Critical Factors of Sustainability for Cocoa Industry in Malaysia: Price Forecasting Methodology

Aye Aye Khin (), Wei Fong Pok (), Mei Peng Low (), Yogambigai a/p. Rajamoorthy (), Peck Ling Tee () and Zi Jian Phan
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Aye Aye Khin: Universiti Tunku Abdul Rahman (UTAR)
Wei Fong Pok: Universiti Tunku Abdul Rahman (UTAR)
Mei Peng Low: Universiti Tunku Abdul Rahman (UTAR)
Yogambigai a/p. Rajamoorthy: Universiti Tunku Abdul Rahman (UTAR)
Peck Ling Tee: Universiti Tunku Abdul Rahman (UTAR)
Zi Jian Phan: Universiti Tunku Abdul Rahman (UTAR)

A chapter in Eurasian Business and Economics Perspectives, 2024, pp 99-118 from Springer

Abstract: Abstract Cocoa is one of the important commodities traded globally and also one of the main export products in Malaysia. This study is to determine the critical factors of sustainability for production, consumption and price and also to develop the price forecasting methodology of cocoa industry. Three cocoa bean price forecasting models were developed, i.e. multiple linear regression (MLR) model, Autoregressive Integrated Moving Average (ARIMA) model and Multivariate Autoregressive Moving Average (MARMA) model. The data from 1987 to 2019 was gathered for production and consumption model by using multiple linear regression (MLR) models. Based on the forecasting accuracy criteria, MARMA (1,1,1) model was found to be the best-fitted model. The novelty of this study is attributed to provide the price forecasting methodology to the policy maker and the industry. Based on the valuable findings, price is significant relationship in both production and consumption models. Moreover, price is also significant relationships among export, import and crude palm oil price. Therefore, Malaysian governors should support the subsidy for cocoa farmers and increase for local demand and get more attracting for cocoa grinders to get the prevailing prices on the international market.

Keywords: Production; Consumption; Price forecasting; Cocoa industry; Malaysia (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-64140-4_6

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