Rice Genomics and Genetics 2015, Vol.6, No.5, 1-10
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prices in market i. If prices in i also Granger cause
prices in j, then prices are determined by a
simultaneous feedback mechanism (SFM). This is the
case of bi-directional Granger causality. If the
Granger-causality runs one way, it is called
uni-directional Granger-causality and the market
which Granger-causes the other is tagged the
exogenous market.
4. Results and Discussion
4.1.
Descriptive Analysis
4.1.2. Average Growth Rate in Retail Prices
The average growth rates of retail prices as depicted in
Table 1 showed that growth was highest in Osun
Market (33.4%), followed by Oyo Market (31.3%)
and Ondo Market (29.8%). The highest average
growth rate was recorded in year 2008. It can also be
observed that there was a negative growth rate across
the markets in the six states in the year 2010. This
observation could be linked with the lifting of the ban
on rice imports which engendered an increase in
importation of the commodity in the periods
immediately following lifting of the ban. The
implication was the flooding of the Nigerian market
with imported rice and the consequent depression in
the prices.
Table 1 Percentage average growth rates of retail prices
Period
Lagos
Ogun
Ondo
Osun
Oyo
Ekiti
2001-2002
10.63
7.95
8.05
1.91
4.64
2.67
2002-2003
20.86
28.91
24.74
29.02
24.35
28.95
2003-2004
17.82
16.50
21.73
21.42
18.35
22.45
2004-2005
18.45
11.10
16.89
18.92
17.83
13.79
2005-2006
-3.53
4.94
0.12
10.23
4.99
4.50
2006-2007
7.86
3.75
2.70
-10.69
7.77
2.21
2007-2008
27.99
16.30
29.76
33.41
31.31
27.17
2008-2009
6.93
22.90
4.26
3.61
8.58
8.96
2009-2010
-1.36
2.59
-10.45
-10.45
-8.37
-12.04
Period Average
11.74
12.77
10.87
10.82
12.16
10.96
4.1.3. Variability in Average Retail Prices
Variability is one of the major attributes that explain
the characteristics of most price data. This attribute
has important implications for food policy and the
welfare of food consumers and a nation’s economy
(Mafimisebi, 2012). The degree of variability in the
prices of imported rice over the period covered by the
data is reflected in the coefficient of variation
computed for the commodity in the region (Table 2).
Retail prices were more volatile in Oyo Market
(35.8%). The least price volatility was recorded in
Ogun Market (31.1%). In general, the relatively low
price variability implied that consumers could
effectively plan their expenditure pattern on rice with
a fairly high degree of expectation that prices are not
likely to substantially deviate from what they were
(Mafimisebi, 2012). This is a positive signal for the
welfare of rice consumers.
Table 2 Coefficient of variation in retail prices
State
Coefficient of variation (%)
Ekiti
32.23
Lagos
32.81
Ogun
34.23
Ondo
31.09
Osun
31.90
Oyo
35.76
Note: Source: Authors’ computation
4.1.4. Order of Econometric Integration of Rice
Price Series
The augmented Dickey-Fuller (ADF) test showed that
all rice price series subjected to the model were
non-stationary at their levels. This meant that they all
contained a unit root since the absolute values of their
test statistics was less than their critical values at both
1% and 5% levels of significance. However, stationa-
rity was reached after the first difference (Table 3).
