Growth Analysis and Future Forecasting of Cotton Production and Productivity: Evidence from the Application of the ARIMA Model

Abstract

Cotton is a major natural fibre crop that supports India’s agricultural and textile sectors. This study analysed and forecast cotton production and productivity in India using annual data from 1966–67 to 2024–25 and the autoregressive integrated moving average (ARIMA) framework. The prediction and simulation (5 observations) are based on the statistical software EViews12. Stationarity was assessed after first-order differencing, and candidate models were evaluated using the Akaike information criterion, Bayesian information criterion, root mean square error, mean absolute percentage error, mean absolute error, and residual diagnostic (ACF and PACF) tests. The ARIMA (3, 1, 0) model was selected for cotton production, and the ARIMA (0, 1, 3) model was selected for productivity, both models satisfied the stated selection and diagnostic criteria and were used to generate five annual forecasts for 2025–26 to 2029–30. Forecast production was estimated at 323.6096 lakh tonnes in 2025–26 and 336.2496 lakh tonnes in 2029–30, Forecast productivity was estimated at 472.5426 kg/hectare in 2025–26 and 493.3535 kg/hectare in 2029–30. Although the annual estimates fluctuate, both forecast series exhibit an overall rising trend during the forecast horizon. The findings provide model-based estimates that may support production planning, resource management, and informed decision-making by relevant authorities.