Modeling and Forecasting of Sugarcane Production in South Asian Countries

Abstract

Sugarcane industry is of crucial importance to the South Asian countries. These countries depend heavily on agriculture and the sugarcane industry has immense potential to contribute towards its economic development. Hence, the precise and timely forecast of sugarcane production is of concern for farmers, policy makers and other stakeholders. In this manuscript, we strived to forecast the production and growth rate of this important commodity using standard statistical approaches. The ARIMA (Auto Regressive Integrated Moving Average) and ETS (Exponential Smoothing) models were applied and compared on the basis of their forecasting efficiency for South Asia countries. This study also investigated the trends in sugarcane production in the region and studies the causes of the decline in production of sugarcane in Sri Lanka and Bangladesh. Furthermore, the expected production for following 7 years was computed using both models. In addition, we also calculated the projected growth rates of sugarcane production of South Asian countries over the years 2020-2027.

Prediction of Fruit Production in India: An Econometric Approach

“…After determining the stationarity of the data series, we tried to build a statistical model. The results inspired by Table 3 revealed clearly that ETS (Holt's nonlinear) models are the best in all the cases according to all the statistics (AIC, RMSE, MAE, MAPE, Theil, BP, VP and CVP) where we have the smallest values; this result means that the predictions using the ETS model will provide the minimum errors and deviations between forecasting and actual values (Mishra et al 2022). However, we will forecast using the two methods for more accurate results.…”