Rice Genomics and Genetics 2015, Vol.6, No.5, 1-10
2
rice demand supply gap of 2.7 million tonnes (or 56%
of demand) is bridged by importation (FMARD,
2012). Research findings from several states in
Nigeria have shown that rice availability and prices
have become a major welfare determinant for the
low-income segment of the country’s populace in
which the highest incidence of food insecurity is
recorded (Akande and Akpokodje,
2003; Rahji and
Adewunmi, 2008; Kassali et al., 2010). Stable price
for food in general and rice in particular is therefore
vitally important to human welfare in Nigeria where
the national poverty incidence figure is above 65%
(National Bureau of Statistics, 2010). The overriding
requirement for attaining the goal of stable rice price
in Nigeria is to see that the IRM achieves and
maintains an acceptable extent of market integration.
Market integration is a generally acceptable proxy for
marketing efficiency (Timmer 2004, Mafimisebi,
2012). If markets are integrated, the price differential
or spread between contiguous markets for the same
commodity cannot be higher than transfer costs
(Mafimisebi, 2012). Price is the central mechanism by
which linkage or integration is established between
markets as well as the key driver of the resource
allocation process that takes place through markets
(FAO, 2005; Mafimisebi, 2012). Furthermore, the
understanding of price formation process is important
for the formulation of effective policy decisions.
In
view of the above, efficient functioning of the IRM
network becomes a
sine-qua-non
in agricultural and
economic development of Nigeria.
Over the years, most research efforts have been geared
toward increasing local rice production to meet
self-sufficiency in its production, making locally
produced rice compete favourably with imported rice,
reversing the excessive outflow of foreign exchange
for importing rice and indeed raising local rice
consumption in Nigeria (Daramola, 2005; Bamidele et
al., 2010). Sadly, little importance has been accorded
research into the country’s rice marketing and
distribution system at both zonal and national levels.
In view of the important role imported rice plays in
the nutrition of Nigerian households and the surge in
the imports of the commodity into the Nigerian
market in response to increasing demand in the last
two decades, there is need to examine the efficiency
and competitiveness of the IRM.
The major objective of the study from which this
paper was derived was to examine the pricing contacts
in the IRM in Southwest zone of Nigeria. The specific
objectives were to (i) compute and explain the trend in
price; (ii) compute and explain price variability; (iii)
test the presence and degree of pricing contacts, if any,
between spatial markets and (iv) identify market(s)
that assume(s) the leadership position(s) in price
formation and transmission in the zone.
2. Theoretical Framework
Co-integration is a statistical property possessed by
some time-series data that is defined by the concept of
stationarity and order of integration of the series. It
deals with relationship between or among variables
where (unconditionally) each has a unit root. It means
that despite being individually non-stationary, a linear
combination of two or more time series can be
stationary. A stationary series is one with a mean
value which will not vary with the sampling period. In
contrast, a non-stationary series will exhibit a time
varying mean. The order of integration of a series is
given by the number of time the series must be
differenced in order to produce a stationary series. A
series generated by the first difference is integrated of
order 1 denoted as I(1). Thus, if a time series is I(0), it
is stationary; if it is I(1), then its change is stationary
and its level is non-stationary.
The concept of co-integration and the method for
estimating a co-integration relation or system (Engle
and Granger, 1987; Johansen, 1988; Johansen and
Juselius, 1990; Juselius, 2006) provide a framework
for estimating and testing for long run equilibrium
relationships between non-stationary integrated
variables. If two prices in spatially separated markets
(or different levels of the supply chain), p1t and p2t,
contain stochastic trends and are integrated of the
same order, say 1(d), the prices are said to be
co-integrated if p1t –βp2t
₌
µ is 1(0).
β is referred to as the co-integrating vector (in the case
of two variables, a scalar), while the equation p1t
–βp2t is said to be the co-integrating regression.
Co-integration implies that these prices move closely
together in the long run, although in the short run,
they may wander in different directions, and this is
consistent with the concept of market integration.
Co-integration analysis thus provides a powerful
