Note: PP = Producer price IDRkg
MP = Rice miller price IDRkg WP = Wholesaler price IDRkg
RP = Retailer price IDRkg
α = the coefficient of Error Correction Model = the coefficient of dynamic short-run
θ = the slope of long-run equilibrium c = the constanta
V RESULTS AND DISCUSSION
5.1 Rice Price Volatilities
The price volatilities in each market institutions are shown by standard deviation of return in the Table 3. Producer price has the highest price volatility
by 24,90. Whilst, rice miller price and wholesaler price have lower volatilities than producer price by 18,30 and 18,10, respectively. The retailer price has
the lowest volatility by 8,7. This result shows that the magnitudes of the price volatility from producer to consumer are decreasing. Farmers in production
market face very high volatility of producer price, meanwhile consumers receive stable price. This unbalance condition is not good for farmers and the market
efficiency.
Table 3 The price volatilities of producer, rice miller, wholesaler, and retailer
Variable PP
MP WP
RP Period
SD SD
SD SD
2000-2012 0,249
- 0,183
- 0,181
- 0,087
- 2000-2006
0,279 -
0,165 -
0,188 -
0,089 -
2007-2012 0,207 25,96
0,205 24,19
0,173 -8,34
0,084 -5,43
Note: Asterisk sign indicates reject Ho: there is no difference between two variances
H
o
: σ
2 1
≤ σ
2 2
, at 95 level of significant
The high volatility of producer price is reasonable due to the price gap of seasonal prices. The rice price at producer level in the harvest time is low because
the abundant of rice supply in the market. On the contrary, the rice price is high in non-harvest time when the supply is shortage. The gap production is too big
between main harvest in February-March which produces 60-65 of total production and the other two harvest time which produce 25-30 and 5-15 of
total production. The capacity of Bulog, which only can purchase 7-8 of total production cannot balance rice price for along the year. The government
instrument to purchase the excess of supply in harvest time cannot dampen the
volatility of seasonal rice price completely. This is the source of rice price volatility problem.
The volatilities of rice miller price and wholesaler price are lower than the volatility of producer price. Since rice miller and wholesaler have ability to hold
the stock for short time and wait for the better price to release it. They also get the advantages from access to the market information. Whereas the retailer has the
smallest price volatility at 8,70. It means that consumers face relatively stable rice price along the year. The rice price stabilization policy through market
operation is successful to provide stable price for people along the year. This study also compares the rice price volatilities between before crisis
period in 2000-2006 and during crisis period in 2007-2012. We test the significance of differences in variances using F-test. We want to confirm the
expectation that the price volatility during crisis period is less than before due to the government intervention to control the price in this period H1:
σ
1 2
σ
2 2
. The result shows only producer price which significantly has price volatility less than
before crisis see Appendix 1. The decrease of producer price volatility is supported by the good production in this time and it is related to the enforcement
of government purchasing price from 2007 until now. Meanwhile, the volatility changes of rice miller price, wholesaler price and the retailer price are not
significantly different. This confirms that there are no shocks of rice prices in the crisis period in Indonesian market in 2007-2012. The rice prices are relatively
stable like before crisis for rice miller, wholesaler, and retailer.
5.2 Rice Price Transmission and Market Integration
5.2.1 Unit Root Test
The first step to examine the market integration is that we have to confirm that the data series are stationary to avoid the spurious regression in the models.
The Table 4 shows the result of Unit Root test to test the stationary of variables. On the level for all variables, there are insufficient evidences to reject the null
hypothesis of non-stationary. Whereas at the first differenced series, there are strong evidences to reject the null hypothesis of non-stationary. This indicates that
all price series are I1.
Table 4 Unit Root test result
Variables t-statistic
Error of Model t-statistic
Producer Producer-Rice miller
Level 2 2.1271
u1 in level 0 -6.9459
Differences 1 -11.7015
Producer-Wholesaler Rice miller
u2 in level 0 -4.2549
Level 10 5.8841
Producer-Retailer
Differences 1 -12.2466
u3 in level 2 -2.9671
Wholesaler Rice miller-Wholesaler
Level 0 1.7797
u4 in level 0 -3.8677
Differences 0 -10.1124
Rice miller-Retailer Retailer
u5 in level 2 -2.4995
Level 2 4.6505
Wholesaler-Retailer
Differences 1 -7.7232
u6 in level 0 -3.8611
Note: the number in parentheses indicates the lag length. One , two , and three asterisks indicate rejection of unit root at 10, 5, and 1 level of significance, respectively.
Critical values for 10 = -1,62; 5 = -1,94; and 1 = -2,56. Reference: Davidson, R. and MacKinnon, J. 1993,Estimation and Inference in Econometrics p 708, table 20.1, Oxford
University Press, London
Beside the stationary test for series price data, we have to confirm the stationary of the errors in the pair wise models. They are the errors of Producer-
Rice miller, Producer-Wholesaler, Producer-Retailer, Rice miller-Wholesaler, Rice miller-Retailer, and Wholesaler-Retailer. Table 4 shows there are strong
evidences to reject the null hypothesis of non stationary for the errors on level for all models. It means all errors are I0. Therefore, we conclude that all variable are
stationary and valid to use. This also means that each pair wise models are cointegrated.
