chapter iii: research methodology 3.1. study...
TRANSCRIPT
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CHAPTER III: RESEARCH METHODOLOGY
This chapter is devoted to the description of the materials and methods used in the
present study. It begins with describing the study area followed by explanations of the
nature and source of data as well as the data collection techniques used. Data collection
techniques as well as method of analysis will be presented. A brief account of the data
analysis methods and the empirical models used are also made.
3.1. Study Area
This study is conducted in central highlands of Ethiopia that fall in the administrative
territory of Oromia National Regional State. With 12 administrative zones and 180
districts, Oromia National Regional State is the largest regional state of Federal
Democratic Republic of Ethiopia. Household data is collected from three towns namely
Bishoftu, Holota, and Woliso. The brief description of the selected towns is presented
below.
Bishoftu: Bishoftu is a town and separate district located in the East Shewa zone at 47
kilometers south of the capital city of the country, Addis Ababa, on the main road to
Adama. According to the population and housing censes of 2007, the total population of
the town was 100,114, of whom 52.1% were women. The absolute location of Bishoftu is
8°45′N latitude and 38°59′E longitude. Topographically the city is located in tepid to cool
sub-moist mid highland at an altitude of about 1920 meters above sea level with moderate
weather condition. The temperature of the area falls within a range of 16°c and
24°c. Bishoftu is truly a resort town, known for five crater lakes: Lake Bishoftu, Lake
Hora, Lake Bishoftu Guda, Lake Koriftu and the seasonal Lake Cheleklaka
Woliso: Woliso is the capital of South West Shewa administrative zone. The town is
located at a distance of 114 kilometers south west of Addis Ababa, along the Addis
Ababa-Jimma route. The total population of the town as per the national census of 2007
is 37,867 (with the proportion of 49.84% male and 50.16% female). The coordinates of
the town is 8°32′N latitude and 37°58′E longitude. It is characterized by temperate type
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of climate with daily temperature ranging from 180c and 270c, and is located 1900m
above sea level.
Holota: Holota is a town and separate woreda in the Oromia Special Zone Surrounding
Finfinne. The town is located 40 kilometers west of Addis Ababa at 9°30' N and 38°30'
E with altitude range from 2300-3800m above sea level. The annual mean temperature
ranges from 14°c to 24°c and annual rainfall ranges from 900-1100 mm. According to
the population and housing censes of 2007 the population of the town is 23,296
(male=11512, female=11,784). (49.41% male and 50.59% female)
Figure 3: The Geographical Location of the Study Area
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3.2. The Data and Method of Analysis
3.2.1. The nature and sources of the data
Both primary and secondary data were used in this study. The primary data constituted
the major input for the study and was collected from peri-urban vegetable farmers using
various survey tools and techniques. The survey data was supplement by field
observation and focus group discussion (FGD). The FGD was conducted at various
stages with different stakeholders such as farmers, municipal workers, and agricultural
expert’s. In addition, secondary sources of data such published & unpublished municipal
documents and internal reports, as well as books, scientific journals, and proceedings
were used to substantiate and elaborate the findings of the study.
3.2.2. Sampling and data collection methods
Two stage sampling techniques were used to select the sample households. In the first
stage, among the emerging towns of central Ethiopia, three towns (namely Bishoftu,
Holota, and Woliso) were purposively selected for two reasons: first, because of their
suitable agro-climatic conditions and easy access to transport facility to central market
(all on the national highways spinning to south, east, and west of the country from Addis
Ababa), these three towns have relatively large number of PU vegetable producers
compared to other towns in central highlands of Ethiopia; second, due to their
geographical proximity to the capital Addis Ababa, there is stiff competition between
farmers and construction sector in PU land. In the second stage, individual farmers were
selected from each town using random sampling techniques. This is because in this study,
individual farming household was used as sample unit up on which the economic analysis
was made up. A household may be defined in various ways but in this study Ellis
definition (cited in Tewodros, 2011) was adopted. According to Ellis, a household is
defined as a social unit characterized by the sharing of the same residence. Since the size
of PU farmers in the three towns was not equal, it is not appropriate to take equal sample
from all the towns. It is rather fair to make the sample size proportional to the total peri-
urban population of the respective towns. Thus, specific households were selected from
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PU areas of each town using simple random techniques taking the size of PU farming
population of each town. According to the information from DAs of each area, the PU
vegetable farmers surrounding Bishoftu, Holota, and Woliso towns were estimated to be
about 1200, 900, and 1000, respectively. Accordingly, 122, 97, and 105 PU vegetable
farming households were selected from Bishoftu, Holota, and Woliso towns, respectively,
making the total sample size to be 324.
Structured questionnaires and interviews specially designed to meet the objectives of this
study were used to collect the primary data. A wide range of data was collected from the
individual sampled households and FGD participants. Beside their demographic and
socioeconomic information, details of their input and output information, as well as
marketing information were collected from PU vegetable farming households. The data
collection was carried out by 12 selected and well trained enumerators under a close
supervision of the researcher. The enumerators had been given two days training by the
researcher itself before they leave for data collections. Thus, the data collection was
commenced only after the data collectors have properly understand the objective of the
research and each of the question items.
Furthermore, before the commencement of the full scale survey, pilot survey was
conducted on 15 peri-urban farmers to check whether the designed survey questionnaire
meets the expectation of the researcher. Based on the input gained from the pilot survey,
the necessary corrections was made to the questionnaire and finalized. To ensure the
validation of responses, completed questionnaires were inspected for errors and edited
regularly and revisiting of the respondents was made where necessary. Furthermore, daily
follow-up and motivation of the enumerators had been done to improve the overall
quality of the sample survey.
3.2.3. Methods of data analysis
Since the objectives of the study were diverse and the nature of the data was
heterogeneous, no single data analysis technique was sufficient to the study. The
socioeconomic data were analyzed using simple statistic techniques such as measures of
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central tendencies (mean, mode, and median), measures of dispersions (range, variance,
and standard deviation), ratios, frequencies, and percentages. ANOVA was also used to
test the significance of differences among different groups. Statistical Package for Social
Sciences (SPSS version 20) was used to describe and summarize the quantitative data
used in descriptive analysis. Regression analysis was used to point out the factors that
explain variations in technical efficiency. Efficiency computation and regression was
carried out using stochastic production function approach with the help of STATA
version 11.
3.3. Empirical Model Specification
The objective of this research necessitates the specification of two models: one for
computation of technical efficiency and another one for determinants of technical
efficiency. The two models are presented in the following two sub-sections.
3.3.1. The stochastic frontier model
The stochastic frontier production function method dominates the analytical background
of efficiency analysis. Although the credit of introducing this method goes to Michael
Farrel (1957), many improvements have been made on the model before it gains its
current form (Nega & Ehui, 2006). The stochastic frontier equation presented in section
2.5 (Equation.2) can be rewritten as follows:
................................................................................... 7
Where:
- ln designate a natural logarithm;
- is the quantity of output of household i;
- is the vector of input quantities used by household i;
- β is a vector of unknown parameters;
- vi is the two side error component (stochastic error term); and
- ui is the one sided error component (estimate of technical inefficiency).
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Specification of the functional form for the production function is another important task
ahead. A wide range of functional forms for the production function are available in
literature: the most frequently used ones are Cobb-Douglass Production function,
Translog specification, Constant Elasticity of Substitution production functions. The
translog production function nests as special cases of the constant elasticity of
substitution and Cobb-Douglas production function. It has both linear and quadratic
terms, and has ability of using more than two factor inputs. More importantly, the
translog function is a relatively flexible functional form, as it does not impose restrictions
on the parameters nor on the technical relationship among inputs; i.e., does not impose
assumptions about constant elasticities of production nor elasticities of
substitution between inputs. It thus allows the data to indicate the actual curvature of the
function, rather than imposing a priori assumptions (Tewodros, 2001; Pascoe et al., 2003;
Alemayehu, 2010). As a result, it has been widely used by researchers of same interest
and proved that it fits the data well. Owing to the aforementioned merits, the translog
production function is selected for empirical analysis. In general terms, the translog
production function can be expressed as:
.......................... 8
Where:
- ln designate a natural logarithm;
- Y is the observed output of a farmer;
- X is a vector of explanatory variables;
- β is a (Kx1) vector of unknown parameters;
- i and j are ith farmer and jth inputs, respectively (where i=1,2,...n and j=1,2,....m);
- vi is the stochastic error term; and
- ui is an estimate of technical inefficiency.
Not to mention, the dependent variable in equation 8 is the total output (in kg/hectare)
that is collected from the farm during the survey period or last production period. Having
defined the dependent variable, selection of appropriate explanatory variable (or defining
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the vector X) is an ardent task ahead. The following are the conventional variables in
production function.
Land: this is the size of vegetable plot and is measured by hectare.
Seed: this is the principal input of the vegetable production. It is measured in the same
unit with yield (kilogram).
Labor: it is the amount of human capital invested on the production of vegetables. In the
stochastic model, labor is the aggregate of family labor and hired labor. Family Labor is
the total labor days the member of the household engaged in different activities of
vegetable production (such as ploughing, sowing, weeding, harvesting and selling).
Obviously, there is heterogeneity among member of a given family (at least in terms of
age and gender) and hence conversion to equivalent man hour is exercised to
accommodate the potential variation in individuals’ labor power. The common
conversion tools is what is commonly called the Norman Conversion ratio (Omotesho,
Muhammad-Lawal, & Yusuf, 2010), which is also used by FAO (Alemayehu, 2010;
Uaiene & Arndt, 2009). Therefore the number of days worked by women and juvenile
(children less than 15 years age) were converted to adult man-hours equivalents using
Norman Conversion ratio of which one woman-hour equals 0.75man-hour while one
child-hour equals 0.5man-hour. Finally, the total working hours is summed up to reach at
total family labor used in the production of PU vegetables. Hired Labor, on the other
hand, is refers to the total labor days a hired labor is engaged in the vegetable farm. The
monetary unit was used because it was very difficult to compute the labor time in terms
of hours or days as some labor are hired to take care of the farm from the beginning to the
end of the vegetable production, and the use of monetary units eliminates such
complications. The total labor, therefore, is the sum total of labor days of family labor
and hired labor.
Fertilizers: Two types of fertilizers are used by vegetable farmers: organic fertilizer and
inorganic fertilizer. Inorganic Fertilizer is the market value of DAP and Urea used by a
vegetable farmer and is measured by kilogram (kg). Beside the inorganic ones, few
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farmers used Organic Fertilizer such as compost and manure. Organic fertilizer nutrient
content, solubility, and nutrient release rates are typically all lower than inorganic
fertilizers. Furthermore, use of organic fertilizers may have multiple benefits (increased
soil organic matter, reduced erosion, better water infiltration and aeration, higher soil
biological activity as the materials decompose in soil). But it increases yields only after
the year of application (residual effects). This is because its speed of release in nitrogen
content is very low, 25-60 percent. As a result, the organic fertilizers are converted to its
inorganic fertilizer equivalence at the rate lower than unity. In consultation with the
agricultural experts in the study area, the organic fertilizer is converted to inorganic
fertilizer equivalence at the rate of 0.5. The total fertilizer, therefore, is the sum of
inorganic fertilizer and inorganic fertilizer equivalence of organic fertilizers, and is
measured by kilogram.
Hand Tools: this refers to the monetary value of small hand tools used by farmers for
ploughing, sowing, weeding, and harvesting/collecting. Since the tools are
heterogeneous, the composite value is computed using price as weight. For equipment
whose economic life is more than one year, the depreciation charges are calculated
according to the rate of straight-line depreciation recorded in the course of time. Thus the
unit of measurement for this variable is Birr.
The ultimate objective of the stochastic frontier model is to estimate farm specific
technical efficiency. This requires specifying the distributional assumption for the error
term ui is another debatable issue. The distribution of ui could be one of the following
four: half normal, truncated normal, exponential and gamma. But when our data is cross-
sectional it is preferable to use the standard distributions; i.e. half- or truncated normal
(Pascoe et al., 2003). In this study, half normal distribution was assumed for the error
term ui and the farm specific technical efficiency was obtained from the frontier
estimation result using Equation 6.
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3.3.2. The efficiency effect model (determinants of technical efficiency)
Estimating the efficiency level of each individual farmer is only half of the story. The
second, yet equally important issue is investigating the factors affecting the efficiency of
vegetable farmers; i.e., identifying sources of efficiency differential has a prime
importance policy intervention. To analyze the effect of certain socio-economic and
institutional factors on the technical efficiency of farmers, a second step analysis was
performed with a two-limit (linear) Tobit model. The Tobit regression model is an
econometric model that is employed when the dependent variable is limited or censored
at both sides. When the data to be analyzed contain values of the dependent variable that
is truncated or censored, according to Kahi and Yabe (2011), Two stage tobit model is
preferred to OLS because the latter might produce biased results, often toward zero4.
In the present study, a two-limit Tobit model was adopted because the dependent
variable, technical efficiency scores, is censored having values ranging between 0 and
1.This is so because technical efficiency of an individual farm is the ratio of the observed
output to the corresponding frontier output conditional on the level of input used
(Nyagaka et al., 2010). Fully efficient farmers operate along the boundary of the frontier
and hence there is no room for further improvement. In this case the ratio of observed to
the frontier (potential) output level will be unity. On the other hand, firms which are
relatively inefficient operate at points in the interior of frontier and score less than unity
but greater than zero. Unless the farmer loses his/her crop due to complete crop failure as
a result of pest and diseases infestation or drought, efficiency score will not be zero.
Therefore, while the scores are bounded between zero and one (two-limit) with the upper
limit set at one, the distribution is censored at both tails.
Thus, following Mussa, Obare, Ayalneh, and Simtowe (2012), the two-limit Tobit
regression model of the following form was estimated:
4 Similar methodology was used by many researchers like Gul and Parlakay (2011), Nyagaka et al (2010), Kahi
and Yabe (2011), Omonona et al., (2010), Koc, Gul, and Parlakay (2011), Gul et al (2009),etc
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....................................................... 9
Where: i refers to the ith farm in the sample,
TEi is technical efficiency of the ith farm;
TEi* is the latent efficiency;
j are parameters of interest to be estimated;
μi is random error term that is independently and normally distributed with mean
zero and common variance of δ2 (μi~NI(0, δ2); and
Zij are socio-economic, institutional, and demographic variables.
The dependent variable in the efficiency model is quite clear, it is the efficiency score!
The efficiency score is a value computed from the stochastic error term for each
household. This estimated efficiency score obtained from the model (using Equation 6)
was made an explicit function of available socioeconomic variables. But there is no clear
cut list of explanatory variables to be included in the efficiency effect model. Thus, the
choice of inefficiency effect variables remains subjective. But there is a general
consensus that technical inefficiency could be the resultant effect of both the farmer and
farm level characteristics. A priori literature coupled with researcher’s knowledge of the
custom of agricultural practice in the country and availability of data is used to guide the
selection of the independent variables. In this study, therefore, the following variables are
sought to be the factors that affect technical efficiency/inefficiency of farmers.
Age: This is the age of the household head and is measured by year. Economic literature
could not specify the sign of this variable; i.e., neither the empirical nor theoretical
arguments brought clear direction as to the impact of age. Therefore, the expected sign is
indeterminate.
Gender: it is a dummy variable that takes in to account the sex of the vegetable farmer.
Unlike the case of developed countries, agricultural activities of developing countries are
not mechanized. Tilling, sowing, harvesting, and marketing are traditional and more of
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laborious that requires physical strength. As a matter of fact, men fit to such requirements
than women. Thus, it is expected that male farmers are more technically efficient than
female farmers.
Family size: is the total number of people living in the household including the
household head during the survey period (2011/12). Large family size may mean high
dependency ratio and high consumption. This in turn may reduce investment and
efficiency. The variable, therefore, is expected to have negative coefficient.
Education: this is the education of the farmer and is measured by the number of years
spent in school. Schulz (cited in Uaiene & Arndt, 2009) argued that literate farmers are
expected to acquire, analyze and use information related to modern farming techniques
better than illiterate farmers. The expected sign of the variable, therefore, is positive
Access to technical support: this is a dummy variable for farmer’s access to technical
support from DAs. Extension services provided by DAs can help PU agriculture farmers
select appropriate crops, schedule production, improve harvesting techniques, and reduce
post-harvest losses. It can also help farmers get optimum prices for their produce by
having them acquire new skills such as grading and sorting. Thus, the more visits a
farmer had, the more efficient he will be and vice versa. This implies that the expected
sign for technical service is positive
Access to credit facilities: this variable takes care of whether the farmer has access to
credit facilities or not. The a priori assumption is that access to credit facility positively
influence technical efficiency because availability of loans provide them financial
freedom to buy the necessary inputs. The expected sign of the coefficient of this variable
in the efficiency model is, therefore, positive.
Off farm income: The effect of off-farm employment on the production of farmer being
involved in off farm activities may be of two fold. First, if farmer spends more time on
off farm activities relative to farm activities, this may negatively affect agricultural
activities. Second, it absorbs the excess family labor that otherwise might be engaged on
same small plot and cause cost to rise and efficiency to fall. Furthermore, it provides cash
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that may well be used to loosen a constraint (which in this setting could well be a credit
constraint) in farming, allowing to households to invest and become more efficient in
farming (Bezemer, Balcombe, Davis, & Fraser, 2005). Thus, it is impossible to clearly
predict the sign of off-farm income.
Location difference: this is the location or town dummy that takes care of the potential
impact of farm location on efficiency score difference. Location differences may result in
efficiency differences for various reasons. They may reflect difference in soil
fertility/structures to the least. As mentioned in methodology section, the data is
collected from sub-urban areas of three different towns: Bishoftu, Holota, and Woliso.
Following the standard economic approach, two dummy variables are introduced: one for
Holota and the other for Woliso. Farmers selected from Bishoftu, therefore, are base or
reference group against which the other two are compared. The expected sign of the
variables included in the above equation is summarized in Table 6.
Table 6: Variables Included in the Efficiency Effect Model
Variable Code Description of the variable Parameters Expected
sign ag Age 1 ? sx Gender (1=male; 0= otherwise) 2 + fS Family size 3 - ed Education 4 + ts Access to technical support
(1=if received technical support; 0 = otherwise) 5 +
cf Access to credit facilities (1=if credit facility is accessible; 0 = otherwise)
6 +
oi Availability of off-farm income (1=if off-farm income is available; 0 = otherwise)
7 +
dh Local dummy for Holota (1=if the farmer is from Holota; 0 = otherwise)
8 ?
dw Local dummy for Woliso (1=if the farmer is from Woliso; 0 = otherwise)
9 ?
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CHAPTER IV: A BRIEF REVIEW OF ETHIOPIAN ECONOMY
4.1. Background
4.1.1. Geography
Ethiopia is located in the eastern-most part of the African landmass, also known as “the
Horn of Africa.” It lies between 3 and 15 degrees north latitude and 33 and 48 degrees
east longitude covering an area of 1.14 million square kilometers (944,000 square miles).
Following the independency of its former province, Eritrea in 1993, Ethiopia becomes a
landlocked country and shares borders with seven African countries: the Sudan and South
Sudan to the west; Eritrea to the north and north-east; Djibouti and Somaliland to the
east; Somalia and Kenya to the south.
Figure 4: Geographic Map of Federal Democratic Republic of Ethiopia (FDRE)
Its size and location have accorded it with diverse topography, geographic and climatic
zones and resources. The diversities may be shown by the existence of high and rugged
mountains, plateaus, deep gorges, river valleys and plains, contrasting landscape with
diverse soil types, and a range of agro-ecological zones (frost, highland, temperate,
lowland and desert).
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Nearly 40% of the Ethiopian land mass is categorized as highland and lies over
1,500meter above sea level. The Great East African Rift Valley divides the highland into
two - the western and northern highlands and the south-eastern highlands. The rift valley
gives birth to the co-existence of a several very high mountain ranges (the Semien
Mountains and the Bale Mountains) and the desert basin (the Danakil desert) in the
country. To be specific, Ethiopia is home not only to the fourth highest mountain in
Africa (Ras Dashen, with elevation of 4,620 meters above sea level) but also to one of
the lowest areas of land in the African continent (Kobar sink in the Dallol Depression, at
160meter below sea level) (Ministry of Water and Energy [MoWE], 2010). The
Ethiopian plateaus are source of big rivers like the Blue Nile, Wabe Shebele, Genale,
Awash, Tekeze, Omo, and Baro. In general, it has 8 River Basins, 1 Lakes Basin and 3
Dry basins (with no or insignificant flow out of the drainage system). Between the two
highlands, Ethiopian Rift Valley lakes (namely Abaya, Chamo, Zway, Shala, Koka,
Langano, Abijata, and Awasa) occupy the floor of the rift valley. But Lake Tana, lies in
the Ethiopian highlands north of the Rift Valley (not in the Rift Valley).
The wide range of altitude has given the country a variety of ecologically distinct areas
which in turn helped to encourage the evolution of endemic animals in ecological
isolation. The country is home to large number of endemic species, notably the Gelada
Baboon, the Walia Ibex and the Ethiopian wolf (or Semen fox). But these endemic
specious are at high risk of extension mainly due to human factors such as deforestation.
At the beginning of the twentieth century around 420,000 square kilometers or 35% of
Ethiopia's land was covered by trees but recent research indicates that forest cover is now
approximately 11.9% of the area. Studies show that Ethiopia loses an estimated 1,410
square kilometers of natural forests each year. Between 1990 and 2005 the country lost
approximately 21,000 square kilometers. To control deforestation, the current
government has launched and implementing massive reforestation programs and
providing alternate energy sources (MoWE, 2010).
With regard to climate, Ethiopia has generally a tropical monsoon climate. The country’s
elevation and geographic location produced three broad ecological and climatic zones:
the ‘Kolla' or hot lowlands, found below approximately 1000meter above sea level; the
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‘Weyna Dega' between 1000-1500 meter above sea level and the ‘Dega' or cool
temperate highlands between 1500 and 3000 meter above sea level. Mean annual
temperatures range from 10°-16°C in the Dega, 16°-29°C in the Weyna Dega and above
30 in the ‘Kolla'. In general, the highlands receive more rain than the lowlands with
annual rainfalls of 500mm to over 2000mm for the former and 300mm to 700mm in the
latter. But the Ethiopian climate is characterized by irregularity of rainfall that often
resulted in recurrent droughts and famines (IDP, 2012).
The land resource of Ethiopia is immense. Out of its total 1.13 million square kilometers
of area, approximately half of its landmass (55 million hectares) is arable land. According
to MoRAD (2010), however, only 16.6 million hectares of land is being cropped,
constituting just 30% of the arable potential. The remaining 70% of the potential is used
in other ways, particularly for grazing. The arable land potential encompasses both rain-
fed and irrigable lands that are agro-ecologically suited to the production of a variety of
crops, including cereals, pulses, oil crops, tree crops and vegetables. Discounting for
availability of water, an estimated 10 million hectares of land is considered suitable for
irrigation. The country is also endowed with minerals of high value such as gold,
tantalum, phosphorus, iron, salt, potash, soda ash, gemstones, coal, geothermal, natural
gas, and other industrial and construction minerals/ rocks. Currently, gold, marble,
limestone, and small amounts of tantalum are mined. Although Ethiopia has good
hydroelectric resources, which power most of its manufacturing sector, it has been totally
dependent on imports oil. In recent years, there have been positive developments in
harnessing hydropower potential through construction of mega dams that could increase
Ethiopia’s current electricity production capacity of 2,000 megawatts to 10,000
megawatts by 2014-2015, generating sufficient power for Ethiopia to sell excess supply
to its neighbors (Central Intelligence Agency [CIA], 2012).
4.1.2. Population
With more than 80 million inhabitants, Ethiopia is the most populous nation in Eastern
Africa and the second-most populous in Africa after Nigeria (CSA, 2011a). Slightly
lower than half (49.7%) of the population is female, a significant number of whom (24%)
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are in the reproductive age (15-49 years).The structure of the population shows that the
economically active population accounts for 49.6% of the total population. Furthermore,
about 43% of the population is under the age of 15 years; 54% between the ages of 15;
and 65 years and only 3% aged over 65. The main characteristic of the Ethiopian
population is, therefore, its youthfulness: the average age of the population is 17 years;
children (0-14 years) and youths (15-24 years) together accounts for almost 64% of the
total (IDP, 2012).
The economically active population is 49.6% of the total population. The population
projection shows that with an annual population growth of more than 2%, Ethiopia will
have more than 120 million people by 2030 (FDRE, 2011). Both total fertility rate and
average household size of the country are high (5.3 and 4.8, respectively). The level of
fertility is significantly lower in urban (3.3) compared to rural (6.4) areas of the
country. Fertility is highest in the Oromiya region (6.4 births per woman) and lowest in
Addis Ababa (1.9 births per woman). The overall dependency ratio for the country is
estimated as 85.9 dependents per 100 people in the working age group 15-64 (IDP, 2012)
Ethiopia's population is highly diverse. There are over 80 ethnic groups characterized by
diverse cultural, linguistic and religious makeup. The Oromo, Amhara, and Tigreans
make up more than three-quarters of the population. The 2007 census report showed the
dominance of Christianity and Islam: about 62.5% of the population is Christians and
one-third (33.9%) is Muslims (CSA, 2008). The remaining 3.6% of the population are
followers of traditional but indigenous African religions such as Wakefana and others.
Christians mainly live in the highlands, while Muslims and adherents of indigenous
African religions tend to inhabit lowland regions. Most of its people speak a Cushitic or
Semitic languages. Amharic is the official language and the most widely spoken local
language followed by Oromifa Tigrinya (ibid, 2008). English is the most widely spoken
foreign language and is taught in all secondary schools.
Regional distribution of Ethiopian population is uneven as nearly 81% of Ethiopia’s
population lives in the three regional States: Oromiya, Amhara, and the Southern
Nations Nationalities and Peoples (SNNP) representing 35, 26, and 20% of the national
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population, respectively. The average population density is 75 per square kilometer, but
there is great variation among regions. Excluding the Harari Region (a city-state) and the
Addis Ababa and Dire Dawa Administrative Councils (both of which are city
administrations), the SNNP has the highest population density (111 people per square
kilometer) followed by Amhara (102 people per square kilometer). Afar Region has the
lowest population density of any region (7 people per square kilometer). Gambella and
Benshangul-Gumuz are also categorized under sparsely populated regions with
population density of less than 11 people per square kilometer. About 23% of the
population is concentrated on 9% of the land area putting pressure on cultivable land and
contributing to environmental degradation. On the other hand, roughly 50%of the land
area represents sparsely populated areas with nomadic or semi-nomadic pastoral people
living in arid plains or in a semi-desert environment. Ethiopia is one of the least
urbanized countries in the world with only 17% of its population live in urban centers.
But a quarter of the urban population resides in the capital, Addis Ababa. As of 2011, the
population of Addis Ababa is estimated at 3.2 million (CSA, 2011a).
4.1.3. Politics and government
Ethiopia is a Federal Democratic Republic, ethnicity being the base of the federation
units. For the last 23 years, the country is ruled by a single party, the Ethiopian People’s
Revolutionary Democratic Front (EPRDF). EPRDF is a coalition of four ethnically-based
resistance groups and formed in 1989. It was spearheaded by the Tigray People’s
Liberation Front (TPLF) and came to power in 1991 following its successful prosecution
of over a decade and a-half of armed struggle against the military regime Derg. EPRDF
crafted and put in effect a new constitution in 1994. The constitution gives every regional
state the right to self determination including the right to secede from Ethiopia. Under the
current (or the 1994) constitution, the executive branch includes a president, Council of
State, and Council of Ministers and executive power resides with the prime minister. The
president is head of state and is elected by the House of People's Representatives for a
six-year term. The prime minister serves as the head of government and is nominated by
thewining party following legislative elections.
87
The federal state has a bicameral parliament (i.e. it has two Houses) and national
legislative elections were last held in 2005. The 108 members of the House of
Federation are chosen by their respective state assemblies to serve five-year terms. The
547 members of the House of People's Representatives are elected by popular vote from
the regions, zones, woredas and kebeles also to serve five-year terms. The judicial
branch comprises federal and regional courts. Suffrage is universal at age 18.
The EPRDF-led government has promoted a policy of ethnic federalism, devolving
significant powers to regional (ethnic based) authorities. The current constitution
Ethiopia gave recognition to nine ethnically-based, semi-autonomous administrative
states (namely Tigray, Afar, Amhara, Oromiya, Somali, Benishangul Gumuz, SNNP,
Gambela and Harari) and two chartered city Administrations (namely Addis Ababa and
Dire Dawa).
Figure 5: Map of Ethiopian Regional States and Chartered Cities
88
The constitution provided power to regional states to raise their own revenues as well as
to establish their own government and democracy according to the federal government's
constitution. The highest governing body of each national regional state is the Regional
Council whose members are directly elected to represent the districts and headed by a
president nominated by the party holding the majority of seats. The regional council has
both legislative and executive power to direct internal affairs of the regions except for
foreign affairs and defense.
Addis Ababa (also called Finfinne), one of the two chartered cities in the Federation, is
the largest city in the country with a population of 2.74 million during the 2007 census
(CSA, 2008)5. The city lies on the central plateau at an altitude of 2300-2400 meter
above sea level with an average temperature of around 160C. Currently, Addis Ababa is
the capital of the Oromia Regional State, seat of the Federal Government (the House of
Representatives and the House of Federation), and the country’s center of commerce and
industry. It is also seat to the African Union (AU) and to the United Nations Economic
Commission for Africa (ECA). Several other international organizations have their head
quarters and offices in Addis Ababa.
4.2. The Economy
4.2.1. Background
The Ethiopian economy is dominated by weak, traditional, and subsistence agricultural
sector since time immemorial. Prior to 1991, economic policy was characterized by
extensive government controls, macro-economic imbalances and restriction on private
sector initiative, all of which resulted in low economic activity and persistent declines in
economic growth (IDP, 2012). The EPDF government, therefore, inherited a weak
command economy characterized by fiscal and current account deficits amounting to
8.7% and 6.9% of Gross Domestic Product (GDP) respectively, in addition to an external
debt burden equivalent to 33% of GDP (MoRAD, 2010). It therefore embarked on far-
reaching reforms to achieve broad-based economic growth. The government introduced
5 The population of Addis Ababa is estimated at 3.2 million in 2011
89
free market economy mainly to stabilise and liberalise the economy. It promoted private
sector participation and redirected government interventions to social and infrastructure
development. In particular, health and education service delivery, and investment in roads
and water resources development were given prominence.
As a result, price controls and subsidies were removed and the exchange rate was
devalued by 250%. The financial services sector was also opened up to competition from
the private sector. Judicial and civil service reforms were made to remove impediments to
pro-poor strategies, policies and investment programmes. Equally, regulations were put
into place to encourage both domestic and foreign investment, particularly in agriculture
and agro-processing. These reforms were underpinned by increased pro-poor public
spending in agriculture, education, health, water, roads, rural electrification, and
telecommunications (MoRAD, 2010). The reform programme has resulted in improved
economic performance. Macro-economic stability was attained and persistent declines in
GDP reversed. Real GDP grew by an average of 5.8% per annum in the period covering
1992/93-2010/11.
Yet, Ethiopia remains one of Africa's poorest states with an estimated real per capita
GDP of USD 392 in 2010/11(National Bank of Ethiopia [NBE], 2011). According to
UNDP Human Development Report of 2013 (UNDP, 2013), Ethiopia's HDI is 0.396,
which gives the country a rank of 173 out of 187 countries with comparable data. The
report also showed that life expectancy at birth is only 59.7 years. Infant and maternal
mortality and child malnutrition rates are among the highest in the world. Under-five
mortality (per 1,000 live births) and Maternal mortality ratio (deaths of women per
100,000 live births) are estimated to be 106 an 350, respectively (ibid, 2013). Roughly
30% of the population live below the national poverty line (1075 Birr/adult in 1995/96
prices). While access to education has increased in recent years, the overall adult literacy
rate (39%) is low even by Sub-Saharan African standards. Only about 58% of the
populations have access to clean drinking water and about 80% have no access to
improved sanitation. About 38% of children under the age of five are underweight and
over 12 million people currently suffer from chronically or transitory or acute food
90
insecurity. HIV/AIDS constitutes a major threat to sustained economic growth, with
about six% of adults estimated to be HIV-positive (MoRAD, 2010).
GDP growth rate shows a significant improvement in the last decade. According to
Ethiopian Government figures, the GDP growth rate for the past 10 years (2001/02-
2010/11) has averaged 9% per annum, and grows in double digit since 2003/04,
though the International Monetary Fund (IMF) and the World Bank have some
reservation on the actual figure.6 These rates also exceed the economic growth rate of
7% required to achieve the Millenium Development Goals (MDGs) and places
Ethiopia among the top performing economies in sub-Saharan Africa. From Table 7, it
is evident that the GDP growth rate shows a grat fluctuation over the decade, swinging
between (-) 2.1 to 12.6 (NBE, 2011)
Table 7: Annual Growth Rate of Real GDP
Year 2001
/02
2002
/03
2003
/04
2004
/05
2005
/06
2006
/07
2007
/08
2008
/09
2009
/10
2010
/11
Growth (%) 1.6 -2.1 11.7 12.6 11.5 11.8 11.2 10 10.4 11.4
Source: NBE, 2011
There is no doubt that the high growth rate registered by the Ethiopian economy (at least
numerically) is the result of good performance in all the major sectors. Table 8 displays
the growth rate of major sectors.
6 The World Bank and the International Monetary Fund have estimated it to be in the range of 7%-8%.
91
Table 8: Absolute Growth Rate of the Major Sectors
Sec
tor
2003
/04
2004
/05
2005
/06
2006
/07
2007
/08
2008
/09
2009
/10
2010
/11
Agriculture & Allied 16.9 13.5 10.9 9.4 7.5 6.4 7.6 9
Industry 11.6 9.4 10.2 9.5 10 9.9 10.6 15
Service 6.3 12.8 13.3 15.3 16 14 13 12.5
Sources: Kasahun, 2012; NBE, 2011
The government of Ethiopia claimed that the growth in agricultural outputs was largely
attributed to improved productivity aided by favorable weather condition and conducive
economic policy (NBE, 2011). But independent observers argued that the increase in
agriculture production has been driven by an expansion in the area of land cultivated,
rather than major improvements in productivity (Mwanakatwe & Barrow, 2010).
According to NBE (2011), the 15% annual growth in industry was largely due to
expansion in electricity and water subsectors whereas the 12.5% growth in services sector
was attributed to growth in financial sector, real estate, and hotel & tourism sectors.
92
4.2.2. Sectoral contributions to GDP
Agriculture is the backbone of the Ethiopian economy7. It contributes more than 40%
to GDP and more than 84% to export trade and foreign exchange earnings. Moreover,
the sector accounts for 85% of employment, and supplies 70% of the raw material
requirements of local industries. The national economy, therefore, is highly correlated
with the performance of the agricultural sector. More often than not, the share of
agriculture in GDP is well above the other two sectors. But in recent years, the service
sector seems to take the lead as its contribution to GDP is increasing at amazing rate
while the share of agriculture is contineously declining. Table 9 portrays the
contribution of the three major sectors to GDP.
Table 9: Percentage Share of Major Sectors in GDP
Year
2001
/02
2002
/03
2003
/04
2004
/05
2005
/06
2006
/07
2007
/08
2008
/09
2009
/10
2010
/11
Agriculture & Allies 49.1 44.9 47 47.4 47.1 46.1 44.6 43.2 42 40.6
Industry 12.9 14 14 13.6 13.4 13.2 13 13 13 13.3
Service 38.6 41.7 39.7 39.7 40.4 41.7 43.5 45.1 46.1 46.1
Source: NBE, 2011
As can be observed from the data in Table 9, the contribution of agriculture declined
from 47.4% in 2004/05 to 40.6% in 2010/11 while the share of the industry increased
from 13.3% in 2009/10 to 13.4% in 2010/11. During the same fiscal year, the share of
services sector increased from 39.7% in 2004/05 to 46.1% in 2010/11. Likewise,
agriculture adds much to the growth rate of GDP. Statistical figures show that the high
growth rate of GDP observed in the last decade is in fact comes from the growth in
agriculture and service sectors. Together these two sectors contribute to more than 85%
of the growth in GDP.
7 Strictly speaking, the economy is primarily based on smallholder farms that produce the bulk (over 90% ) of outputs for consumption and the market (Kasahun, 2012).
93
Source: NBE, 2011
Figure 6: Decomposition of GDP Growth Rate by its Sources
But the contribution of agricultural growth to GDP growth rate is changing its patern over
the period and countercyclical with the contribution of service sector. Table 10 shows the
contribution of the three major sectors to the growth rate of GDP. In 2004/05, agriculture
(and its allies) contributes 50.8% of the GDP growth but it gets lower and lower and
reaches minimum of 27.6% in 2008/09. In the subsequent years its contribution has
increased to 30.8% (in 2009/10) and 41.1% (in 2010/11). The contribution of service
sector growth to GDP growth follows exectly the opppsete pattern. Initially increases but
declines in the last two years of the study. This shows that the agricultural sector is on the
verge of transferring its historical tenure of leadership to the service sector.
0
2
4
6
8
10
12
14
2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11
real
gro
wth
rat
e (%
)
Service
Industry
Agriculture
94
Table 10: Contribution of Major Sectors to Growth Rate of GDP
Year
2004
/05
2005
/06
2006
/07
2007
/08
2008
/09
2009
/10
2010
/11
Agriculture Real value 6.4 5.1 4.4 3.3 2.7 3.2 4.69
% 50.8 44.5 36.9 29.9 27.6 30.8 41.1
Industry Real value 1.3 1.4 1.3 1.3 1.3 1.4 1.53
% 10.1 11.8 10.7 11.7 12.9 13.3 13.4
Service Real value 5.1 5.4 6.4 7 6.3 6 5.29
% 40.1 46.6 54.2 62.5 63.4 57.6 45.6
Source: NBE, 2011
4.2.3. The import-export sector
Ethiopians merchandise trade is improving over time though it is concluded with deficits
every year (i.e., Ethiopia always earn less from its exports than it pays for imports). But
there are improvements in foreign trade too. In 2010/11, for instance, total export of
goods to GDP ratio improved to 10% from 6.7% in 2009/10 (NBE, 2011). As a result,
merchandise trade deficit narrowed by 12.1% vis-a-vis the preceding fiscal year, largely
due to the significant growth in total exports and a small reduction in total imports. The
dominance of agriculture is clearly seen in the foreign market sector of the economy. The
major agricultural export crop is coffee, pulses, oilseeds, and "Chat," a leafy narcotic that
is chewed (Central Intelligence Agency [CIA], 2012). Coffee alone provides
approximately 30.6% of Ethiopia's foreign exchange earnings in 2010-2011, down from
65% a decade ago because of the increase in other exports. Gold was Ethiopia's second-
largest export in 2010-2011, earning 17% of export proceeds. Other traditional major
agricultural exports are finished leather goods,
For a long period of time, the country depends on few vulnerable crops for its foreign
exchange earnings on one hand and reliant on imported oil and capital goods on the other
hand. As a result, the country suffers from severe foreign exchange shortages more often
95
than not. Cognizant of this fact, the current government gives due attention to the
promotion of investment and export in other sectors or subsectors. Today, a slight
diversification is observed in the export sector to include horticultural and floricultural
products. Cut flowers exports have become major export items in recent years and able to
generate a lot of foreign currency to the country. For instance, foreign exchange earnings
from the export of cut flower have improved more than tenfold in less than a decade
(from less than 15 million Birr in 2004 to 175.3 million Birr in 2010/11) (NBE, 2011).
Sources: NBE, 2010/11 Annual report
Figure 7: Export Share of Selected Commodities in 2010/11
Europe and Asia are the largest trade partners of Ethiopia. Europe is the largest
destination for Ethiopia’s exports. In 2010/11, according to NBE (2011), Europe
absorbed about 50% of the total merchandise exports of Ethiopia was shipped to Europe,
followed by Asia that absorbed 26.5% of Ethiopian exports. Figure 8 shows the import
origin and export destination of the Ethiopian foreign market goods.
96
Source: own computation based on NBE data
Figure 8: Import and Export Destination for the Year 2010/11
From Figure 8 it is evident that most of the import items come from Asia followed by
Europe. In 2010/11, for instance, about 67% of its imports were originated from Asia,
21.3% from Europe, 5.5% from America and 6% from Africa. Among Asian countries,
China accounted for 23.3%, Saudi Arabia 13.4%, India 10.8% and Japan 8.1%. The main
items imported from China included chemicals, clothing, glass and glass wares,
machinery, medical and pharmaceutical products, road and motor vehicles, metals,
electric materials and rubber products. Imports from India were mainly electrical
materials, machinery, metals, medical and pharmaceutical products and rubber products
(NBE, 2011).
4.2.4. Agriculture and the Ethiopian economy
Ethiopian agriculture is dominated by smallholder farmers whose land holding is less
than two hectares. According to MoARD (2010), there are about 11.7 million smallholder
households that accounts for approximately 95% of agricultural GDP and 85% of
employment. Furthermore, Ethiopian agriculture is characterized by subsistence, low
0
10
20
30
40
50
60
70
America Europe Asia Oceania Africa
5.5
21.3
67
0.35.95.1
49.9
26.5
0.5
18
Imort origin Export destination
97
input-low output, and rain fed farming system. The use of chemical fertilizer and
improved seeds is quite limited despite Government efforts to encourage the adoption of
such inputs. Low agricultural productivity can be attributed to farmers’ limited access to
agricultural inputs, financial services, improved production technologies, irrigation and
agricultural markets. Lack of poor land management practices of smallholder farmer not
only contributed to low agricultural productivity but also led to severe land degradation.
The country has one of the highest rates of soil nutrient depletion in SSA. Estimates
suggest that the annual phosphorus and nitrogen loss nationwide from the use of dung for
fuel instead of using it for fertilizer is equivalent to the total amount of commercial
fertilizer applied. Land degradation is further exacerbated by overgrazing, deforestation,
population pressure and inadequate of land use planning (ibid, 2010).
Despite such challenges the agricultural sector has performed strongly over most of the
last decade. Since the beginning of the decade, the average growth rate of the
agricultural GDP has been about 10% per annum, which easily surpass the
Comprehensive Africa Agriculture Development Programme (CAADP) target of 6%.
Throughout the decade, the growth rate registered by the sectors was uneven. Rather it
swings between negative and positive values. It hits the negative rates in two consecutive
years 2001/02 and 2002/03, and shows a double digit growth in the next three years
(2003/04 to 2005/06). In all other years of the decade, although its growth is positive the
rate is fluctuating. The GDP growth rate is also fluctuating from year to year following
the changes in agricultural growth rates. This shows that agriculture has been the major
source of the erratic performance of the Ethiopian economy. The Figure 9 shows that
direct link between agriculture and GDP growth trends in Ethiopia.
98
Sources: Kassahun, 2012; NBE, 2011
Figure 9: Annual Growth Rate of Real GDP and Agricultural GDP (1981 – 1999)
The agricultural sector is composed of four main sub-sectors: staple crops, livestock,
traditional exportables (coffee), and non-traditional exportables (fruits, cotton,
horticultural products, and others). The staple crops subsector contributes to 65% of value
added, followed by the livestock subsector. Combined, these two subsectors account for
91% of agricultural value added whereas each of the other two subsectors account for less
than 5% (Otte et al., 2012). Within the staple crops, cereals are the dominant. According
to the Central Statistics Agency’s 2005/06 agricultural sample survey (CSA, 2008),
during the main rainy season of 2005/06, cereals covered 58% of the land area and
accounts for 87% of the volume of grain production. Furthermore, cereal production
accounts for roughly 60% of rural employment (Schneider and Anderson, 2010) and
about 65% of agricultural GDP (Rashid, 2010).The major cereal crops include: teff
(Eragrostis tef), barley (Hordeum vulgare), wheat (Triticum durum), maize (Zea mays),
sorghum (Sorghum bicolour) and finger millet (Eleusine coracana).
0
5
10
15
20
2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11
Agricultural GDP Overall GDP
99
Table 11: Area Cultivated and Yield of Cereals for Selected Years
2008/09 2009/10 2010/11
Total Land Area (Hectare) 9,951,813.70 10,457,783.00 10,807,452.82
% under Private Farmers 98.14 97.98 98.32
Total Production (Hectare) 156,067,839.84 173,208,362.00 191,807,075.05
% under Private Farmers 97.33 96.46 96.81
Source: CSA, 2011b
It can be seen from Table 11 that the total land covered by cereals increased from below
10 million hectares in 2008/09 to 10.8 million hectares in 2010/11. This shows that in
three years time the cereal land was expanded by 8.6%. But much of the expansion was
made in Benishangul Gumuz Regin because in this region, cereal crop area has increased
by 31.1% mainly due to boost up of commercial agriculture in the region. In the
production side, during the same period, total cereal production increased from 156
million to nearly 192 million quintals showing an increment of only 22.9% in three years.
It appears from the data in Table 11 that private farms (smallholders) dominate the
production of cereals. During the period covered in the survey, private farmers hold about
98% of the land under cereal production and produces about 97% of all cereal
production. It is clearly seen from the table that during the period under consideration,
the private holders have expanded their cereal land by 8.8% and their yield by 22.9%,
slightly higher than the percentage increment of total cereal production. From the
preceding discussions, it is evident that although the percentage change of production is
more than that of land brought under cultivation, the change is not sufficient. This may be
because of the expansion brought only more marginal lands to cultivation which in turn
may even lead to severe land degradation (CSA, 2011b).
Major cash crops
The cash crops that have major importance in Ethiopian economy are coffee, chat and
sugarcane. In 2001/02, about 1.5 million, 0.5 million, and 2.1 million farmers cultivated
coffee, chat and sugarcane, respectively. The average holding was 0.062 hectares per
holder for chat, 0.021 hectare for sugarcane, and 0.12 hectare for coffee (Table 12).
100
Table 12: Production of Major Cash Crops in 2001/2002
Crops No. of holders
Total area (ha)
Area per holder (ha)
Total production (qt)
Production (qt/ha)
Productivity (qt/ha)
Chat 1545861 96066 0.062 796520 0.52 8.29
Sugar 563310 11775 0.021 783803 1.39 66.57
Coffee 2120924 246033 0.12 1629110 0.80 6.63
Note: qt=quintal; ha=hectare
Source: Ethiopian Economic Association [EEA], 2005
From Table 12 it is evident that in the year 2001/02, over 78 thousand tons of sugarcane
was produced. Yield per hectare is higher for sugarcane the average being 67 quintals. In
the same year, close to 163 thousand tons of coffee was produced with average yield of
6.6 quintals per hectare. About 60% of the harvested coffee was sold while close to 4%
was used for other purposes including payment for labor. The remaining 36% is reported
to have been consumed at home. Since coffee is the major cash crop in Ethiopia, home
consumption of over a third of the production is very high.
Livestock Production
Ethiopia has the second largest livestock population in Africa (next to Sudan), and the
10th in the world. The livestock resources include but not limited to cattle, sheep, goats,
horse, donkeys, mules, camels, poultry and beehives. The sector has been contributing
considerable portion to the economy of the country. Livestock production accounts for
about 32% of agricultural GDP and draught animal power is critical for all farming
systems (MoRAD, 2010). But its contribution to rural household’s food security sounds
more than its national figure.
Surveys conducted at different times show that large majority of the livestock is kept by
individual (peasant) households living in the rural area. Rural households typically
maintain a mix of livestock species depending on the products and services they need
from their livestock (EEA, 2005). According to the recent agricultural sample surveys
(CSA, 2011b), in the year 2010/1ral households privately owned a total of 53.4 million
101
heads of cattle, 25.5 million sheep, and 22.8 million goats. This number do not include
livestock kept in urban areas by private individuals and medium and large scale dairy
farms, fattening, etc. owned by investors, cooperatives and other institutions. The survey
data also showed the existence of abundant camels and equine animals. As shown in
Table 13, in the year 2010/11, rural residents own more than 1.1 million camels and 8.6
million equine animals such as donkey (72%), horses (24%), and mules (4%). In terms
of its regional distribution, the predominantly pastoral regions of Afar and Somali often
have the highest densities per capita (EEA, 2005).
Table 13: Estimated Number of Livestock in Selected Years
Livestock 2008/09 2009/10 2010/11
cattle 49,297,898 50,884,005 53,382,194
sheep 25,017,218 25,979,919 25,509,004
goats 21,884,222 21,960,706 22,786,946
horses 1,787,211 1,995,306 2,028,233
donkey 5,421,895 5,715,129 6,209,665
mules 373,519 365,584 385,374
camel 759,696 807,581 1,102,119
Sources: CSA, 2011b
Beside the use of animal power for agricultural activities, the rural household keeps cattle
mainly to produce fresh milk necessary for home consumption. The CSA (2011b) survey
data showed that between 2008/09 and 2010/11, more than 9.7 billion liters of cow milk
was produced by the private holders of rural families (of which 42% was produced in the
last year of the survey period). This implies that for the year 2009 to 2011 the average
milk production was about 337,262 liters per cattle or 243 liters per year. In the same
period, more than half billion liters of cow milk, 260 million eggs, and 123.4 million
kilograms of honey was produced by private holders of rural families.
102
Table 14: Livestock Products Produced by Private Holders of Rural Families (in
millions)
Year Cow Milk (in lt) Camel Milk (in lt) Egg (in No.) Honey (in kg) 2008/09 2,714.80 162.13 79.09 42.18 2009/10 2,940.22 150.32 82.23 39.66 2010/11 4,058.00 262.82 98.30 41.52 2008-2011 9,713.01 575.27 259.62 123.37
Note: lt = liter; No.= number; kg = kilogram
Source: CSA, 2011b
The preceding sections confirm the long held view that despite the sizeable animal
population for which the country is famed, the livestock sub-sector is marked by low
productivity and low production (Kassahun, 2012). Evidences show that livestock
products supply is often failed to match increasing demands for livestock products.
Furthermore, the countries average per capita production of livestock product is lower
than neighboring countries’, the African, and the world’s average (EEA, 2005).
Agriculture and the external trade
It has been said time and again that the Ethiopian economy heavily depends on the
agricultural sector as it is in many other developing countries. Agricultural export
accounted for more than 80% of foreign currency earned through its export trade. Most of
the export products are raw products, while few are semi-processed agricultural products.
The major unprocessed agricultural export commodities include coffee, oilseeds, pulses,
fruits and vegetables, Chat, and live animals whereas leather and leather products, meat,
and sugar constitute the major semi-processed export commodities. The share of
processed agricultural products in export earnings is less than 3%, and shows how poor
the performance of the country‘s export sector is in terms of processing and adding value
to its primary commodities. With the exception of flower which has joined the list of
export commodities in the last five years, the structure of Ethiopia‘s export trade had
remained unchanged for decades (EEA, 2005).
103
By and large, despite such big socio-economic importance, due to many natural and man-
made factors, the performance of the Ethiopian agriculture is very low by any standard.
The low performance of the sector is reflected, among many other indicators, in the low
level of land and labour productivity.
The current performance of agriculture may look encouraging. But the long term
indicators of the Ethiopian agriculture performance are not encouraging too. Birhanu,
(cited in EEA, 2005) argued that the per capita income of the population that is dependent
on agriculture is declining from time to time. He showed that the per capita income in
agriculture over the last four decades (1953 – 1995) declined by over 45% compared to
its level in the early 1950s. No doubt that in order for agricultural income rise faster than
population growth, land and labour productivity growth in agriculture is necessary. But
Ethiopian agricultural labor productivity is estimated to be less than one-fifth of the
average for Sub-Saharan Africa. Furthermore, the contribution of agriculture to
government direct revenue is very low. In the past decade, the share of agriculture in
government direct revenue is less than 5%, which is too little and shows how Ethiopian
agriculture is weak in terms of surplus generation (EEA, 2005). Indirect surplus
extraction from agriculture in terms of the supply of cheap food is also low. The sector is
dominated by subsistence farmers who produce largely for their own consumption, and
contribute very little for the market and development of the economy. A high level of
food-self sufficiency gap at the national level and food insecurity at the household level
has been the challenge the country has been facing for decades. That is why many
researchers argued that it is time to transforming the Ethiopian agriculture before the
worst comes to the economy.
4.2.5. The vegetables sub-sector
The agro-climatic conditions in most part of Ethiopian regions make it suitable for the
production of tropical and subtropical vegetables and fruits throughout the year. The soil
types are so diverse to grow diversity of vegetables. The most commonly grown
vegetables include potatoes, cabbages, cauliflower, okra, egg plant, tomato, celery,
cucumbers, pepper, onion, asparagus, water melon, sweet melon, carrots, and green beans
104
(Fekadu & Dandena, 2006). But reliable database on the actual production of each
vegetable is hardly available. The available ones are often discontinuous/incomplete and
even some times contradicting. The sparsely available data shows that the land allotted
for vegetable production is fluctuating over time: it increases in some period and
decreases in others. For instance, between 1993 and 2004, vegetable production shows
average growth of 3.4% per annum over the period since 1993 (WB, 2004).
Table 15: Annual Vegetable Production of Ethiopia, 1993-2003
Year Area harvested (ha) Yield (kg/ha) Total Production (mt)
1993 172800 36921 638000
1994 175600 38383 674000
1995 178200 38412 684500
1996 180100 38740 697700
1997 181600 38849 705500
1998 184000 39158 720500
1999 185500 40189 745500
2000 185200 40578 751500
2001 187300 42686 799500
2002 190591 45159 860688
2003 190591 45159 860690
Note: ha=hectare; kg=kilogram; mt=metric ton
Source: WB, cited in Wiersinga and Jager, 2007
According to EEA report (2005), in 2001/02, the land covered by different vegetables
was estimated to be 98.2 thousands of hectares. In the same year, the report shows, on
average 3.05 million farmers cultivate vegetables and about 0.032 hectare of land was
cultivated by an average holder. However, the area under vegetables has been expanded
in the subsequent years and reached 131,962 hectares in the year 2005 mainly due to the
steady increase in the demand for vegetable crops, both for local and export markets
(Fekadu & Dandena, 2006). Wiersinga and Jager (2009) reported that as of 2009, the area
covered by vegetables was 260,880 hectares (nearly 99.7% of it was under small-scale
105
farmers) and the total yield collected was 2.5 million tons (out of which 85% are
produced by small-scale farmers). This shows that most of vegetables are produced by
individual growers (or smallholder peasant farms).
The recent CSA (2011b) Agricultural Sample Survey had narrowed the data gap in the
sector. The data released by the agency (Table 16) sows that in the year 2008/09, about
165700 hectares of land were covered by vegetables. In the subsequent years, however,
the land under vegetables was reduced to 142700 hectares in 2009/10 and to 134000
hectares in 2010/11; i.e., between 2008/09 and 2010/11, the vegetable land was reduced
by 19.12%. In the production side, however, total vegetable production increased from
6.32 million in 2008/09 to nearly 8.2 million quintals in 2010/11, showing an increment
of 29.12% in three years time.
Table 16: Cultivated Area and Yield of Vegetables
2008/09 2009/10 2010/11
Total Land Area (Hectare) 165,661.00 142,726.10 133,984.80
Under Private Farmers (%) 97.87 96.96 94.54
Total Production (Hectare) 6,317,703.50 6,348,489.30 8,159,290.00
Under Private Farmers (%) 94.79 87.79 82.80
Source: CSA, 2011b
It can be observed from table 16 that vegetable sector is dominated by small holder
farmers in the same way as the agricultural sector in general. Private farmers hold more
than 96% of the vegetable land and produce nearly 90% of all vegetable yields recorded
during 2008/09-2010/11 calendar year. The data shows that during these periods while
the land under private holders shrunk by 21.87%, the vegetable production of this group
rose by12.82%. Generally, it seems clear now that over the last three years period,
tremendous increase in production of vegetables is witnessed throughout the country.
However, this data does not support the widely held view that the vegetable production
gains have largely come about with increased area rather than yield increases (WB,
2004).
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Contribution of vegetables to Ethiopia economy
Vegetables have many important functions in everyday life of Ethiopian people. They are
valuable sources of vitamins, minerals and proteins especially to a country like Ethiopia
where the people experience malnutrition due to heavy dependence on cereals (Fekadu &
Dandena, 2006). Vegetable crops are also important for food security in times of drought,
famine and food shortage. They provide a source of income for the farmers/producers,
create employment opportunity and contribution to the national economy as export
commodities.
Several studies show that most of the vegetables produced in the country are consumed
domestically especially by the producer itself. For instance, out of four million quintals of
vegetables produced in 2001/02, about 38% of it was consumed by the producers
themselves (EEA, 2005). The vegetables produced for domestic consumption are mainly
cabbages, tomatoes, onions, and garlic, while green beans and peas have recently
emerged for export purposes (WB, 2004). Compared to other African countries,
Ethiopians consumed greater proportion of their vegetable products. But they consume
fewer amounts (in both quantity and value) of vegetable products. Also revealed is that
compared to other African countries vegetable products accounts for the lowest share of
Ethiopian households total budget as well as food budget.
Table 17: Vegetable Consumption Pattern of Selected African Countries
Yardsticks
Eth
iopi
a
Bur
undi
Mal
awi
Tan
zani
a
Rw
anda
Ken
ya
Uga
nda
Gha
na
% consuming 93 72 93 98 91 90 88 90
Quantity (kg/pers./yr 25.4 20.8 45.8 38.6 47.5 88.2 53.8 51
Value (USD/pers./yr) 3.3 9.5 19.9 10.3 10.7 21.3 9.3 29.1
Price (USD/kg) 0.13 0.46 0.43 0.27 0.23 0.25 0.17 0.57
% of food budget 4.1 4.1 12.2 9.4 11.6 7.9 8.1 9.2
% of total budget 2.5 2.9 8.6 6.7 9.3 5.6 4.6 5.7
Note: kg=kilogram; pers=person; yr=year
Source: Workafes, cited in Wiersinga and Jager, 2007
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Vegetables are not only important for domestic consumption as a source of key nutrients,
but they also generate some foreign exchange earnings. The major vegetable export
products are potatoes, green beans, okra, melons, white and red onions, shallots,
cabbages, leeks, beetroots, carrots, green chillis, tomatoes and lettuce. Between 1994 and
2004, the quantity of fresh vegetable exports represents some 1% of annual total
vegetable production over this period (WB, 2004). Studies show the growing trend of the
export volume of fruits and vegetables. According to Getachew (2010), the export
volume of fruits and vegetables have been increasing by 7.5% since the beginning of the
new millennium while it was negative (5.8) in the 1980’s. The earnings from the export
of fruits and vegetables are also increasing over the period. In the beginning of the
millennium, the export earnings from the subsector were only 80 million Birr. But the
number increased to 142.21 million in 2005/06 and reached 512.64 million at the end of
the decade (Table 18 below).
Table 18: Value of Vegetable and Fruits Exports (in million Birr)
Year Total Export earning
Fruits & Veg. export earnings
Share of Fruit & Veg. in total export earnings (%)
2001/02 3864.32 80.11 2.07 2002/03 4142.36 82.12 1.98 2003/04 5176.64 109.66 2.12 2004/05 7331.26 139.05 1.9 2005/06 8685.38 114.54 1.32 2006/07 10457.62 142.21 1.36 2007/08 13649.34 118.4 0.87 2008/09 15217.75 124.03 0.82 2009/10 26115.31 412.61 1.58 2010/11 44525.57 512.64 1.15
Source: NBE, 2010/11
In terms of the product composition of exports, in 2001, onions were one quarter of total
export quantities, followed by tomatoes (19%), green peas (18%), and green beans
(15%). In value terms, however, green beans contributed 23%, followed by green peas
(21%), onions (20%) and tomatoes (19%) (WB, 2004). Exports are in a dynamic state
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with varying patterns from year to year. Exports of vegetable products from Ethiopia
have increased from 25,300 tons in 2002/03 to 63,140 tons in 2009/10 (Joosten, Boselie
& Lemma, 2011).
The export of horticultural produces in general and vegetable products in particular of the
country has increased tremendously over years. For instance, in the year 2005, about
32,000 tons of vegetables that worth about USD 12 million was exported mainly to
Djibouti and other countries. This exceeds 2004 export revenue by about USD 8 million
(Fekadu & Dandena (2006). This day, vegetable production is fast growing export
businesses next to flowers. Important export markets for vegetables are the surrounding
countries (Djibouti, Somalia, and Sudan); the main products being non-graded fresh
vegetables. Higher value fresh produce (including graded and pre-packed vegetables and
fresh herbs) are exported to the United Kingdom, United Arab Emirates and the
Netherlands (Joosten et al., 2011).
4.3. The Urban and Peri-Urban Agriculture
As urban populations grow, poverty, food insecurity, and malnutrition increases (WFP,
2002). These nexus between urbanization and poverty is clearly observed in developing
countries like Ethiopia. In the capital Addis Ababa, for instance, 35% of the population is
estimated to be below poverty line (Schmidt and Kedir, cited in Dereje, 2011). Thus, PU
agriculture emerges in response to the growing demands for food, income, employment
and raw material following urbanization. PU agriculture do play important socio-
economic role in generating means of employment and subsistence for producers, as well
as supplying food and raw materials for the urban consumers.
In Ethiopia PU agriculture is the oldest and traditional practice. The urban-based
population is used to keep cattle, sheep, and chickens, or grow rain fed crops such as
maize and vegetables, on the plots adjacent to their houses (Fekadu, 2011). PU
agriculture production is mainly for household consumption, with a small proportion for
sale. Although its overall contribution to the urban economy might not be clearly known
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due to poor data recording and ignorance to the sub-sector, it is clearly observed that
UPU agriculture makes a considerable contribution toward satisfying the basic needs of
the urban population. The sparsely available surveys and studies show that the lives of
large number of households living in urban areas (including the capital, Addis Ababa) are
associated with farming. For instance, in 1994, Gittleman (cited in Fekadu, 2011) found
that nearly half of the sampled urban farmers had an estimated monthly income greater
than 70% of the employed population in Addis Ababa, not including vegetables
consumed by the households themselves or cooperative investment allocations.
Furthermore, PU agriculture play crucial role for the supply of fresh vegetables to Addis
Ababa residents. Studies showed that in 1983, about 63% of the Swiss chard, 17% of the
carrots, about 14% of the beetroots, and 6% of the cabbages supplied to the Addis Ababa
market come from PU agriculture (Axumite, cited in Fekadu, 2011). In the same year,
17% of the randomly selected households produced their own vegetables and that the
area under cultivation in all income categories was usually less than 25 m2 (Fekadu,
2011)
According to Fikadu (2011), the livelihood of nearly 51,000 families living in Addis
Ababa in the year 2000, for instance, depends directly on UA. The total area covered by
urban agricultural activities during the same year was 9,380 hectares (17.4% of the city)
of which about 490 hectares (0.9%) is used for vegetable production (Fekadu, 2011). This
implies that the role of PU agriculture in terms of creating food security and generating
household income is very significant. Tewodros (cited in Dereje, 2011) also shown that
urban farming in Addis Ababa contributes to the livelihood of a significant number
(65%) of urban farmers at both sectoral and household levels, for which livestock and
crop production accounted for 40% and 45%, respectively (Dereje, 2011).
Similarly, the 2001/02 CSA’s Agricultural Sample Enumeration Data further showed
how UPU agriculture is extensively practiced in major urban centers of Ethiopia.
According to this information, about 1.9 million of Ethiopian urban population is known
to be agricultural. While the total number of agricultural holders was 367,195, about
44.5%, 19.6% and 18.7% of the holders are found in Oromia, Amhara and SNNP regions,
respectively. The urban agriculture is fully oriented to the production of vegetables, fruit,
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milk, fish, livestock and poultry. The data shows that about 55% of the urban farmers
were engaged exclusively in livestock (“only livestock”). While 11% of the farmers
practiced crop farming (“only crops farming”), the remaining 34% exercised mixed
farming (crops and livestock). In the same year, there were 11,726 urban holders and
69,518 urban agricultural populations in the capital, Addis Ababa. Over 75% of the
agricultural households in Addis Ababa are engaged only in livestock rearing, while
mixed livestock and crops is about 21%. This may be due to the insufficient supply of
commercial dairy products in the capital (Fikadu, 2011).
Table 19: The Structure, Diversity, Resources and Production of PU Agriculture in
Ethiopia8
Production and Resource diversities National Figure
Urban Agricultural population (in No.) 1,880,878.0
Urban Holders (in No.) 367,195.0
Types of holdings (in %)
crop only 11.0
Livestock only 55.0
Crop & Livestock 34.0
Land size (in %) <0.51ha 60.0
>0.51ha 40.0
Livestock holding (in No.)
cattle 879,916.0
cows 240,417.0
sheep 324,954.0
Goats 195,487.0
Poultry 1,981,890.0
Milk production (in '000 liters) 998,210.2
Vegetable Produced (in qt) 36,996.0
Source: Adapted from EEA, 2005
8 Regional data of similar structure is presented in Appendix-A.
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In terms of landholding the urban farms are obviously smaller in size. At the national
level, 60% of the holdings are less than 0.5 hectare in size. In urban areas of the SNNP
region and Dire Dawa, the holdings are predominantly smaller where 80 and 88%,
respectively, are less than 0.5 hectare (Appendix-A). The data also shows that the urban
and peri-urban agriculture has large cattle resources. At the national level about 800
thousand heads of cattle are owned by the urban dwellers. In Addis Ababa alone, over 31
thousands of heads of cattle are owned. Similarly, over 500 thousand small ruminants
(sheep and goat) are owned by the urban agricultural households. Close to 2 million
poultry are owned by the urban agricultural households. Agricultural households in Addis
Ababa own 33,838 heads of chicken. Vegetable production is also a dominant cropping
activity of the urban agricultural households (EEA, 2005). During the survey year a total
of about 3700 tons of vegetables were produced by the urban holders. But nearly one-
third of the vegetables were produced in one region, SNNP region and more than 440
tons of vegetables were produced by the urban holders of Addis Ababa (Appendix-A).
The urban farmers (including those in the capital) often use traditional tools, extensive
labor and furrow irrigation to cultivate their fields. Fertilizer, manure and wage labor use
is common in crop production but family labor is the most common input for urban
farming activities (Dereje, 2011). Compared to rural agriculture, however, urban and
peri-urban agriculture is relatively capital-intensive with a high level of productivity. It
has absorbed many rural laborers and provided a stable and diversified food supply to the
urban residents in terms of quantity (EEA, 2005).
Urban agriculture policy in Ethiopia
Despite an important and a growing role of the PU agriculture in Ethiopia, not enough
attention has been given to the sector. Its contribution towards urban food security or
livelihoods has never clearly been recognized, and thus, has not received right full place
it deserves from policy makers, urban planners and authorities. Like other production
systems, urban and peri-urban agriculture has technical and institutional challenges such
as management of animals, disease control and public health risks, waste management
and disposal, and availability of formula feeds. The system faced difficulties including
access to suitable and sufficient land and water resources, livestock feed, environmental
112
hazards from urban household and industrial wastes, food safety risks and the like.
Furthermore, PU agriculture often suffers from the expansions of towns in different ways.
Most of the Ethiopian towns (including the capital Addis Ababa) expand horizontally to
the peripheral areas. Many farmers in the peri-urban periphery have been dispossessed of
their agricultural lands. Once deprived off their agricultural lands which is the basis of
their livelihoods the displaced peri-urban farmers end up as casual daily laborer because
entry to other productive activities in the area is so tough for them to penetrate it.
In general, given the enormous social and economic role it is playing, providing support
to this sector is essential in order to improve the organisation, performance and efficiency
of the sub-sector. But several studies noted that the urban agriculture policy in Ethiopia
was not supportive to urban agriculture progress so far. The planner should give much
attention on the urban agriculture benefits. The lack of proper attention from policy
makers, urban planners and local authorities, stemmed from the shortage of information
that substantiates UA’s importance in the city (Dereje, 2011). This is so because studies
and documentation made about this system are not common (EEA, 2005). This in turn
affects the development of sustainable policies to manage urban farming in the city.
To sum up, it is apparent from the preceding discussions that the Ethiopian economy has
continued to register high economic growth. But critics go that the praised growth rates
are not translating into improved living conditions for the poor, including the rural poor,
and a declining poverty headcount. Furthermore, though there is general consensus that
there is growth in agriculture, skeptics have challenged the sustainability of agricultural
growth on the ground that given current technological conditions and the structure of
production, pushing the production frontier further is difficult due to the already existing
pressures on the land (Mwanakatwe & Barrow, 2010). Furthermore, Ethiopia’s economy
is not diversified enough: agriculture and the service sector each contribute more than
40% to GDP, and 80% of employment is still concentrated in agriculture. This
contributes a lot for being one of the world’s poorest countries (with a GDP per capita of
around USD 392). However, Ethiopia has good prospects for growth. Over the next five
years, the government projects a growth rate of 11% thought the International Monetary
Fund forecasted a real GDP growth of about 8% per annum. Even at the latter’s forecast,
113
Ethiopia become the fastest growing African country and third fast growing country
among countries of the world with more than 10 million inhabitants, only lead by China
and India.
Figure 10: Top Five Fast-Growing World Economies (2011-2015)
Source: The Economist (2011)
Inspired by the remarkable growth achievements of recent years and considering the
positive development potential of the country, Ethiopia has planned to reach middle-
income status (GDP per capita of around USD 1,000) within 15 years. The government
has unveiled in October 2010 and begun implementing its ambitious five year
development plan (2010-2011 through 2014-2015) called Ethiopia’s Growth and
Transformation Plan (GTP) that lays out growth, development, and industrialization
targets up to 2015. The GTP is a medium term strategic national framework for the five-
year period (2010/11-2014/15). The overriding development agenda of the GTP is to
sustain rapid, broad-based and equitable economic growth path witnessed during the past
several years and eventually end poverty. The GTP has four main objectives including (1)
maintain at least an average real GDP growth rate of 11.2% and attain MDGs (2) expand
and ensure the qualities of education and health services and achieve MDGs in the social
sector (3) establish suitable conditions for sustainable nation building through the
9.5
8.2 8.17.7
7.2
0
1
2
3
4
5
6
7
8
9
10
China India Ethiopia Mozambique Tanzania
Ave
rage
rea
l GD
P gr
owth
p.a
. (%
)
114
creation of a stable democratic and developmental state; and (4) ensure the sustainability
of growth by realizing all the above objectives within a stable macroeconomic
framework. Generally, GTP is a manifestation of the government’s ambition to lift the
country to middle-income status by 2025.