Modelling of the factor influence of grain market performance indicators on Ukraine’s GDP

The study addressed the impact of grain market performance indicators on the dynamics of Ukraine’s gross domestic product in the context of structural transformations and military challenges. The study aimed to quantitatively determine the strength, direction and nature of the impact of production, export and structural indicators of grain market development on the country’s macroeconomic performance, using economic and mathematical tools. The research methods included statistical analysis of the dynamics of indicators for 2010-2025, correlation analysis, and correlation-regression modelling. A distinctive feature of the methodological approach was the use of variational modelling, which involved constructing several alternative models with different sets of factor variables and testing them against criteria of statistical significance. The results of the study showed that Ukraine’s grain market has transformed into a highly specialised, export-oriented sector: gross grain harvest increased from 39.27 million tonnes in 2010 to 86.01 million tonnes in 2021, and exports – from 2.47 to USD 12.34 billion. The study established that the most significant impact on GDP was exerted by agricultural exports (r = 0.608), whereas the impact of grain exports was moderate (r = 0.415) and had a negative coefficient in the regression models (-21.4…-23.0), indicating a raw material orientation effect. The study demonstrated that production indicators do not have a direct statistically significant impact (r = 0.104) but are realised through export channels. At the same time, a 1% increase in the share of grain in agricultural exports is accompanied by a USD 335 million decrease in GDP, whereas an increase in the share of grain in total exports leads to a 242 million USD rise in GDP. The application of a variational approach to econometric modelling has revealed that the impact of the grain market on GDP is non-linear and structurally determined, with the decisive factors being not production volumes but the parameters of export integration. The practical significance of the results lies in their potential application in the formulation of state agricultural policy, particularly for the transition from a raw material export model to a model with higher added value, which will contribute to improving the efficiency of the grain sector and strengthening macroeconomic stability