基于ARIMA和VAR模型对孟加拉国粮食产量预测的计量分析

Mehedi Hossain, Murshida Khanam, S. Akhter
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引用次数: 1

摘要

在本研究中,进行了计量经济学分析,以确定影响孟加拉国粮食生产的重要因素。这里,我们考虑了1989- 1990年至2019-2020年的时间序列数据。本研究采用向量自回归(VAR)模型和自回归综合移动平均(ARIMA)模型。这两种模型都被用来预测孟加拉国的粮食产量。利用RMSE、MAE和MAPE对两种模型的预测性能进行了比较。结果表明,VAR模型对粮食产量的预测效果优于ARIMA模型。另一方面,通过分析得出,化肥用量对粮食产量的影响不显著,但灌溉面积对粮食产量的影响显著。粮食产量、灌溉面积和化肥三个变量之间存在短期关系。达卡大学学报(自然科学版),70(1):8- 13,2022 (1)
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An Econometric Analysis to Forecast the Food Grain Production in Bangladesh by Using ARIMA and VAR Models
In this study, an Econometric analysis has been conducted to identify the important factors that affect the food grain productions inBangladesh. Here, we have considered time series data for the years from 1989- 1990 to 2019-2020. Vector Autoregressive (VAR)Model and Autoregressive Integrated Moving Average (ARIMA) model have been considered in this study. Both these modelshave been considered to forecast the productions of food grains in Bangladesh. The forecasting performances of these two modelshave been compared by using RMSE, MAE, and MAPE. It has been found that the VAR model is better than the ARIMA model toforecast the food grain production. On the other hand, it has been come out from the analysis that there is no significant impact ofchemical fertilizer on the food grain production, but irrigation area has significant impact on the food grain production. Among thethree variables: food grain production, irrigation area and chemical fertilizer, there exists short run relationship. Dhaka Univ. J. Sci. 70(1): 8-13, 2022 (January)
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