Crude Palm Oil Domestic Production of Major Food Commodities in Indonesia
3 LITERATURE REVIEW
An increasing number of studies have investigated the relationship between crude oil and food prices. These studies show a divergence in findings indicating
that the effect of crude oil price volatilities on food commodity prices is not universal. This has motivated researchers worldwide to further investigate such
correlations. The majority of previous studies have highlighted the existence of volatility spillover from crude oil prices to food commodity prices, an effect that is
becoming stronger as biofuel production increases. Such research concurs with crude oil price volatilities being transmitted onto food commodities prices through
two essential elements, namely production inputs transportation and electricity costs, fertiliser and pesticide prices and biofuel production agricultural
commodities as raw materials.
Research investigating volatility spillovers from crude oil onto the food market through production inputs has focused on agricultural commodities used for
staple food and found a strong relationship between them. Research by Baffes 2007 was based on 35 non-energy commodities traded globally, such as food rice,
maize, soybeans, wheat, and sugar, beverages cocoa, coffee, and tea, raw materials cotton, rubber, and timber, fertilisers, and metals silver, aluminum,
copper, nickel, zinc. This author used annual price data from 1960 to 2005 and analysed data using an Ordinary Least Squares OLS regression method. Results
indicate that linkages between crude oil prices and food commodities are stronger compared to other commodities. Furthermore, research results of Balcombe 2011
also suggest a positive correlation. This author’s findings, acquired using the time varying and panel approach, were based on smaller samples covering 19
agricultural commodities, such as rice, soybeans, maize, wheat, meat, cheese, cocoa,
and sugar from 1957 to 2009. A more recent study by Obadi and Korček 2014 investigated the causality, long-run and short-run linkages between price of crude
oil and food products, such as palm oil, wheat, corn, sugar, rice and barley. Data used in this study were monthly commodity prices over the period January 1975 to
September 2013 and by adopting a Granger causality and a VECM model, a long- run relationship between oil and food prices was identified. In addition, in the long-
run, causality is transmitted from oil prices to all food commodity prices, except for barley which has a two-way causality. Similarly, in the short-run, the direction of
causality runs from oil prices to each of the food commodities, except for sugar. These findings, therefore, suggest that the price of agricultural food commodities
used as sources of food react significantly to oil price fluctuations as oil is a primary input in energy intensive farmin
g Obadi and Korček 2014. In order to investigate the impact of the biofuel boom on volatility
transmission between oil and other commodity prices, previous studies have concentrated on agricultural products being used as raw materials for biofuels and
divided analyses into two time periods, namely prior to and after the 2008 global food crisis. Serra 2011 used weekly price data of international crude oil and the
weekly price of ethanol and sugar from July 2000 to November 2009 to investigate volatility transmission between crude oil, ethanol and sugar prices. The methods
used in this study were the semiparametric GARCH and parametric MGARCH. Results indicate that in the long run, crude oil, ethanol and sugar price levels are
connected by an equilibrium parity, suggesting a strong volatility linkage between them. Research by Ji and Fan 2012 uses daily log returns data covering various
crops soybean, wheat, corn, and sugar and metals gold, silver, aluminum between 7 July 2006 and 30 June 2010. By adopting an EGARCH model, these
authors suggest that the nexus between crude oil prices and agricultural and metal commodity prices has become stronger since the 2008 crisis. The work of Bakhat
and Würzburg 2013, derived from an ECM model, is based on three categories of samples which are food commodities used to produce biofuel, such as soybean oil,
sunflower oil, palm oil and sugar, other food commodities which cannot be converted into biofuels, such as rice, wheat, and beef and agricultural commodities
which are not edible such as rubber, coffee and wool. By analysing monthly data for the period January 2000 to April 2011, these authors found that increasing the
use of biofuels induces stronger linkages between crude oil and food commodities, especially for commodities used as raw materials for biofuel production. Similarly,
recent research by Tadesse, Algieri, Kalkuhl and Braun 2014 which used monthly and annual data of oil and food prices, such as wheat, corn and soybeans, from 1986
to 2009, indicates that in recent years there is an emerging link between food, energy and financial markets. Thus, such results indicate an indirect transmission
between oil price volatility and farming commodities through increased demand for biofuel.
Other researchers state that results of investigations into volatility transmission from oil onto food commodity prices are not statistically significant at
all times. A study by Du, Yu and Hayes 2011 shows that linkages between oil, maize and wheat only exist after 2006. They analysed the weekly data of these
commodities by following a stochastic volatility model and a Bayesian econometric method for estimating the parameters of the model. Similar results were obtained
by Nazlioglu, Erdem and Soytas 2013 who adopted the Hafner and Herwartz test approach and divided the data into two time periods of observation: before the food
crisis 01 January 1986-31 December 2005 and after the food crisis 01 January 2006-21 March 2011. The data used in the study were daily price data of
agricultural commodities, such as wheat, maize, soybeans and sugar. The results indicated that during the pre-crisis period there was no volatility spillover between
crude oil and agricultural commodity prices. In contrast, there was significant volatility transmission during the post-crisis period. Hence, these findings show that
the existence of volatility spillovers may depend on a particular time period marked by the biofuel boom phenomenon after the crisis Nazlioglu, Erdem and Soytas
2013.
Other studies suggest an insignificant effect of volatility spillover between the oil and biofuel markets. Zhang, Lohr, Escalante and Wetzstein 2010 used a
VECM model to show that there is no direct long-run relationship between fuel and agricultural commodity prices asserting that if there were any direct short-run
relationships, then they would be finite, except for sugar because it can affect agricultural product prices through rising biofuel production. These results were
obtained by analysing monthly price data for energy commodities, such as gasoline, ethanol and oil, and farming products, such as rice, maize, soybeans, sugar and
wheat, covering the period March 1989 through July 2008. Similar results were reported by Kaltalioglu and Soytas 2011, who expanded the sample to include a
greater range of commodities. These authors used the monthly price data of oil,
food products fruits, vegetables, meat, poultry, fish, grocery food and non- alcoholic beverages and agricultural raw commodities timber, cotton, wool,
rubber, and hides between January 1980 and April 2008. By adopting a Granger causality in variance approach, they found that there is no volatility spillover from
energy market to food and agricultural raw commodity markets. Gardebroek and Hernandez 2013 used weekly price data of crude oil, ethanol and corn from
September 1997 to October 2011. Based on the results obtained from an MGARCH model, there is a higher correlation between ethanol and corn markets, particularly
after 2006. However, these authors did not find evidence that energy price volatilities stimulate corn prices in the US. A recent study by Abdelradi and Serra
2015 adopted parametric and semiparametric methods suggests similar results. They used weekly price data for the period 06 November 2008 through 14 June
2012. Results indicate that the biofuel industry in Europe does not trigger an increase in food prices. These contradictory findings have motivated researchers to
further analyse the relationships between crude oil price volatilities and food commodity prices in order to shed light on the existence of volatility transmission
in different countries.
4 DATA AND METHODOLOGY
This section presents data and explores the econometric methods used to investigate the relationship between oil prices in the world market and food
commodity prices in the Indonesian market from 2002 to 2015. To measure such a linkage this study adopts the VECM model and the Granger Causality test.