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Forecasting cocoa production of six major producers through ARIMA and grey models
Grey Systems: Theory and Application ( IF 2.9 ) Pub Date : 2020-10-20 , DOI: 10.1108/gs-04-2020-0050
Tawiah Kwatekwei Quartey-Papafio , Saad Ahmed Javed , Sifeng Liu

Purpose

In the current study, two grey prediction models, Even GM (1, 1) and Non-homogeneous discrete grey model (NDGM), and ARIMA models are deployed to forecast cocoa bean production of the six major cocoa-producing countries. Furthermore, relying on Relative Growth Rate (RGR) and Doubling Time (Dt), production growth is analyzed.

Design/methodology/approach

The secondary data were extracted from the United Nations Food and Agricultural Organization (FAO) database. Grey forecasting models are applied using the data covering 2008 to 2017 as their performance on the small sample size is well-recognized. The models' performance was estimated through MAPE, MAE and RMSE.

Findings

Results show the two grey models fell below 10% of MAPE confirming their high accuracy and forecasting performance against that of the ARIMA. Therefore, the suitability of grey models for the cocoa production forecast is established. Findings also revealed that cocoa production in Côte d'Ivoire, Cameroon, Ghana and Brazil is likely to experience a rise with a growth rate of 2.52, 2.49, 2.45 and 2.72% by 2030, respectively. However, Nigeria and Indonesia are likely to experience a decrease with a growth rate of 2.25 and 2.21%, respectively.

Practical implications

For a sustainable cocoa industry, stakeholders should investigate the decline in production despite the implementation of advanced agricultural mechanization in cocoa farming, which goes further to put food security at risk.

Originality/value

The study presents a pioneering attempt of using grey forecasting models to predict cocoa production.



中文翻译:

通过 ARIMA 和灰色模型预测六大生产商的可可产量

目的

在当前的研究中,两个灰色预测模型,Even GM (1, 1) 和非均匀离散灰色模型 (NDGM) 和 ARIMA 模型被用于预测六个主要可可生产国的可可豆产量。此外,依靠相对增长率 (RGR) 和倍增时间 (D t ),分析了产量增长。

设计/方法/方法

二级数据来自联合国粮食及农业组织(FAO)数据库。灰色预测模型使用覆盖2008年至2017年的数据进行应用,因为它们在小样本量上的表现是公认的。模型的性能通过 MAPE、MAE 和 RMSE 估计。

发现

结果显示,两个灰色模型均低于 MAPE 的 10%,证实了它们相对于 ARIMA 的高精度和预测性能。因此,建立了灰色模型对可可产量预测的适用性。调查结果还显示,到 2030 年,科特迪瓦、喀麦隆、加纳和巴西的可可产量可能会分别增长 2.52、2.49、2.45 和 2.72%。然而,尼日利亚和印度尼西亚的增长率可能分别为 2.25% 和 2.21%。

实际影响

对于可持续的可可产业,尽管在可可种植中实施了先进的农业机械化,但利益相关者应调查产量下降的情况,这进一步使粮食安全面临风险。

原创性/价值

该研究提出了使用灰色预测模型来预测可可产量的开创性尝试。

更新日期:2020-10-20
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