The natural consumption rubber production, and price analysis in selected Asean countries and world market

Fong, Yi Chiun (2020) The natural consumption rubber production, and price analysis in selected Asean countries and world market. Master dissertation/thesis, UTAR.

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Abstract

Imbalance of the supply-demand in the natural rubber (NR) market has been happening especially during the recent years where the consumption far exceeded production. It is said that NR market can no longer be explained solely by the fundamental factors (supply and demand), which involves others external causes. For example, world crude oil price, synthetic rubber (SR) price and real exchange rate. The emerging China economy has impacted the NR market too. Therefore, Shanghai NR price would act as an important indicator in the NR market. General objective of the study is to develop 3 models namely the NR production, consumption and price in particular ASEAN countries as well as in the world market. Panel data analysis will be employed the NR production model (Thailand, Indonesia, Malaysia, Vietnam, Myanmar) and NR consumption model (China, India, Japan, USA), by using annual data from 2004 to 2017; VECM will be employed for NR price model, with the estimation period from January 2008 to December 2017. Results indicated (1) in the production model, NR price and total planted area of NR are both having positive relationships with NR production; (2) in the NR consumption model, NR price and NR stock are both having negative relationships with NR consumption; (3) in the NR SMR20 price model, NR world production, Shanghai NR price and SR price are positively related to NR SMR20 price, while NR world consumption is negatively related with NR SMR20 price. Besides, sustainability of NR industry has always been a policy issue especially in producing countries. Government should implement policy to enable the stable and sustainable growth of NR in the countries. Future studies could analyze other emerging NR markets or countries by extending the sampling period as well as adding more relevant variables prior to data availability.

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