Time-Series Analysis and Arima-Based Forecasting of Agricultural Raw Material Imports in Central and Eastern Europe

The paper analyzes the long-term dynamics and short-term forecasts of agricultural raw material imports in Central and Eastern European countries, with an emphasis on structural trends, regional convergence and the performance of ARIMA-type econometric models. The study employs annual data for the period 1995–2024 and focuses on seven economies in the region: Romania, Poland, Hungary, the Czech Republic, Slovakia, Bulgaria, and Croatia. The research methodology combines inferential statistical analysis, Spearman’s correlation coefficients, time-series stationarity testing through the Augmented Dickey–Fuller test and univariate ARIMA modeling following the Box–Jenkins methodology. The results highlight a clear downward trend in the share of agricultural raw material imports in total merchandise imports for all analyzed countries, reflecting processes of structural transformation, agricultural modernization and integration into the European single market. The correlation analysis indicates a high degree of synchronization and regional convergence, particularly among Central European economies, while Romania exhibits a relatively distinct profile characterized by higher volatility. Stationarity tests reveal differing degrees of series integration and the estimated ARIMA models provide high-quality short-term forecasts. Projections for the 2025–2027 period suggest stabilization or a slight decline in agricultural raw material imports, with no significant structural shifts, which are useful in managerial policies at the level of the analyzed countries.