Forecasting cocoa production of six major producers through ARIMA and grey models. Issue 3 (20th October 2020)
- Record Type:
- Journal Article
- Title:
- Forecasting cocoa production of six major producers through ARIMA and grey models. Issue 3 (20th October 2020)
- Main Title:
- Forecasting cocoa production of six major producers through ARIMA and grey models
- Authors:
- Quartey-Papafio, Tawiah Kwatekwei
Javed, Saad Ahmed
Liu, Sifeng - Abstract:
- Abstract : 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.Abstract : 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. … (more)
- Is Part Of:
- Grey systems. Volume 11:Issue 3(2021)
- Journal:
- Grey systems
- Issue:
- Volume 11:Issue 3(2021)
- Issue Display:
- Volume 11, Issue 3 (2021)
- Year:
- 2021
- Volume:
- 11
- Issue:
- 3
- Issue Sort Value:
- 2021-0011-0003-0000
- Page Start:
- 434
- Page End:
- 462
- Publication Date:
- 2020-10-20
- Subjects:
- Cocoa production -- Production economics -- Grey forecasting -- ARIMA -- NDGM
Cybernetics -- Periodicals
Systems engineering -- Periodicals
003.5 - Journal URLs:
- http://www.emeraldinsight.com/journals.htm?issn=2043-9377 ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/GS-04-2020-0050 ↗
- Languages:
- English
- ISSNs:
- 2043-9377
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22886.xml