by tesfaye tura debela - publication.eiar.gov.et:8080
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1
AMBO UNIVERSITY
SCHOOL OF GRADUATE STUDIES
COLLEGE OF BUSINESS AND ECONOMICS
DEPARTMENT OF ECONOMICS
DETERMINANTS OF ONION COMMERCIALIZATION AMONG SMALLHOLDER
FARMING HOUSEHOLDS: THE CASE OF FENTALE DISTRICT, EAST SHOA
ZONE, OROMIA REGIONAL STATE, ETHIOPIA.
BY
TESFAYE TURA DEBELA
June, 2021
Ambo, Ethiopia
i
AMBO UNIVERSITY
COLLEGE OF BUSINESS AND ECONOMICS
DEPARTMENT OF ECONOMICS
DETERMINANTS OF ONION COMMERCIALIZATION AMONG SMALLHOLDER
FARMING HOUSEHOLDS: THE CASE OF FENTALE DISTRICT, EAST SHOA
ZONE, OROMIA REGIONAL STATE, ETHIOPIA
BY: TESFAYE TURA DEBELA
A THESIS SUBMITTED TO THE DEPARTMENT OF ECONOMICS IN
PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF
THE DEGREE OF MASTER OF ARTS IN DEVELOPMENT STUDIES
ADVISOR: FIRAFIS HAILE (ASSISTANT PROFESSOR)
June, 2021
Ambo, Ethiopia
ii
APPROVAL SHEET
Summited by:
Tesfaye Tura Debela ___________ ________
PG Candidate Signature Date
Approved by
1. Advisor
Firafis Haile (Ass. Professor)___ __________ ________
Name Signature Date
2. College/Institute Dean
__________________________ ___________ _______
Name Signature Date
3. Director School of Graduate studies
_______________________________ _________ ________
Name Signature Date
iii
AMBO UNIVERSITY
SCHOOL OF GRADUATE STUDIES
CERTIFICATION SHEET
As a Thesis advisor, I hereby certify that I have read and evaluated this thesis
prepared under my guidance by Tesfaye Tura Debela entitled ‘‘The Determinants of
Onion Commercialization among Smallholder Farming Households: The Case of
Fentale District, Oromia Regional State, Ethiopia’’. I recommend that it be submitted
as fulfilling the thesis Requirements.
Firafis Haile (Ass. Professor) ___________ ________
Name of Major Advisor Signature Date
As mentioned of the Board of Examiners of the MA. Thesis open defence examined.
We certified that we have read and evaluated the thesis prepared by Tesfaye Tura
Debela and examined the candidate. We recommend that the thesis be accepted as
fulfilling the thesis requirements for the award of the degree of Master of Art in
Development Studies.
Yohannis Bekele _______________ ___________
Chairperson Signature Date
Dr. Warkaw Legesse ______________ ___________
Internal Examiner Signature Date
Dr. S. Sivakuma _______________ __________
External Examiner Signature Date
iv
DECLARATION
I undersigned, I declare and affirm that this Thesis is my own work. I have followed
all ethical and technical principles of scholarship in the preparation, data collection,
data analysis and compilation of this thesis. Any scholarly matter that is included in
the Thesis has been given recognition through citation.
This thesis is submitted in the partial fulfilment of the requirements for MA degree in
Development Studies at Ambo University. The Thesis is deposited in the Library of
the University and is made available to borrowers under the rules of the Library. I
solemnly declare that this Thesis has not been submitted to any other institution
anywhere for the award of any academic degree, diploma or certificate.
Brief quotations from this Thesis may be made without special permission provided
that the accurate and complete acknowledgement of the source is made. In all other
instances, however, permission must be obtained from the author of the Thesis.
Name: Tesfaye Tura
Signature ____________________
Submission date: June, 2021
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ACKNOWLEDGEMENT
First and foremost, I want to give thanks to God, who gave me with his endless love
and blessing in my life.
I would like to extend my heartfelt thanks to my advisor Firafis Haile
(Assistant Professor), for his constructive instruction, intellectual and technical
comments, guidance and unreserved support from proposal development up to the
completion of the thesis. A special appreciation also goes to Tefera Goshu (PhD
candidate) at Addis Ababa University for his valuable and constructive comments
added in the thesis.
I would like to thanks my employer Ethiopian Agricultural Research Institute (EIAR)
for giving me time off my duties to pursue further studies, logistic and other financial
support provided to me. My sincere thanks also goes to Mr. Derese Teshome, the
Directorate of Agricultural Extension and Communication Research process at EIAR,
for his unreserved support and facilitation given for the success of my study.
Next, my thanks also goes to Werer Agricultural research centre staffs, Mr Adem
Kediri, Mr. Mehiret Amaneal, Mr. Donis Gurmessa, Mr. Tamiru Olbana, and Mr.
Megersa Diriba who stand behind me by their advice and support me stationaries for
the success of this study. My appreciation and great thanks also goes to Mr. Fekadu
Robi for his support in indicating me the reference management software application.
I would like to acknowledge Fentale District Pastoral Development Office staffs
specially Mr. Berhanu, Mr. Beker and Mr. Bulga Hawas who have given me
necessary data and information needed for the research work during the study.
Furthermore, special thanks go to Mr. Abdala Ibrahim who helped me in facilitating
the data collection process, and thanks to all enumerators who help me in collecting
data.
I am grateful to my beloved Hana Chala and my uncle Fekadu Tolessa and Kumala
Tolessa who have given me moral support, strength and encouragement in completing
my thesis on time.
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TABLE OF CONTENTS
APPROVAL SHEET ................................................................................................... ii
CERTIFICATION SHEET ....................................................................................... iii
DECLARATION ......................................................................................................... iv
ACKNOWLEDGEMENT ........................................................................................... v
TABLE OF CONTENTS .......................................................................................... vi
LIST OF TABLES ...................................................................................................... ix
LIST OF FIGURES ..................................................................................................... x
LIST OF APPENDICES ............................................................................................ xi
ACRONYMS AND ABBREVIATIONS .................................................................. xii
ABSTRACT .............................................................................................................. xiii
1. INTRODUCTION .................................................................................................... 1
Background of the Study .................................................................................... 1
Statement of the Problem .................................................................................... 4
Objectives of the study ........................................................................................ 6
1.3.1. General Objective .......................................................................................... 6
1.3.2. Specific Objectives ....................................................................................... 6
Research Questions ............................................................................................. 6
Significance of the Study .................................................................................... 7
Scope and Limitation of the Study ...................................................................... 7
Organization of the Study ................................................................................... 8
Operational definition of key concepts ............................................................... 8
2. LITERATURE REVIEW ....................................................................................... 9
Concept of Agricultural Commercialization ....................................................... 9
Smallholders Commercialization ...................................................................... 10
Method of measuring smallholders commercialization .................................... 11
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Vegetables commercialization in Ethiopia ....................................................... 13
Onion production and marketing in Ethiopia .................................................... 14
Challenges and opportunities of onion production and marketing in Ethiopia. 16
2.6.1. Challenges of onion production and marketing .......................................... 16
2.6.2. Opportunities for onion production and marketing ................................... 17
Theoretical Framework ..................................................................................... 18
2.7.1. Utility Maximization theory ....................................................................... 18
2.7.2. Comparative Advantage theory.................................................................. 19
Review of Empirical Studies ............................................................................ 19
2.8.1. Demographic Factors .................................................................................. 20
2.8.2. Economic Factors ....................................................................................... 22
2.8.3. Institutional Factors .................................................................................... 24
2.8.4. Market Factors ........................................................................................... 25
2.8.5. Households specific Factors ....................................................................... 26
Conceptual Framework ..................................................................................... 26
3. RESEARCH METHODOLOGY ......................................................................... 28
Description of the study area ............................................................................ 28
Research Design ................................................................................................ 30
Sampling Technique and Sample Size .............................................................. 30
Sources of Data ................................................................................................. 32
Types of Data .................................................................................................... 32
Methods of Data Collection .............................................................................. 32
3.6.1. Interview Schedule ..................................................................................... 32
3.6.2. Focus Group Discussion (FGD) ................................................................. 33
3.6.3. Key Informant interview (KII) ................................................................... 33
Methods of Data Analysis ................................................................................. 34
3.7.1. Descriptive Statistics ................................................................................... 34
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3.7.2. Econometric Model .................................................................................... 34
Definition of Variables used for Analysis......................................................... 38
4. RESULT AND DISCUSSION .............................................................................. 42
Demographic and Socioeconomic Characteristics of sample households ........ 42
Challenges and opportunities of onion production and marketing ................... 50
4.2.1. Challenges of onion production and marketing .......................................... 50
4.2.2. Opportunities of onion production and marketing ..................................... 53
Results from Econometric model Analysis ....................................................... 55
4.3.1. Determinants of onion market participation decision among smallholders
farming households .............................................................................................. 56
4.3.2. Determinants of smallholders onion market participation level ................ 62
5. SUMMARY, CONCLUSION AND RECOMMENDATION ............................ 67
Summary ........................................................................................................... 67
Conclusion ........................................................................................................ 68
Recommendations ............................................................................................. 70
References ................................................................................................................... 72
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LIST OF TABLES
Table 1: Proportional Sample Size.............................................................................. 31
Table 2: Summary of data analysis methods .............................................................. 37
Table 3: Summary of Explanatory Variables ............................................................... 41
Table 4: Results of descriptive statics for continuous variables .................................. 43
Table 5: Result of descriptive statics for categorical explanatory variables ................ 45
Table 6: Result of Probit regression on onion market participation decision of
households .................................................................................................................... 57
Table 7: Result from truncated regression of determinants of onion market
participation level ......................................................................................................... 62
x
LIST OF FIGURES
Figure 1: Conceptual Framework ................................................................................ 27
Figure 3: Bar chart indicate education level of respondent households ...................... 46
Figure 6: Pie chart indicate respondents sources of non /off -farm income ............... 49
Figure 7: Bar chart represents challenges of onion production at study area ............. 51
Figure 8: Bar chart represent the onion marketing challenges at the study area ......... 52
Figure 9: Onion production and marketing opportunities at the study area................. 54
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LIST OF APPENDICES
Appendix 1: VIF for multicollinearity diagnosis (continues variables) ...................... 80
Appendix 2: Contingency coefficient for multicollinearity diagnosis (dummy
variables) ...................................................................................................................... 80
Appendix 3: Conversion factors used to compute tropical livestock unit ................... 81
Appendix 4: The Interview schedule for sample households ...................................... 82
Appendix 5: checklist for Focus Group Discussion..................................................... 86
xii
ACRONYMS AND ABBREVIATIONS
Agro BIG Agribusiness Induced Growth
ATA Agricultural Transformation agency
CCI Crop commercialization index
CSA Central Statistics Agency
DAs Development Agents
ERCA Ethiopian Revenues and Customs Authority
ETB Ethiopian Birr
FAO Food and Agricultural Organization
FAOSTAT Food and Agriculture Organization Statistical Division
FDSEPD Fentale District Socio-economic profile Document
FGD Focus Group Discussion
FWPADO Fentale Woreda Pastorals and Agro- pastorals Development office
GDP Gross Domestic Product
GIS Geographical Information Systems
GOs Government Organizations
GTP Growth and Transformation Plan
HH Household Head
Kg Kilogram
KII Key Informant Interview
m.a.s.l meter above sea level
NPC National Plan Commission
SPSS Statistical Package for the Social Science
TLU Tropical Livestock Unit
USA United States of America
USD United states dollar
VIF Variance Inflation Factor
WUAs Water Users’ Association
xiii
ABSTRACT
This study focuses on analysing the determinants of onion output commercialization
among smallholder farming households. Samples of 180 onion producer smallholder
households were selected through multi-stage random sampling from the three
kebeles of Fentale district. Sources of data were both the primary and secondary
sources. The primary data were collected through Interview schedule, FGD and KIIs
methods. Quantitative data were analysed by descriptive and double hurdle model.
The result of the descriptive statistic reveals that the high cost of inputs, fluctuation in
irrigation access, disease and pest, the input supply shortage, high labour cost, flood
problem and informal sources of seed were the challenges of onion production at the
study area. Besides the high income gained from onion, access to irrigation, good
weather condition and the high yield of onion from a small plot were the major
opportunities to produce and marketing the onion at the area. The result from the 1st
phase of the double hurdle, probit regression, revealed that the total farm holding,
farm allocated for onion, credit access, access to extension and market information
were statistically significant and influence household onion market participation
decision while the result from the 2nd phase, truncated regression, show the age of
household head, sex, farm allocated to onion, irrigation access, number of oxen
owned and distance to the nearest market were influencing smallholder onion market
participation level. Finally, it is recommended that the GOs and other responsible
bodies should ensure the equal distribution of irrigation water for both upper and
lower streams, and strengthen inputs supply chains.
Key words: Commercialization; Double hurdle; Fentale; Onion; Smallholders;
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1.INTRODUCTION
Background of the Study
Agriculture is the main economic pillars of the Ethiopian economy and the overall
economic growth of the country is highly dependent on the success of the agriculture
sector. The sector represents 42.7% of the Gross Domestic Products of the country
and generates about 90% of the foreign exchange earnings of the country.
Additionally, it supplies over 70% of raw materials for domestic industries and about
80% of the population gains their livelihood directly or indirectly from agricultural
production (Alemu and Berhanu, 2018; Nigussie et al., 2015; NPC, 2016; Zehirun et
al., 2015)
However, Ethiopian agriculture is dominated by smallholder farming households in
which 85% of households farming less than 2 hectares while 40% of them are produce
on less than 0.5 hectares of farm (Baltissen and Betsema, 2016).The same authors
explained as the high dependency on rain-fed, low fertilizer application rate, less
wide-spread use of improved seed varieties as well as land degradation combined with
continuously increasing population pressure leading to low level of production to
meet the consumption requirement of the households.
Being one of the emerging fast growing economies in the world, the country requires
maximizing the potential of the agricultural sector and necessarily increasing the level
of smallholders' agricultural productivity which is existed at the base level due to
several socio-economic bottlenecks (Bedaso et al., 2012; Etafa, 2016). Among the
main bottlenecks, poor access to inputs, poor irrigation system ,and technology, lack
of adequate market price, and inadequate linkage between market actors and
smallholders’ farmers contribute to low level of agricultural productivity in
developing countries in general and Ethiopia in particular (Tilaye, 2010).
In Ethiopia, promoting the commercialisation of agricultural production is considered
as the corner stone of the rural development and poverty reduction strategies of the
government (Pender and Alemu, 2007). Ethiopia has liberalized its economy and
developed poverty reduction strategies that underpin market-led strategies for broad
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based agricultural development and economic growth (Boka, 2017). Policy makers
view it as an essential component of agricultural modernisation, specialisation, and
structural transformation of the economy towards more rapid and sustainable growth.
Commercialization of agriculture refers to the progressive shift from household
production for auto-consumption to production for sale in the market. According to
Von Braun and Kennedy (1994) commercialization of subsistence agriculture takes
many forms. They state that “Commercialization can occur on the output side of
production with an increased marketed surplus, but it can also occur on the input side
with an increased use of purchased inputs to increase agricultural products to
commercialize agricultural products”.
A farm household is assumed to be commercialized if it is producing a significant
amount of cash commodities, allocating a proportion of its resources to marketable
commodities or selling a considerable proportion of its agricultural outputs (Muricho
et al., 2017; Poulton, 2018). According to Gebremedhin and Jaleta (2010b) the
meaning of commercialization goes beyond supplying surplus products to markets. It
has to consider both the input and output sides of production, and the decision-making
behaviour of farm households in production and marketing simultaneously.
Despite various agricultural policy reforms in Africa in general and in Ethiopia in
particular, the majority of farmers are still subsistence oriented with a low level of
participation in agricultural markets (Jaleta et al., 2009; Sokoni, 2008). Though the
Government of Ethiopia sees the horticulture sector as one of the high priorities for
export as well as the domestic market, its production is another subsistence farming
practiced by smallholder farmers in Ethiopia and its cultivation is considered as
supplementary to the production of main crops.
Smallholder farmers are the principal suppliers of fruits and vegetables which
accounts for over 95% of the national production of the country (Gebreselassie,
2003). However, despite a long history of irrigated vegetables production, commercial
production has expanded significantly since 2005 when national agricultural strategies
began to favour the high value cash crops and productivity enhancement.
3
Onion vegetable was introduced in Ethiopia in the early 1970 when foreigners
brought it in (Nikus and Mulugeta, 2010) and it is smallholders based commercial
vegetable widely-grown in the country. It is one of the cash crops grown in different
parts of the country, mainly by small farmers, private growers and state enterprises.
The Awash Valley and the Lake Tan regions are the main areas where the bulk of dry
bulbs and onion seed are produced. National level onion production reached 230,700
tons in the 2014-15 production season (CSA, 2015)
In Ethiopia, Onion consumption is regular. It is important in the food seasoning and in
daily stews called ‘wots’ as well it contributes to human health. The production of
vegetables in general and onion in particular, has a comparative advantage
particularly under conditions where arable land is scarce and labour is abundant.
Hence, Onion production in our country is at an increasing rate both in farm area
coverage and the amount produced (Agumas, 2019).
Understanding the extent of smallholder commercialization and its contributing
factors, therefore, has important policy implications. However, smallholder farmers
face many constraints that impede them from taking advantage of market
opportunities (Fischer and Qaim, 2012). Besides lack of marketing knowledge and
skills to sell their products, the informal and inefficient supply chain arrangements in
the traditional sub-sector provide low income and little incentives for growers and
their families. This hinders them to improve their production and marketing activities
and as a result, many of them often opt for lower prices at the farm gate or in the local
markets (Gyau et al., 2016).
Despite its increasing rate of production and economic contribution there is a dearth
of study on the commercialization level of onion output in Ethiopia in general and in
the study area in particular. Therefore, the objective of this study was to analyse the
determinants of onion output commercialization among small-holder farm households
in the study area.
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Statement of the Problem
Horticultural crops have been attracted by many poor farmers around the world. Thus,
worldwide production of fruit and vegetable crops has grown faster than that of cereal
crops (Lumpkin et al., 2005). Producers involved in horticultural production in
general and onion in particular usually earn much higher farm incomes as compared
to cereal producers and per capital farm income has been reported up to five times
higher (CSA, 2016; Lumpkin et al., 2005; Matondi and Chikulo, 2012). Indeed,
horticultural products are considered to be income-boosting alternatives to the basic
grains for smallholder farmers and they contribute to increasing the employment
opportunities.
Onion is an important vegetable and commercial crop produced on small scale in
Ethiopia. It is used as spices and condiments for flavouring various dishes in day-to-
day activities. According to Aklilu (1994) onion grows between 500-2400 m.a.s.l in
the country. Hence, its production is become increasing in different agro-ecologies of
the country in small-scale production systems that make it one of the important
components of commercialization for rural and urban smallholder households as
sources of both daily nutrition and income.
Ethiopia has a great potential to produce the onion throughout the year. Unlike shallot
and garlic, which is rain-fed, onion is produced under irrigation during the dry season
of the year. It is also produced in the home gardens and commercially in different
parts of the country at small scale commercial firms. From production point of view,
onion is comparatively easy to produce which provided it grown in the dry season
when diseases are less prevalent (Nigussie et al., 2015).
Ethiopia is following the strategy that brings dynamic change to transform the
traditional and subsistence agriculture of smallholder farmers to commercial
agriculture by linking the farmers to the market (Hagos and Geta, 2016; Järnberg,
2016). However, due to unavailability of timely and reliable market information for
smallholder farmers, the most marketing transaction heavily relying on intermediaries,
are the major problems (Zewge et al., 2014). On the other hand, high transaction cost
deters the smallholders’ market participation and promote mainly own consumption.
5
This scenario is no stranger for onion vegetable crop in Ethiopia in general and at the
study area in particular.
Output market participation decision and the level of participation of smallholders’
onion producers are subject to combined effect of socio-economic, demographic and
institutional factors in the country in general and at the study area in particular. The
study area, Fentale district, is one of the potential areas for onion vegetable production
which has a significant contribution to the livelihood of smallholder farmers of the
area. Indeed, Onion contribute to enhance the income of the majority of the
smallholder producers as well ensures their food security.
However, despite the production potential and income contribution of the
commodity, there is a dearth of study on onion commercialization status in Ethiopia in
general and at the study area in particular. Most of the previous studies on the
commercialization of smallholder farming in Ethiopia focus on grain crops like wheat,
maize and teff (Alemu and Bishaw, 2015; Ali et al., 2016; Bekele and Alemu, 2015).
On the other hand, some others studies carried out in Ethiopia focused on the
commercialization of horticultural crops in general without particular attention to
vegetables in general and onion in particular (Tufa et al., 2014; Wondowussen and
Bekabil, 2014)
Besides the biased focus of the previous studies on the commercialization of grain
crops and horticulture as a general, a few earlier study undertaken on onion
commercialization in the country were diverted their focus towards the highland rain
fed onion and hence this study aims to generate information on the determinants of
the commercialization of the lowland irrigation based onion produced. Though the
onion production in fentale district is high, the current information related to the
determinants of smallholder households onion output commercialization and the level
of commercialization is lacking.
Therefore, this study was conducted with the main purpose of analyse the factors
determine the decision and level of the onion output market participation among
smallholder onion producers at the study area.
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Objectives of the study
1.3.1. General Objective
The general objective of the study was to analyse the determinants of onion output
commercialization among smallholder farming households at Fentale district.
1.3.2. Specific Objectives
The specific objectives of the study are:
➢ To assess the production and marketing challenges of onion at the study area.
➢ To explore the onion production and marketing opportunities at the study area.
➢ To analyse the determinants of the onion market participation decision among
smallholders' farming households at the study area.
➢ To analyse the determinants of the onion market participation level among
smallholders’ farming households at the study area.
Research Questions
➢ What are the challenges of onion production and marketing at the study area?
➢ What are the opportunities of onion production and marketing at study area?
➢ What are the determinants of onion market participation decision of
smallholder farming households at the study area?
➢ What are the determinants of the onion market participation level among
smallholder farming households at the study area?
7
Significance of the Study
Despite the increasing demand for the onion product both at inside and outside
markets, smallholders’ onion output market participation decision and the level of
participation is affected both by external and internal factors. Clearly analyses these
factors solve the supply shortage of onion product in one way and boost the income
for onion producers on the other. According to Alamerie et al., (2014) in the context
of the efforts to achieve safe, sound and sustainable production of vegetables,
identification of risk sources plays a crucial role.
Hence, the output of this study would be used as input which significantly help as
first-hand information sources for policy makers, planners and development
practitioners who primarily work to improve the livelihoods of smallholders’ onion
producers. Moreover, this study would contribute as a first hand reference for the
further study of the same field or related themes of similar areas. Since, the results and
recommendations made available at the district level, the development agents, the
extension educators, the technical assistants and extension staffs can use as a guide for
their activity in the area of onion output commercialization.
Finally, this study would be contributed as it indicates the areas of policy intervention
to solve the identified problem by the study finding.
Scope and Limitation of the Study
The study was carried out in one area of Oromia regional state, East shoa zone of
Fentale district. Hence, the scope of the study is limited to one district in area
coverage. Additionally, the study was focused on onion producer households to
analyse the factors determine their participation and extent of participation in onion
output market. So it also limited to onion producer smallholder households in the
scope of population coverage.
Concerned with the limitation of the study it is limited to only onion vegetable crop in
which the finding from the study cannot generalized for other crops produced at the
study area. Besides the data used for the study was took at one point of time focused
8
on one production year. This means the data used for the study was cross-sectional
data that received at one time duration from the onion producer households.
Therefore the study is limited to only onion vegetable and in time duration of data
taken at one moment.
Organization of the Study
The study organized in to five major chapters. Chapter one presents the introduction
part of the study, which focused mainly on the background, statement of the problem,
objectives, significance and scope of the study. Chapter two discussed the literature
review part. The literature review deals with different literatures about the concept of
commercialization, onion production and marketing in Ethiopia, empirical studies
related to agricultural commercialization and theoretical and conceptual framework of
the study. Chapter three deals with the methodology part of the study. Here the
description of the study area, research design, sources and types of data, and methods
of data collection and analysis were discussed in detail. In chapter four the result from
the demographic and socio-economic of the respondents, and also the challenges and
opportunities of onion production and marketing were discussed. At the end of
chapter the result from econometric were discussed. Finally, chapter five discussed
the conclusion of the finding and recommendations.
Operational definition of key concepts
Market participation- occurs when the households offered their produced output for
sale or use of purchased inputs for production or both at a time simultaneously
(Gebremedhin and Jaleta, 2010b)
Output-Market participation- is refers to offering the produced commodity to sale
at a specific market price (Hailegiorgis, 2011).
Farming households- refers to the households that depend on agriculture as a
primary source of their livelihoods (CSA, 2015)
Smallholder household- refer to the household with a low asset base and operating
less than two hectares of the cropland (Hagos and Geta, 2016)
Marketing- in this paper, it refers the process of selling the production output either
to the traders or end-consumers (Hailegiorgis, 2011).
9
2.LITERATURE REVIEW
Concept of Agricultural Commercialization
Commercialization as a concept is multi-dimensional and no one definition has been
able to capture all its facets. Jones Govereh and Nyoro (1999) define agricultural
commercialization as “the proportion of agricultural production that is marketed”.
According to these researchers, agricultural commercialization aims to bring about a
shift from production for solely domestic consumption to production dominantly
market-oriented. However, agricultural commercialization is more than marketing
agricultural outputs as commercialization can also occur on the input side with the use
of purchased inputs in agricultural production (von Braun et al., 1994; Von Braun and
Kennedy, 1994).
Agricultural commercialization encompasses the decision-making behaviour of farm
households in production and marketing simultaneously. According to Demeke and
Haji (2014) targeting markets in their production decisions, rather than being related
simply to the amount of product they would likely sell due to surplus production is the
commonly accepted concept of commercialization. Therefore, commercialization
occurs when production is in response to market signals and on the basis of
comparative advantage, whereas subsistence production is based on production
feasibility and subsistence requirements with only surplus product sold after meeting
own consumption needs. Sometimes a proportion of the so called traditional food
crops are sold while on the other hand, some proportions of the so called traditional
cash crops are retained for home consumption (Olwande et al., 2015)
However, there is also the prevalence of commercialization in subsistence agriculture
where farm households supply certain proportion of their output to the market from
their subsistence level (Baltissen and Betsema, 2016; Gebre-Ab, 2006). In most of the
literatures, if not all, definitions of agricultural commercialisation is the degree of
participation in the output market, with the focus very much on cash incomes
(Gebreselassie, 2003). According to Encyclopaedia, Colombia University Press
dictionary definition quoted in Leavy and Poulton (2007) spatial definition describing
commercial agriculture as the growing of crops for sale outside the community.
10
From methodological and analytical perspective, the concept of agricultural
commercialization broadened by asserting that it is a combination of both market
orientation and market participation (Gebremedhin and Jaleta, 2010b). Market
orientation in this context is defined as agricultural production decision based on
market signals while market participation is simply the produce offered for sale and
use of purchased inputs. From this approach, market orientation seems to be more
inclined toward profit maximization while market participation appears to aim at
utility maximization. Therefore, commercialization is a combination of market
oriented production and the actual amount bought from or offered to the market for
sale.
Smallholders Commercialization
Commercializing smallholder agriculture is an indispensable pathway towards
economic growth and development for most developing countries relying on the
agricultural sector. Commercialization of smallholder agricultural producers through
increased participation in the output markets has been promoted as one of the best
strategies to address low agricultural productivity that has led to the high levels of
poverty and food insecurity among rural farming households in developing countries
(Amsalu, 2014; Jaleta et al., 2009).
In Ethiopia, smallholder farmers account for more than 85% of the rural population
that relies on agricultural production (Gebre-Ab, 2006; Tufa et al., 2014). To this
response Ethiopia has liberalized its economy and developed poverty reduction
strategies that underpin market-led strategies for broad based agricultural
development and economic growth (Boka, 2017; Jaleta et al., 2009). Fundamentals of
the strategy included the shift to produce the high value crops, a special focus on
high-potential areas, facilitating the commercialization of smallholder agriculture, and
supporting the development of large-scale commercial agriculture where it was
feasible.
Within the broader strategy, smallholder farming is believed to be the key to the
livelihoods of many rural households (Hailu et al., 2015; NPC, 2016; Zehirun et al.,
2015). Given the total sum of the population that directly and indirectly make their
livelihoods from the sector; its development is viewed as a means to improve the
11
living standards of smallholders and generate economic growth. Smallholder
commercialisation can occur in two ways; either by increasing productivity and
marketed surplus of the food crops or by focusing on cash crops (Osmani and
Hossain, 2015).
Some scholars (Gebre-Ab, 2006; Muriithi, 2013; Samuel and Kay, 2008) consider
smallholder commercialization as a constructed of two indices, which include the
number of food crops and cash crops produced that allows production diversity, with
cash crops such as chat, coffee, cotton, ‘enset’ (false banana), hops (‘gesho’), sugar-
cane, tea and tobacco. Horticulture production is an important source of income for
smallholder farmers and demand for the products is raising in both domestic and
international markets thus increase smallholder farmers’ participation in the market.
Horticultural crop commercialization (Jebesa, 2019) in general and onion in
particular results in higher incomes for smallholder producers, as it has higher
returned when compared with other staple crops. Hence, most of the past literatures
define agricultural commercialisation as the degree of participation in the output
market. Therefore, in this research the researcher is interested in analysing the
determinants of onion commercialization by focused on onion output market
participation side.
Method of measuring smallholders commercialization
The relevance of measuring the level of smallholder commercialization arises from
the interest to make comparisons of households according to their degree of
commercialization. In addition, it also helps to gauge to what extent a given farm
household is commercialized in its overall production, marketing and consumption
decisions, and to analyse the determinants of commercialization (Jaleta et al., 2009).
Different approaches are used to measure household commercialization level (Von
Braun and Kennedy, 1994).
Commercialization can be measured along a continuum from zero (total subsistence-
oriented production) for home consumption to one (100% production is sold) to the
market for generating incomes to the household (Getahun, 2020). This is called
12
household Crop Commercialization Index (CCI) which is computed as the ratio of
gross value of all crop sales over gross value of all crop production multiplied by
hundred. The advantage of using this approach is that it avoids the use of crude
distinctions as commercialized and non-commercialized farms (Jones Govereh and
Nyoro, 1999).
However, this index had its limitations. For instance, consider the case when a farmer
producing one quintal of any crop and sales that all and another farmer producing ten
quintals of the same crop and sales only two quintals. The CCI will tell us that the
first farmer is fully commercialized (100%) while the second is semi-commercialized
(20%). This interpretation does not make sense in such circumstances. Even though
this limitation of using CCI is wrong nothing, there is still some room to use it in
practice especially in the context of developing countries where it is less likely to get
smallholders selling all of their output and very large farms selling none of their farm
output (Poulton, 2018).
As can be understood from the preceding discussion, the degree of participation in the
output market is the conventional way to measure commercialization. However, von
Braun et al. (1994) provide other dimensions to the measurement of
commercialization. Commercialization is calculated as percentage of the total produce
sold from a household or as a percentage of cash crops as compared to all crops
cultivated by household. These authors have specified the forms of commercialization
and integration into the cash economy from at least three different angles and
measured the extent of their prevalence at the household level with the following
ratios:
(1a) Commercialization of agriculture (output side)
= 𝐕𝐚𝐥𝐮𝐞 𝐨𝐟 𝐚𝐠𝐫𝐢𝐜𝐮𝐥𝐭𝐮𝐫𝐚𝐥 𝐬𝐚𝐥𝐞𝐬 𝐢𝐧 𝐦𝐚𝐫𝐤𝐞𝐭
𝑨𝒈𝒓𝒊𝒄𝒖𝒍𝒕𝒖𝒓𝒂𝒍 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝒗𝒂𝒍𝒖𝒆 (1)
(1b) Commercialization of agriculture (input side)
= 𝑽𝒂𝒍𝒖𝒆 𝒐𝒇 𝒊𝒏𝒑𝒖𝒕𝒔 𝒂𝒄𝒒𝒖𝒊𝒓𝒆𝒅 𝒇𝒓𝒐𝒎 𝒎𝒂𝒓𝒌𝒆𝒕
𝑨𝒈𝒓𝒊𝒄𝒖𝒍𝒕𝒖𝒓𝒂𝒍 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝒗𝒂𝒍𝒖𝒆 (2)
13
(2) Commercialization of rural economy
=
𝑽𝒂𝒍𝒖𝒆𝒔 𝒐𝒇 𝑮𝒐𝒐𝒅𝒔 𝒂𝒏𝒅 𝑺𝒆𝒓𝒗𝒊𝒄𝒆 𝒂𝒄𝒒𝒖𝒊𝒓𝒆𝒅
𝒕𝒉𝒓𝒐𝒖𝒈𝒉 𝒎𝒂𝒓𝒌𝒆𝒕 𝒕𝒓𝒂𝒏𝒔𝒂𝒄𝒕𝒊𝒐𝒏𝒔
𝑻𝒐𝒕𝒂𝒍 𝑰𝒏𝒄𝒐𝒎𝒆 (3)
(3) Degree of integration into the cash economy
=
𝑽𝒂𝒍𝒖𝒆 𝒐𝒇 𝒈𝒐𝒐𝒅𝒔 𝒂𝒏𝒅 𝒔𝒆𝒓𝒗𝒊𝒄𝒆𝒔𝒂𝒄𝒒𝒖𝒊𝒓𝒆𝒅 𝒃𝒚 𝒄𝒂𝒔𝒉 𝒕𝒓𝒂𝒏𝒔𝒂𝒄𝒕𝒊𝒐𝒏𝒔
𝑻𝒐𝒕𝒂𝒍 𝒊𝒏𝒄𝒐𝒎𝒆 (4)
Like other authors study the households crop commercialization apply it in the
previous studies (Abera, 2009; Bekele and Alemu, 2015; Seyoum et al., 2011; Tufa et
al., 2014), in this study, onion commercialization, taken as a synonym for producers
household participation in onion market was measured in terms of volume of sales
that means the share of the value of onion output sold in total output sales.
Vegetables commercialization in Ethiopia
The argument on which commodities to target in the process of smallholders’
commercialization emanates from the smallholders asset endowment, agro-ecological
circumstances, technical knowledge of smallholders, and their risk bearing capacity
and attitude towards risk (Getahun, 2020). Vegetable crops are the main sources of
income for smallholder farmers and their demand is also growing in both national and
international markets (Emana et al., 2015; Emana and Gebremedhin, 2007) and as the
result, the numbers of vegetable producers is increasing.
Vegetables are an integral part of the farming system, which plays a crucial role in the
economy of Ethiopia. Despite productivity at smallholders' level is very low as
compared to yields obtained at research centres, vegetable production is increasing
(Ayana et al., 2014; Endris, 2017) because of increased area allocation, increase
productivity per area as well as area put under production. Much of the increase in
production comes from area expansion and increase in small-scale irrigation activities,
enabling two or more production cycles per year.
According to Central Statistics Agency report (CSA, 2012/2013) more than 458
thousand hectares of land is under fruit and vegetable crops in Ethiopia. On the other
14
hand, according to Endris (2017) the share of areas allocated for vegetable production
from the total area under all crops at national level was 2.57%. The area under
vegetables increased from 341,022 hectares with production of 25.9 million quintals
in 2011 to 356,688 hectares with production of 60.6 million quintals in 2015 for
smallholder farmer (CSA, 2015). This implies that the area cultivated to vegetables
increased by 4.6% while the production increased by 134%, between 2011 and 2015.
Similarly, export of vegetables increased from 37,210 tons valued at USD 163.86
million in 2003 to 220,210 tons valued at USD 437.5 million in 2013 (ERCA, 2013)
representing 709% increase in export volume and 167% in revenue. Having this
potential, in the country vegetables like Tomato and Onion are widely grown and
marketed. Farmers produce in two seasons using irrigation water and rainfall.
However, vegetables commercialization was constrained by shortage of
seeds/planting materials, diseases and insect pests, poor postharvest handling and poor
linkage to market and market information (Emana et al., 2015)
Onion production and marketing in Ethiopia
Onion is recognized as one of the most important vegetable crops that cultivated
throughout the world since its introduction. The global trend of onion production has
been in an increasing trend. Instance, from 2000 to 2011, the world onion production
nearly doubled, from 48 million to 85 million tons (AgroBIG, 2016). The world total
onion production was 742.51 million tons per annum. China was the leading world
producer accounts for 205.08 million ton followed by India and USA. In Africa,
Egypt was the leading onion producer country by producing 22.08 million tons of
onion per year for domestic and international markets that rank as the fourth of the
world producer of onion and first exporter of onion in African countries.
Ethiopia is the third biggest onion producer in Africa continental next to the Egypt
and South Africa. The estimated share of Ethiopia’s’ production for the total world
production is only 2.7% between 2000–2011 (AgroBIG, 2016; FAOSTAT, 2019).
From an economic point of view, onion is an important crop for the country when
compared to other vegetables. It is a high-value bulb crop that has produced by
smallholder farmers and commercial growers both for local and export markets in
15
Ethiopia (Aklilu, 1994) and ranked the second in production of all vegetable crops
next to Tomato.
Onion can be cultivated twice per year both under the irrigation and rain feed
conditions in different parts of the country. The Awash valley and the Lake Tan
regions are areas where the bulk of dry bulbs and onion seed are produced. The
national level onion production coverage and productivity reached 22,780 hectares
and 230,700 tons respectively in the 2014/15 production season (CSA, 2015). Indeed,
the averaged over the period of 2010 to 2018, the onion area harvested, production,
and yield at the national level were 28,942 hectares, 313,947 tons and 11.70 tons/ha,
respectively (FAOSTAT, 2019)
Despite an increase in the area of land cultivated with onion and year-round
production scenarios, the productivity has not shown the same change. Although
productivity can be more than 30 tons per hectare, the national average is far below
(10.14 ton/ha) than the world average (19.7 ton/ha) (FAO, 2012).The average yield
per hectare under irrigation is of course higher than under the rain-fed cultivation. In
irrigated areas, the average yield can reach up to 40 tons per hectare provided that
recommended agricultural practices are followed.
According to market survey results onion is widely consumed in Ethiopia in different
traditional and modern dishes/foods. Very small volume of onion is exported to
neighbouring countries to earn foreign currency. According to the report of Ethiopian
Revenue and Customs Authority, ERCA (2015) about 443.8 tons of onion (only
0.14% of total production) was exported and 63,123 USD was obtained. On the other
hand, because of the quality problem, short shelf life of local onion and supply
shortage during off season period, the country imports onion from Sudan. According
to (AgroBIG, 2016) in the past five years on average exporting and importing
volumes were 10,912 and 9,987 tons respectively with about 1,000 tons net export.
The import has been coming from the Sudan, through Metema and retailed at Bahir
Dar and Addis Ababa. Sudan’s onion is well dried, of high quality and has long shelf
life.
16
Despite high demand for onion vegetables in major towns, the majority of small
farmers are unable to reach those markets and sell their products at the farm-gate to
brokers. Most smallholder producers do not try to study the market, even they
continue to produce the same crops that their neighbours grow and compete in the
market for the same product. Some farmers even do not know and talk to their
customers, but only sell their products through middlemen (Getu and Ibrahim, 2018)
Challenges and opportunities of onion production
and marketing in Ethiopia
2.6.1. Challenges of onion production and marketing
Despite the ever-rising demands from time to time of onion vegetable due to the fact
of its importance in Ethiopian daily diet and people’s livelihood, there are challenges
facing the onion productions and its marketing in Ethiopia in general and at study area
in particular. The major production challenges includes shortage of herbicides and
pesticides chemicals, shortage of commercial fertilizers, shortage of irrigation water,
shortage of quality seeds, or absence of improved cultivars, application of
inappropriate agronomic practices and limited awareness of the benefits of intensive
production (Getu and Ibrahim, 2018).
Postharvest loss occurs due to the perishability nature of onion vegetable is one of the
challenges of onion production (Haile et al., 2016). The producers sell their product
on-farm at a low price due to the perishability characteristics of the onion and the
absence of storage facilities.
In the country, the vegetable marketing in general and onion in particular are affected
by different constraints. Poor road and transport facility, a price-setting problem
where traders bargaining power higher discourage producers, poor market
information, product quality problem that differs among producers, presence of
unlicensed traders and lack of product standard are the major challenges in marketing
of vegetable in general and onion in particular (Hailu, 2016; Mossie et al., 2020).
According Wondowussen and Bekabil (2014) producers are not confident to produce
fruit and vegetable constantly due to the fear of failure of local price. Low product
17
prices due to seasonal price fluctuation, the intensive influence of speculators and
brokers in reducing the bargaining power of farmers, poor market access, and poor
access to transportation, and intensive competition among producers are the main
marketing challenges of onion. The absence of direct transaction between the
producer and the large buyer is another behaviour that characterized fruit and
vegetable marketing including onion. Buyers follow brokers who identify the onion to
be purchased, negotiate the price, and purchase and deliver the products.
2.6.2. Opportunities for onion production and marketing
Despite the above explained challenges of onion production and marketing, it is the
source of livelihood for many peoples who have engaged in production and trading. In
Ethiopia, there are many public organizations supporting the development of
horticulture in general and onion in particular (Hunde, 2017). These include Ethiopian
Horticulture Development Agency, Ethiopian Horticulture Producers-Exporters
Association, Ethiopian Fruit and Vegetable Marketing Enterprise, Ethiopian
Horticulture Development Corporation, National Agricultural Research System
operating in decentralized system, Ministry of Agriculture and regional bureaus of
agriculture as well as many of vegetable seed importers.
The onion is produced both under rain-fed and irrigation. It can be produced two or
more times per year under irrigation. This scenario is true in Fentale district because
of the irrigation potential of the area. Those producers who have access to irrigation
can operate more independently of the seasons. Hence, the access of irrigation is one
and the most opportunities of the area for onion production. On the other hand the
labour intensive nature of onion production and marketing creates employment
opportunities.
According to Abebe (2018) availability of market demand throughout the year, a
growing number of buyers, population growth, the rapid urbanization process, high
experience in onion trade and growing price were some of the opportunities of onion
for most of the producers. Indeed, the high cash obtained from onion and small-scale
irrigation development opportunities are also the pull factors of onion production and
marketing.
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Theoretical Framework
This study framework was build up on the theory of utility maximization. Utility is
referred to a measure of relative human satisfaction
2.7.1. Utility Maximization theory
The factors affecting the decision to participate or not to participate, (obviously the
decision to produce or not) in the market (Bekele and Alemu, 2015) is made based on
an expected level of satisfaction derived from selling the output. This decision can be
influenced by socio-economic characteristics of producers (Alene et al., 2008;
Otekunrin et al., 2019). Farmers cultivate land to satisfy their physiological needs of
feeding or to acquire more wealth by commercialising their activities on the farm.
Smallholder farming households make certain decisions about what type of crop(s) to
cultivate, how much to be cultivated, when and where to actually sell or market the
produce the way in which it would result into maximum satisfaction from their labour
in term of returns (Apind, 2015; Otekunrin et al., 2019). Within the utility
maximization framework, the decision to commercialize (participate in onion market
or not) is considered as binary choice. Economic agents i.e. smallholders onion
producers commercialization decisions are influenced by the perceived utility or net
benefit obtainable from the choice they pursue.
According to Tozooneyi (2017) utility cannot be directly observed while the decisions
of economic agents (smallholder producers) are observable through the choices they
make. Suppose that Uj and Uk represent a farm households’ utility for two choices;
commercializing or not commercializing respectively. Hence, the household will only
choose to commercialize if;
Uij (βjXi + еj) > Uik(βkXi + еk) (5)
Where Xi is the vector of explanatory variables that influence the perceived
desirability of each choice, βj and βk are regression coefficients, j, k and e are error
terms that are assumed to be independently and identically distributed with the
subscripts j and k denoting the two choices.
19
It is commonly argued that productivity growth in the smallholder agriculture will
require a more commercialized orientation. With the ever increasing population and
the limited farm land, increasing productivity will increasingly entail the
intensification and commercialization of smallholder agriculture, involving more
intensive use of productivity enhancing inputs, and more market oriented patterns of
crop production (Hailu et al., 2015). Hence, the efforts of the smallholder households
to increase their output market participation of horticultural in general and onion in
particular at the area where there is access to irrigation and farm size decreasing
depend on the utility maximization theory.
2.7.2. Comparative Advantage theory
The theory of comparative advantage provides economic rationale for the proponents
of agricultural trade liberalization (Moon and Pino, 2016). The theory rests on
differences in production costs and factor prices that may arise due to differences in
the endowments of natural resources and production factors. Hence the producers
focus on the commodity that they have technical skill to produce and get more
comparative advantage from it.
Review of Empirical Studies
The contribution of smallholder farmers to reducing poverty and hunger in low-
income countries depends on sustainable access to and participating in markets
(Wiggins and Keats, 2013). Marketing plays an important role in agricultural
commercialization and accessibility of the market for commodities allows
specialization of production, which in turn increase production and productivity.
Therefore, sustainable success in agricultural growth depends not only on achieving
agricultural productivity and household food consumption but also critically depends
on increasing better market access and expansion of market opportunities.
Determinants of smallholder farmers’ market participation can be broadly categorized
as external and internal factors (Getahun, 2020; Hagos and Geta, 2016; Jebesa, 2019).
The external ones include all those factors that are beyond the farm household
including population growth and demographic change, technological change and
introduction of new commodities, development of infrastructure and market
20
institutions, development of the non-farm sector and rising opportunity cost of labour.
These factors influence the process of smallholder market participation by altering the
conditions of commodity supply and demand, output and input prices, transaction
costs and risks that farmers need to cope with.
The internal factors are barriers which relate to the failure by farmers to meet market
expectations due to lack of physical asset, financial assets and human assets. On the
other hand, factors like smallholder resource endowments including land and other
natural capital, labour, physical capital, human capital are household specific and
considered internal determinants of market participation (Gyau et al., 2016; Hagos
and Geta, 2016). In general, the determinants of smallholder farmers’ market
participation decision include; demographic and socio-economic factors, institutional
factors, market factors, technological factors, transaction cost and risk. In this paper
the author classified the factors into five categories to discuss it in detail and briefly.
2.8.1. Demographic Factors
The age of household head, sex, family size and education status of household heads
hypothesized as demographic factors which determine the output market participation
of household. The directional effect of age on commercialization can be ambiguous.
According to study by Melese et al. (2018) on determinants of commercialization by
smallholder onion farmers in Fogera district, south Gondar Zone, Amhara regional
state, by apply Heckman’s two step sample selection model revealed that household
age has negative and significant impact on onion market participation. The negative
and significant relationship between the two variables explained as the older
households tend to have more dependents causing more consumption and lowering
probability of market participation.
The study conducted by Megersa et al. (2020) also shows that age has negative effect
on the farmers’ participation decision in groundnut commercialization. The marginal
effect after probit further indicated that as age of household head increases by one
year, it decreases the farmers’ participation decision in groundnut commercialization
by 0.11%, keeping all other factors constant. This is because, older household takes
the low profit with low risk rather than taking high profit with high risk.
21
On another hand, in their study of smallholder cassava commercialization in Ghana,
Martey et al. (2012) found that increasing age had a positive effect on the commercial
index of a farm household. Older farmers tend to be more commercialized because
they are able to make better production decisions and have greater contacts which
allow trading opportunities to be discovered at a lower cost than younger ones.
Alternatively, some studies found no statistically significant relationship between age
of household head and commercial transition (Kotchikpa and Wendkouni, 2016;
Martey et al., 2012)
Sex of the household head has an influence on the household decision making and
therefore significantly affects market participation. Female headed households
participate more in trade of indigenous fruits (Mwema et al., 2013). However, other
previous studies finding indicate that being male headed household increase the
probability of crops output market participation and have positive effect on being
commercial farmer (Demeke and Haji, 2014). The study conducted by Mossie et al.
(2020) on econometric analysis of onion marketed supply in Northwest Ethiopia also
confirmed that being male head household significantly increase onion quantity
supplied to the market by 2.72 quintals as compared to that of female headed
households, keeping other variables constant.
Family size was found to be negatively influence the groundnut commercialization
intensity at 5% significance level (Megersa et al., 2020). Accordingly as coefficient of
household size indicate as household size increases by one in adult equivalent the
proportion of groundnut quantity supplied to the market decreases by 1.15% keeping
all other factors constant. The justification behind this is that as family members
increase the number of dependence ratio increases and the proportion of quantity for
consumption purpose increases that makes quantity supplied to the market decreases.
On another hand, study by Tozooneyi (2017) on tomato commercialization in
Zimbabwe confirmed that family size significantly exerted a positive influence on
tomato commercialization. The extent of tomato commercialization (output market
participation) increases by 0.6% for every additional household member, holding
other variables constant. One possible explanation is that as the household size
increases, the productivity of the land rises due to cheap labour availability and
22
exceeds the subsistence requirements which will lead to an increase in the marketed
surplus.
Education level is also another demographic factor expected to affect household
market participation. According to study by Senbeta (2020) on factors affecting level
of potato commercialization in Kofale district, West Arsi Zone, Oromia Regional
State, the result from truncated regression model show that education have a positive
and significant influence on farmers’ level of potato commercialization in which on
average, literate household earn about 1032.78 ETB more as compared to illiterate
household head from sales of potatoes, keeping all other factors constant. This
occurred because of education enhances the skill and ability to better utilize market
information, which may reduce marketing costs and make it more profitable from
commercialization. The education of the household head was also found to be of
positive impact on the sales value of horticultural crops and statistically significant.
On average, literate household earn about ETB 1,625 more as compared to illiterate
household head from sales of horticultural crops (Tufa et al., 2014).
2.8.2. Economic Factors
The total farm size, irrigation access, total livestock owned (TLU), oxen ownership
and non/off-farm income source are economic factors affect output
commercialization. According to Osmani and Hossain (2015) study on market
participation decision of smallholders and its determinants in Bangladesh found that
farm size is statistically significant and has positive influence on the decision for
market participation of households. This means that as the farm size increases, the
probability of decision for commercialization increases. Study by Wondowussen and
Bekabil (2014) show that, land holding size significantly influences the intensity of
fruit and vegetable market participation. Under fruit and vegetable it was positively
and significantly associated with sales value of fruit and vegetable products. This is
expected since land is a critical production asset having a direct bearing on production
of surplus due to economies of scale.
Inversely, study by Tozooneyi (2017) revealed that holding other factors constant, a
one-hectare increase in farm size was associated with a 2.93 % decrease in tomato
23
commercialization. The degree of crop commercialization is also more likely to be
influenced by land allocation decisions than only landholding.
The result of study conducted by Kabiti et al.s(2016) on the determinant of
agricultural commercialization among smallholder farmers in Munyati resettlement
area, Chikomba district, Zimbabwe, shows that the irrigation availability is
statistically significant and has a negative effect. Furthermore, the study explains that
when a household moves from being a non-irrigator to an irrigator, the output
commercialization level is expected to decrease by 0.884 units. This is justified to be
as a result of high installation and maintenance costs of the irrigation facilities which
use up some of the production capital that would otherwise be used for increased crop
production.
Livestock ownership and oxen expected to influence household output market
participation. The study on determinants of smallholder commercialization of
horticultural crops in Gemechis district, West Hararghe Zone, the result from
truncated regression model revealed as livestock ownership positively influence the
level of horticultural crops commercialization and statistically significant (Tufa et al.,
2014). The authors justified the result as livestock provides manures and manure is
the main nutrient used by farmers for crop production in study area
Inversely, the study finding on the market participation decision of smallholders and
its determinants in Bangladesh, by employed probit regression show as the livestock
numbers negatively associated to smallholders’ market participation (Osmani and
Hossain, 2015). Indeed, the coefficient from livestock is found to have a statistically
significant and negatively influence on the probability of households to participate in
the output market. This means that as income from livestock of the farmer’s increases,
the probability of farmers’ orientation towards commercialization reduces.
The result from study conducted by Pender and Alemu (2007) and also Gebremedhin
and Jaleta (2010a) confirmed with the negative effect of livestock ownership, it
reduces crop market participation, since livestock offer alternative sources of cash
income and hence the relationship is negative.
24
According to study by Hailu (2017) non/off-farm income was significant and
positively influenced the household heads volume sales of potato. The result show
that household who earns income from non/off-farm activity sold 2.6 quintals more
potato than those who did not have access, by holding other factors constant. This
may due to the fact that farmers who had cash from these sources used as
supplementary income to purchase inputs like improved seed, fertilizers, chemicals
and farm implements for vegetable production and thus supplied more potato to
market than those who had not because they are business oriented. The result from
study by Kabiti et al. (2016) concurs with this as income from non/off-farm would
result in an increase the level of output commercialization.
2.8.3. Institutional Factors
Agricultural extension service and credit facilities are institutional factors expected to
affect household market participation either positively or negatively. Extension access
was negatively and significantly associated with onion market participation (Melese et
al., 2018). This study revealed that, if onion producer gets extension service, the
probability of onion supplied to the market will decrease by 4.9%. The possible
reason was due to those who have access to the extension service and do not
appropriately apply the techniques and advices suggested by the extension agents such
as the way using fertilizers, herbicides and pesticides would cause their production to
reduce or damaged.
Inversely, the study by Regasa et al. (2019) on determinants of smallholder fruit
commercialization the case of southwest Ethiopia revealed that frequency of
extension contact was statistically significant and positively influenced the
participation of the households in marketing of fruits. This further indicates that,
keeping all other factors constant, the probability of household’s participation in
marketing of fruits increase by 22.6%, when the rate of households’ contact with
extension agents increases by providing training and advisory services. This implies
that the knowledge, skill, ideas and shaping attitudes gained through extension agents
can improve household’s productivity, access to market and also reduces losses.
25
The study conducted by Apind (2015) on determinants of smallholder farmers market
participation, the case study of rice marketing in a hero irrigation scheme, result from
multiple regression, show that access to credit positively influenced the extent of
market participation and was significant. The result further explained that a farmer
who acquired credit was more likely to sell 9.32% of their produce than those who did
not to repay the credit.
2.8.4. Market Factors
The distance from all-weather road, distance to the nearest market and access to
market information falls under market factors determine household
commercialization. According to Asfaw et al. (2010) distance to main market variable
is negatively correlated with marketed surplus because of the increased transaction
costs associated with marketing of the farmers’ agricultural produce. This is also
related to better access to improved seeds and other key agricultural inputs. Another
study conducted by Tufa et al. (2014) found that distance to the nearest market was
found to be negatively and significantly influence the value of horticultural output
sold. This result implies that the shorter the time taken to reach the nearest market
would result to a greater degree of commercialization of horticultural crops. Distance
to market was negatively affecting the value of horticultural product sold possibly
because of the increased transaction costs associated with marketing of the farmers’
agricultural produce.
The others previous studies conducted by Etafa (2016); Hailu et al. (2015) and
Tafesse et al. (2020) results also indicated as distance to nearest market have negative
association with market participation. However, the study by Melese et al. (2018)
found inversely as an increase in distance from house to the nearest market by a
kilometre indicated an increase in the probability of onion market participation. The
justification for result was that it is likely better non-farm employment opportunities
in addition to farming activity for households close to the markets may account for
their smaller reliance on onion sale.
26
2.8.5. Households specific Factors
The farming experience and land allotted to specific commodity is also the
determinants of output commercialization. Increases in farming experience of
households increase their perfection. The farming experience of a household head is a
significant positive contributor (Kabiti et al., 2016). Accordingly, a unit increase in
farming experience of the household head results in 2.97% unit increase in output
commercialization. In contrary, the study conducted on smallholder farmers’ crop
commercialization in the highlands of eastern Ethiopia (Ademe et al., 2017) revealed
an experience in farming is found to be statistically significant and negative. The
finding also explains as more experienced household heads might be more concerned
about being food secured and would not want to take the risk of demanding their crop.
In contrary, younger household heads would engage in the markets probably they are
more dynamic to adopt new technologies that enhance productivity.
The land allotted to onion has positive and significant relation with amount of onion
supply to market (Mossie et al., 2020). This implies that those households allocated
more land to onion production have managed to supply more product to the market.
The coefficient from the above study show that an increase in the area allocated to
onion production by one hectare would result in 33.35 quintal increase in the quantity
of onion supplied to the market. The finding of the study conducted by Melese et al.,
(2018) also confirmed with this finding.
Conceptual Framework
The conceptual framework for this study is developed based on literature review and
empirical evidence that discussed above. The framework indicates the
interrelationships in the study, the key variables, both independents and dependent
involved in the study and how they are interrelated. These framed as independent
variables are; Demographics factors (Age, sex, family size and education status of
household head), Economic factors (Total farm size, irrigation access, total livestock
owned (TLU), oxen and non/off-farm income), Institutional factors (access to
extension and credit), Market factors ( distance to all weather road, distance to nearest
market and market information) and Household specific characteristics (onion
27
farming experience and farm land allocated to onion) had expected to have either
positive or negative influence on onion commercialization (output market
participation).
Figure 1: Conceptual Framework
Source: Developed from Melese et al. (2018) & Tozooneyi (2017) with modification
Onion
Commercialization
Demographics factors
• Age HH
• Sex HH
• Family size
• Education level HH
Household specific
factors
• Onion
farming
experience
• Onion farm
size
Economic factors
• Total farm size
• Irrigation access,
• Total livestock
• Oxen
• Non/off-farm income
Institutional factors
• Extension access
• Credit access
Market factors
• Distance from
weather road,
• Distance to market
• Access to mkt info
28
3.RESEARCH METHODOLOGY
This chapter presents the methodology that was employed in this study. It includes the
description of the study area, type and sources of data, sample and sampling technique
that applied to select sample households. Later, model specification of the double
hurdle model and methods of data analysis were discussed. The chapter closed with
the definition and expected sign of the variables these are used in the study.
Description of the study area
The study conducted in Fentale district East Shoa zone administrative division of
Oromia regional state, Ethiopia. Fentale district is located at a distance of about 193
km to the East of capital, Addis Ababa on the highway to Djibouti. The district is
boarded on the Southeast by the Arsi zone, on the Southwest by Boset district, on the
Northwest by Amhara regional state, and on the Northeast by the Afar regional state.
It also located between 8°45′N to 39°50′E which is in tropical climatic zone. The
estimated total area of the district is 1,340 km2 FDSEPD (2013). Methara town is the
capital town and administrative centre of the district.
Regarding to the demography of the district as reported by CSA (2008) the total
population of Fentale district were 82,225 (both rural and urban population), out of
which 43,510 (53%) were male while the female constituted about 38,715(47%) of
the population in the district. Considering the place of residence 20,517 (25%) were
urban dwellers while 61,708(75%) were rural dwellers. The district is dominantly
inhabited by Oromo (Karrayu and Ittu) people. There are also other ethnic group like
Amhara, Tigre, Gurage and Walayta in the district town Methara. In the district,
Orthodox Christian, Islam and Wakeffata are the religions that followed by the
residents.
The land use pattern, as recorded by Fentale woreda agricultural development office,
out of the total area of the woreda 133,964 hectares, arable land accounts for about
14.84% (19,885 hectares), cultivated land constitute around 5% (6,845 hectares),
grass land about 7% (9,239 hectares), national park cover 3,850 hectares or 3 %,
while unusable land in the area constitutes the highest 28.03% (37,544 hectares) and
29
others (FDSEPD, 2013). The mean annual temperature and rainfall of Fentale district
varies between 180C-340C and 377-742 mm respectively with mean annual rainfall of
572 mm.
Crop such as maize, teff, wheat and sesame are practice in the area by using Boset-
Fentale irrigation project. Maize occupied the largest cultivated land area from all
crops produced in the area. It is also the most staple crop of the district. Vegetables
are commonly produced and also share the larger area of land next to cereals
Vegetable such as onion and tomato are the next major crop produced next to maize
according to information obtained from the district Agricultural development office
(FWPADO, 2018).
Figure 2: Map of the study area
Source: Drawn using GIS, 2021
30
Research Design
The study was explanatory type of study with mixed method design. Since the
explanatory design involves a two-phase project in which quantitative data collected
in the first phase, then the analysed results, further enriched with the results of
qualitative phase. The overall intent of this design is to have the qualitative data help
to explain in more detail the initial quantitative results. So, the mixed (quantitative
and qualitative) methods of data collection, analysis and interpretation were applied.
The cross-sectional design was applied for data collection, in which one time moment
of data were collected from onion producers’ smallholder households then analysed
and interpreted to achieve the objectives of the study. The quantitative data collected
through interview schedule and its results were further enriched with the qualitative
type of data that collected from Focus Group Discussion (FGD) and Key Informant
Interview (KII).
Sampling Technique and Sample Size
Multi-stage random sampling technique was employed in this study. At the first stage,
Fentale district was selected purposively depend on its irrigation based onion
production potential. At the second stage, out of eighteen kebeles of the district eight
high potential onion producers’ kebeles were selected and listed according to their
onion production potential and irrigation access with consultation of the district
Agriculture and Rural development expert. At the third stage, from eight onion
producer kebeles listed according to their onion production potential and irrigation
access, the first three highest potential kebeles were selected purposively by
considering the time and others factors to ensure efficiency of the study. These
kebeles are namely, Garadima, Gidara and Alge. Finally, the onion producer
households were selected by simple random sampling depend on proportional
probability to size
According to Fentale district pastoral and agro pastoral development office report, the
total smallholder farm household of the three kebeles, Garadima, Gidara, and Alge
were estimated to be 1000, 870 and 730 respectively. From the total farm households
of the three kebeles which means 2600, the onion producers were estimated to be 60%
31
of their respective numbers. This means 600, 522 and 438 for Garadima, Gidara and
Alge were onion producer smallholder households respectively which is totally 1560
(FWPADO, 2018).
To determine the sample size, the Yamane (1967) formula was employed. It states
that the desired sample size is a function of the target population and the maximum
acceptable margin of error (also known as the sampling error). Expressed
mathematically as;
n = N
1+N( е2) (6)
Where n; represent the desired sample size, N; represent the target population and e;
represent the maximum acceptable margin of error which was set at 7% for this study.
When the sample size calculated by using Yamane formula,
1560
1+1560(0.0049)= 180 (7)
So, according to calculation from Yamane formula the total sample size for the study
was 180 onion producer smallholder households.
The number of respondents selected from each three kebeles by applied probability
proportional to size. The following formula was applied to determine sample size for
each three study kebeles
𝑹𝒆𝒔𝒑𝒐𝒏𝒅𝒆𝒏𝒕 𝒑𝒆𝒓 𝒌𝒆𝒃𝒆𝒍𝒆 =𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐨𝐧𝐢𝐨𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐞𝐫𝐬 𝐩𝐞𝐫𝐤𝐞𝐛𝐞𝐥𝐞
𝐓𝐨𝐭𝐚𝐥 𝐎𝐧𝐢𝐨𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐞𝐫𝐬 𝐨𝐟 𝐭𝐡𝐫𝐞𝐞 𝐤𝐞𝐛𝐞𝐥𝐞𝐬∗ 𝐒𝐚𝐦𝐩𝐥𝐞 𝐬𝐢𝐳𝐞 (8)
Hence, the following table indicate the sample size selected from each kebeles.
Table 1: Proportional Sample Size
Kebele Total HH Onion producers HH Sample Size
Garadima 1000 600 69
Gidara 870 522 60
Alge 730 438 51
Total 2600 1560 180
Source: Column 2 and 3 (FWPADO, 2018)
32
Sources of Data
Both primary and secondary sources of data were used for this study. Primary data
(both qualitative and quantitative) collected directly from the respondents those
selected from each three kebeles.
Secondary data were taken through review various documents both published and
unpublished materials relevant to the study.
Types of Data
Both quantitative and qualitative types of data were collected for the study.
Quantitative data collected by administering pre-tested semi-structured questions
through interview schedule.
Qualitative method was employed to capture data pertaining to local perception and
opinions on onion commercialization, challenges and opportunities that the producers
face, to support quantitative data. This was taken by employed one focused group
discussion (FGD) contains ten number of members in each of the three selected
kebeles and through key informant interviews.
Methods of Data Collection
For this study, both quantitative and qualitative data were collected by employed
semi-structure interview schedule, and Focus Group Discussion (FGD) and Key
Informant Interview (KII) respectively.
3.6.1. Interview Schedule
Interview schedule was employed to collect primary data by face to face contact
interview with sample households through prepared semi-structured questionnaires.
Interview schedule carried out by trained data collectors those who graduate from
different higher education institutions. The questions were forwarded to 180 sample
household heads those randomly selected from the three rural kebeles, Garadima,
Gidara and Alge of the study district. The questions were asked the respondents by
33
translated to Afan Oromo. The interview schedule was conducted after thoroughly
explains the purpose of the interview to the interviewees. The interview schedule was
pre-tested with selected household heads before employed to all sample households.
3.6.2. Focus Group Discussion (FGD)
The focus group discussion (FGD) was employed to collect qualitative data that help
to strengthen quantitative data generated through interview schedule. The members of
FGD composed both men and women those did not involve in the interview schedule
from both youngster and elders age categories. One FGD per sampled kebeles were
conducted and each focus group discussion comprises ten individual members with
equal number of men and women. As the saturation of data existed the FGD limited to
one at each sampled kebeles. The checklist prepared to guide the discussion on right
track. The output of the discussion help to get additional supporting qualitative
evidence on determinants of onion commercialization and other related socio-
economic condition at the study area.
3.6.3. Key Informant interview (KII)
The primary data (both quantitative and qualitative) collected through Interview
schedule and FGD were needed to be further enriched by additional information that
gathered through Key informant interview (KII). Thus, intensive interview were
conducted with key informants that comprise two experts from two different
departments, horticulture and agronomy, one development agent (DA) and one
committee member of farmers’ cooperative from each sampled kebeles are included
as a key informant interviewees. The qualitative data generated from KIIs were help
to enrich the quantitative data collected through Interview schedule.
34
Methods of Data Analysis
Both descriptive statistics and econometric model were employed to analyse data for
this study.
3.7.1. Descriptive Statistics
First, data entered to excel were imported and generated using tabulation plans for
further analysis purpose. The analysis was done through employed Statistical Package
for Social Sciences (SPSS) version 22 and STATA version 14. This was done by
applied appropriate statistical methods. Descriptive statistics such as percentage,
mean, standard deviation, graphs and tables were used to explain household
characteristics like education status, age, sex, farm size, family size and farm size
allotted for onion production.
Additionally, following the first and second specific objectives of the study the
descriptive statistics (percentage and graphs) were employed to categories and rank
the challenges and opportunities of onion production and marketing at the study area.
Besides, the qualitative data were analysed by content analysis, narrations, and
interpretations of the meanings of words.
3.7.2. Econometric Model
The decision to commercialize onion and level of commercialization are considered to
be two separate decisions in this study. Cragg (1971) proposed the double hurdle
model in such scenario since the model allows these effects to differ. The double
hurdle model was selected at the cost of Tobit model. Unlike Tobit model, double
hurdle model allow to separate the decision to market participation and extent of
participation made. The model assumed that an individual passes through two
hurdles/steps. The first hurdle is the decision of whether participate or not, while the
second hurdle is at what extent to participate (Garcia, 2013). Additionally, the extra
advantage of double hurdle model as compared to the tobit model is that the double
hurdle model assumes the factors that negatively affect decision to participate in
market (commercialize) may have a different impact on extent of participation.
35
Model specification
The double hurdle model was applied to analyse the determinants of onion
commercialization in terms of output market participation. The double hurdle model
involves two-step estimation procedures. In the first stage, probit regression was
employed to analyse the factors governing market participation decision following the
study conducted by Osmani and Hossain (2015) for a given reference period which is
referred to as onion output commercialization decision in this study. Mathematically
expressed as;
yi* = xiβ+εi ɛi⁓N (0, 1) (9)
yi = 1 if yi* > 0 i= 1, 2, 3……………..180
0 if yi* ≤ 0
Where, yi* is a latent (unobservable) variable represent households’ decision whether
or not to participate in the onion output market; xi is a vector of independent variables
hypothesized to affect household’s decision to participate in the onion output market;
β is a vector of parameters to be estimated; yi is a response variable for status of
households’ participation in the market; εi is a disturbance term assumed to be
independently and normally distributed with zero mean and constant variance σ2; and
i = 1, 2,…n (n=the number of observations).
In probit model the interest is not so much in significance of the coefficients but in
effect of a change in xi on conditional probability. In probit model the marginal effect
is the coefficient multiplied by scale factor. Hence, the result explained in marginal
effect is expressed as;
∆𝑝(𝑦𝑖=1)
∆𝑥𝑖 = 𝜑(𝑥𝛽) ∗ 𝛽𝑖 (10)
Where x and β represent the explanatory variables and coefficient of observation i
respectively, while 𝜑 represent probability density function (pdf) of normal
distribution.
36
Marginal Effect measures the change in the probability of y=1 as a result of a unit
change in a particular explanatory variable x. According to Osmani and Hossain
(2015) market participation decision is estimated as binary variable yi=1 if the
household participates in output markets and yi = 0 otherwise. Probit model employed
to estimated maximum likelihood using STATA version 14.
In the second stage, truncated regression model was applied to analyse the
determinants of the value of onion that were marketed which referred as the level of
onion commercialization in this study. We say y is truncated when we only observe x
for observations where y would not be censored. We do not have a full sample for (y,
x), we exclude observations based on characteristics of y. in this study the level of
onion output commercialization(y) observed only for respondents participate in onion
output market.
A truncated regression fits a regression model on a sample drawn from a restricted
part of the population. Under the normality assumption of the whole population, the
error terms in a truncated regression model have a truncated normal distribution,
which is a normal distribution that has been scaled upward so that the distribution
integrates to one over the restricted range. In this study the extent of
commercialization was modelled as a regression truncated at zero. Expressed as
zi*=xiɑ+µi, µi ⁓Ν (0, δ 2) (11)
zi = z i* if zi*> 0 and yi=1, 0 otherwise
Where, zi is the level of onion commercialization which depends on latent variable
zi* being greater than zero and conditional to the decision to commercialize yi; ɑ is
parameter to be estimated µi; is model residual associated with observation i.
Truncation reduces variance compared to the variance in the un-truncated distribution.
As the result, the truncated regression model with the lower left truncation equal to 0
was employed to determine factors influencing sales value of onion product.
Multicollinearity test: - Multicollinearity, or near-linear dependence, is a statistical
phenomenon in which two or more explanatory variables in regression model are
highly correlated. Sometimes add more predictors to a regression analysis fail to give
37
clear understanding of the model because of multicollinearity. The presence of
multicollinearity increases the standard errors of each coefficient in the model, which
in turn changes the result of the analysis. According to Noora (2020) multicollinearity
makes some of the significant variables under study to be statistically insignificant.
As a rule of thumb, if the VIF is greater than 10 the variable is said to be highly
collinear and no collinearity problem if less than 10. For this study variance inflation
factor (VIF) for continuous variables and contingency coefficient for dummy
variables were used to test multicollinearity.
Table 2: Summary of data analysis methods
Data collection
methods
Data analysis methods Specific objectives to
be addressed
Interview schedule
FGD, KII
Descriptive statistics
(percentage &graphs),
qualitative methods
1 and 2
Interview schedule
FGD, KII
Econometric model(probit
regression) and qualitative
methods
3
Interview schedule
FGD, KIIs
Econometric
model(truncated regression)
and qualitative methods
4
38
Definition of Variables used for Analysis
Numerous empirical studies show that, in Ethiopia, smallholder commercialization is
determined by household specific factors, household resource endowments,
institutional factors and market related factors. Hence, through reading literatures on
smallholder household farm commercialization the following explanatory variables
are identified.
A. Dependent variables
Onion output market participation (MKTPAR):- Dependent variable indicates the
probability of selling onion crop or not. It is dummy variable equal to 1 if household
sell onion product in a production season; 0 otherwise.
Value of onion sold (ONVALU):- Dependent variable indicates value of onion sold
and it is continuous that measure in Ethiopian birr (ET Birr).
B. Independent variables
Age (AGEhh):- Age of the household head in number of years; a continuous variable
take as one of the explanatory variables to influence participation in onion production.
Its expected sign will be positive because as an individual stays long, he/she would
have better knowledge and would decide to participate.
Sex of the household head (SEXhh):- is a dummy variable taking 1 if household
head is male and 0 if female. No sign attached with this variable. It would be negative
or positive.
Education of household head (EDUNhh):- it is education level of household head.
Categorical variable measured in years. It has a great impact on the decision and level
of participation in onion output market. Its expected sign will be positive. Education
develops the skill and the capacity to adopt different technologies and inputs. As
educational level increases the awareness, knowledge, and capacity will develop. This
further upgrades farmers’ exposure to market information.
39
Household family size (HHSZ):-Family size of a respondent is one of the continuous
variables proposed to influence participation decision. The sign attach to it is positive
since the more number of family members an individual has the more probability to
participate in production. This is because he /she would have a cheap labour source.
Farming experience (EXP):- it is a continuous variable measures in terms of years
household head has been practice onion farming activity. It expected to be positively
affects the onion commercialization as the producers with high experience is risk
taker to adopt new technologies and increase production and productivity.
Total size of farm owned (FRMSZ):-Total size of land a respondent owned is a
continuous variable and takes as another variable to influence commercialization
decision. The expected sign is positive. The more land owned the more will be the
probability to participate in the decision.
Land allotted for onion production (ONFRM):- It is farm size a respondent locate
for onion production and it is a continuous variable and takes as another variable to
influence commercialization of onion. The expected sign is positive. The more land
located for onion production the more probability to be participate in onion output
market.
Total livestock Owned (TLSTOCK):-This variable is continuous variable referring
to the number of livestock holding of the household measured in Tropical Livestock
Unit (TLU). Livestock is an important source of income, food and draft power and
represents an asset, which indicates the wealth and social status of the household and
eases financial constraints. It is effect is hypothesised as positive.
Number of oxen owned (OXEN):- is a power for ploughing. The expected influence
is positive. It was discrete continuous variable.
Irrigation access (IRRGA):-Access to irrigation has a positive relation with the
market participation. This is because, a farmer using irrigation would have a better
productivity and will also produce two or more times per year that may lead to excess
production for consumption and will supply to the market. It is dummy variable that
represent by 1 if the household access to irrigation and 0 otherwise.
40
Distance from all-weather road (DROAD):- it is continuous variable and measured
in walking minutes, the more time needed to reach a main road the lesser would be the
probability to participate in production. Hence the expected sign is negative.
Distance to nearest market (DMRKT):-This also a continuous variable and
measured in walking minutes. The expected sign for this continuous variable is
negative because the nearer a farmer to a market the more frequent chance to get an
access to.
Credit access (CREDT):-It is the availability of the microfinance institutions like
credit association within the kebele or within a short distance to the farmer. If the
farmer has an access, he/she could borrow the money and be able to purchase inputs
that increase the production and productivity to secure food security and supply
surplus to market. So it has a positive sign .This variable is a dummy variable, 1 if the
farmer has an access to credit and, 0 otherwise.
Agri. Extension access (EXTSER):- this is a dummy variable indicating Agricultural
extension service farmer’s access to. The expected sign is positive. Since, a trained
farmer knows much to participate in market.
Market information (MKTINFO):- a variable proposed to influence decision to
participation positively. If a farmer could get updated information, he/she would be
able to participate. It is dummy variable represented by 1, if a farmer got information,
and zero if not.
Non-farm and off-farm income access (NOFINCM):- farmer’s access to different
income sources has a high probability to feel secured regarding economic aspect. It is
a dummy variable and a strong positive relationship to the decision to participate and
level of commercialization.
41
Table 3: Summary of Explanatory Variables
Source: own definition, 2021
Explanatory Variables Type
Measurement Expected
effect
Age of Household head Continuous Year +ve
Sex of the household head Dummy Male=1, Female=0 +/-ve
Education of HH Categorical Illiterate=1,read&write=2
1-6grade=3,7-8grade=4,9-
12grade=4,college/university=5
+ve
Household family size Continuous Number +ve
Farming experience Continuous Year +ve
Total farm size Continuous Hectare +ve
Land allotted for onion Continuous Hectare +ve
Total livestock owned Continuous TLU +ve
Number of oxen owned Continuous TLU +ve
Irrigation access Dummy Yes=1,No = 0 +ve
Distance from road Continuous Minutes of walk -ve
Distance to nearest market Continuous Minutes of walk -ve
Credit access Dummy Yes=1,No = 0 +ve
Extension access Dummy Yes=1, No = 0 +ve
Market information access Dummy Yes=1, No = 0 +ve
Non/off-farm income Dummy Yes=1, No = 0 +ve
42
4. RESULT AND DISCUSSION
In this chapter, the results of the findings are discussed thoroughly followed by the
discussion of the respective issues of interest. First, descriptive analyses of the
demographic and socioeconomic characteristics of the sample households are
presented. Then after, the result of the challenges and opportunities of onion
production and marketing are discussed. At the end of the chapter, the econometric
(empirical) analysis of the market participation and the level of participation of
sample households are presented.
Demographic and Socioeconomic Characteristics
of sample households
Table 4 and 5 below presents the descriptive result of continuous and dummy
variables of the respondents respectively with their respective result from descriptive
statistics. The sample population of onion producer respondents those contacted
during the survey was 180. Regarding to marital status, out of the total sample
households 81% was married while 7.4%, 6.3% and 5.3% was widowed, single and
divorced receptively. The result from the survey also indicated that, out of the total
respondents 85% was male headed household while 15% was female headed
household.
According to the result from descriptive statistics during the survey year (2019/2020)
production seasons, 5332.95 kilograms at average onion were produced by sample
smallholder households. Out of the total production at average, 5320.37 kilograms at
average onion product were sold while 12.58 kilograms at average were consumed at
home. Despite the variation in the level, the data show that at the study area the
respondents produce the onion for market to gain income that enables them to buy
food crops and agricultural inputs. In the following section the descriptive results of
explanatory continuous and dummy variables were discussed in detail.
Age of household head (AGEhh): The results indicated in table 4 shows that the
mean age of the respondent smallholder household heads was 36.05 years with 18 and
82 years of the minimum and the maximum age respectively.
43
Family size (TFMZE): The result from table 4 show the average family size of the
sample households was 5 persons, with minimum and maximum family size of 1
person and 18 persons, respectively.
Table 4: Results of descriptive statics for continuous variables
Variables
Obs
Mean
Std. Dev.
Min
Max
AGEhh
180
36.03
13.82
18
82
TFMZE 180 5.03 2.32 1 18
EXP(years) 180 10.52 6.99 1 38
TFRMLD(hect) 180 0.63 0.36 0.06 3
ONFRMLD(hect) 180 0.35 0.39 0 3
TLHOLD(TLU) 180 5.18 8.16 0 52.25
OXENOWNED(TLU) 180 0.84 1.06 0 5
DROAD(minute) 180 13.11 14.56 1 60
DMKT(minute) 180 147.78 64.14 40 300
Source: Own computed from survey, 2021
Farming Experience (EXP): For producers with high farming experience their
confidence to overcome the expected risk will be high. The result from descriptive
statistics as shown in table 4 indicate the onion farming experience of sample
households was 10.52 years at average with minimum of 1 year and maximum of 38
years respectively.
Total Farm holding size (TFRMLD): Another smallholder household characteristic
which can depict the background of the smallholder household is the land holding
size. The total farm size in this case includes all the farm land that smallholders
owned both irrigable and non-irrigable land. Most of the respondents land holding
size is below a hectare (ha) even if there are also those own smaller size less than
0.125 hectare. The result from descriptive statistics as indicated in table 4 above, the
sample households land holding size was 0.63 hectare at average while the minimum
and the maximum farm landholding was range from 0.063 and 3 hectares
respectively.
44
The farm rented in by sample households during the survey year was also count as
farm hold by respondent household. However, despite small farm land holding the
producers benefit from Boset-Fentale irrigation project which enables them to
produce two or three times per year.
Farm allocated for Onion (ONFRMLD): The result from descriptive statistics
indicated in table 4 show the farm land allocated for onion production by sample
households was 0.35 hectare at average with 0.39 hectare of standard deviation.
Indeed, the results show the minimum of 0 hectare i.e. No farm land allocated for
onion production during survey year and 3 hectare of maximum allocation. Here also
the farm rented in and produced onion during the survey year included in this size of
onion allocated farm.
Livestock Holding (TLHOLD): Livestock production plays an important role at the
study area. Total numbers of livestock holding of the households was measured in
Tropical Livestock Unit (TLU). Livestock are used for various purposes. Use as
sources of income, for crop cultivation and transportation of products. Livestock are
also considered as a measure of wealth in the area. Farm households who have a
number of livestock are considered as wealthy farmer in the farm community. As
indicated in table 4 the average livestock holding of sample households was 5.18 with
the standard deviation of 8.16. The minimum holding size is 0 while the maximum are
52.52 in tropical livestock unit (TLU).
Number of oxen owned (OXENOWEND): Oxen use a farming household and help
to plough the farm. Specially, in Ethiopia in general and at study area in particular
smallholders commonly use oxen as draught power. The average oxen number owned
by sample households were 0.841 in tropical livestock unit (TLU) while the minimum
and maximum number of oxen owned by sample smallholders were 0 and 5 in TLU
respectively.
Distance from all-weather road (DROAD): As indicated in table 4 the residence of
sampled households was located at average walking minutes of 13.11 away from all-
weathers road. The minimum and maximum of sample households from all-weather
road was 1 minute and 60 minutes respectively.
45
Distance from the nearest market (DMKT): As observed from table 4 the average
distance needed for sample producer’s to travel to reach the nearest market place
where sold their products took an average walking minutes of 147.78 with the range
of 40 and 300 minimum and maximum walking minutes respectively.
Table 5: Result of descriptive statics for categorical explanatory variables
Variable Response Frequency per cent
SEXhh Female 27 15
Male 153 85
EDUNhh Unable to read &write 61 33.8
Read &write only 29 15.9
Primary(1-6) 41 22.8
Junior secondary(7-8) 22 12.2
Secondary(9-12) 23 12.7
Tertiary(university/college) 4 2.6
IRRGA Yes 167 92.8
No 13 7.2
CREDT Yes 54 30
No 126 70
EXSER Yes 61 33.9
No 119 66.1
MKTINFO Yes 139 77
No 41 23
ONFINCM Yes 41 23
No 139 77
Source: Own computed from survey, 2021
Sex of household head (SEXhh): The result from descriptive statistics of dummy
variable as indicated in table 5 above 85% (153) of sample household heads is male
while the left 15% (27) is female-headed households.
Education level of household head (EDUNhh): the author treated the educational
status of household heads as categorical variable in this study. The result from
descriptive statics as indicated in table 5 and figure 3 show 33.8% of sample
46
household heads was unable to read and write while 15.9% , 22.8%, 12.2% ,12.7%
and 2.6% of them have an education status of read and write, primary school (1- 6),
junior secondary (7-8), secondary (9-12) and tertiary (university or college) education
level respectively.
Figure 3: Bar chart indicate education level of respondent households
Sources, own computed, 2021
Irrigation access (IRRGA): Irrigation is the most important variable for production.
Specially, at the study area the crops production mostly depends on the irrigation
access as the area get low rainfall amount per year. As indicated by table 5 the result
from descriptive statistics show 92.8% (167) of sample households was access to
irrigation during the survey year while 7.2% (13) of sample households did not get
irrigation service during the survey year. The sample households those not get
irrigation during the survey year was produced other crops such as maize and teff with
rain feed during main season.
Credit access (CREDT): Access to credit is also expected as one of the variables that
positively influence onion output commercialization since access to credit enhance the
purchase of inputs that use to increase their productivity. The result of descriptive
statics shown in table 5 indicate that out of the total sample households, 30 % (54) of
47
them was access to credit during survey year while 70% (126) did not get credit
service.
Figure 4: Pie-chart indicate respondents sources of credit
Source: own computed, 2021
Indeed, as indicated in figure 4 out of the sample households those benefited from
credit service 87% of them was get credit from their families and friends during the
survey production year. The others 7% and 5% of the credit user sample households
took credit from the government organizations and microfinance institutions
respectively. According to data from the FGDs, the participants were explaining that
at the study area the smallholder households’ credit taking habit is at an infant stage.
Access to Agricultural Extension service (EXTSER): The result of descriptive
statistics show that indicated in table 5 during the production year of the survey
undertaken in the study are, out of the total respondents 33.9% (61) of respondents
were benefited from agricultural extension service while 66.1% (119) were not
benefited from extension service. This implies as majority of the respondents were not
benefited from agricultural extension services in the area during the survey year.
Access to market information (MKTINFO): An access to market price information
before delivering their product (onion) to the market help producers to benefit from
their product. Untimely availability of market information is a major deterrent to the
intensity of commercialization in smallholder agriculture (Matsane and Oyekale,
48
2014). This problem is more detrimental to rural farmers those mostly sell their
product at farm-gate prices to middlemen who on their part have access to price and
market information prevailing in other markets.
As indicated in table 5 the sample households get access to market information before
delivering their onion product to market during the survey production seasons were
77% (139) while 23% (41) of them did not get market information. Even though the
majority of sample households were get market information during the survey
production year the main source of their information was the brokers who make the
information biased to benefit by themselves from the market price.
Figure 5: Bar-chart show respondents’ sources of market information
Source: own computed, 2021
Hence despite the importance of market information, the sources of information for
most of the respondents were brokers. As the results from descriptive analysis
indicated in figure 5, out of the sample households those benefited from market
information during the survey production year 46% of them were get information
from brokers that they did not satisfied to it. The other respondents 36%, 14.5%, 2.8%
and 0.7% of them were get market information from neighbours, traders, mass media,
and development agents respectively.
49
Non/off -farm income sources (ONFINCOM): As indicated in table 5 most of the
sample households were depends on farm as the primary source of their income. Only
23% (41) of the sample households were participate on other additional income
sources. The majority, 77% (139) of the respondents did not benefit from participating
in other income sources.
Figure 6: Pie chart indicate respondents sources of non /off -farm income
Source: own computed, 2021
Besides out of the sample households’ those access to non/off -farm income sources
48% of them were participate in labour work as additional source of income. The
other respondents, 25%, 18%, 7% and 2% of them were participate in petty trade,
charcoaling, handcraft and transportation service (by motor cycle) respectively.
50
Challenges and opportunities of onion production
and marketing
Here below the challenges and opportunities of the onion production and marketing
were discussed. The discussion based on the survey data collected from the sample
smallholder onion producer households and the data from FGDs and KIIs. The
sketched graphs depend on the survey data collected through open-ended questions
and categorized depend on the respondents responses.
4.2.1. Challenges of onion production and marketing
Despite the ever-rising demand for onion vegetable from time to time due to the fact
of its importance in Ethiopian daily diet and people’s livelihood, there are the
challenges face onion productions and marketing in Ethiopia in general and at the
study area in particular. The major production and marketing challenges are includes
shortage of herbicides and pesticides chemicals, shortage of commercial fertilizers,
shortage of irrigation water, shortage of quality seeds, the low product prices (due to
seasonal price fluctuation), intensive influence of speculators and brokers in reducing
the bargaining power of farmers, poor market access, poor access to transportation,
and intensive competition among producers. Haile et al. (2016) Pointed outs that
postharvest loss occurs due to the perishability nature of onion vegetable is one of the
constraint of onion production. The producers sell their product on-farm with low
price due to the perishability characteristics of the onion and absences of storage
facilities.
At the study area, onion production and marketing process is constrained by many
factors. The open-ended question regarding the production and marketing challenges
were forwarded to sample smallholder onion producer households. Additionally, the
information concerned the onion production and marketing were raised and discussed
with the FGD and KIIs. According to report from sample households as indicated in
figure 7 below about 31% of the respondents were reported high input cost as the
challenge for the onion production at the study area. The high cost of input followed
by fluctuation in irrigation access, disease/pest, high labour cost, input supply
51
shortage, flood and informal source of seed challenges and reported by 28%, 22%,
20%, 14%, 12% and 2% of the sample households respectively.
Figure 7: Bar chart represents challenges of onion production at study area
Source: Own computed from survey, 2021
The input supply and utilization includes fertilizer and seed expected to increase
production and productivity. The data from Focused Group Discussion (FGD) show
that the sources of onion seed at the study area are informal (sometimes unknown
traders). While the producers simply buy from traders with too high cost and beyond
cost even sometimes it may not germinate. Besides, the FGD participants explained
that the herbicides and pesticides bought from informal traders, in which sometimes it
is not work when applied to the perspective pest or insects.
Another reported concerning the onion production constraint at the study area was
fluctuation in irrigation access. This was due to the reason most of the time the onion
produced off season during drought when the irrigation water shortage was happen.
As the result, limited access to irrigation water would occur.
The other reported production challenge was unavailability of inputs at time required.
The FGD participants in addition explain that the inputs that supplied by GO like
0% 10% 20% 30% 40%
Diseasese and pest
flood
fluctuation of irrigation
access
High input cost
High labour cost
Informal source of seed
Input suppl shortage
Onion production challenges reported by respondents
52
fertilizer was not available at required time and the producers obligated to buy from
other district with high cost.
Figure 8: Bar chart represent the onion marketing challenges at the study area
Source: own constructed from survey data, 2021
The marketing challenges as shown in figure 8 above were reported by sample
households. 26% of respondents report low capacity of smallholder households to
take product at distant market. This implies that smallholders exposed to high cost of
transportation to take the product to the distance market. Furthermore, the KIIs
explained that the producers asked high loading and unloading cost when they want to
transport the onion product to the distance market.
The other reported constraint was high output price fluctuation. The 19% of
respondents were report high price fluctuation of onion as the challenge of marketing
onion. This show that even at the same production season the price of onion was ups
and downs. This results in selling of onion with predetermined low prices by traders
and others due to no storage facilities.
Additionally, the 15% and 7% of the respondents were report the brokers’ illegal
marketing practice and perishability of the product as the challenges of onion
0%
5%
10%
15%
20%
25%
30%
Brokers illegal
market practice
Low access to
market
Output price
fluctuation
perisheability
Onion marketing challenge reported by respondents
53
marketing respectively. This implies that brokers decided the price that the producers
could not get profit from the product. The study finding by Bekele et al. (2016)
strength this finding that marketing system for onion, tomato and banana were
predominantly constrained by a number of difficulties like weight cheating, unfair
pricing of products by brokers and low quality of the products and lack of
cooperative. They used to organize the collection of onions at the farm-gate while
paying low price to smallholder farmers. On the other hand the perishability nature of
onion together with low capacity of smallholders to take the product to distance
market forced them to sell their product with low price at the farm-gate.
Most of the smallholder producers did not get the information on market price of
onion before the brokers enter their area. They relied on the word of mouth of brokers
that provided to them at the time they enter to the farm to buy onion. The reliance of
smallholder producers on brokers sources of market price information expose
producers to low on farm-gate price (Ndukai, 2015). This problem at large became a
hindrance of smallholder farmers to know onion market performance trend for
decision making of whether to continue to cultivate onion or switch to other high
value horticultural crops.
4.2.2. Opportunities of onion production and marketing
Fentale district has the advantage of having good local agro-ecological condition and
the Boset-Fentale irrigation project make the district more favourable to growth vast
horticultural crops and onion in specific. Despite the small land holding size of the
small household, at the area they get profit from the farm by producing two or three
times per year. As KIIs discussed the development of Boset-Fentale irrigation
development project open the door for smallholders to shift from solely depend on
livestock herding to mixed farming practice.
Now days at the area, the smallholder households produce onion through irrigation
water use and benefited from it despite the above mentioned challenges. As indicated
in figure 9 below about 67% sample households were report the high capital sources
gain from onion as the opportunity to produce and marketing onion at the area. This
54
implies that since onion produced all year round at the area most of the households are
use as their primary sources of income to buy food crops and agricultural inputs.
The commencement of on farm onion seed making was also another opportunity of
onion production and marketing. Besides the irrigation access, good weather
condition and the high yield from a small plot farm were reported by sample
households as the opportunity to produce and marketing onion at the study area.
Figure 9: Onion production and marketing opportunities at the study area
Source: own constructed from survey data, 2021
Accordingly, the irrigation access, good weather condition of the area and high yield
from a small plot were reported by 13%, 8% and 5% of sample households
respectively. Additionally, the short duration of maturity, easy to produce, soil fertility
and own labour sources were also reported 6% of sample households. The study
conducted by Bekele et al. (2016) point out the relatively fertile arable land of the
Awash River and abundant irrigation water potential as opportunities of marketing in
vegetable in Afar region logia.
0%
10%
20%
30%
40%
50%
60%
70%
80%
Good
weather
High income
sources
High yield
per area
Irrigation
facility
Others
Onion production & marketing opportunities at study
area
55
Results from Econometric model Analysis
In this section, the econometrics result of the earlier discussed external and internal
factors of onion output commercialization were discussed in detail. These factors are
Demographic factors (Age of HH, Sex of HH, Education level of HH and family
size), Economic factors (farm size, livestock holding, oxen owned and Irrigation
access), Market factors (distance from all-weathers road, distance from the nearest
market and access to market information), Institutional factors (such as access to
extension service and access to credit service) and Households specific factors
(farming experience and land allotted to onion) were discussed in detail with their
direction of influence on both onion market participation decision and the level.
Multicollinearity test:- A STATA software package (version 14) was employed
to run the double hurdle model (probit regression at the first stage and truncated
regression at the second stage). The model first checked for problems of
multicollinearity and the result found no serious problem of multicollinearity. The
Variance Inflation Factor (VIF) were less than 10 for continuous explanatory
variables and the Contingency Coefficient for dummy variables were also below 1 as
indicated in appendix-1 and 2.
56
4.3.1. Determinants of onion market participation decision
among smallholders farming households
In this study about 16 variables are identified as the factors to determine the decision
and level of smallholders’ onion market participation. The outcome of the probit
model inference for the determinants of the likelihood of household to participate in
onion output market or not are presented below in table 6. To interpret the result of
the first stage of the double hurdle, the probit model, the marginal effect were used as
the coefficients of the probit model are difficult to interpret since they measure the
change in the unobservable y* associated with a change in one of the explanatory
variables. The marginal effects of each variable on the predicted probability of
households’ onion market participation decision were evaluated at the means of the
explanatory variables.
The decision to participate in the onion output market was estimated by maximum
likelihood. The probit regression model results show that the function of the
participation decision in onion output commercialization was highly significant at less
than 1% significance level (Prob > chi2 = 0.0000). This indicates as the model has
strong explanatory power of independent variables to explain the factors determining
the commercialization decision of smallholder households. The 0.657 value of Pseudo
R2 show that, about 66% of the variation in decision to participate in onion output
commercialization among the smallholder households were attributed to the
hypothesized variables.
Out of the 16 explanatory variables hypothesized to determine the onion market
participation decision among smallholder farming households, seven of them were
statistically significant and determine the decision of smallholders’ onion market
participation
As indicated in table 6, seven explanatory variables that determine the probability of
smallholder households to participate in the onion output market were the sex of
household head, onion farming experience, total farm holding, farm allocated for
onion production, credit access, access to extension and market information. Out of
57
the seven independent variables these were statistically significant and influence the
probability of the onion producers market participation decision, total farm holding
size and credit access was significant in contrast direction of hypothesized while the
others five variables were significant positively in expected direction
Table 6: Result of Probit regression on onion market participation decision of
households
ONMKTPAR Coef. Robust
Std. Err.
z P>|z| Marginal
effect
AGEhh 0.000 0.012 0.004 0.997 .0000
SEXhh 0.806 0.427 1.888 0.059* .2089
EDUNhh 0.023 0.110 0.208 0.835 .0059
TFMZE -0.043 0.073 -0.584 0.559 -.0111
EXP 0.040 0.024 1.695 0.090* .0105
TFRMLD -0.551 0.221 -2.487 0.013** -.1428
ONFRMLD 1.017 0.208 4.879 0.000*** .2637
IRRGA 0.722 0.440 1.641 0.101 .1873
TLHOLD 0.003 0.030 0.110 0.912 .0008
OXENOWNED 0.014 0.174 0.083 0.934 .0037
CREDT -0.831 0.386 -2.151 0.031** -.2153
EXTSER 0.646 0.365 1.771 0.077* .1676
MKTINFO 1.600 0.335 4.769 0.000 *** .4149
OFINCOM -0.230 0.328 -0.702 0.482 -.0597
DROAD 0.007 0.328 0.766 0.444 .0018
DMKT -0.001 0.009 -0.179 0.858 -.0001
Constant -0.590 0.832 0.832 0.478
Number of obs = 180 Wald chi2 (16) = 180.62
Log likelihood = -37.457 Prob > chi2 = 0.0000
Pseudo R2 = 0.6570
*, ** and*** represent 10%, 5% and 1% significance level respectively.
Source: result from probit model, 2021
.
58
Sex of household head as indicated in table 6 the sex of household head determine
the onion market participation decision of smallholder farming household positively
and statistically significant at 10%. Furthermore, the result from marginal effect after
probit indicate that being a male headed household increases the probability of
participating in the onion market by 20.89% than the counter female headed
household, keeping other factors constant.
Besides, the qualitative information collected through Focus Group Discussion (FGD)
show that, lack of initial cost and shortage of labour force were influence female
headed households to engage in onion production at the area. This finding confirm
with the finding of (Demeke and Haji, 2014; Wonduwossen and Bekabil, 2014) which
find as the male headed household increase the probability of crops output market
participation and have positive effect on being commercial farmer and the male
headed households were more likely to participate in fruit and vegetable crops
marketing respectively.
Onion Farming experience of household was also another explanatory variable that
affect the market participation decision of smallholders’ onion producers. In table 6
the result from probit regression indicated that the farming experience of household
was positively influence the probability to participate in the onion output markets and
was statistically significant at 10% significance level. The marginal effect after probit
also implies that as the farming experience of smallholder onion producers’ increase
by 1 year, the probability of deciding to participate in onion market increase by 1%,
hold the other factors constant.
This implies that as farming experience increase, the perfection and self-confidence of
producer also increase in which willingness to adopt new technologies that increase
the productivity on another hand. This finding concurs with Kabiti et al. (2016)
finding that reveals a unit increase in farming experience of the household head
results in 2.97% unit increase in output commercialization. In contrary, the study
conducted on smallholder farmers’ crop commercialization in the highlands of eastern
Ethiopia (Ademe et al., 2017) reveals the experience in farming is found to be
statistically significant and negative. The result justified as the younger household
59
heads would engage in the markets probably because they are more dynamic to adopt
new technologies that enhance productivity.
Total farm holding size as indicated in table 6 above, the regression result show that
the farm size of sample households was significantly associated with households’
onion market participation at less than 5% significance level. In contrary to prior
expectation, farm holding size was found to be negatively associated with
smallholders’ onion market participation and statically significant. Furthermore, the
result from marginal effect after probit reveals that as the farm size of the household is
increases by 1 hectare, the probability to participate in the onion output market
decreases by 14.28%, keep other variables constant.
This finding implies that, as farm size of smallholder household increase the
production shift to food crops rather than producing onion, then the onion market
participation reduced. This result confirmed with research conducted by Tozooneyi
(2017) on factors influencing commercialization of smallholder Tomato production in
Zimbabwe, which revealed that holding other factors constant, a one-hectare increase
in farm size was associated with a 2.93% decrease in Tomato commercialization.
However, this result contrast with the result of study by Osmani and Hossain (2015)
,and Wondowussen and Bekabil (2014) which reveals as the farm size increases, the
probability of decision for commercialization increases.
Farm allocated to onion production was the important variable that found to have a
positive and significant influence on farmers’ likelihood to participate in the onion
output market at less than 1% level of significance. As indicated in table 6 the result
of marginal effect show a 1 hectare additional land the household allocate for onion
crop would increase the farmers’ likelihood of market participation by 26.37 %. The
positive and significant relationships between the two variables indicate that land
allocated for onion directly associated with onion productivity of household that in
turn enhance onion output commercialization. This result was towards the result of
study conducted by Mossie et al. (2020) which found land allotted to onion has
positive and significant relation with amount of onion supply to market.
60
Access to credit was one of the variables that in contrary with the prior expectation
and was negatively associated with the households’ market participation decision. The
result from probit regression as indicated in table 6 reveals that access to credit was
negatively affect the market participation probability of onion producers household
and statistically significant at less than 5%. Moreover, the result of marginal effect
show that keeping other variables constant, for smallholder household access to credit
the probability of onion output market participation decrease by 21.53% than that of
the counterpart no access to credit.
This result implies that the smallholder households who took credit consider the credit
as sources of income to buy agricultural inputs then divert the production to food
crops for home consumption and sell surplus rather than cash crop while the
household not access to credit obligated to produce cash crop like onion to get income
source enable them to buy agricultural inputs. The data from focus group discussion
also show that smallholder household access to credit fear risk of price fluctuation and
disease to produce onion rather they engaged in other business work.
Access to extension service was consistent with the prior expectation and positively
associated with households’ onion market participation decision at less than 10%
significance level. From marginal effect after probit the result as indicated in table 6,
holding others variable constant, the smallholder these benefited from extension
service participate more likely in the onion output commercialization by 16.76% than
the counterpart not benefited from the extension services. This implies that
households’ contact with extension agents increases their production and productivity
by using provided training and advisory services.
This study is in line with the finding of Regasa et al. (2019) conducted on
determinants of smallholder fruit commercialization in Southwest Ethiopia which
point out that frequency of extension contact was statistically significant and
positively influenced the market participation of the households. Another study
finding by Abrha et al. (2020) revealed that extension contact is related to access to
formal training and informal on onion production and marketing for producer farmers.
The positive and significant relationship indicates that extension contact had
improved onion farming household ability to acquire new technology and capacity of
61
production, which in turn improves productivity and thereby increase marketable
supply of onion.
In contrary, the finding of study by Melese et al. (2018) point out that extension
access was negatively and significantly associated with onion market participation.
The possible reason could be due to those who have access to the extension service
and do not appropriately apply the techniques and advices suggested by the extension
agents such as the way using fertilizers, herbicides and pesticides would cause their
production to reduce or damaged.
Access to market information was as prior expectation, it found to have positive and
significant influences on the farmers’ participation decision in the onion output
commercialization at less than 1% significance level as indicated in table 6.The
marginal effect of this variable after the probit regression disclosed that as farmer’s
has access to market information the probability of participation decision in the onion
output commercialization increases by 41.49%, keeping all other factors constant.
This implies that access to market information enhance the producers to be able to get
their products to market during the high market price and receive equitable price
treatment.
Farmers need information pertaining to output prices so as to make the right decision,
ahead of the production season, regarding which type of crops to produce and sell.
This indicates that access to market information helps farmers’ to be market oriented
for their production (when and where to sell). The study finding by Apind (2015)
revealed that the source of market information increased the chance that a farmer
would sell rice in Kenya.
62
4.3.2. Determinants of smallholders onion market
participation level
The factors determining the level of onion output market of smallholder sample
households were analysed by using truncated regression model. The level of
smallholders farming onion commercialization (output market participation) is
measured in sells value of onion crop.
Table 7: Result from truncated regression of determinants of onion market
participation level
*, ** and *** represent at 10%, 5% and 1% significance level respectively
Source: own computed from model, 2021
It is worth mentioning in this stage that only the smallholder sample households who
sell onion during the survey year of production seasons are considered in this step of
VLUESOLD Coef. Robust
Std. Err
Z P>|z|
AGEhh 1090.57 429.233 2.541 0.011**
SEXhh 34889.75 15699.77 2.222 0.026**
EDUNhh 162.26 2222.41 0.073 0.942
TFMZE -2602.05 1952.84 -1.332 0.183
EXP -307.05 745.09 -0.412 0.680
TFRMLD 5906.67 4256.70 1.388 0.165
ONFRMLD 13880.13 4925.27 2.818 0.005***
IRRGA 42549.30 25560.63 1.665 0.096*
TLHOLD 460.30 342.72 1.343 0.179
OXENOWNED 10764.76 3094.96 3.478 0.001***
CREDT 16629.83 14566.81 1.142 0.254
EXTSER 8746.79 13909.70 0.629 0.529
MKTINFO 20910. 16942.88 -1.234 0.217
OFINCOM -1191 10759.91 -1.103 0.270
DROAD 25.487 316.09 0.081 0.936
DMKT 132.169 64.52 2.049 0.040**
Constant -1.05e+05 34826.17 -3.015 0.003
Number of obs =137 Wald chi2(16) = 291.66
Log likelihood = -1580.369 Prob > chi2 = 0.0000
63
analysis. Therefore as indicated from truncated regression number of observation as
indicated in table 7 the number of onion market participants included in this stage
analysis was 137 respondents. As the result showed in table 7 the model was
statistically significant at 1% level that indicating the goodness of fit of the model to
explain the relationships of the hypothesized variables in terms of at least one
covariate. Out of 16 variables expected to influence the level of smallholder
households’ onion market participation, six of them were statistically significant. The
age of household head, sex of household head, farm allocated to onion, irrigation
access, number of oxen owned and distance to the nearest market were variables
influence smallholder onion market participation level. Five statistically significant
variables were affect smallholders onion market participation level in prior expected
direction except the distance to the nearest market which affect positively in contrary
to prior expectation direction.
Age of household head was found to be positively influences the onion market
participation level at 5% significance level as indicated in table 7. The coefficient of
the age show that an increase by 1 year in the age of household head, the proportion
of the value of onion sold increase by 1090 ETB. This implies that the older
household heads have more experienced and have taken confidence to apply new
technologies that increase the onion production and increase the level of value get
from onion sold compared to the counter younger household heads. The data from
focus group discussion was also indicate that younger people are move to town to
search job in industrial/services sector and not willing to stay in agricultural sector
hence their onion market participation levels become lower when compare with elder.
The finding of this study is in line with the finding of Martey et al. (2012) that found
increasing in the age had a positive effect on the commercial index of a farm
household. Older farmers tend to be more commercialized because they are able to
make better production decisions and have greater contacts which allow trading
opportunities to be discovered at a lower cost than younger ones. In contrast study by
Seyoum et al. (2011) was found the negative influences of age on groundnut
commercialization intensity at 1% significance level. This implies that active labour
force in agricultural product is more actively engaged in groundnut supply to the
market as compared to their older counterpart.
64
Sex of household head variable was found to be positive and statistically significant
influence on the level of onion market participation in value of sold at 5% level of
significance as indicated in table 7. The positive sign show that male headed
household significantly earn 34,889 ETB more from selling onion to market than that
of female-headed households, keeping other variables constant. This implies that
female headed household influenced by shortage of initial working capital and labour
to produce onion and highly participate in the markets at the study area.
This finding confirmed with finding of Hailu (2017) on potato commercialization that
reveal the positive influence of sex of household head. The reason behind male
headed households supplied more potato to market than female headed households, is
that females can take higher care than males about households consumption by saving
from produce to feed household; this can reduce the quantity to be sold. Another
Study conducted by Mossie et al. (2020) on Econometric analysis of onion marketed
supply in Northwest Ethiopia also confirmed that being male head household
significantly increase onion quantity supplied to the market by 2.719 quintals as
compared to that of female headed households, keeping other variables constant.
Farm allocated to onion was one of the variables that influence the level of the value
of onion marketed positively. The result show that the land allocated to onion has
significant effect on value of sales of onion at 1% significant level with expected
positive sign. The regression coefficient show that as indicated in table 7 a hectare
increase in farm allocated to onion production increase the value get from onion sold
by 13,880 ETB, holding other variables constant. This implies that more farm land
allotted to onion production increase the production volume of onion which in turn
increase the value from sold of onion.
This result was concurs with the finding of Hailu (2017) which found increase in the
size of one hectare of land allocated for potato is increase volume sales of potato by
84.561quintals, keeping other factors constant. Others studies by Mossie et al. (2020)
and Melese et al. (2018) also confirmed with this finding these found land allotted to
onion has positive and significant relation with amount of onion supply to market.
65
Access to irrigation was also found to be positive and statistically significant
implication on the value of onion output sold at 10% significance level in prior
expected sign. The coefficient of truncated regression show that households with
access to irrigation earn at average about 42,549 ETB more than those households
produce with rain fed, keeping constant other variables. This implies that households
with access to irrigation produce two or three times per year and benefited more from
onion selling than who produce with rainfall.
That means smallholder onion producers with access to irrigation have more
opportunities to supply more onion products than farmers without access to irrigation
due to improvement in onion cropping intensity and economies of scale. The finding
of the study by Wondowussen and Bekabil (2014) concurs with this finding which
found access to irrigation positively influence fruit and vegetable value sold. The
result of finding by Tufa et al. (2014) also confirmed with this finding which found
irrigation was positive and statistically significant implication on the value of
horticultural output sold at 1% level.
Number of oxen owned statistically significant and positively influence the level of
smallholder household market participation level at 1% significance level as indicated
in table 7. Moreover, the coefficient of regression show the one unit increase in the
number of oxen owned by smallholder household the level of onion sold to market at
average (in value) increase by 10,764 ETB, keeping other variables constant. This
implies that oxen use as draught power especially for smallholder farming
households, having more oxen enable to produce more and increase market
participation level. The focus group discussion participants also explained that even
the household with no or small pilot of farm but have oxen rent in farm and produce
onion in which enhance their income. The results of finding by Hailu et al. (2015)
agree with this result as draught powers positively and significantly influence crops
commercialization.
Distance to the nearest market was the variable affect the level of onion market
participation in contrary to the prior expectation. As indicated in table 7 it was
statistically significant and positively affects the level of onion market participation at
10% significance level. The regression coefficient show that by maintaining other
66
variables constant, when the number of a walking minute to the nearest market
increases by one minute the level of onion output marketing also increase by 132 ETB
at average in value sold. This due to reason that as the distance from market of
household increase they took whole their product at once to reduce the transition cost
which in turn increases the volume of onion marketed. Long distance from market
increases the cost of transportation.
The producers take the product all at once that increase their level of market
participation to reduce transaction cost. This result agree with the finding of Melese
et al. (2018) which found that an increase in distance from house to nearest urban
market in kilometre indicated an increase in the probability of onion market
participation by 2.2%. The reason is that it is likely better non-farm employment
opportunities in addition to farming activity for households close to the markets may
account for their smaller reliance on onion sale.
67
5. SUMMARY, CONCLUSION AND
RECOMMENDATION
Summary
Changing the subsistence-oriented production system into a market-oriented
production system as a way to increase the smallholder farming household income
and reduce rural poverty has been in the policy spotlight of many developing
countries including Ethiopia. Growing economies requires maximizing the potential
of the agricultural sector and necessarily increasing the level of smallholders'
agricultural productivity which is existed at the base level due to several socio-
economic bottlenecks.
The objective of this study was to analyse the determinants of onion output
commercialization among smallholder farming households at Fentale district. 180
Onion producers sample were selected through multi-stage random sampling
technique. Both quantitative and qualitative data were collected through Interview
schedule, FGD and KIIs. The data collected were analyzed by descriptive statistics
and double hurdle econometric model. The descriptive analysis result reveals that the
high cost of inputs, fluctuation in irrigation access, diseases and pests, input supply
shortage, high labour cost, flood problem and informal sources of onion seed were the
challenges for onion production and low access to market, high output price
fluctuation, the broker illegal marketing practice and the perishability nature as the
marketing challenge of onion. Indeed, the result of descriptive statics reveals the
onion production and marketing opportunities such as high income gained from
onion, irrigation access, good weather condition of the area and high yield from a
small plot of land.
The result of probit regression show sex of household head, farming experience, farm
allocated to onion, access to extension, total farm size, credit and market information
were determine the onion market participation decision while the truncated regression
result show age of household head, sex of household head, farm allocated to onion,
irrigation access, number of oxen owned and the distance to the nearest market were
variables influence the level smallholder onion market participation.
68
Conclusion
In Ethiopia, smallholder producers are the principal suppliers of fruits and vegetables
which account for over 95% of the national production of the country. However,
despite a long history of irrigated vegetables production of the country, the
commercial production were expanded significantly since 2005 when the national
agricultural strategies began to favour the high value cash crops and productivity
enhancement.
Ethiopia is the third biggest onion producer in Africa continent. However, the
estimated share of the commodity production for the total world production is only
2.7%. The market participation decision and level of participation of the smallholders’
onion producers is subject to combined effect of socio-economic, demographic and
institutional factors in the country. Similarly, though the onion production in Fentale
district is high, the producers’ decision and the level of onion commercialization are
subjected to various socio-economics factors.
The results from descriptive analysis and qualitative data point out the challenges and
opportunities of onion production and marketing at the study area. Thus, according to
the result from descriptive statistics and qualitative data from FGD and KII, the high
cost of inputs, fluctuation in irrigation access, diseases and pests, input supply
shortage, high labour cost, flood problem and informal sources of onion seed were the
challenges for onion production respectively according to their severity. Similarly the
study result reveals the low access to market, high output price fluctuation, the broker
illegal marketing practice and the perishability nature as the marketing challenge of
onion product at the study area.
Furthermore, the result of the descriptive statistics and qualitative data from FGD and
KII reveals that at the area, the high income gained from onion, irrigation access,
good weather condition of the area and high yield from a small plot of land were the
opportunities to produce and marketing onion. Indeed, in similar way, the result from
study indicate short duration of maturity, easy to produce, soil fertility and own labour
sources were also the opportunities that reported at the area to produce and marketing
onion.
69
On the other hand, the results from econometric model find the factors determine the
onion output market participation decision and the level of participation. At the first
phase of the double hurdle model the result of probit regression was show out of
sixteen explanatory variables hypothesized to determine the onion market
participation decision among smallholder farming households, seven of them, the sex
of household head, onion farming experience, total farm holding, farm allocated for
onion production, credit access, access to agricultural extension and market
information were statistically significant and influence households onion market
participation decision.
The sex of household head, farming experience, farm allocated to onion, access to
extension and market information were determine the onion market participation
decision of smallholder farming households positively and statistically significant in
the prior expected direction. Total farm size and credit access were in contrary to the
prior expectation and found to be negatively associated with the smallholders’ onion
market participation decision and statically significant.
At the second phase of the double hurdle model, the truncated regression coefficient
show the age of household head, sex of household head, farm allocated to onion,
irrigation access, number of oxen owned and the distance to the nearest market were
variables influence the level smallholder onion market participation and statistically
significant. In this step except the distance to the nearest market which affect in
contrary direction of prior expectation, all other variables were influence positively in
an expected direction.
The study indicate the intervention areas for policy makers and others development
practitioners who primarily work to improve the livelihoods of smallholders’ onion
producers to handle the factors hinders onion commercialization. The challenges and
opportunities exposed by this study also indicate the focus direction for development
practitioners
70
Recommendations
• The shortage of herbicides and pesticides chemicals and the shortage of
commercial fertilizers were the major production and marketing challenges of
onion at the study area.
• Therefore, the Government Organizations and others development practitioners
should subsidies the agricultural inputs for smallholders farm households.
• Indeed, the low product prices due to seasonal price fluctuation, intensive
influence of speculators and brokers reduce the bargaining power of smallholders
farming households.
• Hence strengthening the bargaining power of smallholders farm households are
the areas needs policy interventions.
• Access to agricultural extension service influence the onion commercialization
positively.
• Government Organizations and others development practitioners should give
attention for up-grading of the skills of extension agents on the effective way of
technology disseminations and the share of information about the technology to
the producers.
• There is also the need to reduce the farmer to extension worker ratio so that
extension services are easily accessible by the majority of producers in the study
area.
• Extension agents must also be well motivated to regularly visit and monitor the
progress of farm households’ production activities.
• By being female headed household the smallholders household did not benefit as
that of the counter male headed households at the study area.
• Then another issue needs policy intervention is the support of female headed
households through subsidies the inputs and increase their awareness and
knowledge about the onion production and marketing.
• On the other hand improving their access to education, institutional services, and
market access and market information is the prerequisite to enhance their onion
production and productivity and also increase their onion output market
participation.
71
• The fluctuations in irrigation water access were influence the smallholder
households to benefit from onion commercialization as irrigation contributes two
or more per year.
• Hence the access to irrigation water is the crucial issue and have unrepresentative
role to produce crops both for home consumption and market at the study area.
• There is the need to establish more main canals or improve farmers’ accessibility
to reliable irrigation water to increase the production of market oriented crops like
onion.
• Besides strengthen the roles of water users’ association (WUA) is also important
to ensure the equal distribution of irrigation water for both upper and lower
streams.
• Depend on brokers as the primary source of market information hinders the onion
commercialization process while the producers not get profit from market price.
Indeed, the cooperation of producers is prerequisite to overcome marketing price
biased by brokers and then get bargaining powers. The strengthening of
smallholders’ market linkage is another area needs policy implications.
• Additionally the Government organizations and others responsible bodies should
strength the inputs supply chains and ensure the availability of inputs at required
time in both amounts and quality for smallholder producers.
The future research direction
• Panel study on Onion commercialization
• Compare Onion and others cash crop commercialization
• Whole commercialization status of smallholders( by use all crops produced at
the area)
72
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Appendices
Appendix 1: VIF for multicollinearity diagnosis (continues variables)
Variables VIF 1/VIF
AGEhh 1.709 0.585
TFMZE 1.304 0.767
EXP(years) 1.307 0.765
TFRMLD(timad) 2.325 0.430
ONFRMLD(timad) 2.993 0.334
TLHOLD(TLU) 1.854 0.539
OXENOWNED(TLU) 1.880 0.531
DROAD(minute) 1.204 0.830
DMKT(minute) 1.689 0.592
Appendix 2:Contingency coefficient for multicollinearity diagnosis(dummy variables)
Variable SEX EDUNhh IRRG CRE
D
EXSER MKTI
N
ONFINC
SEXhh 1.00 .023 .109 .079 .047 .255 .058
EDUNhh .023 1.00 .023 .021 -.020 .119 -.039
IRRGA .110 .023 1.00 .186 .074 .307 .009
CREDT .079 .276 .183 1.00 .450 .089 .027
EXSER 0.047 -.020 .074 .450 1.00 .180 .042
MKTINF 0.255 .119 .307 .089 .180 1.00 .232
ONFINC .058 -.039 .009 .027 .042 .042 1.00
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Appendix 3: Conversion factors used to compute tropical livestock unit
Animal Conversation factor
Ox and cow 1
Bull/woyefen 0.34
Heifer 0.75
Calf 0.25
Sheep and goat(adult) 0.13
Sheep and goat(young0 0.06
Donkey(adult) 0.7
Donkey(young) 0.35
Camel 1.25
Source: (Storck et al., 1991)
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Appendix 4: The Interview schedule for sample households
Interview Schedule on Determinants of Onion Commercialization
among smallholders farming Households: The case of Fentale District of
east shoa zone, Oromia regional state, Ethiopia
Instructions for Enumerators: Make brief introduction before starting any question,
introduce you to the farmers, greet them in local ways and make clear the objective of
the study. Please fill the interview schedule according to the farmers reply (do not put
your own feeling). Please ask each question clearly and patiently until the farmer gets
your points. Please do not use technical terms and do not forget local units. During the
process write answers on the space provided. Prove that all the questions are asked
and the interview schedule format is properly completed.
Date of interview -------------------------------------
Name of the kebele----------------------------------
Name of Enumerator ----------------------------------------------------------
Signature ----------------------------
I. Demographic characteristics of Household
1. Name of household head ------------------------------------------------------------------
2. Age of household head -------------years old
3. Sex of household head 0. Female 1.Male
4. Marital status 1.Single 2.Married 3.Divorced 4. Widowed
5. Religion of household head 1.Muslim 2. Christian 3. Wakeffata 4. Other (Specify)
6. Education status of the household head (1).Unable to read and write (2). Read and
write only (3).Primary [1-6] (4). Junior secondary [7-8] (5).Secondary [9-12]
(6).Tertiary (college and Universities)
7. Total family size including you------------------------------
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II. Livelihood activities and farm use information
8. What is your household’s major means of income generation? (Multiple answer
possible) (1). Crop production (2) Livestock production (3) Handcrafts (4)
Trading (5) Other income generation (specify) --------------------------------------------
9. How long has the household been growing onion? ----------------years
10. Total farm land holding (including rented in during production season) ----------------
hectare
11. Out of total farm land, how many hectares allotted for onion production? ----
hectare
12. Do you have irrigation access for onion production? 0. No 1. Yes
13. Do you participate in onion output marketing from September, 2019 to June, 2020? 0.
No 1.Yes
No Name Age Educational
Sex
level(years In
Male Female schooling)
1
2
3
4
5
6
7
8
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14. If the answer for Q.13 is yes, how many Onions produced and marketed from
September, 2019 to June, 2020?
Amount of onion
produced in kg
Amount sold in kg value of sold onion in ET
Birr
1st round
2nd round
Total
III. Livestock own information
15. Do you have the following live stocks? 0. No. 1. Yes
Type o livestock 1. Yes 0. No If yes, how many in number?
1 Oxen 0. No 1. Yes
2 Bull 0. No 1. Yes
3 Cows 0. No 1. Yes
4 Heifers 0. No 1. Yes
5 Sheep 0. No 1. Yes
6 Goats 0. No 1. Yes
7 Donkeys 0. No 1. Yes
8 Camels 0. No 1. Yes
IV. Information on institutions service
16. Do you have access to credit in case you need it for onion production? 0. No 1.Yes
17. If yes Q. no.16, what is/are the sources of the credit? (1) Families and Friends (2)
MFI (3) Banks (4) Government agencies (5) NGO (6) Others
18. Did the household have access to extension services for onion production? 0. No 1.
Yes
19. If yes, to question 18, how many times did the household contact with extension
visits during the onion production period.___________?
22. Did you know market price before you sold onion? 0. No 1. Yes
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23. If yes, what was/were your source of market information? (1)Neighbours
(2) Traders (3) Mass media (Newspaper, TV, Radio) (4). DA’s (5).Others (specify)
24. Do you /your family participate in off/non-farm activities? 0. No 1. Yes
25. If yes, what is/are your source of off/non-farm activities? 1. Petty trade 2.
Handcrafts, 3. Labour work 4.Others
26. If the answer for Q .No.23 is yes, how many average incomes (ET birr) you get
from off/non-farm activities per year? ------------------birr
27. How far is your place of living from all-weather roads? [In minutes of walking]---
28. How far is your place of living from the market where you sell your onion
production [In minutes of walking] --------------------------
V. challenges and opportunities of onion production and Marketing
29. What are the challenges you face while you produce and marketing onion? Please
list according to the severity.---------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------
30. What are the opportunities of onion production and marketing? ----------------------
-------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------
--------------------------------------------
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Appendix 5: checklist for Focus Group Discussion
FGD (focus group discussion) checklist
Determinants of onion commercialization among smallholders
farming households, the case of fentale district, East shoa
zone Oromia regional state, Ethiopia.
1. What is the average farm land holding of the producers at Kebeles?
2. For what purpose onion produced at your area? Cash (selling almost all what
produced or for consumption purpose)?
3. What are the constraints to onion production and marketing at the area?
4. How far you walk to get onion inputs (it may be market or farmers’
cooperative the place where you buy the inputs like fertilizers, pesticides and
herbicides)
5. Is the price fair?
6. Where do you sell the onion output? How long you move to sell it? Is the price
for output fair?
7. What are the good opportunities (pull factors) at the area to produce onion and
marketing it?
8. From where you buy initial onion seed? Is the price fair?
9. How you rate the access of irrigation water for onion production?
10. Let us discuss the other service you get such as credit, training, expert advice?