5 RESULTS
In order to analyse the relationships between world crude oil prices and food commodity prices in Indonesia during the period January 2002 to August 2015 this
study has conducted a series of tests according to the methodology discussed in the previous section. Results of the empirical analysis are reviewed in this section.
5.1 Augmented Dickey-Fuller Unit Root Test
The augmented Dickey-Fuller ADF root test is a standard pre-test to a time series analysis aiming to check the presence of unit roots in the series. The test is
carried out to each logarithm series starting from level to the first difference at the 5 level of significance. The estimated results of the ADF test are presented in
Table 5.1 below.
Table 5.1 Results of Augmented Dickey-Fuller Test
Variable Level
1
st
Difference ADF Statistic
Critical Values ADF Statistic
Critical Values Crude Oil
-2.378 -2.886
-6.537 -2.886
World Rice -1.969
-2.886 -7.265
-2.886 World Maize
-1.951 -2.886
-5.940 -2.886
World Wheat -2.316
-2.886 -6.575
-2.886 World Soybean
-2.474 -2.886
-6.883 -2.886
World Sugar -1.744
-2.886 -6.761
-2.886 World Palm Oil
-2.169 -2.886
-5.948 -2.886
Domestic Rice -0.507
-2.886 -8.442
-2.886 Domestic Maize
-0.588 -2.886
-7.596 -2.886
Domestic Wheat -1.797
-2.886 -4.283
-2.886 Domestic Soybeans
-1.712 -2.886
-6.422 -2.886
Domestic Sugar -1.780
-2.886 -5.873
-2.886 Domestic Cooking Oil
-2.600 -2.886
-6.197 -2.886
Domestic Petroleum -2.180
-2.886 -9.445
-2.886
Table 5.1 shows that the null hypothesis of the existence of unit roots cannot be rejected for each variable at level, meaning that the series are non-stationary at
the level at the 5 level of significance. This implies that these variables at level cannot be used for time series analysis because non-stationary data may produce a
spurious regression. Therefore, the unit root test is carried out in the first differenced logarithm.
As indicated in Table 5.1, results show that the null hypothesis can be rejected for all variables, implying that these variables are stationary and integrated of the
same order, I1. Therefore, the test of cointegration can be carried out in order to detect the existence of long-run relationships between the variables.
5.2 Johansen Cointegration Test
The objective of the Johansen cointegration test is to determine whether a group of variables which are non-stationary at level, is able to fulfill a necessary
condition for cointegration where all variables are stationary at the same level, namely order 1, I1. This study tests bivariate relationships between the prices of
crude oil and each food commodity, the domestic prices of gasoline and domestic food commodities, and the prices of food commodities in the world market and the
domestic food commodity prices at the 5 significance level, in order to identify existence of long-run relationships between them.
As presented in Table 5.2, the Johansen cointegration test reveals that long term relationships between crude oil and domestic food commodity prices were
only identified in maize, implying there are no cointegration relationships between crude oil prices and following commodities: rice, wheat, soybeans, sugar and
cooking oil. Likewise, this test found no evidence for existence of long term associations between domestic petroleum prices and domestic food commodity
prices despite the existence of long term relationships between the prices of domestic petroleum and crude oil.
Table 5.2 Results of Johansen Cointegration Test
Variables Lags
Max. Rank
Eigen Value
Trace Statistic
Critical Value
No. of CEs
AIC SIC
World Rice-Crude Oil 3
2 1
0.08477 4.8222
3.76 1
World Maize-Crude Oil 2
2 -
- -
- -
World Wheat-Crude Oil 2
2 1
0.09992 4.8315
3.76 1
World Soybeans-Crude Oil 3
2 1
0.06267 5.9970
3.76 1
World Sugar-Crude Oil 2
2 -
- -
- -
World Palm Oil-Crude Oil 4
2 1
0.06516 5.2613
3.76 1
Domestic Rice-Crude Oil 3
2 -
- -
- -
Domestic Maize-Crude Oil 2
2 -
19.4794 15.41
1 Domestic Wheat-Crude Oil
3 2
- -
- -
- Domestic Soybeans-Crude Oil
2 2
- -
- -
- Domestic Sugar-Crude Oil
2 2
- -
- -
- Domestic Cooking Oil-Crude Oil
2 2
- -
- -
- Domestic Petroleum-Crude Oil
2 1
1 0.09574
5.8815 3.76
1 Domestic Rice-Domestic Petroleum
4 1
- -
- -
- Domestic Maize-Domestic Petroleum
1 1
- -
- -
- Domestic Wheat-Domestic Petroleum
3 2
- -
- -
- Domestic Soybeans-Domestic Petroleum
1 1
- -
- -
- Domestic Sugar-Domestic Petroleum
2 1
- -
- -
- Domestic Cooking Oil-Domestic
Petroleum 3
2 -
- -
- -
Domestic Rice-World Rice 4
2 -
- -
- -
Domestic Maize-World Maize 1
1 1
0.09367 3.8286
3.76 1
Domestic Wheat-World Wheat 3
2 1
0.09759 4.4057
3.76 1
Domestic Soybeans-World Soybeans 2
1 1
0.11679 6.8907
3.76 1
Domestic Sugar-World Sugar 2
2 -
- -
- -
Domestic Cooking Oil-World Palm Oil 2
2 -
- -
- -
In terms of linkages between food commodity prices in the world market and crude oil prices, this test finds long-run relationships for all commodities, except
for maize and sugar. Similar relationships are also detected in the links between food commodities in the domestic and the world markets, except for rice, sugar and
cooking oil.
For variables with cointegration relationships, this study conducts further estimation using the Vector Error Correction Model VECM in order to analyse
both the long-run and short-run relationships between the cointegrated variables.
On the other hand, this study adopts the Granger Causality test in order to investigate causality relationships between variables with no cointegration
associations Giles 2011; Gogoi 2014. Moreover, the lag lengths generated by the Schwarz Information Criterion SIC are employed in this study because it suggests
the most parsimonious model compared to Akaike Information Criterion AIC.
5.3 VECM Analysis
A VECM model can be used to identify long-run and short-run relationships between the prices of oil and food commodities. This method defines a framework
where the dynamics of the short-run relations of each price series are bound to the long-run equilibrium relations.
As shown in Table 5.3 below, the VECM results confirm a bidirectional long term association between domestic price of maize and crude oil prices, implying
that the price of maize in Indonesia is being caused by crude oil prices and vice versa. Similarly, results show that there is a bidirectional long term relationship
between domestic petroleum prices and crude oil prices. Therefore, these results indicate that in the long run crude oil prices can directly affect the domestic price
of maize through changes in the cost of production due to the intensive use of fossil fuel, whereas the reverse relationships suggest that the domestic price of maize and
petroleum seem to be the leading indicator of crude oil price fluctuations.
Table 5.3 Results of VECM
Relationships Direction of Causality
Domestic Food Commodity – Crude Oil:
Domestic Maize – Crude Oil
LMZ ⇔ CO
Domestic Petroleum – Crude Oil:
Domestic Petroleum – Crude Oil
PO ⇔ CO
World Food Commodity – Crude Oil:
World Rice – Crude Oil
WRC ⇔ CO
World Wheat – Crude Oil
WWHT ⇔ CO
World Soybean – Crude Oil
WSOY ⟹ CO
World Palm Oil – Crude Oil
WPLM ⟹ CO
Domestic Food Commodity – World Food Commodity:
Domestic Maize – World Maize
WMZ ⟹ LMZ
Domestic Wheat – World Wheat
LWHT ⇔ WWHT
Domestic Soybean – World Soybean
WSOY ⟹ LSOY
In the context of world food commodity prices and crude oil prices, results reveal unidirectional long-run causalities from world soybean prices to crude oil
prices and from world palm oil prices to crude oil prices. The existence of these relationships may be caused by massive use of soybeans and palm oil as feedstocks
in the production of biofuel during the past decade. Furthermore, results show bidirectional causalities between rice prices in the world market and crude oil prices,
and world wheat prices and crude oil prices. This means that volatilities in crude oil prices can be directly transmitted onto rice and wheat prices in the world market in
the long run and inversely, changes in the world prices of rice and wheat can affect crude oil prices. The volatilities spillover from the world price of wheat onto the
price of crude oil may occur as wheat is used for producing biofuels. Thus, rising
