Econometric Modeling of Rice Production in the Surkhandarya Region Using the Arima Model and Forecasting for 2025–2028

This article presents an econometric analysis of the dynamics of rice production in the Surkhandarya Region during 2010–2024 using the AutoRegressive Integrated Moving Average (ARIMA) model. Official statistical data from the National Statistics Committee of the Republic of Uzbekistan were used for the study. First, a descriptive statistical analysis of the time series was conducted, and its stationarity was examined using the Augmented Dickey–Fuller (ADF) test. After stationarity was achieved, the optimal parameters of the ARIMA model were selected based on the ACF and PACF plots. The models were evaluated according to the Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), Hannan–Quinn Criterion (HQC), and Log Likelihood, and the most appropriate model was identified. Based on the selected model, forecast values of rice production for 2025–2028 were calculated. The findings have practical significance for short-term forecasting of rice production in the Surkhandarya Region, agricultural production planning, and management decision-making.