IMPORT ACTIVITY IN UKRAINE: FORECASTING, MATRIX MODELLING AND GOVERNMENT REGULATION

Introduction. Ukraine's import activity is an important component of the national economy, which affects the stability of the domestic market, price levels, industrial development, and the foreign trade balance. In the context of global economic instability, changes in international trade policy, and domestic challenges, there is a need to forecast import activity and its influencing factors. Purpose. The purpose of this study is to model scenarios of development of Ukraine's import activity and influencing factors using Markov processes, which will help to determine the likely states of import activity and influencing factors and propose government regulation measures to minimise risks and maximise benefits. Materials and methods. The research materials are: 1) data of the State Statistics Service of Ukraine; 2) works of the authors in the field of forecasting, which focus on the development of innovative approaches to data analysis, modelling future economic and social processes, as well as creating reliable forecasting models. In order to achieve this goal, the study involved modelling based on Markov processes, which is described by a system of Kolmogorov differential equations and a corresponding system of algebraic equations. The system of differential equations was solved using the Runge-Kutta numerical method, and the system of algebraic equations was solved using the Gauss-Laplace numerical method. The research methodology involved representing the import activity and the factors of influence in the form of a state graph, where each state of the system is clearly defined and mutually exclusive. Using the Kolmogorov system of differential equations, the probabilities of the system being in different states were calculated, which allowed forecasting future changes in import flows. Results. The results of the calculations showed that import activity in the future may be in three different states (‘very good', ‘good' and ‘satisfactory') with approximately the same probability of 28.57%, and for the factors of influence there is a high probability of being in the ‘satisfactory' state in close proximity to the ‘unsatisfactory' state, which is unacceptable and emphasises the need for constant monitoring and management of import activity and factors of influence to ensure stability and growth in the face of uncertainty. Based on the results of the forecast, the NBU has proposed state regulation measures to stabilise the current situation. Discussion. Prospects for further research include expanding the range of analysed factors, introducing innovative approaches and technologies, and adapting to uncertainty and crisis situations.