Сausal-econometric modelling of the relationships between gross value added and production factors in the development of Ukraine’s manufacturing

The article discusses the causal econometric modeling of the relationship between gross value added (GVA) and production factors of the development of the processing industry in Ukraine. The war and the accompanying economic challenges require the development of effective strategy models that can contribute to the recovery of the industry, which is a key driver of economic growth. The authors used a multiplicative power production function, taking into account three main factors: labor costs, fixed assets, and capital investments. The regression analysis showed a high accuracy of the model, with a determination coefficient of R² = 0.9691, which indicates the effectiveness of the variables used to explain the variations in GVA. The results of the study confirm that labor costs are the most significant factor influencing GVA (coefficient 0.893), compared to fixed assets (coefficient 0.333). The study also emphasizes the need to increase investment in technological development, modernize production facilities, and support human capital. The analysis of the industry dynamics for 2015-2022 demonstrates the dependence of its indicators on external economic factors, such as the pandemic and the war, which caused a significant decline in capital investment and wages, which negatively affected GVA. The proposed model is a tool for forecasting the economic development of the manufacturing industry in the postwar period. Its use allows us to determine the optimal directions of state policy aimed at increasing labor productivity, investment activity, and increasing the competitiveness of the industry. The study is a valuable contribution to the creation of effective analytical tools for the neo-industrial development of Ukraine's economy.