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Forecasting cocoa production of six major producers through ARIMA and grey models

Tawiah Kwatekwei Quartey-Papafio (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Saad Ahmed Javed (School of Business, Nanjing University of Information Science and Technology, Nanjing, China)
Sifeng Liu (Institute for Grey Systems Studies, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 20 October 2020

Issue publication date: 18 June 2021




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.


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.


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.


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



This work was supported by a project of the National Natural Science Foundation of China entitled “Research on network of reliability growth of complex equipment under the background of collaborative development” (71671091). It is also supported by a joint project of both the NSFC and the Royal Society of UK entitled “On grey dynamic scheduling model of complex product based on sensing information of Internet of things” (71811530338), a project of the Leverhulme Trust International Network entitled “Grey Systems and Its Applications” (IN-2014–020). At the same time, the authors would like to acknowledge the partial support of the Fundamental Research Funds for the Central Universities of China (NC2019003) and support of a project of Intelligence Introduction Base of the Ministry of Science and Technology (G20190010178).


Quartey-Papafio, T.K., Javed, S.A. and Liu, S. (2021), "Forecasting cocoa production of six major producers through ARIMA and grey models", Grey Systems: Theory and Application, Vol. 11 No. 3, pp. 434-462.



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