Methodology for comprehensive assessment of the effectiveness of financial support for sustainable development of the agricultural sector based on a risk-oriented approach
DOI:
https://doi.org/10.26906/EiR.2026.1%20(100).4392Keywords:
sustainable development financial support, agricultural sector, risk-based approach, ESG risks, composite indicatorsAbstract
The article develops an original methodology for comprehensive assessment of the effectiveness of financial support for sustainable development of the agricultural sector based on a risk-oriented approach. The study addresses a significant scientific problem: the absence of integrated tools that simultaneously incorporate ESG risk assessment and measure the multidimensional effectiveness of financial flows through a domain-based index construction. The proposed methodology is aligned with the regulatory logic of sustainable finance as established by the National Bank of Ukraine (Sustainable Finance Policy, ESG Risk White Paper), EBA guidelines on ESG risk management, IFRS S2 climate-related disclosures, and NGFS climate scenarios. The author proposes a two-level risk quantification system adapted to the military-climate context of Ukraine, and a system of indicators in five interconnected domains (Economic, Inclusion, Environmental, Social, Governance), each reflecting a specific channel of the mechanism’s impact on agricultural sector sustainability. A key methodological innovation is the inclusion of the G-component directly in mechanism performance indicators. Based on the OECD/JRC methodology for constructing composite indicators, the Integrated Mechanism Effectiveness Index (IME) is built through alternative weighting regimes (AHP/Delphi, PCA, Shannon entropy) and two aggregation schemes (additive and geometric), enabling robustness testing. The methodology is validated using publicly available data for the Ukrainian agricultural sector (2021 vs 2023), demonstrating that the additive IME captured a 5–7% decline in overall mechanism effectiveness due to military shocks, while the geometric IME revealed improved balance through strengthening of the weakest domains. The results confirm the methodology’s operational value for identifying critical domains and substantiating financial policy priorities under conditions of military-climate transformation. It can be applied by banks, regulators, and public authorities for evidence-based targeting.
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