




































 
 

In ternationa l
Scholars
Journa ls

                                                                                                               

African Journal of Agricultural Marketing ISSN: 2375-1061 Vol. 3 (8), pp. 241-251, August, 2015. Available 
online at www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s) retain the copyright of this article. 
 

 
 

Full Length Research Paper 
 

Gender role in market supply of potato in Eastern 
Hararghe Zone, Ethiopia

* 

 

Mahlet Abitew1, Bezabih Emana2, Mengistu Ketema3, Jeffreyson K. Mutimba4 and Jemal 
Yousuf1 

 
1
Department of Rural Development and Agricultural Extension, Haramaya University, Dire Dawa, 

Ethiopia. 
2
HEDBEZ Business and Consultancy General Manager, Addis Ababa, Ethiopia. 
3
School of Agricultural Economics, Haramaya University, DireDawa, Ethiopia. 

4
East and Southern Africa Coordinator of Sasakawa Africa Fund for Extension Education (SAFE), Addis Ababa, 

Ethiopia. 
 

Accepted 28 June, 2015 
 

Potato is an important vegetable that is produced for food security and income generation. Both men and 
women households are the major actors in potato production and marketing. However, there are different 
factors that affect the households' production and supply. In this regard, various research results have 
identified major causes that hinder sufficient production and marketing. But the results do not reveal the 
gender difference among households in the production and marketing. The analysis of this study is based 
on a survey of 400 household heads from three randomly selected districts of Eastern Hararghe zone. 
Descriptive statistics and linear regression model with Ordinary Least Square were used to analyze 
determinates of supply. Result of the descriptive statistics showed that there are differences between 
households in terms of age, dependency ratio, access to market information and quantity produced. The 
estimate of OLS result reveals that, the amount of potato produced, livestock holding and farming 
experience are some of the significant variables that affect the households’ level of potato supply positively 
and negatively at different probability levels. Hence, identifying the various factors in the production and 
supply of potato will help the households in maximizing their benefit and improve their capacity.   
 
Key words: Quantity supplied, potato, household heads, quantity produced, ordinary least square, Eastern 
Hararghe zone. 

 
 
INTRODUCTION 
 
Potato is a major vegetable crop and most diverse in the 
world (IYP, 2008). Worldwide more than 320 million tons 
of potatoes are produced annually on 20 million hectares 
of land (FAO, 2010). Moreover, potato is grown in more 
than 100 countries and ranks 4

th
 among the worlds’ most 

important staple food crops after rice, wheat, and maize 
(FAOSTAT,2007), and it has been recognized as  one  of  
 
 
Corresponding author E-mail: mahleta2001@gmail.com 

the main crops to alleviate hunger in the world. In Africa, 
most of the production is concentrated in East Africa 
(70%), followed by South Africa (21%) and West Africa 
(8%) (FAO, 2010).  
Ethiopia has suitable edaphic and climatic conditions for 
the production of high quality ware and seed potatoes 
(Tekalign, 2010; Endale et al., 2008). Moreover, in 
2013/14, the area under potato production in Ethiopia was 
about 66,745 hectares with an average national yield of 
117 quintal  per  hectare  for  the  main  cropping  season  



 
 

Abitew et al.          241 
 
 
 
(CSA, 2014). Most highlands with altitudes ranging from 
1,500 - 3,000 meters above sea level (m.a.s.l) and annual 
precipitation of 600 - 1,200 millimeters (mm) are suitable for 
potato cultivation (Medhin et al., 2001; FAO, 2008). Eastern 
Oromiya is a major potato producing area. It covers the 
eastern highlands of Ethiopia, which includes Fedis, 
Haramaya, Kombolcha, Kersa, Meta, Kurfa Chelle, Grawa, 
and Jarso (Bezabih and Hadera, 2007). Furthermore, the 
area under potato production in East Hararghe was 2,207.12 
hectares with an average yield of 193 quintal per hectare 
(CSA, 2014). 
Potato constitutes a major ingredient in every meal of the 
households in Eastern Oromiya. The presence of a regional 
domestic market and cross-border and export market outlets 
to the neighboring countries like Djibouti and Somalia have 
contributed to the development of potato culture in Hararghe 
(Tekalign, 2010). Export as well as local marketing of potato 
is an essential activity of the farming households where it 
generates income. Out of the total volume of potato 
marketed to Somalia, 75 percent is supplied from East 
Hararghe and about 25 percent from the central part of 
Ethiopia including the Rift Valley and Shashemene 
(Bezabih, 2008). However, the supply is neither sufficient 
nor constant to satisfy the demand of the market at both 
market outlets.  
Given the economic and social importance of potato, men 
and women farmers managed their farms in a better way so 
that they can be prominent in the production and supply of 
potato.  In a married household, men and women work 
together to produce potatoes; men devote their efforts to 
activities requiring more physical effort such as land 
preparation, but many tasks are shared (Amaya, 2009). 
However, farm managed by women are generally 
characterized by low level of mechanization and 
technological inputs, which often translate into low 
productivity (FAO, 2006). Even though, both households 
face various constraints that hamper their effective 
production and supply, women-owned businesses face 
greater constraints and receive far fewer services and less 
support than those owned by men (Bardasi et al., 2007; Ellis 
et al., 2006; World Bank, 2007a,b). These disadvantages 
reduce women’s effectiveness as actors in value chain and 
also restraint their overall engagement in market activities. 
Yet, quantitative analysis of gender deferential in potato 
supply to the market has not been studied in eastern 
Oromiya. The major objective of the paper is, therefore, to 
assess the effect of gender on market supply of potato. 
Moreover, this paper aims at assessing the factors that 
hinder male and female headed households from effective 
potato production and marketing, how the factors affect them 
and why the factors affect them differently.  
 
 
METHODOLOGY 

 
Sampling procedure, type of data and method of data 
collection 

 
The study was  conducted  in  Eastern  Oromiya  National  

Regional State of Ethiopia. A multi-stage random 
sampling technique was used to select the districts, rural 
kebele and sample household heads. In the first stage, 
study districts from the zone were selected purposively 
based on their higher potato production potential as 
compared with other districts. Accordingly, Kombolcha, 
Kersa and Haramaya districts were selected for the 
survey. In the second stage, 12 potential kebeles

1
 were 

randomly selected from the selected districts. In the third 
stage, 400 household heads were randomly selected 
where the sample gender representation was based on 
the proportion of male and female headed households 
i.e., 372 male headed households and 28 female headed 
households. The sample households were drawn 
randomly from each kebele based on probability 
proportional to size sampling techniques.  
Both qualitative and quantitative data were collected from 
primary and secondary data sources. Primary data were 
collected from sample farm households using pre-tested 
structured interview schedule, focus group discussions 
and observations. The primary data were firsthand 
information collected through individual contact in their 
vicinity. The data collected include producers’ household 
characteristics, quantity produced, potato production 
characteristics, quantity supplied and access to markets 
and information. Besides, relevant secondary data 
sources like government and non-government reports, 
relevant text books, journals and bulletins were reviewed 
to supplement the survey data at different times of the 
study period.  
 
Data analysis  
 
To measure factors affecting market supply of potato by 
farm households, a linear regression model was 
employed. A number of household and institutional 
factors are identified as the main features that affect the 
market supply of potato. This model was chosen for a 
reason that the dependent variable i.e. quantity supplied 
is continuous (Gujarati, 2003) and other assumptions of 
OLS are fulfilled in the field survey data. Moreover, 
different studies on market supply used Ordinary Least 
Square (OLS) regression to assess determinants of 
market supply of agricultural products (Kinde, 2007; 
Betelihem, 2013; Mahilet, 2013). Therefore, the study 
chooses linear regression model to analyze the major 
causes of market supply of potato.  
 
The econometric model specification of supply function 
takes the following form. 
     Yi = α + Xiβ + Ui                                                                                                             
(1) 
Where     Yi = is the amount of potato supplied to market   
            

                                                           
 1Kebele is the administrative structure below district. A cluster of 
kebeles form a district. 



 
 

242        Afr. J. Agric. Mark. 
 
 
 
    Xi = explanatory variables determining the amount of 
market supply 
               α = intercept 
               β = coefficient of i 

th
 explanatory variable 

                Ui = unobserved disturbance term  
 
The estimates of coefficients of the regression equation 
obtained using the method of Ordinary Least Squares. 
OLS assumes that the random term follows normal 
distribution with zero mean and constant variance. The 
successive values of the random term are also assumed 
to be independent. The OLS assumes also that the 
explanatory variables are non-stochastic and they are not 
perfectly linearly related to one another (Gujarati and 
Sangeetha, 2007). It is hypothesized that male and 
female farmers produce and supply different quantities of 
potato to the market to maximize their gross income. 
However, the households’ decision to supply is 
influenced by various factors. Therefore, the main 
hypothesis variables for the study are listed below.  
 
Dependent variable 
 
Quantity supplied to market (QtySupp): It is a continuous 
variable measured in quintal and represents the actual 
supply of potato by farm households to the market in the 
survey year.  

 
Independent variables 
 
Education of the household head (EduHH): It is a dummy 
variable that measures whether a farmer has attended 
formal education or not (Table 1). It assumes a value of 1 
if the household head attended formal education and 0 
otherwise. It is believed that if a farmer attained formal 
education of any level there is a possibility of increment in 
their productivity as they have better knowledge than 
those who did not attend formal education. In addition, 
educated farmers are exposed to better technologies that 
will help them increase production and supply. There are 
many studies that show the relationship between 
education and quantity supplied to a market. For 
instance, Yeshitila (2012), has indicated that there is a 
positive relationship between education and vegetable 
marketing.  Similar studies conducted by Gizachew 
(2005) and Rehima (2006), revealed that formal 
education has positive relationship with household 
market participation and marketed volume. It is also 
found that the more the producers of Paddy got educated 
the more the supply in the market and it is also indicated 
that education improves level of sales that affects the 
marketable surplus (Astewel, 2010). Therefore, in this 
specific study, formal education is expected to have a 
positive relationship with quantity of potato supplied to 
the market.  
 

Gender of the household head (GenderHH): It is a dummy 

variable which takes a value of 1 if the household is 
headed by male and 0 otherwise (Table 1). Both men and 
women participate in potato production where male 
headed households are believed to have better tendency 
than female headed households in production and supply 
of potato. Lack of capital, access to credit and extension 
services and size of the land can be mentioned as some 
of the reasons for the variance occurred between the 
households. The study conducted by Gizachew (2005), 
indicates that there is a negative relationship between 
sales of volume of milk and male-headed household. 
Study by Mamo and Degnet (2012), also showed that sex 
is a determinant factor in the household head in the 
livestock market. Furthermore, the study made by Dawit 
(2010), discovered that sex of the household head is one 
of the factors that positively affect the probability of 
marketable supply of poultry in Alamata and Atsbi 
Womberta woredas of Tigray. A study done by Lewis et 
al., (2008), stated that gender difference and the 
marketing styles at Oklahoma wheat producers showed 
that men tend to sell more grain frequently than women. 
Therefore, the effect of sex of the household heads on 
marketed supply of potato in the study area will be 
determined.  
Women empowerment (WomenEmp): It is a dummy 
variable taking the value of 1 if woman is empowered in 
the household and 0 otherwise. Empowered women have 
a chance to decide and access to different production 
inputs, better communication and acquiring knowledge from 
different institutions and having better time schedule to 
supply product to the market. Moreover, empowered women 
are expected to produce more and supply better than 
disempowered women in the households. However, this may 
not be always true in the situation that women have small 
pieces of land, low access and linkage with extension 
agents, and hence low quantity produced. Therefore, 
women empowerment effect on marketed supply of potato is 
undefined will be determined based on context specific data. 
Family size (FamSize): This refers to the number of 
household members and it is a continuous variable that is 

measured in man equivalent Storck et al., (1991), that is the 

availability of active labor force in the household, which 
affects the farmer’s marketed supply. As potato is a 
vegetable crop, it is a labor intensive activity for both the 
production and market supply. Accordingly, household 
heads that have active labor force tend to supply more 
potato to the market than others. Thus, family size is 
expected to have positive impact on the amount of 
agricultural products sold. The study conducted by Fantahun 
(2010), also indicates that large family size has an effect in 
decreasing the supply of malt barley in Amhara region. 
Furthermore, study by Wolday (1994), showed that 
household size has significant positive effect on quantity of 
“tef” marketed and has negative effect on quantity of maize 
marketed. Another study by Gezahagn (2010), also details 
that family size has positive effect on the households’ gross 
income  from  the  production  of  groundnut.   Hence,  in this 
context,  the  effect  of  family  size   has   positive  effect  on 



 
 

Abitew et al.          243 
 
 
 

marketed supply of potato (Table 1). 
Dependency ratio (DependR): This variable is the ratio of 
the number of children below 15 years of age, disabled 
members and elders above 65 years of age to the 
number of economically active family members (15-65 
years of age). An increase in dependency ratio in the 
household affects the quantity supply in a way that more 
shortage of labor in production of potato. Thus, 
dependency ratio is expected to have negative effect on 
households’ marketed supply of potato.  
Farming experience of the household head (FarmExper):  
It is a continuous variable that indicate the farming 
experience of the household head in years (Table 1). A 
household with better farming experience in potato 
cultivation is expected to adopt new recommendations for 
securing higher yield than those with less farming 
experience. A study conducted by Ayelech (2011), 
indicates that farmers with longer farming experience are 
expected to be more knowledgeable and skillful and are 
more successful in their production. Thus, farming 
experience is expected to have positive relation with 
marketed supply of potato in the study areas.  
Livestock holding (TLU): This is a continuous variable 
that measures the total number of livestock owned by a 
household in terms of tropical livestock unit (TLU) (Table 
1). Households that have high TLU are expected to have 
a better wealth status in the society. Livestock holding in 
a household is useful as it increases fertility status of the 
soil as a result of usage of organic manure and as a 
source of income from sale of livestock and its products. 
This particular variable creates an opportunity for a 
household to use organic manure in addition to inorganic 
fertilizer so as to increase potato production. Therefore, 
the variable is expected to have positive linkage with the 
amount of potato supplied to the market. 
Availability of irrigation (AvIrrigat): This is a dummy 
variable which takes a value of 1 if the households have 
access to irrigation 0 otherwise. It is one of the most 
important inputs for potato production in the study area, 
where producers have a chance to produce more than 
one time per year. The study by Tadesse (2011), shows 
that, the farmers who have access to irrigation are using 
it for production of high value cash crops in West 
Hararghe Zone. Thus, this variable is hypothesized to 
have positive influence on potato supplied. 
Access to market information (AccMktInf): It is a dummy 
variable taking a value of 1 if the household has access 
to market information and 0 otherwise. The better the 
information the farmers have about the products 
marketing, the higher would be their supply. Moreover, 
farmers marketing decisions are based on market price 
information, but poorly integrated markets may convey 
inaccurate price information, leading to inefficient product 
movement (Abraham, 2013). However, information 
dissemination might not be the same at once to benefit all 
equally. A study by Muhammed (2011), also reveals that 
if wheat producers get accurate market information, the 

amount of wheat to be supplied to the market increases. 
Similarly, study by Mahilet (2013), indicates that 
marketable surplus of malt barley producers who have 
access to market information are greater than those who 
did not. Thus, we can hypothesize that access to market 
information will have a positive implication on marketable 
supply of potato.  
Access to credit (AccCred): This is a dummy variable that 
takes the value 1 if the household receives loan for 
potato production and 0 otherwise. Farmers who have 
access to credit would increase their financial capacity as 
it assists to make proper decision regarding purchasing 
of modern input to increase production and volume of 
supply. The study by Alemnewu (2010) and Muhammed 
(2011), pointed out that if pepper and tef producers have 
access to credit, the amount to be supplied to the market 
would increase. We also hypothesize here that access to 
credit has positive influence on the level of production 
and sales. 
Distance to the nearest market (DisMkt): It is a 
continuous variable measured in kilometer that the 
farmers are required to travel in order to sell their product 
and spend some time in the market. The closer the 
market area the lesser the transportation and transaction 
costs and time spent. Moreover, there is no doubt that 
transportation has great importance for marketing 
agricultural product. The study by Shilpi and Umali 
(2007), found that the likelihood of sales at the market 
increases significantly (positively) with an improvement 
with market facilities and a decrease in travel time from 
the village to the market. The study by Mahilet (2013), 
stated the analysis of value chain of malt barely also 
indicated that if the proximity from the farm to market 
increases, the volume of malt barley supplied to the 
market decreases. In this study, the variable is expected 
to have a negative relationship with farm level marketed 
supply of potato (Table 1).  
Quantity of potato produced (QtyProd): It is a continuous 
variable measured in quintals within a year 2013/14. An 
increase in output level increases the marketed supply of 
the crop. The studies of Abay (2007); Adugna (2009) and 
Ayelech (2011), pointed out that the amount of tomato, 
papaya, avocado and mango produced by farming 
households has augmented significant marketable supply 
of the agricultural products. The higher output the farmer 
obtain, the higher would be the marketed amount. In 
addition, different studies Kindie (2007); Bosena (2008) 
and Assefa (2009), disclosed that the amount of sesame, 
cotton and honey produced by households are 
significantly and positively affected by marketable supply 
of each of the products. Though similar study is lacking in 
potato, we hypothesize that the quantity of potato 
produced can have a positive effect on marketed supply. 
Off/Non- farm activities (OffNonFarm): It is a continuous 
variable which refers to the income obtained by the 
sample households from off/non-farm activities. 
Increased  availability  of  opportunities  for  off/non-farm  



 
 

244        Afr. J. Agric. Mark. 
 
 
 

    Table 1. Summary of dependent and independent variables used in Linear Regression model. 
 

Variables Definition        Values Expected sign 

Dependent variable  

QtySupp Quantity supplied to the market Amount sold in quintals   

Independent variables     

EduHH Educational level of household head 1 if  attended  formal education, 0 
otherwise 

+ 

GenderHH Gender of the household head 1 if male, 0 otherwise +/- 

WomenEmp Women empowerment index in the households 1 if women empowered, 0 
otherwise 

+/- 

FamSize Total  active labor force in the household  Man equivalent   + 

DependR Non-active labor force in the household Ratio of non active to working 
labor 

- 

FarmExper Farming experience of household head Number of years since started 
farming activity 

+ 

TLU Livestock holding in the household  Tropical livestock unit + 

AvIrrigat Availability of irrigation facilities  1 if yes, 0 otherwise + 

AccMktInf Access to market information in the household 1 if access to information, 0 
otherwise 

+ 

AccCred 

 

Access to credit in the households 1 if the household take loan, 0 
otherwise 

+ 

DisMkt Distance to the nearest market Number of kilometer - 

QtyProd Quantity potato produced by the households Quintals + 

OffNonFarm Off/non-farm activities in male headed households Birr per year - 

    

  Source: Own computation from survey data (2012/13) 

 
employment have negative relationship with supply of potato 
(Table 1). Most of the time, farmers are engaged in different 
income generating activities along with their main task of 
farming. They buy khat, vegetables, fruits, etc from other 
farms in their vicinity and sell with better price to other 
market places in the cites. In addition, this other income 
generating activities are assumed to have inverse 
relationship with marketed supply of vegetable crops. 
Different studies have identified that access to other income 
sources is negatively related to the sales volume of milk, 
kales and maize in Kenya and banana market in Uganda 
(Omiti et al., 2009; Komarek, 2010). As we can infer from the 
study of Rehima (2006), stated that if pepper producer have 
non-farm income, the amount of pepper supplied to the 
market decreases. Therefore, the effect of this variable on 
the market supply of potato at farm level could be negative. 
In general, the definition of variables and the hypothesized 
signs of influence on potato market supply are summarized 
in Table1.  
 
RESULTS AND DISCUSSIONS 
 
Descriptive statistics 
 

The mean age of the sample household heads was 35.74 years 

with the minimum and maximum age of 20 and 70 years, 
respectively. The average age of male household heads was 
35.38 years compared to 40.5 years for female headed 
households with the mean age difference between the two 
groups being statistically significant at 1percent level. This 
indicates that most of the household heads were within the 
vibrant age category. Male headed households have almost 
similar farming experience (27.27 years) as compared with 
female headed households (26.79 years) which shows that the 
household heads have rich experience on potato production 
and marketing in the zone with no significant difference 
between the gender of the household heads (Table 2).  
 

The mean family size of the total sample households was 5.81 
persons ranging from 2 to 13.  On average, male headed 
households have relatively larger family sizes (5.94) than the 
female household heads (4.11) with mean difference of 5.81 
persons (Table 2).  Labor availability or active labor force is a 
prominent input for potato production as well as marketing. The 
average man equivalent in the zone was 2.66 with standard 
deviation of 1.21, where male headed households have better 

active labor availability than female headed households. 
The dependency ratio also ranges from 0-6 with the 
mean values of 1.28 and 2.79 for male and female 
household heads, respectively with significant mean 
difference at 1percent significance level (Table 2).  



 
 

Abitew et al.          245 
 
 

Table 2. Demographic characteristics of sample producers.  
 

 

Variables 

MHHs
* 

FHHs
* 

Total   

t- value Mean SD* Mean SD Mean SD 

Age (Years) 35.38 10.10 40.50 7.71 35.74 10.03 2.62*** 

Farming experience 
(Years) 

27.27 1.93 26.79 2.01 27.26 1.92 -0.95 

Family size 5.94 2.19   4.11 1.07 5.81 2.18 -1.60 

    Dependency ratio 1.28 0.91 2.79 1.13 1.39 1.00 8.29*** 

    Economically active  

    labor force (ME) 

2.72 1.21 1.53 0.43 2.66 1.21 11.64*** 

* 
MHH= Male headed household; FHH= Female headed household; SD= Standard deviation         

 *** indicate the level of significance at 1 percent. 
 

 

The sample households in the study area comprise 93 
percent male headed households and 7 percent female 
headed households. This indicated that female headed 
households are not widely engaged in potato production 
and marketing. Educational background of the sample 
households is essential to develop positive attitude 
towards adopting improved technologies, build up 
communicative skill and use of necessary information to 
increase production and productivity. The chi-square 
result revealed that education is a dummy variable that 
shows statistically significant difference between the 
households at 1 percent level of significance. About 65.1 
percent and 28.6 percent of sample male and female 
headed households, respectively, were attending formal 
education (they can read and write). The female headed 
household is characterized by higher proportion of not 
attending formal education than the male headed 
households.  
Based on the survey result, the average land holding of 
the sample households was found to be 0.531 hectares 
with standard deviation of 0.410 ranging between 0.06 
and 2.88 hectares. The mean land holding owned was 
0.538 ha and 0.437 ha for male and female headed 
households, respectively. In the year 2012/13, the mean 
average land used for vegetable crops is 0.036 hectares 
with standard deviation of 0.066, where there is no 
statistically significant difference. Specifically, land under 
potato was 0.139 hectares with standard deviation of 
0.097, where there is no statistical significance difference 
among male and female headed households. Moreover, 
major cereal crops like sorghum, maize, wheat and khat 
were dominantly grown on the farm of the households in 
the study districts. The data discloses that the mean land 
areas allocated for khat (Catha edulis) and maize have 
statistically significant difference among male headed 
and female headed households at 5 and 10 percent level 
of significance. In this regard, male headed households 
have allocated better land size for khat and maize than 
female headed households. In addition, 56 percent of the 
sample households have medium fertility of the land and 
it has statistical significant difference at 1percent level of 
probability.  
Livestock rearing is another important income generating 

source that almost all the sample households were 
engaged in. The total livestock holding measured in 
terms of TLU was found to be 2.69 with standard 
deviation of 2.11 which is relatively large as compared to 
the small land holding allocated for grazing purpose and 
continuous expansion of crop land. Moreover, the 
average livestock holding was 2.79 and 1.31 TLU for 
male and female headed households respectively with 
statistical mean difference at 1percent level of probability.  
Market information is an important component for the 
timely supply of agricultural products and to satisfy the 
demand of the market. The households have different 
access to market where the benefit also varies. In the 
study areas, access to market information shows 
statistical differences between male headed and female 
headed households at 5percent level of probability (Table 
3). On average, 48.5 percent of the sample households 
have at least potato price information from the nearby 
local market. In addition, more than half of the sample 
male headed households have access to market 
information by different means of communication like 
mobile phone.  
Farm households took credits from different credit 
institutions like Microfinance, cooperatives and informal 
money lenders for various purposes. From the sample 
households, 41.2 percent used the money for the 
purchase of farm inputs like improved seeds, fertilizers 
(Urea and DAP), chemicals (pesticides and herbicides) 
and farm implements (Akafa and pumps), where as 16.5 
percent used to purchase livestock such as goats, sheep, 
and cow either for fattening or to increase the number of 
livestock to generate income from sell of the animals and 
their products. As the data indicated, on average, 60.5 
percent of the sample households had access to credit 
where the proportion of male headed households who 
accessed credit was, 59.7 percent (Table 3) with the 
reason that male headed households have better capital 
to invest on. Moreover, the average distance that most of 
the households used to travel to sell their product to the 
nearest market was about 6.67 kilometers, where it is 
6.66 and 6.78 kilometers for male and female headed  
households, respectively, with no statistically significant 
mean difference between households.  



 
 

246        Afr. J. Agric. Mark. 
 
 
 

Table 3. Institutional characteristics of sample households. 

 

 

Variables 

MHHs 

(N= 372) 

FHHs 

(N= 28) 

Total 

(N= 400) 

     

    χ
2
-value 

N % N % N % 

Access to market information 188 50.5 8 28.6 196 48.5 5.025** 

Access to credit 222 59.7 20 71.4 242 60.5 1.505 
      ** indicate the level of significance at 5 percent 

 
 
 
The result of the survey reveals that, quantity produced 
and off/non- farm income generation activities are some 
of the variables that show 1 and 10 percent level 
significant difference between male and female headed 
households (Table 4). The average quantity produced in 
the households is 37.2 quintals per seasons where the 
male headed households had better chance to produce 
and supply potato to the market (38.7 quintals) than the 
female headed households since they produced 17.7 
quintals.  From the total quantity produced, on average, 
30.7 quintals was supplied to the nearby market by the 
sample households i.e., 32.1quintals and 11.4 quintals by 
male and female headed households, respectively. The 
total yield of the households was 267.1 quintal per 
hectares.    
Rural farm households earn cash income from different 
sources where, off/non-farm income generation activities 
are among them. The survey result (Table 4) shows that 
the income that is generated from this source was 
1,135.50 Birr in 2012/13 with standard deviation of 3,739 
Birr. Female headed households had better income 
(2,660.71 Birr) than the male household heads (1,020.70 
Birr) with a significant mean difference at 10 percent level 
of probability.   
Women empowerment is a process in which women gain 
greater share of control over resources material, human, 
intellectual and financial resources and control over 
decision making in the household, community, society, 
nation and to gain power (Pooja and Rathod, 2013). 
Women Empowerment Agricultural Index (WEAI) was 
calculated by adopting the two sub indexes i.e. 5DE (Five 
domains) and GPI (Gender Parity Index) from (IFPRI, 
2012) which was developed by Alkire et al., (2012), that 
discussed about how to compute women empowerment 
in agriculture. The first index assesses the degree to 
which women are empowered in five domains of 
empowerment (5DE) which reflects the percentage of 
women who are empowered and, among those who are 
not, the percentage of domains in which women enjoy 
adequate achievements. Each of the domains has 
indicators with their corresponding weights. The domains 
are Production (Input in productive decisions and 
Autonomy in production), Resources (Ownership of 
assets, purchase, sale, or transfer about credit, access to 
and decision about credit),  Income  (control  over  use  of 

income), Leadership (group member, speaking in public), 
and Time (Workload and leisure). 
The second index GPI reflects the percentage of women 
who are empowered or whose achievements are at least 
as high as the men in their households. For those 
households that have not achieved gender parity, the GPI 
shows the empowerment gap that needs to be closed for 
women to reach the same level of empowerment as men. 
Such index excludes female headed households. The 
benchmark of WEAI and its sub indexes is an individual 
empowerment if he or she enjoys adequate 
achievements in 80 percent or 0.80 of the weighted 
indicators or more. 
The survey result reveals that empowerment index in the 
households has statistically significant difference 
between households at 1 percent level of probability. 
From the total sample households, on average, 92.6 
percent of women were not empowered and 6.4 percent 
were empowered. This is due to the large sample size of 
male headed household where women in these 
households do not have equal access and control over 
resources. The data also shows that on average 53.6 
percent of women in female headed households were 
empowered than women in male headed households. 
This is due to the fact that female headed households 
have full access and control over resources than women 
in male headed households. On the contrary, on average 
97 percent of women in the male headed households 
were not empowered as every resource in the household 
are fully controlled by the male.  
 
Econometric result 
 

Potato in the study district is produced by male and 
female household heads for different reasons. 
Agricultural production and marketing are essential 
means of livelihood for both male and female headed 
households. The current survey output indicated that, the 
difference in the supply of potato by male and female 
headed households is due to the fact that women have 
less quantity produced than male headed households. 
Besides quantity produced, there are various constraints 
that hinder their maximum supplies to the market, and  
thus identifying and making critical analysis of the causes 
of the difference in the supply is necessary.   



 
 

Abitew et al.          247 
 
 
 
Table 4. Potato produced and income from off-nonfarm activities of male and female households. 

 

Variables 

MHHs FHHs Total   

t- value Mean SD Mean SD Mean SD 

Quantity produced (Qt) 38.7 35.7 17.7 14.2 37.2 35.0   6.438*** 

Off/non-farm activities 
(Birr/year) 

1020.70 3614.34 2660.71 4949.84 1135.50 3739.0    1.719* 

***and * indicate the level of significance at 1 and 10 percent, respectively. 

 
 
Linear regression specified in Equation (1) was estimated 
using the OLS method to assess the effect of gender on 
market supply of potato. Prior to running the model, all 
the hypothesized explanatory variables were tested for 
the existence of multicollinearity and heteroscedasticity 
problems. However, the result shows that there is no 
serious problem in the model output.  Coefficient of 
determination (R

2
) was used to check goodness of fit for 

the regression model. Hence, R
2 

for potato was 0.966 
which indicates that 97 percent of the variation in the 
farm level marketable supply of potato was attributed to 
the variables included in the model. It also clarifies that 
potato is the major cash crop for the majority of 
producers and shows that the higher the output, the 
higher is the producers willing to supply to the market. 
Similar findings explained the direct or positive relation 
between volume of production and market supply of the 
products by (Omiti et al., 2009; Wolday, 1994; Bosena, 
2008; Rehima and Dawit, 2012).  
As it can be observed from the econometric result in 
Table 5, a total of 13 hypothesized explanatory variables 
(7 continuous and 6 dummy) were included in the model 
to explain the household level determinants of market 
supply of potato. Out of these variables, six were found 
significantly influence farm level marketed supply at 1, 5, 
and 10 percent probability levels. These variables include 
gender of the household, farming experience, livestock 
holding (TLU), access to market information, quantity 
produced and access to credit. The signs of the 
parameter of the significant variables are similar with the 
hypothesis except for livestock holding (Table 1). 
Gender of the household head positively and significantly 
influenced marketed supply of the households at 10 
percent probability level. In the study areas, both male 
and female household heads were engaged in potato 
production and marketing. The data shows that supply of 
potato to the market is higher for male-headed 
households by 2.76 quintals as compared to that of 
female-headed households, keeping other variables 
constant. This is due to the fact that male headed 
households have better financial capability, better land 
size, better extension contacts, and better access to 
market information. Therefore, we can infer from the 
analysis of the model that male household heads supply 
more potato to the market as compared to female 
household heads. Hence, this finding is congruent with 

the study by (Dawit, 2010; Lewis et al., 2008; 
Muhammed, 2011). 
As expected, farming experience of the household heads 
was found to be positively and significantly associated 
with the quantity of potato supplied to the market at 
5percent level of probability (Table 5). As producer’s 
farming experience increases by one year, the amount of 
potato supply also increases by 0.308 quintal, keeping 
other variables constant. This is mainly due to the fact 
that more experienced households have better 
accumulated wealth that can be used for purchasing 
production inputs (fertilizer, seeds, irrigation pump), 
access to information related to the use of new 
recommended packages and pricing of the product. It is 
also believed that more experienced household heads 
are wise in resource use, has better skill of potato 
production and likely to have positive effect on market 
participation and marketed supply of potato than less 
experienced ones. This result is also supported by Abay 
(2007), who indicated that as farmers’ experience 
increases the volume of tomato supplied to the market 
also increases. In addition, Abraham (2013), indicated 
that farming experience and the amount of supply have 
positive and significant relationship with vegetable 
production. Moreover, one year increment in production 
of vegetables maximize marketable surplus of vegetables 
of households by 0.362 quintal (Tadesse, 2011). 
Livestock holding (TLU) affects the amount of potato 
supply negatively and significantly at 1percent probability 
level. This implies that, on average, a unit increase in 
livestock ownership causes 0.41 quintal decrease in the 
amount of supply of potato, keeping other factors 
constant (Table 5). It is known that livestock production is 
one of income generating activity in the rural community 
where producers with an increased number of livestock 
create an opportunity to generate their income by sales of 
livestock by-products and live animals. This implies that 
there is an indication in the specialization of livestock 
production than potato production and supply for income 
generation. Moreover, livestock production and potato 
production compete for the scarce land and water 
resources so that most of the time farmers have to make 
choices. To strengthen the above finding, Rehima (2006), 
indicated that a unit increase of livestock causes a 
decrease in the volume supply of pepper. In a similar 
way, Ouman et al., (2010), observed that  livestock  hold- 



 
 

248        Afr. J. Agric. Mark. 
 
 
 

Table 5. Determinants of marketed supply of potato by farm households. 
 

Variables Coef. Std. Err.                   t- value 

Education of HH 0.198 0.643                        0.31 

Women Empowerment  0.406 1.440                        0.28 

Gender of HH 2.765* 1.512                        1.83 

Family size  -0.329 0.276                       -1.19 

Dependent Ratio -0.166 0 .342                      -0.48 

Farm Experience 0.308** 0 .157                        1.96 

Livestock holding  -0.411***  0 .150                       -2.73 

Availability of irrigation -0.550 1.597                       -0.34 

Distance to market 0.304 0 .266                       1.14 

Access to market information 1.413** 0 .658                        2.15 

Access to credit 1.587** 0.637                        2.49 

Quantity produced 0.883***   0.010                       91.04 

Off/non-farm income 0.000 0.000                       0.37 

_Constant term -14.273** 5.157                      -2.77 

Number of observation   400 

F(13, 386) 852.88 

Prob>F 0.000 

R-Squared 0.9664 

Root MSE 5.9009 
 

Dependent variable is quantity supply of potato in quintal. ***, ** and * are statistically significant at 1%, 5% 
and 10% level, respectively. Source: Own computation from survey data. 

 
 

 
holding is adversely affected by the volume of banana 
supplied to the market in Central Africa. Nevertheless, 
some scholars indicate that livestock holdings (TLU) is 
positively related to the level of cereal, cotton, and 
sesame sales in market participation (Siziba et al., 2011; 
Alene et al., 2008; Larsen, 2006; Makhura et al., 2001; 
Kindie, 2007). 
As hypothesized, the model result specifies that access 
to market information has positively and significantly 
influenced the amount of market supply of potato at 5 
percent probability level (Table 5). The data also revealed 
that if the producers get market information, the amount 
of potato supplied to the market also increases, on 
average by 1.413 quintal keeping others constant. This 
shows that access to market information like where to 
sell, how to sell and price information plays a pivotal role 
in deciding the amount of potato to be supplied to the 
market. This finding is in line with Muhammed (2011), 
who illustrated that access to market information 
significantly increases marketable supply of tef in Halaba 
Special district. Similarly, the study by Abraham (2013), 
indicated that access to market information by household 
heads increases marketed supply of potato significantly 
in Habro and Kombolcha district.   

The result also indicated that quantity produced affects 
marketed supply positively and significantly at 1percent 
probability level (Table 5). The survey result indicates 
that a one quintal increase in potato production results in 
0.883 quintal increase in amount of marketed supply, 
keeping other factors constant. These shows that the 
more the households produce, the more they supply to 
the market. This is due to the fact that almost all 
producers have an objective to generate income from 
what he/she produced as there is consistency in the 
general expectation. In a similar way, previous studies by 
Omiti et al., (2009); Astewel (2010); Rehima and Dawit 
(2012); Adugna (2009); Ayelech (2011); Wolelaw (2005) 
and Assefa (2009), indicated that consistent increase in 
agricultural production positively and significantly 
increase the amount of marketed potato supply. 
The result also indicates that, access to credit has 
positive and significant influence on the market supply of 
potato at 1percent significant level. From this result it can 
be deduced that those households with better access to 
loan have better chance to increase their market supply 
by 1.587 quintal than those who do not have access 
(Table 5). Most of the time, access to credit in the 
households is determined by cash on hand that is usually



 
 

Abitew et al.          249 
 
 
 
used for purchasing improved varieties, fertilizers, 
chemicals and  labor wage etc. Moreover, there are 
different credit associations in rural areas that provide 
loan to benefit producers so that they can improve their 
livelihood. Earlier studies Legesse (1992); Tesfaye and 
Shiferaw (2001) and Rahmeto (2007), also revealed that 
credit is one of the factors that affected the probability of 
adoption of improved varieties, quantity of fertilizer and 
haricot bean, respectively. Similarly the study by 
Muhammed (2011), indicated that access to credit 
positively and significantly affected the amount of wheat 
sold to the market. 
 
 
CONCLUSIONS AND IMPLICATIONS 
 
The study was conducted in Eastern Hararghe Oromiya 
regional state of Ethiopia to determine the gender role in 
market supply of potato. The result reveals that both male 
and female headed households participate in the 
production and supply of potato but there are various 
factors that affect the quantity supplied to the market. 
Age of the households, dependency ratio, economically 
active labor force and quantity produced are some of the 
variables that are statistically significant which indicates 
the differences in the socio demographic characteristics 
between households. Moreover, the result of the model 
also shows that gender of the households, farming 
experience, livestock holding, market information, 
quantity produced and access to credit are major factors 
statistically and significantly determining the quantity of 
potato supplied to the market. Quantity produced is highly 
determined by quantity supplied where the households 
decide to supply after satisfying the household 
consumption and seed for next year.  
The result of the study became an indicator for program 
designers and implementers who have direct relation with 
potato producers to maximize their benefit. Livestock 
production is one of the enterprises where the 
households generate income. Increasing the livestock 
holdings in the households’ creates an opportunity to 
produce organic fertilizer (compost) used to increase 
potato production.  Organic fertilizer is rarely applied by 
the farm households for production of agricultural 
products even though almost all households are aware 
about the steps of preparation. Thus, increasing the 
livestock holding and train how to prepare and apply 
compost are essential achievement for the households to 
secure better quantity of production for supply.  
Lack of strong institutional support lagged the rural farm 
households from executing farm activities on time. Brief 
and recent information about credit and market like price 
are essential to motivate producers to supply potato to 
the market on time and also collect benefit immediately. 
Due to this, there is inconsistency in supply among the 
households. Therefore, in the rural areas, there should be 

strong institutions used to deliver recent and major information 

that benefit producers in production and supply of potato 
to the market.  
Both male and female headed households used their 
labor in production and supply of potato. However, the 
extent of participation in production activities are varies 
among the households. In most of the cases, male 
headed households are very efficient and effective in 
production as well as supply where economically active 
labor force is much higher and dependency ratio are 
lower as compare with female headed households. 
However, with the current situation of female headed 
households, there should be gender focused 
interventions that support, encourage and give priority for 
increasing production, supply and minimize differences 
among the household heads.  
 
 
ACKNOWLEDGEMENTS 
 
The authors would like to thank to Haramaya University 
for providing the chance to pursue the study and financial 
support from Sasakawa Africa Fund for Extension 
Education (SAFE).  
 
 
REFERENCES 
 
Abay A (2007). Vegetable Market Chain Analysis in 

Amhara National Regional State: The Case of Fogera 
Woreda, South Gonder Zone. M.Sc Thesis Department 
of Economics, Haramaya University. 

Abraham T (2013). Value Chain Analysis of Vegetables: 
The Case of Habro and Kombolcha Woredas in Oromia 
Regions, Ethiopia. M.Sc Thesis Presented to the 
School of Graduate Studies of Haramaya University. 

Adugna G (2009). Analysis of Fruit and Vegetable Market 
Chains in Alamata Southern Zone of Tigray: The Case 
of Onion, Tomato and Papaya. An MSc Thesis 
Presented to the School of Graduate Studies of 
Haramaya University. 98p. 

Alemnewu A (2010). Market Chain Analysis of Red 
Pepper: The Case of Bure Woreda, West Gojjam Zone, 
Amhara National Regional State, Ethiopia. M.Sc thesis 
to school Agricultural Economics, Haramaya University. 

Alene AD, Manyong VM, Omanya G, Mignouna HD, 
Bokanga M, Odhiambo G (2008). Smallholder Market 
Participation under Transactions Costs: Maize Supply 
and Fertilizer Demand in Kenya. Food Policy, 
33(4):318–328. 

Alkire S, Meinzen-Dick R, Peterman A, Quisumbing R, 
Seymour A, Vaz GA (2012). The Women 
Empowerment in Agriculture Index. Poverty, Health, 
and Nutrition Division. IFPRI  discussion  paper  01240, 
December, 2012.  

Amaya N (2009). Effects of  access  to  information  on  farmer's 

market channel choice: The Case of Potato in Tiraque 
Sub-watershed (Cochabamba – Bolivia). Unpublished  



 
 

250        Afr. J. Agric. Mark. 
 
 
 
   MS Thesis. Blacksburg, VA: Virginia Polytechnic Institute 

and State University. 
Assefa A (2009). Market Chain Analysis of Honey 

Production: In Atsbi Wemberta District, Eastern Zone of 
Tigray National Regional State, Ethiopia. An MSc Thesis 
Presented to the School of Graduate Studies of Haramaya 
University. 85p. 

Astewel T (2010). Analysis of Rice Profitability and 
Marketing Chain: The Case of Fogera Woreda, South 
Gondar Zone, Amhara National Regional State, Ethiopia. 
An MSc Thesis Presented to the School of Graduate 
Studies of Haramaya University.  

Ayelech T (2011). Market Chain Analysis of Fruits for 
Gomma Woreda, Jimma Zone, Oromia National Regional 
State. M.Sc Thesis Presented to School of Graduate 
Studies, Haramaya University.p110. 

Bardasi EC, Mark Blackden, Juan Carlos Guzman (2007). 
“Gender, Entrepreneurship, and Competitiveness in 
Africa.” Chapter 1.4 of Africa Competitiveness Report 
2007. Washington, DC: World Economic Forum, World 
Bank, and African Development Bank. 

Betelihem G (2013). Value Chain Analysis of Haricot Bean: 
The Case of Doba District, Western Hararghe Zone, 
Oromia National Regional State, Ethiopia M.Sc thesis to 
School of Agricultural Economic, Haramaya University. 

Bezabih E, Hadera G (2007). Constraints and Opportunities 
of Horticulture Production and Marketing in Eastern 
Ethiopia. Dry lands Coordination Group (DCG) Report No. 
46. 1P. 

Bezabih E (2008). Participatory Value Chain Analysis at 
Kombolcha District of Eastern Hararghe, Ethiopia. Draft 
Report, July, 2008. Addis Ababa. 

Bosena T (2008). Analysis of Cotton Marketing Chains: The 
Case of Metema Woreda, North Gondar Zone, Amhara 
National Regional State Ethiopia. MSc Thesis School of 
Agricultural Economics, Haramaya University. 

CSA (Central Statistical Authority) (2014). Agriculture 
Sample Survey 2013/2014 (2006 E.C) (May, 2014). 
Report on Area and Production of Major Crops (Private 
Peasant holdings, meher seasons). Addis Ababa Ethiopia, 
The FDRE statistical bulletin Volume 01-532. 

Dawit G (2010). Market Chain Analysis of Poultry. The Case 
of Alamata and Atsbi-Wemberta woredas of Tigray 
Region. MSc Thesis School of agricultutal Economics, 
Haramaya University. 50-56P. 

Ellis A, Claire M, Mark CB (2006). Gender and Economic 
Growth in Uganda: Unleashing the Power of Women. 
Directions in Development, Washington, DC: World Bank. 

Endale G, Gebremedhin W, Bekele K,  Lemaga B (2008). 
Post Harvest Management. in Root and Tuber Crops: The 
untapped resources, ed. W. Gebremedhin, G. Endale, and 
B. Lemaga, 113– 130. Addis Abeba: Ethiopian Institute of 
Agricultural Research. 

Fantahun A (2010). Malt Barley Market Chain Analysis in 
Wegera District, North Gonder, Ethiopia. An M.sc. Thesis 
Presented to the School of Graduate Studies of Haramaya 
University. 

FAO (Food and Agriculture Organization) (2006). 
Agriculture, Trade Negotiations, and Gender. Prepared by 

Zoraid Garcia, with contributions from Jennifer Nyberg and 
Shayama Owaise Saadat. Rome: FAO. (2008). 
International Year of the Potato. Hidden Treasure, Potato 
World. FAO, 2008. 

FAO (Food and Agriculture Organization of United Nations), 
(2010). Strengthening Potato Value Chains: Technical and 
Policy Options for Developing Countries PP. 43-55. 

FAOSTAT (Food and Agriculture Organization Statistics) 
(2007). FAOSTAT Agricultural Data. Agricultural 
Production, Crops, Primary. Subset Agriculture. United 
Nations Food and Agriculture Organization. 

Gezahagn K (2010). Value Chain Analysis of Groundnut in 
Easter Ethiopia. M.Sc thesis, School of Agricultural 
Economics, Haramaya University. 

Gizachew  G (2005). Dairy Marketing Patterns and 
Efficiency: A Case Study of Ada’a Liben District of Oromia 
Region, Ethiopia. MSc Thesis School of Agricultural 
Economics, Harmaya University. 

Gujarati DN (2003). Basic Econometrics. 4th Edition. 
McGraw Hill, New York. pp.563-636. 

Gujarati DN, Sangeetha (2007). “Basic Econometrics” 
(fourth edition). Tata MacGraw–Hill publishing company 
limited, New Delhi. 

IYP (International Year of the Potato), (2008). International 
Year of the Potato, FAO. 

Kindie A (2007). Sesame Market Chain Analysis: The case 
of Metema Woreda, North Gonder Zone, Amahara 
National Regional State. An M.Sc Thesis Presented to the 
School of Graduate Studies of Haramaya University. pp 
38-41. 

 Komarek A (2010). The Determinants of Banana Market 
Commercialization in Western Uganda. Afr. J. Agri. Res. 
5(9): 775-784. 

Larsen MN (2006). Market Coordination and Social 
Differentiation: A Comparison of Cotton-Producing 
Households in Tanzania and Zimbabwe. J. Agrarian 
Change 6(1):102-131.  

Legesse D (1992). Analysis of Factors Influencing Adoption 
and the Impact of Wheat and Maize Technologies In Arsi 
Nagele, Ethiopia. M.Sc. Thesis. 

Lewis TC,  Wade BB, Kim BA, EmilioT (2008). Gender 
Difference in Marketing Styles. J of Agri. Eco. Vol. 38: pp 
1-7. 

Mahilet M (2013).  Value Chain Analysis  of  Malt  Barley: 
The  Case  of  Tiyo  and  Lemu-Bilbilo  Districts  in  Arsi  

Zone, Oromia National Regional State, Ethiopia. M.Sc 
Thesis of Agricultural Economic, Haramaya University.  
pp. 42-48. 

Makhura MN, Kristen J, Delgado C (2001). Transaction 
Costs and Small Holder Participation in the Maize Market 
in the Northern Province of South Africa. pp 463-467. 
Seventh Eastern and Southern Africa Regional Maize 
Conference. 11th -15th February, 2001. 

Mamo G, Degnet A (2012). Patterns and Determinants of 
Livestock Farmers’ Choice of Marketing Channels: Micro-
level Evidence. EEA/EEPRI working paper, Addis Ababa. 

Medhin G, Giorgis W, Endale G, Kiflu B, Bekele K (2001). 
Country Profile on Potato Production and Utilization: 
Ethiopia.  Ethiopian Agricultural Research Organization  



 
 

Abitew et al.          251 
 
 
 
  (EARO), Holetta Agricultural Research Centre, National 

Potato Research Program. 
Muhammed U (2011). Market Chain Analysis of Teff and 

Wheat Production in Halaba Special Woreda, Southern 
Ethiopia. M.Sc Thesis Presented to the Graduate School 
of Haramaya University. Ethiopia.   

Omiti J, Otieno D, Nyanamba T, Cullough EMc (2009). 
Factors Influencing the Intensity of Market Participation by 
Smallholder Farmers: A Case Study of Rural and Peri-
Urban Areas of Kenya. Afjare, 3(1): 57-82. 

Ouman E, Jagwe J, Obare AG, Abele S (2010). 
Determinates of Smallholder Farmers’ Participation in 
Banana Markets in Central Africa: The Role of 
Transactions Costs. Agric. Econ. 41: 111-122. 

Pooja D, Rathod MK (2013). Empowerment of Rural Women 
through the Activities of Mahila Arthik Vikas Mahamandal. 
Indian J. App. Res, 3(8), 4-6.  

Rahmeto N (2007). Determinants of Adoption of Improved 
Haricot Bean Production Package in Alaba Special 
Woreda, Southern Ethiopia. Msc. Thesis to School of 
Agricultural Economic, Haramaya University. 

Rehima M (2006). Analysis of Red Pepper Marketing: The 
case of Alaba and Siltie in SNNPRS of Ethiopia. An MSc 
Thesis Presented to the School of Graduate Studies of 
Harmaya University. 

Rehima M, Dawit A (2012). Red Pepper Market in Siltie and 
Alaba in SNNPRS of Ethiopia: Factors Affecting 
Households’ Marketed Pepper. Int. Res. J. Agric. Sci. Soil 
Sci. Vol. 2(6): pp. 261-266.  

Shilpi F, Umali-Deininger D (2007). Where to sell? Market 
Facilities and Agricultural Marketing. Policy Research 
Working Paper series 4455, The World Bank. 

Siziba S, Nyikahadzoi K, Diagne A, Fatunbi AO, Adekunle 
AA (2011). Determinants of Cereal Market Participation by 
sub-Saharan Africa Smallholder Farmer. Learning Publics 
J. Agr. Environ. Studies, 2 (1):180-193. 

Storck H, Bezabih E, Berhanu A, Borowiccki A, Shimelis WH 
(1991). Farming Systems and Resource Economics in the 

Tropics: Farming System and Farm Management 
Practices of Small Holders in the Hararghe Highland. Vol. 
11. 

Tadesse N (2011).  Value Chain Analysis of Vegetables in 
Daro Lebu District of West Hararghe Zone, Oromia 
Region, Ethiopia. An MSc Thesis Presented to the School 
of Graduate Studies of Harmaya University. 

Tekalign T (2010). Potato Value Chain Analysis in Eastern 
Ethiopia: A study conducted as part of a project entitled 
“Value Chains for Poverty Reduction in the Agri-Food 
Sector-Problem-Based Learning in Higher Education” 
which is within the Edulink program of Europe Aid”, 
coordinated by Humboldt Universität zu Berlin, Germany. 
December, 2010. 

Tesfaye Z, Shiferew T (2001). Determinants of Adoption of 
Maize Technologies and Inorganic Fertilizer in Southern 
Ethiopia. Research Report No. 39. Ethiopia Agricultural 
Research Organization (EARO). 54p. 

Wolday A (1994). Food Grain Marketing Development in 
Ethiopia after Reform 1990. A Case study of Alaba Siraro. 
A PhD Dissertation Presented to Verlag Koster University. 
Berlin. 

Wolelaw S (2005). Factors Determining Supply of Rice: A 
Study in Fogera District of Ethiopia. An MSc. Thesis 
Presented to the School of Graduate Studies of Alemaya 
University. 

World Bank (2007a). “Cultivating Knowledge and Skills to 
Grow African Agriculture: A Synthesis of an Institutional, 
Regional, and International Review.” World Bank, 
Washington, DC. 

World Bank (2007b). “Gender and Economic Growth in 
Kenya: Unleashing the Power of Women. Directions in 
Development.” World Bank, Washington, DC.  

Yeshitila A (2012). Analysis of Vegetable Marketing in 
Eastern Ethiopia: The Case of Potato and Cabbage in 
Kombolcha woreda, East Hararghe Zone, Oromia National 
Regional State, MSc. Thesis School of Agricultural 
Economics, Haramaya University. 

 
 
 
 


