An application of box-jenkins methodology for forecasting of green gram productivity in Odisha

Abstract

A study was conducted on forecasting of green gram productivity of Odisha. Box-Jenkins Autoregressive integrated moving average (ARIMA) time-series methodology was considered for forecasting. The different ARIMA models are judged on the basis of Autocorrelation Function (ACF) and Partial autocorrelation Function (PACF) at various lags The data from 1971-72 to 2006-07 are used for model building and from 2007-08 to 2015-16 used for successful cross-validation of the selected model on the basis of the absolute percentage error. The ARIMA models are fitted to the original time series data as well as the first difference data to check the stationarity. The possible ARIMA models are identified on the basis of significant coefficient of autoregressive and moving average components. The best fitted models are selected on the basis of low value of Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). ARIMA (0,1,1) without constant found to be best fitted for green gram productivity having absolute percentage error ranging from 15.89% to 43.60% in cross-validation of model.The best fitted Box-jenkins ARIMA model has been used to forecast the productivity of green gram for the year 2016-17 to 2018-19. The model showed the forecast in productivity for the year 2018-19 to be about 231.53 kg per hectare with lower and upper limit 42.76 and 420.30 kg per hectare respectively.