Financial stability and profitability of enterprises as indicators of the economic efficiency of Russian livestock subsectors: SPARK data for 2021-2025

The article presents a comparative analysis of the financial stability and profitability of Russian dairy cattle, pig, and poultry enterprises. The relevance of the study stems from the fact that aggregated industry-level livestock profitability indicators published by Rosstat do not provide sufficient insight into the financial position of individual organizations or the degree of differentiation within livestock subsectors. The purpose of the study is to identify the specific combinations of profitability and financial stability across individual livestock subsectors and to assess their significance for economic efficiency and the sustainability of subsector performance. The empirical basis comprises a sample of 505 active organizations from three livestock subsectors, formed using data from the SPARK-Interfax information and analytical system for 2021-2025, while Rosstat industry statistics were used to characterize the broader sectoral context. The study calculates median values of return on net assets, the equity-to-assets ratio, the current liquidity ratio, the debt-to-net-assets ratio, and the share of loss-making organizations for each subsector. The results show that dairy cattle farming is characterized by relatively stable profitability and a conservative capital structure; pig farming combines acceptable median profitability with a high share of loss-making organizations and comparatively low current liquidity; poultry farming demonstrates the highest profitability potential together with the greatest amplitude of annual changes: following the improvement observed in 2023-2024, median return on net assets fell to 7.4% in 2025, while the share of loss-making organizations increased to 24.5%. It is concluded that differences in profitability, capital structure, liquidity, and debt burden should be taken into account, when assessing economic efficiency and designing support measures for individual livestock subsectors. The results may be used by lending institutions and public agricultural support authorities for differentiated risk assessment and the allocation of subsidies across livestock subsectors.