Abstract
Instability of Natural Rubber (NR) prices is a key economic issue in the NR industry. A few studies have been conducted to investigate this issue especially giving more attention on the seasonal variations in NR prices. However, a little attention has been paid on studying the changes in long term trend and volatility in NR prices. Consequently, this study aims to undertake an in-depth analysis on the instability of NR prices giving more emphasis on both short run and long run price variations. During this study, we recognized that the long term price trends succumb to frequent changes that affect long term investments and the policy setup in the NR industry. Stochastic volatility of random shocks in RSS prices was identified as a serious issue which especially affects the rubber smallholder sector. Further, it was noticed that the usual seasonal variations in NR prices are overwhelmed by the frequent changes in long term trends and random shocks of NR prices. Moreover, we identified that seasonal stochastic time series models are more efficient than the decomposition time series techniques for modeling NR prices in the presence of the above mentioned issues persistent in NR price series.
Highlights
It is a common phenomenon that developing countries are dependent on export earnings through a few commodities of which majority are of primary in nature
It is claimed that there is an inherent instability of natural rubber prices, it is not clearly visible in observed prices which is indicated by the apparent trend present in the nominal price series depicted in the Figure 1
It is clear that the trends in prices are due to the effect of rising inflation persisting in the Sri Lankan economy
Summary
It is a common phenomenon that developing countries are dependent on export earnings through a few commodities of which majority are of primary in nature. The behavior of prices of different NR grades has been studied by Wijesuriya et al (1995) identifying their trends and the seasonal variations. Edirisinghe and Herath (2004) have further investigated the seasonal behavior of NR prices of Sri Lanka and some of the international markets by employing the decomposition time series methods. There are many studies carried out to investigate the NR price instability with respect to changes in the conditional mean and the variance of NR prices in other international markets employing appropriate theoretically sound methodologies. Arumugam and Anithakumari (2013) have used a Seasonal Autoregressive Moving Average model to identify seasonal variation in NR production in India With this background, this study was done to identify the instability of NR prices in the local market using appropriate time series methods
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