Historical pattern of rice productivity in India

Abstract

Forecast of productivity (yield) has an importance over production and area separately because it depends on both. Trend of the same reveals the necessity of the resources to be managed, for increasing yield in future. The forecast values of the series are obtained using autoregressive integrated moving average (ARIMA) model and the trend is determined by the means of Mann Kendall’s trend test. In the present work we have found that the productivity of rice for overall country shows an increasing trend. Mann Kendal’s trend analysis reported that the productivity has a steadily increasing trend which was also evident from the Sen’s slope coefficient (Q). ARIMA (1,1,1) model with constant was found to be appropriate model for forecasting the productivity of rice. The forecast values were obtained for the subsequent four years starting from 2018 to 2021. Forecast error was also calculated and it was found to be less than 2 per cent i.e., 1.36 per cent.

Keywords

• ARIMA
• forecast
• Mann Kendal’s trend
• MAPE
• productivity