworld.com/articles/2012/12/climate-friendly-agriculture-and-renewable-energy-working-hand-in-hand-toward-climate-mitigation.html
• Saidi, K. ve Ben Mbarek, M. (2016). Nuclear energy, renewable energy, CO2 emissions, and economic growth for nine developed countries: Evidence from panel Granger. Progress in Nuclear Energy, 88, 364–374. doi: 10.1016/j.pnucene.2016.01.018
• Ullah, A., Khan, D., Khan, I. ve Zheng, S. (2018). Does agricultural ecosystem cause environmental pollution in Pakistan? Promise and menace. Environmental Science and Pollution Research, 25, 13938–13955. doi: 10.1007/s11356-018-1530-4
• Waheed, R., Chang, D., Sarwar, S. ve Chen, W. (2018). Forest, agriculture, renewable energy, and CO2 emission, Journal of Cleaner Production, 172, 4231-4238. doi: 10.1016/j.jclepro.2017.10.287
• Westerlund, J. (2007), Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69, 709-748. doi: 10.1111/j.1468-0084.2007.00477.x
• World Bank (2020). World Development Indicators. Erişim adresi http://data.worldbank
• Zhang, L., Pang, J., Chen, X. ve Lu, Z. (2019). Carbon emissions, energy consumption and economic growth: evidence from the agricultural sector of China's main grain-producing areas. Science of the Total Environment, 665, 1017-1025. doi: 10.1016/j.scitotenv.2019.02.162