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Forecasting the volume of foreign direct investment in Ukraine’s agricultural sector based on polynomial regression
The article presents a scientifically grounded medium-term forecast of foreign direct investment (FDI) in the agricultural sector of Ukraine for 2025–2027, using second-degree polynomial regression and the autoregressive integrated moving average model (ARIMA (1,1,1)). The study takes into account the complex and nonlinear dynamics of investment flows, the inertia of processes, and the influence of external and internal factors. To improve the accuracy of the forecast, adjusted statistical data for 2014–2024 were used, excluding anomalous periods that could distort the modeling results.
The calculations indicate a moderate growth in FDI in 2025–2027 (USD 3,245.3 million in 2025, USD 3,300.0 million in 2026, and USD 3,350.0 million in 2027), reflecting a gradual recovery of investment activity and stabilization of macroeconomic conditions. The model demonstrates an acceptable level of predictive accuracy based on MAE, RMSE, MAPE, and WAPE indicators, while the absence of residual autocorrelation confirms its adequacy.
The results highlight the need to strengthen state policy to enhance the investment attractiveness of the agricultural sector, in particular through infrastructure development, reduction of regulatory pressure, provision of legal protection for investors, and activation of international support. It is concluded that the proposed model is suitable for forming a baseline forecast scenario in conditions of high variability in the investment environment. The findings can be utilized by public authorities, research institutions, and investment analysts for making informed management decisions in the economic development of agriculture.
Keywords: foreign direct investment, agricultural sector, polynomial regression, forecast, trend model, Ukraine, investment climate.
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https://orcid.org/0000-0003-4253-8696