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International convergence towards a climate-neutral economy: modeling the agricultural sector

Author

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  • Krysovatyy, Andriy
  • Maksymova, Iryna
  • Kurilyak, Vitalina
  • Radin, Michael
  • Kurilyak, Maksym

Abstract

Purpose. This article aims to construct a comprehensive convergent model for assessing the global and EU’s progress, degree of consolidation and symmetry of agricultural economies towards climate neutrality in the context of key international green initiatives. Methodology / approach. This research employs both qualitative and quantitative analyses to assess convergence measures in the agricultural sector’s carbon emissions. The quantitative component relies on the sigma and beta convergence models to evaluate international convergence in carbon emissions CO2 dynamics. The dimensions of modeling are as follows: global sample within 194 countries with reliable emissions data; European Union, focusing on convergence within the EU27 member states, the United Kingdom, and Ukraine. The time period covers open data from 1972–2022. The dynamics of sigma and beta convergence is determined for the points, namely UN Stockholm Conference (1972), UN Rio Conference (1992), Kyoto Protocol (entry into force in 2005), Paris Agreement (2015). Additionally, statistical indicators of variation, skewness, Gini and Theil indices were calculated for delineating global smoothness and the concentration of agricultural emissions. Results. The results of the study reveal an inertial and divergent trend of the agricultural economy towards decarbonisation, which slows down the overall movement towards “net zero” due to the presence of clubs of lagging agricultural countries that increase emissions in violation of international agreements. The reduction in emissions skewness in recent years shows that more countries are “pulling” decarbonisation due to their high capacity to move towards net zero, but this is not enough. The EU is the most prominent example of accelerated climate convergence, but markers of its weakening in recent years are identified due to the inability of economies to maintain the pace of decarbonisation caused by economic constraints, technological barriers, policy and regulatory issues, and misunderstandings of climate neutrality goals. It is shown that the long-term decarbonisation capacity of the agricultural sector is the key trigger for a country to make a positive contribution to the global convergence towards climate neutrality. At the current stage, the pace of decarbonisation plays a much greater role for consolidating efforts in the agricultural economy and achieving climate neutrality than the initial level of emissions in the sector. Factors in this process include proactive compliance with global climate agreements, technology sharing and cooperation, digitalisation and smart agriculture, and green financing and investment. Its implementation requires a three-way integration of stakeholder actions, strategy selection and results evaluation. Originality / scientific novelty. The study’s originality lies in its large-scale analysis of over 50 years of emissions dynamics and the context of five key green agreements that provided support for the green transition. It allows studying international convergence in agricultural sectors globally and within the EU. The novelty implies the integrated use of sigma and beta convergence models that identifies predictors of convergent and divergent processes and separates countries into leaders and laggards of agricultural decarbonisation. This approach provides a comprehensive view of modern climate policy, the impact of international green initiatives, and the position of individual towards climate neutrality in agriculture. Practical value / implications. The practical value lies in the ability to adjust climate policies for the agricultural economy’s decarbonisation, facilitating the determination of prospective outcomes for achieving climate neutrality. The aforementioned factors facilitate the process of governmental decision-making. The assessment of international programmatic agreements' effectiveness is enhanced through these models. The study offers a framework for global convergence towards climate neutrality in agriculture, highlighting the importance of digital technologies and smart agriculture as significant factors in global convergence.

Suggested Citation

  • Krysovatyy, Andriy & Maksymova, Iryna & Kurilyak, Vitalina & Radin, Michael & Kurilyak, Maksym, 2024. "International convergence towards a climate-neutral economy: modeling the agricultural sector," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 10(2), June.
  • Handle: RePEc:ags:areint:355962
    DOI: 10.22004/ag.econ.355962
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    References listed on IDEAS

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    1. Salena Tramel, 2018. "Convergence as political strategy: social justice movements, natural resources and climate change," Third World Quarterly, Taylor & Francis Journals, vol. 39(7), pages 1290-1307, July.
    2. Arkadiusz Kijek & Tomasz Kijek & Anna Nowak, 2020. "Club convergence of labour productivity in agriculture: Evidence from EU countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(9), pages 391-401.
    3. Niklas H�hne & Michel den Elzen & Martin Weiss, 2006. "Common but differentiated convergence (CDC): a new conceptual approach to long-term climate policy," Climate Policy, Taylor & Francis Journals, vol. 6(2), pages 181-199, March.
    4. Sun, Huaping & Kporsu, Anthony Kwaku & Taghizadeh-Hesary, Farhad & Edziah, Bless Kofi, 2020. "Estimating environmental efficiency and convergence: 1980 to 2016," Energy, Elsevier, vol. 208(C).
    5. Bisrat Kinfemichael, 2019. "The rise of services and convergence in labor productivity among countries," Applied Economics Letters, Taylor & Francis Journals, vol. 26(21), pages 1749-1755, December.
    6. Junfang Zhao & Dongsheng Liu & Ruixi Huang, 2023. "A Review of Climate-Smart Agriculture: Recent Advancements, Challenges, and Future Directions," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    7. Peng Guo & Huizhong Shen & Yilin Chen & Hancheng Dai & Zelin Mai & Ruibin Xu & Ruixin Zhang & Zhanxiang Wang & Jinling He & Lianming Zheng & Haitong Zhe Sun & Kainan Ke & Jing Meng & Maodian Liu & Jin, 2024. "Carbon dioxide emissions from global overseas coal-fired power plants," Nature Climate Change, Nature, vol. 14(11), pages 1151-1157, November.
    8. Haoting Wu & Junfang Zhao & Jianqing Wan, 2023. "A Review of Veterinary Drug Residue Detection: Recent Advancements, Challenges, and Future Directions," Sustainability, MDPI, vol. 15(13), pages 1-12, July.
    9. Enrico Piero Marelli & Maria Laura Parisi & Marcello Signorelli, 2019. "Economic convergence in the EU and Eurozone," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(7), pages 1332-1344, November.
    10. Jingxiu Qin & Weili Duan & Shan Zou & Yaning Chen & Wenjing Huang & Lorenzo Rosa, 2024. "Global energy use and carbon emissions from irrigated agriculture," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
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