Modelling the efficiency of the agricultural sectors in EU countries and Ukraine: integrated assessment, convergence analysis, and typology

Purpose. The study aims to develop an integrated approach to assessing the efficiency of the agricultural sectors of EU countries and Ukraine and to examine their convergence patterns, stability, and development trajectories. It also seeks to determine whether lower-efficiency countries demonstrate catching-up dynamics, whether cross-country disparities diminish over time, and how Ukraine is positioned within the European agricultural efficiency framework. Methodology. The integrated efficiency index combines normalised CRS-DEA, VRS-DEA, SFA, and Malmquist total factor productivity change estimates. CRITIC is used as the principal objective weighting method, while entropy weighting provides a robustness check. β- and σ-convergence models, correlation analysis, and criterion-based typological classification are applied to EU data for 2016–2024; Ukraine is assessed for 2016–2022 because comparable later data are unavailable. Results. The findings reveal substantial cross-country differences in agricultural efficiency, with Denmark, the Netherlands, Belgium, and Italy among the leading countries, while Ukraine remains in the low or unstable efficiency group. The results confirm predominantly conditional β-convergence and partial, non-monotonic σ-convergence. Higher average efficiency is strongly associated with lower volatility, while CRITIC- and entropy-based country rankings are highly consistent. Four distinct efficiency trajectory groups are identified. Originality. The study integrates deterministic and stochastic frontier methods, productivity dynamics, objective weighting, convergence analysis, and country typology within a unified analytical framework. Unlike approaches based on a single efficiency measure or predefined weights, the proposed methodology combines static and dynamic dimensions of agricultural performance using data-driven weighting. The integrated index is applied not only to country ranking but also to analysing convergence, stability, and heterogeneous development trajectories. Practical implications. The results provide an analytical basis for differentiated agricultural policies tailored to the efficiency level, dynamics, and stability of each country group. Policy priorities include maintaining technological leadership in highly efficient countries, supporting modernisation in catching-up economies, and strengthening structural and institutional support in low or unstable efficiency systems.