BACKGROUND
OF THE STUDY
The beef value chain is an important
sector to Nigeria’s economy as it provides employment and income generating
activities to many Nigerians. It is a source of livelihood to millions of
people through beef cattle production and marketing, beef marketing and
processing. The value chain consists of input suppliers, producers, marketers,
transporters, middlemen and processors who are interrelated to provide beef
cattle and its by-products to consumers. Kaplinsky
and Morris (2002) defined value chain as the “full range of activities which
are required to bring a product or service from conception, through the
different phases of production (involving a combination of physical
transformation and the input of various producer services), delivery to final
consumers, and final disposal after use”. Thus, beef value chain can be viewed
as the series of activities and links required in the movement of beef products
to final consumers passing through diverse stages of production, processing,
transformation and delivery. The consumers being the end users of the resultant
products of the chain are important actors.
Consumer behaviour, wants and needs
significantly define demand and supply of products in value chains. As consumers
are empowered by greater knowledge and changing needs, powers in value chains
are said to be shifting from the supply side to the consumer side (Labuschagne et al., 2010). Demand for products are also determined
by a multitude of factors such as own price, availability of substitutes,
household income, consumer preferences (Eastin & Arbogast, 2011), expected duration of price change, the
product's share of household's income, as well as demographic factors such as
changes in household size, age distribution of the population and sex (Udoh et al., 2013). Consumption patterns are also changing
due to a combination of population growth, rising incomes, urbanisation (Bénard et al., 2010) and
changing food preferences (Food and Agriculture Organization [FAO], 2018). A
combination of these factors can lead to changes in meat demand especially
beef. This can have impact on all segments of the beef value chain, which
include input supply, production, processing and distribution.
The Nigeria’s domestic market
opportunity for cattle is large and expected to continue growing with increase
in population. Available statistics on the number of cattle slaughtered in the
country have shown that beef consumption in 2014 amounted to 380,000 tonnes and
is projected to grow up to 1.3 million tonnes by 2050 (Federal Ministry of
Agriculture & Rural Development [FMARD], 2015). Beef alone accounts for
about 70% of total national meat supply (Mafimisebi
et al., 2013). Despite the large national herd of cattle (19.5 million) as well
as large population of sheep (41.3 million) and goats (72.5 million) (National
Bureau of Statistics [NBS], 2016), Nigeria is still unable to meet its animal
protein demand. The average minimum supply of animal protein per capita per day
was about 14g, far below the recommended minimum of 35g of protein expected to
come from animal products (FAO, 2019). Hence, the livestock sector is expected
to meet the growing demand for high-value animal protein most particularly
cattle.
Borno State is
a major supplier of cattle to the country. Cattle population in the State is
estimated at over 2 million (Borno State Ministry of
Animal Resources and Fisheries Development, 2011). Beef is the most preferred
source of animal protein in the State (Maina &
Baba, 2012). The beef value chain provides employment and income to a large
percentage of the stakeholders involved from production to consumption. The
value chain involves fattening or raising of beef cattle (production),
distribution to markets, processing into beef, further processing into several
beef products and onward movement to consumption points. Beef and its products
pass through successive actors who are serially linked before reaching its
end-users. At each point in the link, as value is added to the products, more
products are formed attracting more consumers. These products include cattle
(live animal), beef (raw), processed beef products such as suya (tsire, kilishi and balangu), dambun nama (fried
shredded meat) among others. Actors in the beef value chain take into
consideration purchasing behaviour of their potential consumers in order to
provide desired products.
Understanding the extent to which
consumer needs and preferences play on demand for beef and its products as well
as how it influences production (or prices) will have impact on all segments of
the value chain. Due to the interdependence of products in the beef value
chain, the whole system needs to be studied together. However, demand studies
in the study area (Maina & Baba, 2012) only
examined the retail node of the chain thus, negating the interdependence of the
various nodes of the beef value chain. Related value chain studies in the study
area (Ghide & Mohammed, 2016; Ghide
et al., 2017) emphasised the supply side of the market with emphasis on costs,
revenues and margins without recourse to the demand side of the market; the
consumers. This study focused on the consumption points of the retail and
processing nodes of the beef value chain. Own price elasticity, cross price
elasticity and expenditure elasticity were estimated for beef as well as
processed beef products.
MATERIALS
AND METHODS
The Study
Area
The study was carried out in
Maiduguri, Borno State, Nigeria. It is located in
north eastern Nigeria between latitudes 130 06I and 130
14I E and longitudes 110 46I and 110
54I N (GEONETcast UNIMAID, 2015).
Projected population of inhabitants of Maiduguri is put at 1,340,438 in 2020 at
annual growth rate of 3.2 percent from a population of 732,696 people in 2006
census (National Population Commission [NPC], 2006). The climate is generally
hot with a mean temperature of 37oc and mean rainfall of 647mm per
annum (Lake Chad Research Institute, 2019). Trading, farming and civil service
are the major occupations of the people of Maiduguri. Common crops grown
include groundnut, cowpea, millet, maize and vegetables such as onions,
tomatoes, peppers, cucumber, amaranths. Cattle, sheep, goats and chickens are
the major livestock reared.
Maiduguri is a major supplier of
cattle to the country and has a large livestock market popularly known as Kasuwan shanu, where
livestock most especially cattle are traded as well as fattened. It also has a
large abattoir situated opposite the cattle market which is able to handle 200
cattle a day as well as hundreds of sheep and goats (Maiduguri Central Abattoir
[MCA], 2020). Between the cattle market and abattoir, a large number of people
are employed as fatteners, input suppliers, traders, transporters, butchers,
middlemen, by-products retailers, and processors. These actors ensure that
cattle and its products reach the consumers at the right time and form. Road
side sales of cattle by-products such as beef and offal and processed beef
products are carried out across the study area. Beef is
processed into variety of products which could be roasted, cooked, fried, and
dried in accordance with consumer preferences and preservation motives. Tsire (indigenous name for
spicy meat skewer/kebabs), Balangu (indigenous
name for spicy high moisture roasted meat) and Kilishi (indigenous name for
beef jerky), collectively referred to as Suya are the commonest processed
and consumed beef products sold in the study area.
Sources of Data
Primary
data was used for the study which was obtained through structured questionnaire
that was administered through interview by trained enumerators. Information
obtained include socio-economics characteristics and detailed
expenditure on products.
Sampling Procedure
For
this study, research subjects were selected from the retail node and processing
nodes of the beef value chain. The retail node represents the point where beef
is handled and the processing node represents the point where processed beef is
handled. Since elasticities of demand were measured
which involved estimation of budget shares, these two nodes were considered as
the most important points were consumers actual responses would be measured.
This is because beef and processed beef products are directly part of the food
basket or part of consumption in which the amount spent on their consumption
can be measured. The production node where live cattle are handled was not
considered because it will not reflect budget share since cattle as a whole is
not directly part of the food basket.
Two
stage sampling were used to select respondents. In the first stage, 10 affluent
and 10 less affluent selling points were purposely selected within the
Metropolis. This selection was done in order to capture preferences of all
classes of consumers. This was done so as to give a good representation of
combination of heterogeneous classes of people with different food consumption
behaviour and socio-economic conditions (Islam & Jabbar,
2010). In the second stage, in a period
of 20 weeks, 100 buyers each of beef, tsire, balangu and kilishi respectively were selected by convenience sampling
from the selected affluent and less affluent sales points. The selection
amounted to 100 buyers from the retail node and 300 buyers from the processing
node. Altogether, 400 respondents were selected for the study.
Convenience sampling was used to select the sample for the study as the
population was large and there was no sampling frame. For the
retail node, beef was considered alongside similar products consumed in the study
area which include mutton, chevon and camel meat. For
the processing node, the three products studied (tsire, kilishi and balangu) were
measured together.
Analytical Techniques
For analysis of data, Linear
Approximate Almost Ideal Demand System (LA/AIDS) was used. The LA/AIDS model of
Deaton and Muellbauer (1980a) was employed to
estimate elasticities of demand. The study assumed
three-stage budgeting. The first stage comprised of an allocation of total
expenditure to a broad group of goods and at the second stage subsequently
allocates to the individual commodities (Deaton & Muellbauer,
1980b). The first stage requires knowledge of total expenditure and
appropriately defined group prices while in the second and third stages
individual expenditures are functions of group expenditure and prices within
the group. The weak separability of the utility
function is a necessary and sufficient condition for the broad group and at the
stage group (Deaton & Muellbauer, 1980b). A
demand function is weakly separable if the marginal rate of substitution
between any two goods that belongs to the same group are independent of
quantities of goods outside the group (Taljaard et
al., 2004). The study assumed the four meat products in the retail node (beef,
mutton, chevon and camel) are weakly separable and
were modelled together. Similarly, the three suya products (tsire, balangu and kilishi) are also
weakly separable hence also modelled together. Therefore, the empirical model
for the retail node consisted of four budget share equations corresponding to
each meat product estimated using the seemingly unrelated regression technique.
The same was done for the processing node where three budget share equations
corresponding to each suya
product were also estimated.
Following Sacli and
Ozer (2017), the model is expressed as:
………1
Where:
= budget share of
the 
good (which
include beef, tsire,
balangu, kilishi) defined
as
……………………………2
weighted average
price of items in the group
= quantity consumed of
good i (kg)
total expenditure on the
group of goods analysed (₦) i.e beef, chevon, mutton, camel for retail node and tsire, balangu and kilishi for
processing node
weighted average
price of items in the 
group (beef, mutton, chevon, camel for retail node and tsire, balangu and kilishi for
processing node)
error term
model
parameters
stone’s price index defined by
……………………………3
Where:
predicted
budget share of ith good (beef and the suya products)
The adding up, homogeneity and symmetry restrictions
were imposed on equation 1 during estimation.
The own price, cross-price and income elasticities were calculated from the LA/AIDS using the
following formulas:
Marshallian own and
cross-price elasticity,
……..……………………...4
Hicksian own and
cross-price elasticity,
...................................5
Where:
= Kronecker delta (
for own price, 
0 for cross-price elasticities)
Expenditure/income elasticity,
………………………………..6
For the estimation of elasticities,
Stata 15.1 version was used to run the analysis using
the command written by Poi (2008). This Stata command
uses Seemingly Unrelated Regression (SUR) by using maximum likelihood
estimation technique. Separate analyses were run for the meat group (beef with
other meat items) and for the processed beef products group.
A priori
expectation
The 
parameters (price
coefficient) are expected to be negative for own price elasticity. For cross
price effects, substitutive relationship will have positive values while
complementary relationship will have negative values. Beef is expected to have
a positive cross price effect with all the other meat products. Tsire, balangu and kilishi are also
expected to have positive cross price effects. The 
parameters
(expenditure coefficient) is negative for inferior goods and positive for
normal goods. Beef, tsire,
balangu and
kilishi are
expected to have positive coefficients.
RESULTS
AND DISCUSSION
Elasticities of Demand for Beef
Table 1 presents results for the
different elasticities for beef alongside mutton, chevon and camel. The diagonal values in bold face
represent the own-price elasticity while the other values either side of the
diagonal values are the cross-price effects. The uncompensated price elasticity
(also called the Marshallian price elasticity)
measure the relationship between a change in the quantity demanded and a change
in price of a commodity holding total expenditure constant (Henningsen,
2017). It contains both the income and price effects. The uncompensated own
price elasticity for beef, mutton, chevon and camel
were consistent with economic theory as all had the expected negative signs. The
price coefficient for beef was less than one (0.9664) but very close to unitary
so could be regarded as unitary elastic. This shows that a 1% increase in the
price of beef will result in approximately 1% decrease in quantity demanded.
Price elasticity of mutton (0.121), chevon (0.2759)
and camel (0.1919) were all inelastic and lower than the price elasticity of
beef. Mutton, chevon and camel were more irresponsive
to price change than beef.
Regarding cross-price elasticities, beef had a negative and significant
relationship with all the other meat products making them complements. This means
an increase in the price of beef by 1% would lead to a decrease of about 0.2%,
0.2% and 0.03% of the quantity demanded of mutton, chevon
and camel by consumers in Maiduguri. In the study area, cattle, sheep and goat
are commonly reared together. Generally, feed and management practices are
similar most especially cattle and sheep. Increased feed prices which may
result in increased price of cattle will also yield increased prices of sheep
and goat. This may make demand for beef, mutton and chevon
to move together in the event of price increases. However, the effect of a
price change of beef on the other meat items is not the same as the effects of
price change of the other meat items on beef. A 1% increase in the price of
mutton, chevon and camel meat would decrease the
demand for beef by 0.4%, 0.2% and 0.3% respectively.
The compensated price elasticity (also
called the Hicksian price elasticity) measure the
relationship between a change in the quantity demanded and a change in price of
a commodity, holding the utility level constant (Henningsen,
2017). The Hicksian
elasticity is reduced to contain only price effects (substitution effects), and
is thus compensated for the effect of a change in the relative income on
demand. The results in Table 1 showed compensated own price elasticity for beef
and all the other meat items were negative which was consistent with a priori expectation. This shows that as
prices of all the meat products go up, their quantity demanded decreases. However,
the magnitude of the price elasticity coefficients for all the meat products
were low. Price coefficient for beef was 0.0526 which showed beef to be highly inelastic, it had very low response
to price change. This finding suggest that without considering income, beef
consumers in Maiduguri do not reduce quantity of beef consumed much with
increase in its price.
Marshallian
elasticity generates gross complements and substitutes, where gross denotes
both the income and substitution effects. Consequently, Hicksian
elasticity generate net complements (or substitutes) when the effect of income
is not present at all. Due to presence of the income effect, good i can
be a gross substitute for good j, and at the same time j can be a
gross complement to i (Piipponen,
2017). The cross price elasticity of beef with other meat items showed beef had
a negative relationship with mutton and positive relationship with chevon and camel. This showed beef and mutton were
compliments while beef was substitute to chevon and
camel. The magnitude of the coefficients of the Hicksian
cross price relationship were smaller than the Marshallian
cross price relationship which indicate a weaker relationship. The results
showed a similar cross price relationship between beef and mutton
(complementarity) with and without the income effect. The relationship between
beef with chevon and camel with the income effect was
complementary but substitutive without the income effect. The cross price
effects of beef were significant with only chevon and
camel unlike the Marshallian cross price effects that
were significant for all the meat items. The consumption of beef showed the
strongest substitution response to the price of camel (0.2954) than to the
price of chevon (0.1986). This implies that beef
consumption in the study area is affected by the price of camel and chevon. It showed no effect to the price of mutton.
The expenditure (or income) elasticity
measures the percentage increase in consumption due to a percentage increase in
total expenditure (or income). Table 1 shows the expenditure elasticity of beef
was positive which showed it was a normal good. The coefficient exceeded unity
(1.3752) which showed beef to be considered a luxury good in Maiduguri. This
finding implies that beef was income elastic hence affected by income changes.
If income increased by 1%, the demand for beef increased by over 1.3%.
Considering beef is regarded as the most preferred meat in the study area, it
was expected to have an inelastic response to income change. This was not the
case as the results showed beef to be a luxury good. Understandably as with all
luxury goods, consumers would buy more of beef when their income increases. Cheaper
sources of protein such as fish in the study are available which could be among
the reasons why beef was considered a luxury good. Expenditure coefficient for
mutton (0.6278) was also positive but less than unity, making it income
inelastic so a necessity good. The results suggest that although beef is
regarded the most preferred meat in the study area, mutton is considered a more
important source of protein than beef. Aside its consumption as a healthier
protein source, sheep in the study area is used for sacrifice during naming
ceremonies and Eid celebrations. This could make consumers have a high regard
for mutton irrespective of their income. Expenditure coefficients for chevon (-0.0731) and camel (-0.0563) were negative and very
low. This means that both meat products are considered inferior goods in the
study area.
CONCLUSION
AND RECOMMENDATION
Beef was considered a luxury good in
Maiduguri and taking Marshallian price elasticity, change
in demand for beef was the same as its price change and it is complements with
mutton, chevon and camel. Beef demand was unresponsive
to its price change and had a complementary relationship with mutton and
substitute with chevon and camel by taking the Hicksian elasticity. For the processed products, kilishi and balangu were
luxuries and tsire
was a necessity. Kilishi
had the same response to its price change, tsire and balangu were more responsive to
their price change were all complements except for kilishi and balangu under the Marshallian elasticity. Taking the Hicksian
elasticity, kilishi
was irresponsive to its price change while tsire and balangu were responsive to their
price change and all were complements except for kilishi and balangu as well. The study recommends
that since most of the products studied
were luxury goods and have elastic demand, policy measures geared at ensuring
increased incomes such as employment creation which would concurrently increase
purchasing power of consumers should be exploited.
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