INTEGRAL ASSESSMENT OF THE ADAPTIVE CAPACITY OF THE TAX SYSTEM OF UKRAINE BASED ON FUZZY LOGIC IN THE WARTIME AND POSTWAR PERIODS

Abstract

Introduction. The full-scale war, the structural contraction of economic activity, the growing budget deficit, and the increasing financing needs of the security sector have significantly complicated the maintenance of the state’s fiscal sustainability. Under such conditions, the tax system must not only ensure the stability of budget revenues but also demonstrate the capacity for rapid response to crisis shocks, support economic activity, and facilitate post-war economic recovery. Traditional econometric approaches are unable to fully account for the nonlinear nature of interrelationships, multicriteria characteristics, and the high degree of uncertainty inherent in contemporary crisis processes. In this context, the application of fuzzy logic methods becomes particularly relevant, as they enable the formalization of complex socio-economic systems under conditions of incomplete certainty.

Purpose. The purpose of the study is to develop a conceptual and methodological approach to the integral assessment of the adaptive capacity of the tax system of Ukraine based on a multi-level Mamdani fuzzy model under conditions of wartime and post-war transformations.

Materials and Methods. The research materials include: (1) official statistical data on the functioning of the tax system of Ukraine during 2018–2025; (2) scientific works of domestic and foreign scholars addressing fuzzy modeling, fiscal sustainability, and the adaptability of tax systems; and (3) analytical materials concerning macroeconomic and fiscal transformations within a wartime economy. The following scientific methods were employed in the study: systems analysis (for constructing the structure of the integral index of adaptive capacity); analysis and synthesis (for selecting indicators and developing sub-indices); methods of fuzzy set theory and Mamdani fuzzy inference (for developing the multi-level fuzzy model); scenario analysis (for forecasting the development of the adaptive capacity of the tax system); and theoretical generalization (for interpreting the modeling results).

Results. The article proposes a scientifically grounded approach to the integral assessment of the adaptive capacity of the tax system of Ukraine under wartime and post-war transformations. Adaptive capacity is interpreted as the ability of the system to ensure the stability of fiscal revenues, flexibly respond to macroeconomic shocks, and maintain budget equilibrium. A multi-level fuzzy model based on the Mamdani algorithm was developed, aggregating four sub-indices: fiscal performance, flexibility of tax policy, structural resilience of the tax base, and institutional capacity. The advantages of applying fuzzy logic for modeling nonlinear interrelationships and uncertainty were substantiated. The dynamics of the integral indicator for 2018–2025 were obtained, and scenario forecasting was conducted, enabling the model to be used as an instrument for the strategic analysis of fiscal policy.

Discussion. Further research should focus on improving the structure of the integral model through the inclusion of indicators reflecting tax compliance, the level of the shadow economy, environmental and behavioral factors, as well as the application of adaptive neuro-fuzzy systems and machine learning methods for the automated optimization of membership functions and the fuzzy rule base.