TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES

Ziya Gökalp Göktolga

doi:10.37880/cumuiibf.1940440

TR EN

ÇEVRESEL KUZNETS EĞRİSİ HİPOTEZİNİN TARIMSAL KİRLİLİK BAĞLAMINDA GEÇERLİLİĞİNİN TESTİ: G20 ÜLKELERİNDE PANEL VERİ ANALİZİ İLE BİR UYGULAMA

Öz

Tarımsal kirlilik küresel ölçekte kritik seviyelere ulaşmış olup, tarımsal emisyonların ekonomik kalkınmayla nasıl değişeceğinin araştırılması önem arz etmektedir. Bu çalışma, tarımsal kirliliğin 1990-2020 dönemi boyunca G20 ülkeleri için Çevresel Kuznets Eğrisi (EKC) yaklaşımını takip edip etmediğini deneysel olarak araştırmaktadır. Araştırma, özellikle karbondioksitten (CO2) önemli ölçüde daha yüksek küresel ısınma potansiyeline sahip olan azot oksit (N2O) ve metan (CH4) emisyonlarına odaklanmaktadır. Bu çalışma, yatay kesit bağımlılığı ve heterojenliği hesaba katan panel veri tekniklerini kullanmaktadır; CIPS birim kök ve Westerlund eş bütünleşme testleri kullanılmış ve katsayılar CCEMG tahmincisi kullanılarak hesaplanmıştır. Bulgular, tarımsal N2O emisyonları için EKC hipotezini desteklemekte ve ters U şeklinde ilişki ortaya koymaktadır. N2O emisyonları için dönüm noktası, yaklaşık 1,377 trilyon dolarlık bir GSYİH eşiğinde belirlenmiştir. Ayrıca, emisyonların azaltılmasında yenilenebilir ve fosil enerji tüketiminin rolleri de analiz edilmiştir. Bu sonuçlar, G20 ülkeleri için ekonomik büyüme, tarımsal sürdürülebilirlik ve enerji dönüşümü arasındaki dengeye ilişkin kritik politika çıkarımları sunmaktadır.

Anahtar Kelimeler

TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES

Öz

Agricultural pollution has reached critical levels globally, making it important to investigate how agricultural emissions will change with economic development. This study empirically investigates whether agricultural pollution follows the Environmental Kuznets Curve (EKC) framework for G20 countries over the 1990-2020 period. Distinctively, the research focuses on nitrous oxide (N2O) and methane (CH4) emissions, which possess significantly higher global warming potential than carbon dioxide (CO2). This study employs panel data techniques that account for cross-sectional dependence and heterogeneity, using CIPS unit root and Westerlund cointegration tests; coefficients were calculated using the Common Correlated Effects Mean Group (CCEMG) estimator. The findings support the EKC hypothesis for agricultural N2O emissions and reveal inverted U-shaped relationship. The turning point for N2O emissions is identified at a GDP threshold of approximately $1.377 trillion. The findings do not support the EKC hypothesis for agricultural methane (CH4) emissions. Furthermore, the roles of renewable and fossil energy consumption in mitigating emissions are analyzed. These results provide critical policy implications for G20 nations regarding the balance between economic growth, agricultural sustainability, and energy transition.

Anahtar Kelimeler

Kaynakça

Afshan, S., Ozturk, I., Yaqoob, T. (2022). Facilitating renewable energy transition, ecological innovations and stringent environmental policies to improve ecological sustainability: evidence from MM-QR method. Renewable Energy, 196, 151–160.
Alkhars M.A., Alwahaishi S., Fallatah M.R. & Kayal, A. (2022). A literature review of the Environmental Kuznets Curve in GCC for 2010–2020. Environmental and Sustainability Indicators, 14, 100181. https://doi.org/10.1016/j.indic.2022.100181
Al-Mulali, U. & Ozturk, I. (2016). The investigation of environmental Kuznets Curve hypothesis in the advanced economies: the role of energy prices. Renewable and Sustainable Energy Reviews, 54, 1622–1631.
Anwar, A., Siddique, M., Dogan, E. & Sharif, A. (2021). The moderating role of renewable and non-renewable energy in environment-income nexus for ASEAN countries: evidence from Method of Moments Quantile Regression. Renew. Energy 164, 956–967.
Apergis N. (2016). Environmental Kuznets Curves: new evidence on both panel and country-level co2 emissions. Energy Economics, 54, 263-271.
Arrow, K., Bolin, B., Costanza, R., Folke, C., Holling, C.S., Janson, B., Levin, S., Maler, K., Perrings, C. & Pimental, D. (1996). Economic growth, carrying capacity, and the environment. Ecological Application , 6(1), 13-15.
Aslan, A., Destek, M.A. & Okumus, I. (2018). Bootstrap rolling window estimation approach to analysis of the Environment Kuznets Curve hypothesis: evidence from the USA. Environ. Sci. Pollut. Control Ser. 25, 2402–2408.
Awaworyi Churchill S., Inekwe J., Ivanovski K. & Smyth R. (2018). The environmental Kuznets Curve in the OECD: 1870–2014. Energy Economics, 75, 389-399.

Bilgili, F., Koçak, E. & 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.
Blomquist, J. & Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters 121, 374 - 378.
Bölük, G. & Mert, M. (2015). The renewable energy, growth and environmental Kuznets Curve in Turkey: an ARDL approach. Renewable and Sustainable Energy Reviews, 52, 587–595.
Breusch, T. & Pagan, A. (1980). The Lagrange multiplier test and its application to model specification in econometrics. Review of Economics Studies, 47 (1), 239–253.
Dinda S. (2004). Environmental Kuznets Curve hypothesis: a survey. Ecological Economics, 49:431–55.
Dong K., Sun R., Jiang, H. & Zeng X. (2018). CO2 emissions, economic growth, and the environmental Kuznets Curve in China: What roles can nuclear energy and renewable energy play? Journal of Cleaner Production,196, 51-63.
Dumitrescu, E.I. & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29 (4), 1450–1460.
Farhani, S. & Shahbaz, M. (2014). What role of renewable and non-renewable electricity consumption and output is needed to initially mitigate CO2 emissions in MENA region?. Renewable and Sustainable Energy Reviews, 40, 80–90.
Grossman, G.M. &Krueger, A.B. (1991). Environmental impacts of the north American free trade agreement. John M. Ohlin Program Discussion Paper No. 158, Princeton.
Grossman, G. M. & Krueger, A. B. (1995). Economic growth and the environment. The Quarterly Journal of Economics, 110(2): 353-377.
Iwata, H., Okada, K. & Samreth, S. (2010). Empirical study on the environmental Kuznets Curve for CO2 in France: the role of nuclear energy. Energy Policy, 38 (8), 4057–4063.
Jalil, A. & Feridun, M. (2011). The impact of growth, energy and financial development on the environment in China: a cointegration analysis. Energy Economics 33 (2), 284–291.
Jebli, M.B., Youssef, S.B. & Ozturk, I. (2016). Testing environmental Kuznets Curve hypothesis: the role of renewable and non-renewable energy consumption and trade in OECD countries. Ecological Indicators, 60,824–831.
Kasman, A. & Duman, Y.S. (2015). CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: a panel data analysis. Economic Modelling, 44, 97–103.
Kuznets, S. (1955). Economic growth and income inequality. The American Economic Review, 45(1): 1-28.
Lau, L.S., Choong, C.K., Ng, C.F., Liew, F.M. & Ching, S.L. (2019). Is nuclear energy clean? revisit of environmental Kuznets Curve hypothesis in OECD countries. Economic. Modelling. 77, 12–20.
Lean, H.H. & Smyth, R. (2010). CO2 emissions, electricity consumption and output in ASEAN. Applied Energy 87 (6), 1858–1864.
Lopez, J.C., Quijano, G., Souza, T.S.O., Estrada, J.M., Lebrero, R. & Muñoz, R. (2013). Biotechnologies for greenhouse gases (CH4, N2O, and CO2) abatement: state of the art and challenges. Applied Microbiology and Biotechnology, 97, 2277-2303.
NASA. (2025a). Climate change, Carbon dioxide. https://climate.nasa.gov/vital-signs/carbon-dioxide/?intent=11
NASA. (2025b). Climate change, Global Temperature. https://climate.nasa.gov/vital-signs/global-temperature/?intent=111
Olale E., Ochuodho T.O., Lantz V. & Armali J. (2018). The environmental Kuznets Curve model for greenhouse gas emissions in Canada. Journal of Cleaner Production 184 (2018) 859-868.
Panayotou, T. (1993). Empirical tests and policy analysis of environmental degradation at different stages of economic development. Working Paper, International Labour Office, Geneva.
Pao, H.T. & Tsai, C.M. (2011). Multivariate Granger causality between CO2 emissions, energy consumption, FDI (foreign direct investment) and GDP (gross domestic product): evidence from a panel of BRIC (Brazil, Russian Federation, India, and China) countries. Energy, 36 (1), 685–693.
Paratama, D.P. (2023). Analysis of the determinants of economic growth in G20 countries 2012-2021. Indonesian Journal of Development Economics, 6(3), 290-311.
Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74, 967-1012.
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.
Pesaran, M.H. & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142 (1), 50-93.
Pesaran, M. H. (2015). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6–10), 1089–1117.
Pesaran, M. H. (2021). General diagnostic tests for cross section dependence in panels. Empirical Economics, 60, 13–50.
Selden, T.M. & Song D. (1994). Environmental quality and development: is there a Kuznets Curve for air pollution emissions? Journal of Environmental Economics and Management, 27:147–62.
Shafiei, S. & Salim, R.A. (2014). Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: a comparative analysis. Energy Policy, 66, 547–556.
Shafik, N. & Bandyopadhyay, S. (1992). Economic growth and environmental quality: time series and cross country evidence. Working Papers for World Development Report 1992, World Bank, Washington, DC (1992) p. 904.
Sharif, A., Baris-Tuzemen, O., Uzuner, G., Ozturk, I. & Sinha, A. (2020). Revisiting the role of renewable and non-renewable energy consumption on Turkey’s ecological footprint: evidence from Quantile ARDL approach. Sustainable Cities and Society. 57, 102138.
Sugiawan, Y. & Managi, S. (2016). The environmental Kuznets Curve in Indonesia: exploring the potential of renewable energy. Energy Policy 98, 187–198.
Suri, V. & Chapman, D. (1998). Economic growth, trade and energy: implications for the environmental Kuznets Curve. Ecological Economics, 25,195–208.
Wang Q., Zhang F. & Li R. (2023). Revisiting the environmental Kuznets Curve hypothesis in 208 counties: The roles of trade openness, human capital renewable energy and natural resource rent. Environmental Research, 216, (3), 114637.
Westerlund, J. (2007). Testing for error correction in panel data. Oxford. Bulletin of Economics and Statistics. 69(6), 709-748.
World Bank (2025). World Bank web site. https:// https://data.worldbank.org/indicator/ EN.GHG.CH4.AG.MT.CE.AR5
Yang, Z., Abbas, Q., Hanif, I., Alharthi, M., Taghizadeh-Hesary, F., Aziz, B. & Mohsin, M. (2021). Short-and long-run influence of energy utilization and economic growth on carbon discharge in emerging SREB economies. Renew. Energy 165, 43–51.
Yılmaz, G. & Daşdemir, E. (2020). Renewable energy use and energy productivity: a panel data analysis. Journal of Sustainable Economics and Management Studies, 1(1), 73-82.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Panel Veri Analizi

Bölüm

Araştırma Makalesi

Yazarlar

Ziya Gökalp Göktolga ^*
0000-0003-4438-4096
Türkiye

Yayımlanma Tarihi

26 Temmuz 2026

Gönderilme Tarihi

29 Nisan 2026

Kabul Tarihi

22 Temmuz 2026

Yayımlandığı Sayı

Yıl 2026 Cilt: 27 Sayı: 3

DOI

https://doi.org/10.37880/cumuiibf.1940440

IZ

https://izlik.org/JA23RF85AP

Kaynak Göster

RIS / Bibtex

APA

Göktolga, Z. G. (2026). TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 27(3), 1090-1106. https://doi.org/10.37880/cumuiibf.1940440

AMA

1.Göktolga ZG. TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2026;27(3):1090-1106. doi:10.37880/cumuiibf.1940440

Chicago

Göktolga, Ziya Gökalp. 2026. “TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES”. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi 27 (3): 1090-1106. https://doi.org/10.37880/cumuiibf.1940440.

EndNote

Göktolga ZG (01 Temmuz 2026) TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi 27 3 1090–1106.

IEEE

[1]Z. G. Göktolga, “TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES”, Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, c. 27, sy 3, ss. 1090–1106, Tem. 2026, doi: 10.37880/cumuiibf.1940440.

ISNAD

Göktolga, Ziya Gökalp. “TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES”. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi 27/3 (01 Temmuz 2026): 1090-1106. https://doi.org/10.37880/cumuiibf.1940440.

JAMA

1.Göktolga ZG. TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2026;27:1090–1106.

MLA

Göktolga, Ziya Gökalp. “TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES”. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, c. 27, sy 3, Temmuz 2026, ss. 1090-06, doi:10.37880/cumuiibf.1940440.

Vancouver

1.Ziya Gökalp Göktolga. TESTING THE VALIDITY OF THE ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN THE CONTEXT OF AGRICULTURAL POLLUTION: AN APPLICATION WITH PANEL DATA ANALYSIS IN G20 COUNTRIES. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi. 01 Temmuz 2026;27(3):1090-106. doi:10.37880/cumuiibf.1940440