Journal of Statistics Applications & Probability
Around 70% of the world’s sugar is produced from sugarcane. The production of sugarcane is fluctuated from year to year due to fluctuation of area under sugarcane cultivation. According to FAO, sugar requirement per capita/day is 29g and Bangladesh requires 1.0-1.2 million tonnes of sugar/year to meet the demand of domestic consumption. To meet the demand of domestic consumption of sugar, it is too much essential to estimate the production of sugar since sugar is produced mainly from sugarcane in Bangladesh which leads us to do this research. The main purpose of this research is to identify the Auto-Regressive Integrated Moving Average (ARIMA) model that could be used to forecast the production of sugarcane in Bangladesh. This study considered the published secondary data of yearly sugarcane production in Bangladesh over the period 1971 to 2013. The best selected Box-Jenkins ARIMA model for forecasting the sugarcane productions in Bangladesh is ARIMA (0,2,1). The comparison between the original series and forecasted series shows the same manner indicating fitted model are statistically well behaved to forecast sugarcane productions in Bangladesh i.e., the models forecast well during and beyond the estimation period to a satisfactory level.
Moyazzem Hossain, Md. and Abdulla, Faruq
"Forecasting the Sugarcane Production in Bangladesh by ARIMA Model,"
Journal of Statistics Applications & Probability: Vol. 4:
2, Article 14.
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol4/iss2/14