Türkiye'de Hayvansal ve Bitkisel Üretim Endeksi ile Yük Kapasite Faktörü Arasındaki İlişki: LCC Hipotezi Üzerinden Ampirik Kanıtlar

Öz

Bu çalışma, Türkiye’de tarımsal göstergeler üzerinden Yük Kapasitesi Eğrisi (LCC) hipotezinin geçerli olup-olmadığını tespit etmeyi amaçlamaktadır. Tarımsal göstergeler odağında çevresel dengenin hem arz hem de talep tarafını dikkate alarak LCC hipotezinin geçerliliğini araştıran ilk çalışma olması çalışmanın özgün değerini oluşturmaktadır. 1974-2022 dönemine ilişkin yıllık verilerin kullanıldığı bu çalışmada değişkenlerin farklı seviyelerde durağan olmaları sebebiyle ARDL prosedürü ve Toda-Yamamoto nedensellik testi uygulanmıştır. Ayrıca LCC hipotezinin geçerliliğinin tespitinde, çoklu doğrusal bağlantı sorunundan kaçınmak için Narayan ve Narayan (2010) yaklaşımı benimsenmiştir. Çalışma kapsamında oluşturulan model eşbütünleşik olup yük kapasitesi faktörü ile kişi başına gelir, fosil yakıt tüketimi, bitkisel ve hayvansal üretim endeksi değişkenleri arasında uzun dönemli bir ilişki olduğu doğrusal birleşimlerinin denge noktasına yakınsadığı tespit edilmiştir. Kişi başına düşen Gayrisâfi Yurtiçi Hâsıla (GSYH) değişkeninin uzun dönem katsayısı kısa dönemki değerinden daha yüksektir. Bu bulgu kişi başına düşen gelirin çevresel kaliteyi iyileştirici etkisinin uzun vadede daha güçlü ve belirgin olduğunu ortaya koymaktadır. Bu sonuç, U şeklinde olan LCC hipotezinin Türkiye için geçerli olduğunu göstermektedir. Ayrıca uzun dönemde, hayvansal üretim endeksinin çevresel kalite üzerindeki etkisi pozitifken fosil yakıt tüketiminin çevresel kalite üzerindeki etkisi ise negatiftir. Nedensellik testi sonuçlarına göre bitkisel üretim endeksinden yük kapasitesi faktörüne, yük kapasitesi faktöründen hayvansal üretim endeksine, hayvansal üretim endeksinden kişi başına düşen gelir ve bitkisel üretim endeksine, fosil yakıt tüketiminden hayvansal üretim endeksine doğru tek yönlü nedensellik ilişkisi varken kişi başına düşen gelir ile bitkisel üretim endeksi arasında ve fosil yakıt tüketimi ile bitkisel üretim endeksi arasında çift yönlü nedensellik ilişkisi vardır. Bu bulgular ekonomik büyümeyi teşvik eden ve ekolojik sürdürülebilirliği sağlayan politikaların oluşturulmasını, tarım ve çevre politikalarının bütüncül bir yaklaşımla ele alınmasını zorunlu kılmaktadır. Bu doğrultuda politika yapıcılara çevre dostu, yenilikçi ve sürdürülebilir tarım ve hayvancılık uygulamalarının teşvik edilmesi önerilebilir.

Anahtar Kelimeler

• ARDL
• Bitkisel üretim endeksi
• Hayvansal üretim endeksi
• LCC hipotezi
• Tarım çevre ilişkisi
• Toda-Yamamoto nedensellik testi

Relationship between Livestock and Crop Production Indexes with Load Capacity Factor in Türkiye: Empirical Evidence from LCC Hypothesis

Öz

This study aims to determine whether the Load Capacity Curve (LCC) hypothesis, is valid for Türkiye through agricultural indicators. The original value of the study is that it is the first study to investigate the validity of the LCC hypothesis by considering both the supply and demand sides of the environmental balance with a focus on agricultural indicators. In this study, where annual data for 1974-2022 were used, the ARDL procedure and the Toda-Yamamoto causality test were applied because the variables were stationary at different levels. In addition, the Narayan and Narayan (2010) approach was adopted to avoid the problem of multiple linear connections in determining the validity of the LCC hypothesis. The model created within the scope of the study is cointegrated, and it has been determined that there is a long-term relationship between the load capacity factor and the per capita income, fossil fuel consumption, crop, and animal production index variables and that their linear combinations converge to the equilibrium point. The long-term coefficient of the Gross Domestic Product (GDP) per capita variable is higher than its short-term value. This finding reveals that the effect of per capita income on improving environmental quality is stronger and more pronounced in the long term. This result shows that the U-shaped LCC hypothesis is valid for Türkiye. In addition, in the long term, the effect of the animal production index on environmental quality is positive, while the effect of fossil fuel consumption on environmental quality is negative. According to the causality test results, there is a unidirectional causality relationship from the crop production index to the load capacity factor; from the load capacity factor to the livestock production index, from the livestock production index to per capita income and crop production index, from fossil fuel consumption to the livestock production index. At the same time, there is a bidirectional causality relationship between per capita income and crop production index and between fossil fuel consumption and crop production index. These findings necessitate the establishment of policies that encourage economic growth and ensure ecological sustainability, as well as the holistic approach to agricultural and environmental policies. In this direction, it can be recommended to policymakers to encourage environmentally friendly, innovative, and sustainable agricultural and animal husbandry practices.

Anahtar Kelimeler

• ARDL
• Crop production index
• Livestock production index
• LCC hypothesis
• Agriculture-environment relationship
• Toda-Yamamoto causality test

Kaynakça

1. Aktürk, E. and Gültekin, S. (2024). The impact of food production on ecological footprint in Turkey: an analysis across agriculture, livestock, and aquaculture. Environment, Development and Sustainability, 1-26. https://doi.org/10.1007/s10668-024-04944-4
2. Ali, S., Shah, A.A., Ghimire A. and Tariq, M. A. U. R. (2022). Investigation the nexus between CO2 emissions, agricultural land, crop, and livestock production in Pakistan. Frontiers in Environmental Science, 10: 1014660. https://doi.org/10.3389/fenvs.2022.1014660
3. Ali, Z., Yang, J., Ali, A. and Khan, A. (2024). Balancing agriculture, environment and natural resources: insights from Pakistan’s load capacity factor analysis. Clean Technologies and Environmental Policy, 26(4): 1227-1246. https://doi.org/10.1007/s10098-023-02673-2
4. Alvarado, R., Ortiz, C., Jiménez, N., Ochoa-Jiménez D. and Tillaguango, B. (2021). Ecological footprint, air quality and research and development: The role of agriculture and international trade. Journal of Cleaner Production, 288: 125589. https://doi.org/10.1016/j.jclepro.2020.125589
5. Appiah, K., Du J. and Poku, J. (2018). Causal relationship between agricultural production and carbon dioxide emissions in selected emerging economies. Environmental Science and Pollution Research, 25: 24764-24777. https://doi.org/10.1007/s11356-018-2523-z
6. Ayyildiz, M. and Erdal, G. (2021). The relationship between carbon dioxide emission and crop and livestock production indexes: a dynamic common correlated effects approach. Environmental Science and Pollution Research, 28(1): 597-610. https://doi.org/10.1007/s11356-020-10409-8
7. Aziz, N., Sharif, A., Raza A. and 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. https://doi.org/10.1007/s11356-020-07798-1
8. Caglar, A. E., Destek M. A. and Manga, M. (2024). Analyzing the load capacity curve hypothesis for the Turkiye: A perspective for the sustainable environment. Journal of Cleaner Production, 444: 141232. https://doi.org/10.1016/j.jclepro.2024.141232

9. Çamkaya, S. (2024). LCC hipotezi çerçevesinde çevresel kalite ve kentleşme arasındaki ilişki: Türkiye’den ampirik kanıtlar. Fiscaoeconomia, 8(2), 739-760. https://doi.org/10.25295/fsecon.1435550
10. Çetin, M., Saygın, S. ve Demir, H. (2020). Tarım sektörünün çevre kirliliği üzerindeki etkisi: Türkiye ekonomisi için bir eşbütünleşme ve nedensellik analizi. Tekirdağ Ziraat Fakültesi Dergisi, 17(3): 329-345. https://doi.org/10.33462/jotaf.678764
11. Chandio, A. A., Akram, W., Ahmad F. and Ahmad, M. (2020). Dynamic relationship among agriculture-energy-forestry and carbon dioxide (CO2) emissions: empirical evidence from China. Environmental Science and Pollution Research, 27: 34078-34089. https://doi.org/10.1007/s11356-020-09560-z
12. Chandio, A. A., Akram, W., Ozturk, I., Ahmad, M. and Ahmad, F. (2021). Towards long-term sustainable environment: does agriculture and renewable energy consumption matter? Environmental Science and Pollution Research, 28(38): 53141-53160. https://doi.org/10.1007/s11356-021-14540-y
13. Daştan, M. (2024). The role of renewable energy, technological innovation, and human capital on environmental quality in Türkiye: Testing the LCC hypothesis with smooth structural shifts. Yüzüncü Yıl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (65): 76-91. https://doi.org/10.53568/yyusbed.1480175
14. De, U. K. and Tamang, R. K. (2023). Pattern of agricultural progress in India’s north-east and the contributing factors: An econometric analysis. Journal of Tekirdag Agricultural Faculty, 20(3): 509-527. https://doi.org/10.33462/jotaf.1114386
15. Demir, İ. C. ve Balkı, A. (2019). Türkiye’de Wagner Kanunu’nun sınanması: 1960-2016 Dönemi analizi. Vergi Raporu, 234: 20-21.
16. Dogan, A. and Pata, U. K. (2022). The role of ICT, R&D spending and renewable energy consumption on environmental quality: Testing the LCC hypothesis for G7 countries. Journal of Cleaner Production, 380: 135038. https://doi.org/10.1016/j.jclepro.2022.135038
17. Durmuş, İ. ve Gücüyeter, İ., (2024). Karbon ayak izi ve yeşil organizasyon kavramlarına yönelik bibliyometrik araştırmalar. Ege Üniversitesi Ziraat Fakültesi Dergisi, 61(1): 113-124. https://doi.org/10.20289/zfdergi.1388506
18. Engle, R. F. and Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: Journal of the Econometric Society, 55(2): 251-276. https://doi.org/10.2307/1913236 Global Footprint Network (2024). Global Footprint Network. https://www.footprintnetwork.org/ (Erişim Tarihi: Nisan 2024).
19. Göçoğlu, V. and Göksu, S. (2024). How do industrialization and agricultural land use affect urban population in Turkey? Policy implications in the context of SDGs. Journal of Policy Modeling, 46(1): 198-211. https://doi.org/10.1016/j.jpolmod.2023.08.004
20. Göksu, S. ve Balkı, A. (2023). ARDL ve NARDL Eşbütünleşme Analizleri: Adım Adım Eviews Uygulaması. Serüven Yayınevi, Ankara, Türkiye. https://hdl.handle.net/11630/11330
21. Gyamfi, B. A., Onifade, S. T., Erdoğan S. and Ali, E. B. (2023). Colligating ecological footprint and economic globalization after COP21: Insights from agricultural value-added and natural resources rents in the E7 economies. International Journal of Sustainable Development & World Ecology, 30(5): 500-514. https://doi.org/10.1080/13504509.2023.2166141
22. İçen, N.M.E. (2024). Türkiye’de yük kapasite faktörünün belirleyicileri nelerdir? Genişletilmiş ARDL yaklaşımı. Ekonomik ve Sosyal Araştırmalar Dergisi, 20(2): 299-312.
23. Johansen, S. and Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration-with appucations to the demand for money. Oxford Bulletin of Economics and statistics, 52(2): 169-210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x
24. Kayişoğlu, Ç. ve Türksoy, S. (2023). Tarımda sürdürülebilirlik ve gıda güvenliği. Bursa Uludağ Üniversitesi Ziraat Fakültesi Dergisi, 37(1): 289-303. https://doi.org/10.20479/bursauludagziraat.1142135
25. Khan, S. A. R., Godil, D. I., Quddoos, M. U., Yu, Z., Akhtar, M. H. and Liang, Z. (2021). Investigating the nexus between energy, economic growth, and environmental quality: A road map for the sustainable development. Sustainable Development, 29(5): 835-846. https://doi.org/10.1002/sd.2178
26. Landrigan, P. J., Fuller, R. Acosta, N. J., Adeyi, O., Arnold, R., Baldé, A. B. ... and Zhong, M. (2018). The Lancet commission on pollution and health. The Lancet, 391(10119): 462-512.
27. Landrigan, P. J., Stegeman, J. J., Fleming, L. E., Allemand, D., Anderson, D. M., Backer, L. C. ... and Rampal, P. (2020). Human health and ocean pollution. Annals of Global Health, 86(1). https://doi.org/10.5334/aogh.2831
28. Lee, J. and Strazicich, M.C. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics, 85(4): 1082-1089. https://doi.org/10.1162/003465303772815961
29. Li, J., Dong, K., Wang, K. and Dong X. (2023). How does natural resource dependence influence carbon emissions? The role of environmental regulation. Resources Policy, 80: 103268. https://doi.org/10.1016/j.resourpol.2022.103268
30. Mahmood, H., Alkhateeb, T. T. Y., Al-Qahtani, M. M. Z., Allam, Z., Ahmad, N. and Furqan, M. (2019). Agriculture development and CO2 emissions nexus in Saudi Arabia. PloS One, 14(12): e0225865. https://doi.org/10.1371/journal.pone.0225865
31. Mateo-Sagasta, J., Zadeh, S. M., Turral, H. and Burke, J. (2017). Water Pollution from Agriculture: A Global Review. Executive Summary. FAO, Rome, Italy.
32. Nabuurs, G. J., Mrabet, R., Hatab, A. A., Bustamante, M., Clark, H., Havlík, P., House, J. I., Mbow, C., Ninan, K. N., Popp, A., Roe, S., Sohngen, B., Towprayoon, S. and Steinfeld, J. P. (2023). Agriculture, Forestry and Other Land Uses (AFOLU). In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Eds(s): Shukla, P.R., Skea, J., Slade, R., Al Khourdajie, A., van Diemen, R., McCollum, D., Pathak, M., Some, S., Vyas, P., Fradera, R., Belkacemi, M., Hasija, A., Lisboa, G., Luz, S. and Malley, J., Cambridge University Press, Cambridge, U.K. and New York, NY, U.S.A. https://doi.org/10.1017/9781009157926.009
33. Narayan, P. K. (2005). The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics, 37(17): 1979-1990. https://doi.org/10.1080/00036840500278103
34. Narayan, P. K. and Narayan, S. (2010). Carbon dioxide emissions and economic growth: panel data evidence from developing countries. Energy Policy, 38: 661–666. https://doi.org/10.1016/j.enpol.2009.09.005
35. Narayan, P. K. and Smyth, R. (2005). Electricity consumption, employment and real income in Australia evidence from multivariate Granger causality tests. Energy Policy, 33(9): 1109-1116. https://doi.org/10.1016/j.enpol.2003.11.010
36. Nathaniel, S. P., Adeleye, N. and Adedoyin, F. F. (2021). Natural resource abundance, renewable energy, and ecological footprint linkage in MENA countries. Estudios de Economía Aplicada, 39(3): 1-16. https://doi.org/10.25115/eea.v39i2.3927
37. Our World in Data, (2024). https://ourworldindata.org/energy (Erişim Tarihi: Nisan 2024).
38. Pata, U. K. (2021). Do renewable energy and health expenditures improve load capacity factor in the USA and Japan? A new approach to environmental issues. The European Journal of Health Economics, 22(9): 1427-1439. https://doi.org/10.1007/s10198-021-01321-0
39. Pata, U. K. and Ertugrul, H. M. (2023). Do the Kyoto Protocol, geopolitical risks, human capital and natural resources affect the sustainability limit? A new environmental approach based on the LCC hypothesis. Resources Policy, 81: 103352. https://doi.org/10.1016/j.resourpol.2023.103352
40. Pata, U. K. and Isik, C. (2021). Determinants of the load capacity factor in China: a novel dynamic ARDL approach for ecological footprint accounting. Resources Policy, 74: 102313. https://doi.org/10.1016/j.resourpol.2021.102313
41. Pata, U. K. and Karlılar Pata, S. (2024). Assessing the power of biofuels and green technology innovation on the environment: The LCC perspective. Energy & Environment, https://doi.org/10.1177/0958305X241279
42. Pata, U. K. and Kartal, M. T. (2023). Impact of nuclear and renewable energy sources on environment quality: Testing the EKC and LCC hypotheses for South Korea. Nuclear Engineering and Technology, 55(2): 587-594. https://doi.org/10.1016/j.net.2022.10.027
43. Pata, U. K. and Samour, A. (2022). Do renewable and nuclear energy enhance environmental quality in France? A new EKC approach with the load capacity factor. Progress in Nuclear Energy, 149: 104249. https://doi.org/10.1016/j.pnucene.2022.104249
44. Pata, U. K., Kartal, M. T. Erdogan S. and Sarkodie, S.A. (2023). The role of renewable and nuclear energy R&D expenditures and income on environmental quality in Germany: Scrutinizing the EKC and LCC hypotheses with smooth structural changes. Applied Energy, 342: 121138. https://doi.org/10.1016/j.apenergy.2023.121138
45. Pesaran, M. H., Shin, Y. and Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3): 289–326. https://doi.org/10.1002/jae.616
46. Phillips, P.C. and Hansen, B.E. (1990). Statistical inference in instrumental variables regression with I (1) processes. The review of Economic Studies, 57(1): 99-125. https://doi.org/10.2307/2297545
47. Qin, G., Niu, Z., Yu, J., Li, Z., Ma, J. and Xiang, P. (2021). Soil heavy metal pollution and food safety in China: Effects, sources and removing technology. Chemosphere, 267: 129205. https://doi.org/10.1016/j.chemosphere.2020.129205
48. Raihan, A. (2023a). An econometric evaluation of the effects of economic growth, energy use, and agricultural value added on carbon dioxide emissions in Vietnam. Asia-Pacific Journal of Regional Science, 7(3): 665-696. https://doi.org/10.1007/s41685-023-00278-7
49. Raihan, A. (2023b). The dynamic nexus between economic growth, renewable energy use, urbanization, industrialization, tourism, agricultural productivity, forest area, and carbon dioxide emissions in the Philippines. Energy Nexus, 9: 100180. https://doi.org/10.1016/j.nexus.2023.100180
50. Reddy, V. R. and Behera, B. (2006). Impact of water pollution on rural communities: An economic analysis. Ecological economics, 58(3): 520-537. https://doi.org/10.1016/j.ecolecon.2005.07.025
51. Ridwan, M., Akther, A., Tamim, M.A., Ridzuan, A. R., Esquivias, M. A. and Wibowo, W. (2024). Environmental health in BIMSTEC: the roles of forestry, urbanization, and financial access using LCC theory, DKSE, and quantile regression. Discover Sustainability, 5(1): 429. https://doi.org/10.1007/s43621-024-00679-4
52. Ritchie, H., Rosado, P. and Roser, M. (2022). Environmental Impacts of food production. Published online at OurWorldinData.org. https://ourworldindata.org/environmental-impacts-of-food (Access Date: April 2024).
53. Sarkodie, S. and Owusu, P. (2017). The relationship between carbon dioxide, crop and food production index in Ghana: By estimating the long-run elasticities and variance decomposition. Environmental Engineering Research, 22(2): 193-202. https://doi.org/10.4491/eer.2016.135
54. Shah, M. I., AbdulKareem, H. K., Ishola B. D. and Abbas, S. (2023). The roles of energy, natural resources, agriculture and regional integration on CO2 emissions in selected countries of ASEAN: Does political constraint matter? Environmental Science and Pollution Research, 30(10): 26063-26077. https://doi.org/10.1007/s11356-022-23871-3
55. Siche, R., Pereira, L. Agostinho, F. and Ortega, E. (2010). Convergence of ecological footprint and emergy analysis as a sustainability indicator of countries: Peru as case study. Communications in Nonlinear Science and Numerical Simulation, 15(10): 3182-3192. https://doi.org/10.1016/j.cnsns.2009.10.027
56. Toda, H. Y. and Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66(1-2): 225-250. https://doi.org/10.1016/0304-4076(94)01616-8
57. Topal, S. (2024). LCC hipotezi çerçevesinde Türkiye’de kirlilik sığınağı ve kirlilik hale hipotezlerinin sınanması. Uluslararası Yönetim İktisat ve İşletme Dergisi, 20(2): 418-436. https://doi.org/10.17130/ijmeb.1414228
58. Ürkmez, İ., Sevim, A. and Çatık, A. (2024). The relationship between agriculture and carbon dioxide emission in Türkiye: A non-linear Evidence. Journal of Tekirdag Agricultural Faculty, 21(1): 94-110. https://doi.org/10.33462/jotaf.1239615
59. Usman, M. and Makhdum, M. S. A. (2021). What abates ecological footprint in BRICS-T region? Exploring the influence of renewable energy, non-renewable energy, agriculture, forest area and financial development. Renewable Energy, 179: 12-28. https://doi.org/10.1016/j.renene.2021.07.014:
60. WHO (2016). World Health Organization, Ambient Air Pollution: A Global Assessment of Exposure and Burden of Disease. WHO document production services, Geneva, Switzerland. https://iris.who.int/bitstream/handle/10665/250141/9789241511353-eng.pdf (Erişim Tarihi: Mart 2024).
61. World Bank (2024). World Development Indicators. https://databank.worldbank.org/reports.aspx?source=world-development-indicators (Erişim Tarihi: Nisan 2024).
62. Xu, Y., Li, C. and Wang, J. (2023). How does agricultural global value chain affect ecological footprint? The moderating role of environmental regulation. Sustainable Development, 31(4): 2416-2427. https://doi.org/10.1002/sd.2518