Analysis and Forecasting of Rice Production Behavior in Bangladesh
Keywords:Bangladesh; Mean Absolute Error; Rice production; Root Mean Squared Error; Theil Inequality; Autoregressive distributed lag (ARDL).
This research looks at how numerous factors, including the price of rice, area, improved seed distribution, areas irrigated by different improved methods, and fertilizer, influence rice production in Bangladesh. This study employed the autoregressive distributed lag (ARDL) model to investigate the short-run and long-run effects of each exogenous variable on rice production. In this research work, auto regressive integrated moving average (ARIMA) and hybrid ARIMA-(general autoregressive conditional heteroskedastic) GRACH were used to forecast rice production in Bangladesh from 1983 to 2030. The parameters of price of rice, area irrigated by different improved methods, area, and fertilizer were found to have a significant and positive impact on rice production in this study, both in the short run and the long run, according to the ARDL model. According to the lowest Root Mean Squared Error, Mean Absolute Error and Theil Inequality Coefficient criteria, the linear hybrid ARIMA (11, 1, 11)–EGARCH (1, 1)–M model performed better in predicting the rice production in Bangladesh.
IUBAT Review—A Multidisciplinary Academic Journal, 5 (1): 1-14
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