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Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
- 65 -
Sheep Price Patterns and Factors Affecting Price Variations in
the Highland Markets of North Shewa, Ethiopia
T. Beneberu* and Amer S. Jabarin**
ABSTRACT
Research on sheep marketing situations and constraints in Ethiopia in general, and north central highlands in
particular, remained very limited. This study examined sheep price patterns and factors underlying price
variations. It also tried to find out major constraints in sheep marketing system in selected districts of North
Shewa Zone (NSZ). Based on their importance of sheep marketing sites, four markets from NSZ were selected.
The markets were surveyed on the main weekly market day for a period of two years. Data were recorded on
price, weight (kg), sex, age, color, body condition and buyers' expected use of the animal for all transactions. A
total of 7976 observations were recorded. Primary data were collected by interviews from 619 sellers and 618
buyers from all selected markets to get insight about market constraints and situations using pre tested structured
questionnaires. Econometric model and descriptive analytical methods were used for the analysis based on
liveweight price.
The results showed that there was a considerable week-to-week variation throughout the year in liveweight
prices in the study markets. Animal characteristics that affect liveweight price were weight, sex, age, body
condition and color. The sheep market prices varied with respect to these characteristics. This suggests that
weekly liveweight average prices vary partly due to varying in sheep characteristics in the markets. The major
marketing constraints identified in the study areas were transportation, financial and information services. These
constraints were found to make price disparities and instabilities.
It is recommended that the government can take measures to help farmers by constructing market infrastructures.
These measures include: (i) improving transport infrastructure; (ii) promotion of regional trade (iii) establishing
market information systems and (iv) improving communication infrastructure.
KEYWORDS: Price variations, sheep marketing, animal characteristics, market constraints.
1. INTRODUCTION
Livestock plays a significant role in the national
economy of Ethiopia. It is a major activity in the country
and contributes about 30 - 40% of agricultural GDP and
more than 85% of farm cash income. It also contributes
about 13-16% of total GDP. Between 1987/88 and
1995/96, the share of livestock in total exports averaged
16% (Winrock, 1992; Befekadu and Berhanu, 2000).
Farmers consider livestock a more reliable form of
wealth than the other alternatives and sheep are a readily
convertible source of cash at the time of need as well as
an important source of meat. On the average, three heads
of sheep are slaughtered per family per year and about
40% of farmer’s cash income from animal trade in the
central highlands is accounted for by sales of sheep
(Gryseels, 1988).
* Sheno Agricultural Research Center, P. O. BOX 112, Debre
Birhan, Ethiopia.
**Associate Professor of Agricultural Economics (Corresponding
Author), Department of Agricultural Economics an
d
Agribusiness, University of Jordan, P. O. BOX 13021, 11942,
Amman, Jordan. Received on 8/3/2005 and Accepted fo
r
Publication on 15/1/2006.
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 66 -
The estimated 21.7 million sheep in Ethiopia
represent only 9% of the total Tropical Livestock Unit
(TLU1); yet produce highly significant outcomes. Sheep
and goats generate almost 50% of cash income, about
25% of domestic meat consumption with a production
surplus which is exported mainly as live animals and
almost 50% of domestic wool requirements of the
country (FAO, 1994). Other studies showed that sheep
alone contribute about 20% at the national level of all
domestic meat consumption and are a major source of
earnings through the sale of live animals and skins. Sheep
rank second to cattle on the farm in their contribution to
both subsistence and cash income generated from
livestock production (Shapiro, 1991).
The rest of the paper is organized as follows. The data
and model are described in section 2. Section 3 describes
the results found and discusses the policy implications.
Finally, section 4 provides summary and conclusion
remarks.
2. ANALYTICAL FRAMEWORK
This study is based on a multi-visit formal survey
conducted in four markets in North Shewa Zone (NSZ),
Ethiopia. From NSZ, four districts namely Kimbibit,
Angolelana Asagrt, Lalo Mama Midr and Gera Keya with
one key market each – Hamus Gebeya, Chacha, Molale
and Mehal, Meda, respectively were selected on purpose
on the basis of their importance as sheep marketing sites.
Primary data were collected by interviews from 619
sellers and 618 buyers from all selected markets to get
insight about market constraints and situations using pre
tested structured questionnaires. Data on sheep weight
and characteristics were collected on the main weekly
market day. Secondary data include animals population,
rainfall etc. were collected from Zonal Agricultural
Department (ZAD) and other sources. For data collection
in the markets, enumerators who were multitalented in
sheep marketing were used. A festival period was
1 Tropical Livestock Unit defined as a standard unit of 250 kg
of live weight. The conversion rates for individual species
are: cattle = 0.7, and sheep and goat = 0.1 each.
represented by two market days: the market falling on the
festival day (or the preceding market day closest to the
festival day) and the one preceding it. Recordings were
done at the exit gate(s) for fenced market place or at one
or two of the most frequented departure routes if the
market is opened. Ages were approximated by the type
and number, teeth and body conditions are assessed by
certain physical characteristics apparent in sheep of
different degrees of fatness, i.e., on and around the back
bone in the loin area and the last rib, and above the
kidney (Carles, 1983). Four body condition scores
ranging from one for poor to four for very fat sheep were
used in this study. The scores were given by the
researcher.
Analysis of data was involved using econometric
techniques and descriptive statistics. (i.e. multiple
regression model, and descriptive statistics such as
percentage and mean were used to describe and analyze
the data.) Data were analyzed using SPSS (1999) and
Excel (2000).
For most of the seasons/festive days, the week
number that a specific season happened in the previous
year did not repeat exactly in the same week number in
the forthcoming year. Therefore, regression analysis for
both years at the same time was not possible. Thus, data
from August 2001 to July 2002 were used for regression
analysis, moreover, this year data represent relatively to
the normal situation. However, both years’ data were
utilized for trend analysis. For this study, a reduced form
of price equation model will be estimated. The quantity
equation is not the interest of this study.
In the model, the presences of dummies (animal
characteristics and seasons) have impacts on shifting the
constant term, weight and time (b0, W and T). The model
used in the analysis was as follows:
() () ( )
() () () ()
()
8354
2
0
1111
54 3 5
11 1 1
4483
1111
4
1
***
****
*
iii iiiiiiii
iiii
ii ii i i i i i
ii i i
ii ii ii ii
iiii
iii
i
bbWbWbT bZ bS bA bC
bL bY bW T bW S bW A
bW C bW Y bW Z bT S
bT C e
P+
====
== = =
====
=
=+ + + + + +
++ + + +
+++ +
++
∑∑∑∑
∑∑ ∑ ∑
∑∑∑∑
∑
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
- 67 -
Where P is liveweight price in Ethiopian Birr (US$1=
8.60 Ethiopian Birr); W is weight in kg; T is time in
week; Z, S, A, C, L and Y are dummy variables
representing season, sex, age, condition, color, and buyer
purposes, respectively. The bі’s are structural parameters
of the equation and the error term eі’s, represents error
term.
In the model, one dummy was assigned at random as
a base for each category having the value zero. Therefore,
the number of dummies should be K-1 where K is the
number of groupings by that category (Maddala, 1992).
Base dummy variables were: non-festival season, female,
greater than four years, Very fat, other colors and
fattening for season, sex, age, body condition, color and
buyers purposes, respectively. The arbitrariness of the
dummy variable assigned to the basis is undesirable
features of the statistical package.
In the model, liveweight price was used as a
dependent variable. The advantage of using liveweight
price instead of price per head as a dependent variable is
that, it is possible to capture the wide variation in
weights, both within and between weeks; moreover,
liveweight price could give us more useful market
information.
The explanatory variables in the model are defined in
the following manner:
T = Weeks in the year: week 1, week 2 ---week 52.
Zi = 8 seasons: Ethiopian New Year, Id-al-fater
(Ramadan), Christmas, Id-al-adha, Easter, Lent (Period of
fasting before Easter, which is 55 days in Ethiopia),
Maulid (Birth day of the Prophet Mohammed), and non-
festival season.
Si = 3 sexes: male, castrated and female.
Ai = 5 age categories in year: A < 1, 1 < A < 2, 2 < A
< 3, 3 < A < 4 and A > 4, where A is age.
Ci = 4 body conditions: Poor, Average, Fat and Very
fat.
Li = 5 sheep color: Black, white, Brown and red,
Black and white, and others.
Yi = 4 buyer purpose: resale (profit), consumption,
reproduction and fattening.
3. RESULTS AND DISCUSSION
Sheep bought in all markets were different in some
way by buyers’ purpose. Mehal Meda and Molale are
markets where large proportions of sheep were bought for
profit by individuals especially traders and middlemen.
Hamus Gebeya and to some extent Chacha markets
represent buying for consumption purpose. Mehal Meda
and Molale market, respectively by traders, middlemen
and others who want to make profit out of sale on the
same or other market days. Purchasing for reproduction
and fattening purpose have the lowest proportion in all
markets (Table 1).
In general, age-wise, sheep less than or equal to two
years are dominant that were sold in all markets and the
percentage of sheep sold decreased as the age increased.
Sex distribution of sheep sold in the studied markets was
almost the same in all markets. However, sex
distributions within a market were considerably different.
Male sheep were dominant in all markets followed by
female sheep and castrated sheep were the lowest.
Moreover, sheep of average body condition were
dominant in all markets (Table 2).
Both the quantity purchased and supplied noticeably
increase during religious festivals. Apart from producers'
response to increased demand for sheep during festivals,
seasonality of supply is affected by lambing pattern and
producers' need for cash. Small ruminants were the
primary to be considered for sale when food and seed
grain stocks were depleted, and they are the main source
of income generation as recognized in many studies
(Zelalem and Fletcher, 1993; Rodriguez 1997; Barrs,
1998). The highest demand for grain seed and the lowest
stock of food grain occurs during June to end of
September. In addition, cash needs during September for
grain purchase, expenses like school fee and others are
required as it is the Ethiopian New Year time.
There is a remarkable fluctuation in weekly average
liveweight price and monthly average liveweight price in
all the study markets depending on the seasonal effects of
the year (Figures 1 and 2. Dating started from August
2000 and ended on July 2002). For the sake of clarity,
figures are drawn for two markets at a time for weekly
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 68 -
average liveweight price pattern. Demand for sheep
increases during Christian and Muslim holidays and in
the time of different ceremonies, generating a predictable
positive effect on prices.
The highest prices for sheep were recorded on
September, December, January, March and April/May.
These months are the times when the most important
festivals occurred. September is Ethiopian New Year,
which is celebrated by all people. The months December,
January, March and April/May accompanied with famous
religious festivals that are celebrated widely: Id-alfater,
Ethiopian Christmas, Id-al-adha and Ethiopian Easter all
demanding mostly sheep for home consumption. Lent
period, time of fasting before Easter, which is 55 days in
Ethiopia, is recognized by relatively low purchases of
sheep. During this period, less food is eaten in general,
while meat, egg and dairy products in particular are not
eaten by most Orthodox Christians.
From the liveweight price values, it was noticed that
relatively higher price was paid for sheep at Chacha and
Hamus Gebeya markets than Mehal Meda and Molale
markets, the latter two markets are located in remote
areas with very limited transportation facilities.
Probability levels of (F) tests of significance of the
variables and interactions included in the liveweight price
equation for each market under consideration are
presented in Table (4). The results indicate that most
factors are significant in at least two or three markets
from four markets.
The different patterns of variation in price per head
and liveweight price caused by week to week variation in
average weights is shown by plotting average price per
head and average liveweight price on the same graph
(Figure 3, is included only for one market as it happened
to be the same for the rest). It was evident from the
figures that there was weight difference from week to
week. If the weights did not vary at all from week to
week, the two price lines would maintain a constant
difference.
In the model, quadratic structure of the effect of
weight on liveweight price indicates that prices first
decline to a minimum and increase as weight increases.
This basically depends on the sign of the coefficient of
the variable in the second- order (quadratic), which is W2
in this case. If the coefficient of W2 is negative, the curve
will be concave downward, however, if coefficient of W2
is positive the curve will be concave upward and has
minimum value of liveweight price. It is desirable to
determine the maximum or minimum value of liveweight
price and the corresponding value of weight (Jerrold,
1984; Andargachew and Brokken, 1993). By comparing
the annual average weight of the sheep (sex-wise) and
taking the weight of the sheep at which minimum
liveweight price occurs (W*) for each market, it is
possible to judge the importance of weight with other
animal characteristics in determining the price of the
sheep for all markets.
At Chacha, the average weight of male sheep was
higher than W* while for female, the average weight was
slightly lower than, W*. Thus, for males and females
premiums in liveweight price were offered both as
weights increased above and decreased below W* (Table
5). At Hamus Gebeya, both male and female sheep had
lower overall average weight than W*. Thus, for males
and females premiums in liveweight price were offered as
weights decreased below W*. At Mehal Meda and
Molale markets, male, castrated and female sheep had an
overall average weight higher than W*. Hence for males
and females premiums in liveweight price were offered as
weights which increased above W*. In these markets,
liveweight prices of all the three sex categories were
rising as weights increase. One can only guess as to why
the relationship between liveweight price and weight are
so different from the other two markets. These markets
are remote and animals are purchased mainly for resale
(see Table 1). Since there is no transportation, animals
purchased for resale must be trekked a long distance from
where they were bought to other markets. Therefore,
traders favor higher weight in these markets to
counterbalance weight loss.
The average weight of castrates was well above W* in
all markets indicating that liveweight price was strongly
rising with increasing weights. This reflects a higher
demand for castrates that are both fat and heavy and
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
- 69 -
results in higher price per animal. Farmers castrate sheep
for fattening in order to fetch higher prices. Heavy and
fatty sheep are the choice of those people who are in a
good economic status. In general, consumers prefer lambs
because of their tenderness and low weight and low
weight converts to low price per head.
Applying multiple regression analysis on the data
collected from August 2001 to July 2002, the adjusted
R2s for liveweight price were 0.367, 0.470, 0.552, and
0.553 for Chacha, Hamus Gebeya, Mehal Meda and
Molale market, respectively. Estimated parameters of the
main effects of liveweight price equation for Chacha,
Hamus Gebeya, Mehal Meda and Molale markets are
shown in Table (6).
Positive and negative coefficients within a set of
dummy variables signify premiums and discounts,
respectively, relative to the dummy in the base in
Ethiopian Birr. The t-test was used to check whether the
individual premiums or discounts were different from
zero.
The negative effect of weight in the model indicates
that overall lower premiums are paid for heavier animals.
Andargachew and Brokken (1993) and Jabbar and
Diedhiou (2001) have come to a similar conclusion,
namely that animals with higher weights fetched lower
prices. This is because consumers prefer lambs for their
tenderness and tenderness possession belong to lower
ages (mostly below two years). Lower age means lower
weight and this converts to low price per head, which
might be another target for the buyers.
The effect of time on the liveweight price indicated
that as time went within a year (from August 2001 to July
2002), there was a trend of decreasing sheep price. The
reason was that most sheep were demanded for the
purpose of slaughtering during festival days, and most of
these festival days occur within the first half of the year.
However, this should not be considered as a regular event
within year cyclical phenomenon since certain major
festival days such as Eid Al-adha is linked to the Lunar
Calendar which changes every year.
Interpretation of the rest of the results of regression
analysis can be done using reduced form of the
econometric model. For Hamus Gebeya market,
substituting the values of coefficients from Tables (6 and
7) to the reduced form, the following equation is obtained
for sex effect.
2
4.239 0.036 0.031
WW
ii
P++
=
Using the annual mean weight values of sheep in the
above equation, for a sheep weight 22 kg, other variables
are equal, a whole ram would be 20.04 Birr which is
more expensive than ewes. The reduced form equation
for castrated sheep can be obtained by the same manner
as indicated above, which is:
2
4.926 0.084 0.031
WW
ii
P++
=
For a sheep weight 34 kg, other variables are equal; a
castrated sheep would be 43.62 Birr more expensive than
ewes.
For Hamus Gebeya market, the equation for a sheep
of yearling (sheep age less than or equal to one year)
would be as follows:
2
6.845 0.058 0.031
WW
ii
P−+
=
For a sheep weight 20 kg, other variables are equal; a
yearling would be 18.09 Birr more expensive than any
sheep more than four years old. For the same market, the
equation for a lamb (sheep age between one or equal to
two years) would be as follows:
2
6.185 0.029 0.031
WW
ii
P−+
=
For a sheep weight 27 kg, other variables are equal; a
lamb would be 28 Birr more expensive than any sheep
more than four years old.
The effect of color on liveweight price in the model
for Mehal Meda market can be expressed in the following
reduced form:
2
4.086 0.025 0.04
WW
ii
P++
=
For a sheep weight 23 kg, other variables are equal; a
white sheep would be 25.82 Birr more expensive than
any sheep of other colors assigned to the base (other
colors that were not included in the dummies).
The effect of season on liveweight price in the model
for Chacha market can be represented in the following
reduced form of equation:
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 70 -
2
5.361 0.022 0.027
WW
ii
P−+
=
For a sheep weight 18 kg, other variables are equal; a
sheep sold during Ethiopian New Year would be 13.71
Birr more expensive than season assign to the base (none
festival season).
The formulation of equation in reduced form and
interpretation of the results can be done by the same
procedures for the rest of the variables in all markets.
Moreover, although some characteristics of the sheep
were found to be insignificant in the analysis, they remain
as a base for expectations of their relevance to the sheep
buying decision.
Even though markets' liberalization was declared
since March 1990, there are still other barriers that
require serious attention. Therefore, identifying issues
and problems to guide future policy decisions with the
aim of reducing costs in the marketing system and
thereby promoting the welfare of producers and
consumers in the study areas call for attention. Among
others, transportation, credit and market information
facilities are the most important issues to be mentioned.
In rural Ethiopian markets, marketing channels for all
farm products are short and not complex. This is
primarily due to the absence of commercial livestock
processing in the study areas. Farmers sell their products
directly to consumers or they sell to middlemen or traders
and finally reach to consumers. Road network, financial
services and market information services are some of the
prior essential components of sheep marketing in the
study areas. These components are important for the
improvement and development of the marketing system.
In all markets of the study areas, buyers and sellers
bargain on one-to-one basis with relatively few brokers or
other third party market intermediation. Farmers
frequently arrive at the market without a firm idea of the
price that they will receive, or prices they might receive
in other markets, and they are mostly engaged in
negotiation (Table 8).
Regarding the repayment schedule of the loan,
farmers are asked to pay their debit within a short period
where investment in sheep production or fattening might
not bring any significant returns. Hence, the credit
repayment scheme in the area did not consider the
farmers’ situation and market conditions. Moreover, the
rural credit system has no risk component. Whether the
farmers’ efforts have succeeded or failed even due to
factors beyond control, the loans would be paid.
Therefore, the existing credit repayment schedule system
and the problem of risk needs further study and remedial
measures must be taken accordingly. In doing so,
farmers’ willingness in taking and using credit can be
enhanced and the intended purpose of credit will be
achieved.
Climate is not the only problem in the areas that
hinder sheep production. However, there are varieties of
physical infrastructural shortcomings that impede the
physical flow of animals which create barriers to
domestic trade. Lack of these infrastructures has
hampered marketing of agricultural products and
discouraged investment in more marginal areas and in the
livestock sector. One of the most important physical
infrastructural weaknesses for sheep marketing system in
the areas relate to transportation. More than 75% of the
people who come to the market have no access to vehicle
transportation (Table 9).
Road infrastructure in the study areas has poorly
developed. At Mehal Meda and Molale there is only one
dry weather road, which is below standard that connects
the districts’ capitals to the main road. At Hamus Gebeya
and Chacha the main road passes nearby the markets
although it is not accessible to most of the rural farmers.
Therefore, it is clear that the people of the study areas are
not blessed with the benefits of using regular transport.
In general, as current practice indicates, proclaiming a
free market economy alone could not enable the farmers
to obtain the benefits of such a policy. Rather, what is
more important and worth considering are: overcoming
the highly undeveloped rural-urban road networks,
forming and strengthening well-managed agricultural
cooperatives on a voluntary basis, developing rural,
regional, and central product markets and establishing
market information exchange systems, and other aspects
of the marketing infrastructure.
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
- 71 -
It is only when such conditions are fulfilled or at least
improved to a reasonable level that market information
and goods can flow better among different markets
relatively quickly, easily and reliably. Farmers could also
be in a position to improve their bargaining power. Such
developments would, hence, enable farmers to get the
right market price for their products, which would help
them to exert more effort on resources for improving their
agricultural production.
4- SUMMARY AND CONCLUSION
The result of this study showed that there was a
considerable week-to-week variation throughout the year
in sheep liveweight prices. These variations could relate
to variations in overall demand and on the characteristics
of animals offered for sale. Animal characteristics that
affect liveweight price were weight, sex, age, body
condition and color.
The results suggest that there may be some benefit
from coordinating breeding, fattening and marketing
programs to take the best advantage from some preferred
animal characteristics and selected seasons or festival
markets. Investments in rural infrastructure
(communications, roads, electricity, education, credit and
extension) can promote rural development by providing
access to relevant information, facilitating marketing of
agricultural inputs and products and development of agro
industries, which is essential to the population.
Therefore, the government can take measures to help
farmers by constructing market infrastructures so as to
shrink price disparities and instability. These measures
include: (i) Improving transport infrastructure. (ii)
Establishing market information systems (iii) Improving
communication infrastructure and (iv) Promotion of
regional trade.
ACKNOWLEDGMENTS
The authors wish to thank the Ethiopian Agricultural
Research Organization (EARO) for making available the
funds necessary to carry out this research.
Table (1): Percentage market structure of the study markets by buyers’ purpose.
Markets names
Chacha H/Gebeya M/Meda Molale
Buyer purposes % % % %
1. Consumption 31.4 59.5 29.2 22.9
2. Profit/resale 45.8 23.9 55.5 55.6
3. Reproduction 14.7 10.1 11.3 15.0
4. Fattening 8.1 6.5 4.0 6.5
No. of observations 1054 983 987 948
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 72 -
Table (2): Characteristics of traded animals in the study markets (%)
Markets name Animal Characteristics
Chacha H/Gebeya M/Meda Molale
Age (A) in years % % % %
A < 1 51.7 72.5 57.0 31.3
1< A < 2 16.7 8.3 29.8 35.9
2< A < 3 5.2 2.6 3.4 13.8
3< A < 4 8.2 5.8 4.6 8.5
A > 4 18.2 10.7 5.2 10.4
Color
Black 9.7 13.0 7.6 17.5
White 19.9 14.6 15.7 27.1
Brown & red 24.1 22.7 23.6 21.9
Black & white 23.5 19.3 21.7 16.9
Others 22.8 30.3 31.4 16.6
Sex
Male 48.4 51.1 47.1 48.8
Castrated 7.6 5.5 8.2 8.6
Female 44.0 43.4 44.7 42.5
Body condition
Poor 2.1 3.5 19.8 13.7
Average 71.5 74.3 63.2 48.4
Fat 16.0 14.5 12.7 21.8
Very fat 10.3 7.7 4.4 16.0
No. of observations 1054 983 987 948
Table (3): Mean and standard deviation for the study markets
Chacha H/Gebeya M/Meda Molale
Mean Std. D.* Mean Std. D Mean Std. D. Mean Std. D.
Weight (kg) 23.22 6.373 21.76 6.192 23.72 6.273 22.01 6.328
Price per head (Birr) 100.48 36.611 94.31 35.614 81.69 35.146 89.74 37.501
Liveweight price (Birr) 4.30 0.741 4.32 0.764 3.36 0.702 4.03 0.892
Std. D.* = Standard Deviation.
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
- 73 -
Table (4): Tests of significance (Prob. > F) of factors included in liveweight price equation for all markets.
Chacha market H/Gebeya market M/Meda market Molale market
Weight 0.9484 0.0001 0.5113 0.1642
Weight2 0.8092 0.0001 0.9343 0.7669
Week 0.1949 0.0001 0.0099 0.0078
Sex 0.1069 0.0004 0.0001 0.8207
Age 0.3682 0.0001 0.0211 0.1892
Body condition 0.1871 0.0001 0.0001 0.0008
Color 0.3199 0.0001 0.0005 0.0014
Buyers purpose 0.5504 0.2184 0.5275 0.6297
Season 0.0001 0.0051 0.0937 0.0427
Wt. X Week 0.8003 0.0008 0.0198 0.0028
Wt. X Sex 0.0213 0.0001 0.0001 0.0573
Wt. X Age 0.4130 0.0106 0.0186 0.0320
Wt. X Body condition 0.3680 0.0016 0.0004 0.0488
Wt. X Buyers purpose 0.7372 0.2204 0.3630 0.5311
Wt. X Season 0.0003 0.0305 0.0196 0.1275
Week X Sex 0.3596 0.5439 0.0959 0.1100
Week X Body condition 0.5748 0.4421 0.0001 0.0320
Table (5): Overall average weight by sex and weights at which minimum liveweight prices occur in the study
markets.
Markets Minimum
liveweight
price
W* Average weight
male sheep Average weight
castrated sheep Average weight
female sheep
Chacha 4.23 21.98 23.22 33.18 21.50
H/Gebeya 4.15 25.00 21.70 33.93 20.28
M/Meda 2.35 20.45 24.27 34.40 21.16
Molale 3.98 18.79 23.31 30.01 18.90
W*= weight of the sheep at which minimum liveweight price occurs.
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 74 -
Table (6): Estimated parameters of main effects of liveweight price equation for all markets.
Chacha
market H/Gebeya market M/Meda market Molale
market
Intercept 5.025*** 4.847*** 3.921*** 4.547***
Weight -0.034 0.002 0.025 -0.034
Weight 2 0.027 0.031 0.040 0.031
Time -0.084 -0.014*** -0.002 0.042
Sex
Male -0.013 -0.608*** -0.855*** 0.204***
Castrated 0.034 0.078 0.364*** 0.303***
Female @
Age (year)
A < 1 0.033 1.998*** 0.145** 0.415***
1 <A < 2 -0.047* 1.338*** -0.012 0.037
2 <A < 3 -0.018 0.461*** 0.503*** -0.026
3 <A < 4 0.021 -0.065 -1.142*** -0.107
> 4 @
Body condition
Poor -0.050 -1.775*** -1.834*** -1.114***
Average 0.084 -0.964*** -0.785*** 0.073
Fat -0.080 -0.081 -0.050 -0.139
Very fat @
Color
Black -0.020 -0.253*** -0.147** -0.029
White 0.103** 0.126** 0.165*** 0.118**
Brown & Red 0.005 0.010 -0.005 0.042*
Black & White 0.014 -0.164*** -0.006 0.195***
Others @
Buyers purpose
Consumption 0.045 -0.021 -0.030 0.031
Resale -0.030 -0.005 0.080 0.001
Reproduction 0.018 -0.008 -0.022 0.236***
Fattening @
Seasons
New year 0.336*** 0.252*** 0.424*** 0.824***
Id-al-fater -1.380*** 0.006 0.030 0.015
Christmas -0.412*** -0.004 -0.038 0.032
Id-al-adha 0.248*** 0.206** 0.032 -0.050
Lent -0.866*** -0.217*** 0.142*** 0.020
Easter 0.247*** 0.196** 0.202*** -0.027
Maulid -0.011 -0.014 0.001 -0.006
Non-festival @
N 1054 983 987 948
Adjusted R2 (liveweight price) 0.367 0.474 0.552 0.553
Std. Error 0.589 0.554 0.471 0.594
F- value 41.729 41.229 56.132 74.406
Significance < 0.0001 < 0.0001 < 0.0001 < 0.0001
Where *, ** and *** indicate statistical significance at 10%, 5% and 1% levels, respectively. A=age in years.
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
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Table (7): Estimated parameters of interaction effects of liveweight price equation for all markets
Chacha market Hamus Gebeya market Mehal Meda market Molale market
Interaction with weight
Weight X Time -0.039 0.113 -0.001*** 0.041
Weight X Sex
Male 0.007*** 0.034*** 0.045*** 0.061**
Castrated 0.026 0.082 0.242 -0.095
Female @
Weight X Age (year)
A < 1 0.018 -0.060*** 0.005 -0.030***
1 <A < 2 -0.042 -0.031*** 0.010*** 0.032
2 <A < 3 -0.020 -0.196* -0.053 -0.036
3 <A < 4 0.022 0.010*** 0.046*** 0.007***
> 4 @
Weight X Condition
Poor -0.080*** -0.110 -0.092 -0.038***
Average -0.029*** 0.146 0.165* -0.057***
Fat -0.013*** -0.025*** -0.013*** -0.026***
Very fat @
Weight X Buyers purpose
Consumption 0.035 -0.024 -0.008 0.010
Resale -0.036 0.006 -0.003** 0.000
Reproduction 0.006 -0.017 -0.021 -0.061
Fattening @
Weight X Seasons
New year 0.012 -0.081 0.013 -0.027
Id-al-fater 0.045** 0.010 -0.008*** 0.025
Christmas 0.193* -0.002 -0.011*** 0.030
Id-al-adha -0.026 -0.151 0.026 0.009**
Lent 0.030*** 0.062 0.069 0.013
Easter 0.036 -0.061 0.029 -0.019
Maulid -0.003 -0.021 0.010 -0.013
Non-festival @
Interaction with Time
Time X Sex
Male 0.044 0.046 0.009 0.005
Castrated 0.019 0.021*** 0.018*** -0.067
Female @
Time X Condition
Poor -0.050 0.011 0.023*** -0.069
Average -0.012*** 0.056 -0.004 0.006***
Fat -0.010*** -0.075 -0.001 0.052
Very fat @
Where *, ** and *** indicate statistical significance at 10%, 5% and 1% levels, respectively. A=age in years.
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 76 -
Table (8) Ways of sheep price formulations in the study markets.
Chacha Market Hamus Gebeya
Market Mehal Meda Market Molale Market
Buyer
% Seller
% Buyers % Seller % Buyers
% Seller
% Buyers
% Seller
%
Based on the previous market day
price
22.1 35.3 23.1 47.5 23.4 28.6 32.3 28.3
Collecting information on market
day
11.0 7.8 15.6 15.6 10.1 6.5 21.9 13.8
Negotiation 66.9 56.9 61.3 36.9 66.5 64.9 45.8 57.9
No. Observations 145 153 160 160 158 154 155 152
Table (9) Access for vehicle transportation in the study markets.
Chacha market Hamus Gebeya market Mehal Meda market Molale market
Buyer % Seller % Buyer % Seller % Buyer % Seller % Buyer % Seller %
Access 26.9 24.2 22.5 20.6 19.6 13.6 15.5 9.9
No access 73.1 75.8 77.5 79.4 80.4 86.4 84.5 90.1
No. Observations 145 153 160 160 158 154 155 152
Figure 1: Weekly average liveweight price values pattern for two years at Hamus Gebeya and Mehal Meda
markets.
0
1
2
3
4
5
6
1
7
13
19
25
31
37
43
49
55
61
67
73
79
85
91
97
103
Weeks
Liveweight price (Birr )
H/Gebeya
M/Meda
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
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Figure 2: Pattern of monthly average liveweight price in the study markets.
Figure 3: Weekly average price per head and liveweight price contrast for two years at M/Meda market.
0
1
2
3
4
5
6
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Months
Liveweight price (Birr)
Chacha
H/G ebeya
M/Meda
Molale
0
20
40
60
80
100
120
140
160
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
Weeks
Price/head (Birr)
0
1
2
3
4
5
6
Liveweight price (Birr)
Price/head
Liveweight price
Sheep Price Patterns… T. Beneberu and Amer S. Jabarin
- 78 -
5. REFERENCES
Andargachew, K. and Brokken, R. F. 1993. Intra-annual
Sheep Price Patterns and Factors Underlying Price
Variations in the Central Highlands of Ethiopia. Agric.
Econ., 8(1): 125-138.
Barrs, R.M.T. 1998. Costs and Return of Camels and Small
Ruminants in Pastoral Herds of Eastern Ethiopia. P. 162-
175. In: Proceedings of the Sixth Ethiopian Society of
Animal Production, 14-15 May 1998. A. Ababa,
Ethiopia
Befekadu, Degefe and Berhanu Nega, 2000. Annual Report
on the Ethiopian Economy: Volume I, 1999/2000. The
Ethiopian Economic Association, Addis Ababa,
Ethiopia. 429 pp.
Carles, A.B. 1983. Sheep Production in the Tropics. Oxford
University Press, New York.
Jabbar M.A. 1998. Buyer Preferences for Sheep and Goats
in Southern Nigeria: A Hedonic Price Analysis. Agric.
Econ., 18(1): 21–30.
Jabbar M.A. and Diedhiou, M.L. 2001. Does Breed Matter
to Cattle Farmers and Buyers? Evidence from West
Africa (eds). International Livestock Research Institute
(ILRI), Addis Ababa, Ethiopia.
Jerrold, H.Zar 1984. Biostatistical Analysis, 2nd ed. Prentice-
Hall International, Inc. Englewood Cliffs, New Jersey,
USA.
Little, Peter D. 2000. Cross Border Livestock Trade and
Food Security in the Somalia and Northern Kenya
Borderlands. Unpublished Manuscript. Binghamton, NY:
Institute for Development Anthropology.
Maddala, G.S. 1992. Introduction to Econometrics, 2nd ed.
Macmillan Publishing Company, New York.
Rodriguez A.R. 1997. Rural Poverty and Natural Resources
in the Dry Areas: The Context of ICARDA’s Research.
Working Paper. ICARDA (International Center for
Agricultural Research in the Dry Areas), Aleppo, Syria.
20 pp.
SPSS, 1999. Statistical Package for Social Sciences, Release
4.0, for Sun 4 (Unix). SPSS Incorporated.
Winrock International, 1992. Assessment of Animal
Agriculture in Sub-Saharan Africa. Winrock
International Institute for Agricultural Development,
Morrilton, Arkansas, USA. Pp.125. Cited in Robin
Mearns (1996) Balancing Livestock and the
Environment, Washington, DC, September 27-28, an
associated event to the Fourth World Bank Conference
on Environmentally Sustainable Development.
Yishak Mengesha, Ehui S., Jabbar M. and Shapiro B. 1999.
Handbook of Livestock Statistics for Developing
Countries. ILRI (International Livestock Research
Institute), Addis Ababa, Ethiopia.
Zelalem A. and Fletcher, I. 1993. Small Ruminant
Productivity in the Central Ethiopian Mixed Farming
Systems. In: Proceedings of the Fourth National
Livestock Improvement Conference, 13-15 Nov. 1991.
A. Ababa, Ethiopia. IAR, A. Ababa, Ethiopia.
Jordan Journal of Agricultural Sciences, Volume 2, No.1, 2006
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ﻷﺍﻤﻨـ ﻁﺎﺍﻌﺴﻟـﻴﻐﺘ ﻰﻠﻋ ﺓﺭﺜﺅﻤﻟﺍ لﻤﺍﻭﻌﻟﺍﻭ ﺔﻴﺭـﺭﺎﻌﺴﺃ ﺕﺍﺭ ﺴﺃ ﻲﻓ ﻑﺍﺭﺨﻟﺍـﻕﺍﻭ ﻴﺸ ﻕﻁﺎﻨﻤـ ﺎﻴﺒﻭﻴﺜﺇ ﻲﻓ ﺍﻭ
ﺕ .ﻭﺭﻴﺒﻴﻨﻴﺒ
*
ﻲﺤﺒﺼ ﺭﻤﺎﻋﻭ ،ﻥﻴﺭﺎﺒﺠ
**
ﺹـﺨﻠﻤ
ﻨﻫ ﺙﺎﺤﺒﻷﺍ ﻲﻓ ﺓﺭﻴﺒﻜ ﺔﻴﺩﻭﺩﺤﻤ ﻙﻟﺎ لﺍﻭﺤﺄﺒ ﻕﻠﻌﺘﺘ ﻲﺘﻟﺍ ﻡﺎﻋ لﻜﺸﺒ ﺎﻴﺒﻭﻴﺜﺇ ﻲﻓ ﺎﻬﻬﺠﺍﻭﺘ ﻲﺘﻟﺍ ﺕﺍﺩﺩﺤﻤﻟﺍﻭ ﻑﺍﺭﺨﻟﺍ ﻕﺍﻭﺴﺃ ، ﻲـﻓﻭ ﻁﺴﻭﻟﺍ ﺔﻴﻟﺎﻤﺸﻟﺍ ﺕﺎﻌﻔﺘﺭﻤﻟﺍ ﻕﻁﺎﻨﻤﻰ ﺩﻴﺩﺤﺘﻟﺎﺒ . ﺓﺭﺜﺅـﻤﻟﺍ لﻤﺍﻭﻌﻟﺍﻭ ﻑﺍﺭﺨﻟﺍ ﺭﺎﻌﺴﺃ ﻁﺎﻤﻨﺃ ﺙﺤﺒﻟﺍ ﺍﺫﻫ لﻭﺎﻨﺘﻴ ﻭ ﻲـﻓ ﺕﺍﺭـﻴﻐﺘﻟﺍ ﺔﻘﻁﻨﻤﻟﺍ ﻩﺫﻫ ﻲﻓ ﺔﻴﺭﻌﺴﻟﺍ، ﺒﻟﺍ ﺍﺫﻫ لﻭﺎﺤﻴﻭ ﻕﻁﺎـﻨﻤ ﻲـﻗ ﻑﺍﺭـﺨﻟﺍ ﻕﻴﻭﺴﺘ ﻡﺎﻅﻨ ﻪﺠﺍﻭﺘ ﻲﺘﻟﺍ ﺕﺍﺩﺩﺤﻤﻟﺍ ﻡﻫﺃ ﻰﻠﻋ ﻑﺭﻌﺘﻟﺍ ﺙﺤ ﺎﻴﺒﻭﻴﺜﺇ ﻲﻓ ﺍﻭﻴﺸ لﺎﻤﺸ ﺔﻘﻁﻨﻤ ﻲﻓ ﺓﺭﺎﺘﺨﻤ . ﺕﺎـﻴﺎﻐﻟ ﻕﺍﻭﺴﺃ ﺔﻌﺒﺭﺃ ﺭﺎﻴﺘﺨﺍ ﻡﺘ ﻑﺍﺭﺨﻟﺍ ﻕﻴﻭﺴﺘ ﻊﻗﺍﻭﻤﻟ ﺔﻴﺒﺴﻨﻟﺍ ﺔﻴﻤﻫﻷﺍ ﻰﻠﻋ ﺀﺎﻨﺒﻭ
ﻁﺴﻭﻟﺍ ﺔﻴﻟﺎﻤﺸﻟﺍ ﺕﺎﻌﻔﺘﺭﻤﻟﺍ ﻕﻁﺎﻨﻤ ﻲﻓ ﺔﺴﺍﺭﺩﻟﺍ ﻩﺫﻫﻰ، ﺃ ﻕﺍﻭﺴﻷﺍ ﺢﺴﻤﺒ ﻡﺎﻴﻘﻟﺍ ﻡﺘ ﺩﻘﻟﻭ ﻲﺴﻴﺌﺭﻟﺍ ﻡﻭﻴﻟﺍ ﻲﻓ ﺎﻴﻋﻭﺒﺴ ﻲـﻓ ﻉﻭﺒـﺴﻷﺍ ﻥﻴﻤﺎﻋ ﺓﺩﻤﻟﻭ ﺎﻤﻜ ، ﻡﺍﺩﺨﺘـﺴﺍ ﻊـﻗﻭﺘﻭ ﻡﺴـﺠﻟﺍ ﺔﻟﺎﺤﻭ ﻥﻭﻠﻟﺍﻭ ﺭﻤﻌﻟﺍﻭ ﺱﻨﺠﻟﺍﻭ ﻥﺯﻭﻟﺍﻭ ﻑﺍﺭﺨﻟﺍ ﺭﻌﺴﺒ ﺔﻘﻠﻌﺘﻤﻟﺍ ﺕﺎﻨﺎﻴﺒﻟﺍ ﻊﻴﻤﺠﺘ ﻡﺘ
ﻊﻴﺒﻟﺍ ﺕﺎﻘﻔﺼ ﻊﻴﻤﺠﻟ ﻑﺍﺭﺨﻠﻟ ﻱﺭﺘﺸﻤﻟﺍ، ﺙـﺤﺒﻟﺍ ﺍﺫﻫ ﺕﺎﻴﺎﻐﻟ ﺔﻠﺠﺴﻤﻟﺍ ﺕﺍﺩﻫﺎﺸﻤﻟﺍ ﺩﺩﻋ ﻎﻠﺒ ﺙﻴﺤ 7976 ﺓﺩﻫﺎﺸـﻤ . ﺕـﻌﻤﺠﻭ ﺍ ﺕﺎﻨﺎﻴﺒﻟﺍ ﺔﻠﺒﺎﻘﻤ لﻼﺨ ﻥﻤ ﺔﻴﻟﻭﻷ619 ﺔﻋﺎﺒﻟﺍ ﻥﻤ ﻭ618 لـﺠﺃ ﻥـﻤ ﺔـﺴﺍﺭﺩﻟﺍ ﺔﻘﻁﻨﻤ ﻲﻓ ﺓﺭﺎﺘﺨﻤﻟﺍ ﻕﺍﻭﺴﻷﺍ ﻲﻓ ﻥﻴﺭﺘﺸﻤﻟﺍ ﻥﻤ
ﺔﻴﻘﻴﻭﺴﺘﻟﺍ ﺕﺍﺩﺩﺤﻤﻟﺍ ﻡﻫﺃ ﻰﻟﺇ لﻭﺼﻭﻠﻟ ﺔﻴﻠﻴﺼﻔﺘﻟﺍ ﺕﺎﻤﻭﻠﻌﻤﻟﺍ ﻰﻠﻋ لﻭﺼﺤﻟﺍ . ﻕﺭـﻁﻭ ﻲﺴﺎﻴﻗ ﻱﺩﺎﺼﺘﻗﺍ ﺝﺫﻭﻤﻨ ﻡﺍﺩﺨﺘﺴﺍ ﻡﺘ ﻙﻟﺫﻜ لﻴﻠﺤﺘﻟﺍﺍﻑﺍﺭﺨﻠﻟ ﻲﺤﻟﺍ ﻥﺯﻭﻟﺍ ﺭﺎﻌﺴﺄﺒ ﻕﻠﻌﺘﻤﻟﺍ لﻴﻠﺤﺘﻟﺍ ﻲﻓ ﻲﻔﺼﻭﻟ .
ﺔـﺴﻭﺭﺩﻤﻟﺍ ﻕﺍﻭﺴﻷﺍ ﻲﻓ ﻡﺎﻌﻟﺍ لﻼﺨ ﻉﻭﺒﺴﺃ ﻰﻟﺇ ﻉﻭﺒﺴﺃ ﻥﻤ ﻑﺍﺭﺨﻠﻟ ﻲﺤﻟﺍ ﻥﺯﻭﻟﺍ ﺭﺎﻌﺴﺃ ﻲﻓ ﺭﻴﺒﻜ ﻥﻴﺎﺒﺘ ﺩﻭﺠﻭ ﺞﺌﺎﺘﻨﻟﺍ ﺕﺭﻬﻅﺃ . ﻲﺤﻟﺍ ﻥﺯﻭﻟﺍ ﺭﺎﻌﺴﺃ ﻰﻠﻋ ﺓﺭﺜﺅﻤﻟﺍ ﺕﺎﻔﺼﻟﺍ ﺕﻠﻤﺸﻭ : ﻥﻭﻠﻟﺍﻭ ﻡﺴﺠﻟﺍ ﺔﻟﺎﺤﻭ ﺭﻤﻌﻟﺍﻭ ﺱﻨﺠﻟﺍ ﻭ ﻥﺍﻭﻴﺤﻟﺍ ﻥﺯﻭ، ﺒﺘ ﺙﻴﺤ ﺭﺎﻌﺴﻷﺍ ﺕﻨﻴﺎ ﺹﺌﺎﺼﺨﻟﺍ ﻩﺫﻫ ﺏﺒﺴﺒ . ﺔﺴﺍﺭﺩﻟﺍ ﺔﻘﻁﻨﻤ ﻪﺠﺍﻭﺘ ﻲﺘﻟﺍ ﺔﻴﻘﻴﻭﺴﺘﻟﺍ ﺕﺎﺒﻭﻌﺼﻟﺍ ﻡﻫﺃ ﻥﺃ ﺔﺴﺍﺭﺩﻟﺍ ﺕﻨﻴﺒ ﻙﻟﺫﻜ : ﺕﺎﻤﺩﺨﻭ لﻴﻭﻤﺘﻟﺍ ﻭ لﻘﻨﻟﺍ ﺔﻴﻘﻴﻭﺴﺘﻟﺍ ﺕﺎﻤﻭﻠﻌﻤﻟﺍ، ﺕﺎﺒﻭﻌﺼﻟﺍ ﻩﺫﻫ ﺭﺜﺅﺘ ﺙﻴﺤ ﻲﻓﺎﻫﺭﺍﺭﻘﺘﺴﺍ ﻡﺩﻋﻭ ﺭﺎﻌﺴﻷﺍ ﻥﻴﺎﺒﺘ . ﻴﻠﻋﻭﻪ ﺜﺤﺎﺒﻟﺍ ﻲﺼﻭﻴ ﻥﺎ ﺎﺴﻤﺒ ﺔﻴﺒﻭﻴﺜﻹﺍ ﺔﻤﻭﻜﺤﻟﺍ ﻡﺎﻴﻗ ﺓﺭﻭﺭﻀﺒ لﻼﺨ ﻥﻤ ﻑﺍﺭﺨﻟﺍ ﻲﺒﺭﻤ ﺓﺩﻋﺇﺀﺎﺸﻨ ﻲـﺘﻟﺍ ﺔﻴﻘﻴﻭﺴﺘﻟﺍ ﺔﻴﺘﺤﺘﻟﺍ ﻰﻨﺒﻟﺍ لﻤﺸﺘ :1( ﻭ لﻘﻨﻠﻟ ﺔﻴﺘﺤﺘﻟﺍ ﻰﻨﺒﻟﺍ ﻥﻴﺴﺤﺘ2( ﻭ ﺔﻴﻤﻴﻠﻗﻹﺍ ﺓﺭﺎﺠﺘﻠﻟ ﺞﻴﻭﺭﺘﻟﺍ3 ( ﻭ ﺔﻴﻘﻴﻭﺴـﺘﻟﺍ ﺕﺎﻤﻭﻠﻌﻤﻠﻟ ﻡﻅﻨ ﺱﻴﺴﺄﺘ4 ( ﺴـﺤﺘﻴ ﻥلﺎﺼﺘﻻﺍ لﺌﺎﺴﻭ.
________________________________________________ * ﺯﻜﺭﻤ )ﻭﻨﻴﺸ (ﺎﻴﺒﻭﻴﺜﺇ ،ﻥﺎﻫﺭﺒ ﻱﺭﺒﺩ ،ﺔﻴﻋﺍﺭﺯﻟﺍ ﺙﻭﺤﺒﻠﻟ. ** ،ﺔﻴﻋﺍﺭﺯﻟﺍ لﺎﻤﻋﻷﺍ ﺓﺭﺍﺩﺇﻭ ﻲﻋﺍﺭﺯﻟﺍ ﺩﺎﺼﺘﻗﻻﺍ ﻡﺴﻗﺔﻴﻨﺩﺭﻷﺍ ﺔﻌﻤﺎﺠﻟﺍ ،ﺔﻋﺍﺭﺯﻟﺍ ﺔﻴﻠﻜ. ﺙﺤﺒﻟﺍ ﻡﻼﺘﺴﺍ ﺦﻴﺭﺎﺘ 8/3/2005 ﻪﻟﻭﺒﻗ ﺦﻴﺭﺎﺘﻭ ،15/1/2006.
