AN APPLICATION OF TIME SERIES ARIMA FORECASTING MODEL FOR PREDICTING SUGARCANE PRODUCTION IN INDIA
Manoj Kumar, Madhu B. ANAND
Abstract
Manoj Kumar, Madhu B. ANAND
Abstract
A time series modeling approach (Box-Jenkins’ ARIMA model) has been used in this study to forecast sugarcane production in India. The order of the best ARIMA model was found to be (2,1,0). Further, efforts were made to forecast, as accurate as possible, the future sugarcane production for a period upto five years by fitting ARIMA(2,1,0) model to our time series data. The forecast results have shown that the annual sugarcane production will grow in 2013, then will take a sharp dip in 2014 and in subsequent years 2015 through 2017, it will continuously grow with an average growth rate of approximately 3% year-on-year.
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A time series modeling approach (Box-Jenkins’ ARIMA model) has been used in this study to forecast sugarcane production in India. The order of the best ARIMA model was found to be (2,1,0). Further, efforts were made to forecast, as accurate as possible, the future sugarcane production for a period upto five years by fitting ARIMA(2,1,0) model to our time series data. The forecast results have shown that the annual sugarcane production will grow in 2013, then will take a sharp dip in 2014 and in subsequent years 2015 through 2017, it will continuously grow with an average growth rate of approximately 3% year-on-year.
Key concepts: Autoregressive integrated moving average, Production (economics), Box–Jenkins, Time series, Series (stratigraphy), Econometrics, Production model, Statistics