Forecasting crop yield: A comparative assessment of ARIMAX AND NARX MODEL

Abstract

Weather variability within and between seasons is uncontrollable source of variability in yields. The extent of weather influence on crop yield depends not only on the magnitude of weather variables but also on the distribution pattern of weather over the crop season. Therefore, when forecasting is carried out for dynamic behaviour of crop yield, it should be able to take advantage not only of historical data of crop yield, but also of the impact of various driving forces from the external environment. In the present investigation, an attempt has been made to forecast wheat yield at Kanpur district of Uttar Pradesh by considering most important weather variable i.e. maximum temperature at Critical Root Initiation (CRI) stage of wheat crop which comes around 21 days after sowing of the crop. Both parametric (ARIMA model) and nonparametric approach (NARX model) have been employed. It is observed that NARX model outperformed the ARIMAX model as far as modelling and forecasting is concerned. Besides Mean absolute prediction error (MAPE), Relative MAPE (RMAPE) and Root mean square errors (RMSE), Diebold- Mariano test has also been employed to compare the predictive accuracy of two competing models.