Market chain analysis of milk production 5 final

COLLEGE OF BUSINESS AND ECONOMICS, POST GRADUATE
STUDIES
MARKET CHAIN ANALYSIS OF MILK PRODUCTION: THE CASE
OF DEBERE BERHAN TOWN, AMAHARA REGION, ETHIOPIA
M.Sc. Thesis
By
Dereje Admassu Reta
DEPARTMENT OF ECONOMICS,COLLEGE OF BUSINESS AND
ECONOMICS, DEBRE BREHAN UNIVERSITY
June, 2020
Debre Berhan, Ethiopia

DEBRE BREHAN UNIVERSITY
DEPARTMENT OF ECONOMICS COLLEGE OF BUSINESS AND
ECONOMICS
MARKET CHAIN ANALYSIS OF MILK PRODUCTION: THE CASE OF
DEBERE BERHAN TOWN, AMAHARA REGION, ETHIOPIA
M.Sc. Thesis
By
Dereje Admassu Reta
Advisor
Tsega A. (Phd)
A Thesis Submitted to the Department of Economics of Debre Berhan
University
In Partial Fulfillment of requirements for the degree of Masters of Science
in Economics (Development Economics)
June, 2020
Debre Berhan, Ethiopia

STUDIES
THESIS SUBMISSION FOR DEFENSE
APPROVAL SHEET OF THE THESIS - I
This is to certify that the thesis/dissertation entitled: “Market Chain Analysis of Milk
Production: The Case Debere Berhan Town, Amahara Region, Ethiopia” submitted in partial
fulfillment of the requirements for the degree of Masters of Science with specialization in
Development Economics of the Graduate Program of the Economics, College of Business and
Economics, Post Graduate Studies, Debre Berhan University and is a record of original
research carried out by Dereje Admassu Reta Id. No - DBUE/086/10, under my supervision,
and no part of the thesis/dissertation has been submitted for any other degree or diploma.
The assistance and help received during the course of this investigation have been duly
acknowledged. Therefore, I recommend that it to be accepted as fulfilling the thesis/dissertation
requirements.
TSEGA A.(PHD): ________________ _______________________
𝑁𝑎𝑚𝑒 𝑜𝑓 𝑀𝑎𝑗𝑜𝑟 𝐴𝑑𝑣𝑖𝑠𝑜𝑟 𝑆𝑖𝑔𝑛𝑎𝑡𝑢𝑟𝑒 𝐷𝑎𝑡𝑒

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DECLARATION
I, the undersigned, declare that this thesis is my own original work and has not been presented
in any other university. All sources of materials used for this thesis have been duly
acknowledged.
Name: Dereje Admassu Reta
Signature: ---------------------
Date: June ,2020

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STUDIES
THESIS/DISSERTATION FINAL SUBMISSION
APPROVAL SHEET OF THE THESIS - II
We, the undersigned members of the boarded of the examiners of the final open defense by
Dereje Admassu Reta have read and evaluated his thesis/dissertation entitled “Market Chain
Analysis of Milk Production: The Case Debere Berhan Town, Amahara Region,
Ethiopia”, and examined the candidate. This is therefore to certify that the thesis/dissertation
has been accepted in partial fulfillment of the requirements for the degree of Master of Science
in Development Economics.
_______________________ ______________________ ____________________
Chairperson Signature Date
_________________________ ____________________ ___________________
𝑁𝑎𝑚𝑒 𝑜𝑓 𝑀𝑎𝑗𝑜𝑟 𝐴𝑑𝑣𝑖𝑠𝑜𝑟 𝑆𝑖𝑔𝑛𝑎𝑡𝑢𝑟𝑒 𝐷𝑎𝑡𝑒
_________________________ ____________________ ___________________
𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐸𝑥𝑎𝑚𝑖𝑛𝑒𝑟 𝑆𝑖𝑔𝑛𝑎𝑡𝑢𝑟𝑒 𝐷𝑎𝑡𝑒
_________________________ _____________________ ____________________
𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝐸𝑥𝑎𝑚𝑖𝑛𝑒𝑟 𝑆𝑖𝑔𝑛𝑎𝑡𝑢𝑟𝑒 𝐷𝑎𝑡𝑒

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ACKNOWLEDGEMENT
First of all, I would like to thanks God for his kind help ln all aspects of what the world looks
like and partly to enable me to live with health because of his willingness.
I am deeply grateful and thankful to my advisors Tsega Adego (PHD), who devoted his
precious time and energy to comment on the research proposal development from the very
beginning. Successful accomplishment of this research would have been very difficult without
his generous time devotion from the early design of the questionnaire to the final write-up of
the thesis by adding valuable, constructive and ever teaching comments and thus i am indebted
to him for his kind and tireless efforts that enabled me to finalize this thesis. Unreserved thanks
also go to my thesis research Market Chain Analysis of Milk Production, Tizita Gebeyehu
(Prof.) for her examine deeply to write-up for betterment of the thesis.
In addition, I would like to express my sincere appreciation and gratitude to North Showa Zone
livestock and fish development offices and Debre Berhan town administration office to give
basic information for this research,
Finally, my special thanks and heartfelt gratitude extend to my families and
relatives. My wife, Abebech Tefera, both for her encouragement, initiation, patience, and all
round support and the responsibility she took in taking care of our family during my study. Yet
importantly, I would like to thank my daughter Samikatawit for their affection and love.

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TABLE OF CONTENTS
ACKNOWLEDGEMENT....................................................................................iv
TABLE OF CONTENTS.......................................................................................v
LIST OF TABLES AND FGURES......................................................................ix
List of Tables....................................................................................................................................... ix
Lists of Figure....................................................................................................................................... x
LIST OF APPENDIX TABLE ............................................................................xi
LIST OF ACRONYMS ...................................................................................... xii
ABSTRACT....................................................................................................... xiii
CHAPTER ONE....................................................................................................1
INTRODUCTION .................................................................................................1
1.1. Background of The Study........................................................................................................1
1.2. Statement of the Problem ......................................................................................................2
1.3. Objectives of The Study ..........................................................................................................4
1.3.1. General Objective ..........................................................................................................4
1.3.2. Specific Objectives.........................................................................................................4
1.4. Research Questions.................................................................................................................5
1.5. Significance of The Study........................................................................................................5
1.6. Scope and Limitation of the Study..........................................................................................5
1.7. Organization of The Research.................................................................................................6
1.8. Research Ethics........................................................................................................................6
CHAPTER TWO ...................................................................................................7
LITERATURE REVIEW ......................................................................................7
2.1.1. Basic Concepts of Market Chain .........................................................................................7
2.1.1.1. Marketing...................................................................................................................7
2.1.1.2 Marketing System..........................................................................................................7
2.1.1.3. Marketing Channel....................................................................................................8
2.1.1.4. Market Chain Actors.................................................................................................8

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2.1.1.5. Marketing Costs.........................................................................................................8
2.1.2. Concepts of theoretical Literature......................................................................................9
2.1.2.1. Dairy Production in The World ...............................................................................9
2.1.2.1. Dairy Production Systems in Ethiopia...................................................................10
2.1.2.1.1. The Commercial Milking Cow ...............................................................................10
2.1.2.1.2. The Urban/Peri-Urban ..........................................................................................11
2.1.2.1.3. The Mixed Crop-Livestock.....................................................................................11
2.1.2.1.4. The Pastoral/Agro-Pastoral Systems....................................................................12
2.1.2.2. Dairy Sector Policy in Ethiopia ..............................................................................12
2.1.2.3. Ethiopia Dairy Marketing System..........................................................................13
2.1.2.4. Value Chain Relationships in Amhara Region .....................................................13
2.1.2.5. Ethiopian Prospects On Dairy Production..........................................................13
2.1.2.6. Milk Potential Commercialization Areas in Ethiopia ..........................................14
2.1.2.7. Determinates Participation Decision of Milk Production & Milk Supply....................14
2.1.2.7.1. Demographic Factors ..............................................................................................14
2.1.2.7.2. Economic Factors.....................................................................................................15
2.1.2.7.3. Institutional Factors ................................................................................................15
2.2. Conceptual Framework.........................................................................................................16
CHAPTER THREE .............................................................................................17
METHODOLOGY OF THE STUDY.................................................................17
3.1. Description of Study Area.....................................................................................................17
3.1.1. Location ........................................................................................................................17
3.1.2. Climate..........................................................................................................................19
3.1.3. Demography and Population Dynamics ....................................................................19
3.2. Data Source and Collection Methods........................................................................................20
3.2.1. Data Types and Sources ..............................................................................................20

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3.2.2. Method of Data Collection................................................................................................20
3.3. Sample Methods and Size.....................................................................................................20
3.4. Research Design and Rationale ............................................................................................22
3.5.1. Description Statistics ...................................................................................................22
3.5.1.1. Analysis of Structure Conduct and Performance .................................................22
3.5.1.2. Market Concentration Ratio.................................................................................22
3.5.1.3. Marketing Margin .................................................................................................23
3.5.2. Econometric Models ....................................................................................................24
3.5.2.2. Econometric Model for Deciding Participation...........................................................25
3.5.2.1. Market Supply Econometric Model......................................................................26
3.5.3. Variables Description and Hypothesis.......................................................................29
3.6. Pilot Survey Summery...........................................................................................................35
CHAPTER FOUR................................................................................................37
RESULTS AND DISCUSSION..........................................................................37
4.1. Results of descriptive Analysis of Milk Producer ..................................................................37
4.1.1. The Influences of Demographic Characteristic ..............................................................37
4.1.1.1. Participant, Age, Gender/Sex, Experience and Land..................................................37
4.1.1.2. Education......................................................................................................................38
4.1.1.3. Number of Children.......................................................................................................40
4.1.3.4. Number of Family Households ......................................................................................41
4.1.2. Influence Economic Factors On Milk Production ..........................................................42
4.1.2.1. Number of Cross Breed Milking Cows.....................................................................42
4.1.2.2. Price Per Liter Offered at The Market.....................................................................43
4.1.2.3. Income Sources Households......................................................................................43
4.1.3. Influences of Institutional Factors On Milk Production................................................44
4.1.3.4. Extension Service........................................................................................................45

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4.2. Results of Descriptive Analysis of Actors ...............................................................................46
4.2.1. General Background of the Actors...................................................................................47
4.2.2. Institution On Milk Marketing /Supporting Actors.......................................................47
4.2.4. Their Roles and Linkages in of Milk Value Chain and Channels..............................48
4.2.4. Analysis of Structure, Conduct and Performance of Milk Market.............................53
4.2.4.2. Market Conduct ............................................................................................................53
4.2.4.3. Milk Market Performance (Marketing Costs and Margin).............................54
4.3. Results from The Econometrics Model ................................................................................56
4.3.1. Determinant of Milk Market Participation Decision .....................................................56
4.3.2. The Factors Affecting the Volume of Milk Supplied to The Market ............................60
4.4. Prospects and Major Constraints On Fresh Row Milk Market Value Chain........................63
4.4.1. Major Constraints of Dairy Production and Marketing................................................63
4.4.2. Major Prospects of Dairy Production and Marketing ...................................................65
CHAPTER FIVE .................................................................................................67
CONCLUSION, POLICY IMPLICATIONS......................................................67
5.1. Conclusion..................................................................................................................................67
5.2. Policy Implications...................................................................................................................69
5.3. Suggestion for Further Research ...............................................................................................71
REFERENCES ....................................................................................................72
APPENDIX: SURVEY QUESTIONNAIRES.....................................................a
APPENDIX: TABLES ..........................................................................................i

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LIST OF TABLES AND FGURES
List of Tables
Table 1: Population Size with dairy farmer on Debre Birhan …….………………… 21
Table:2 Milk retailing kiosks, High and medial Processers, Consumers/hotels,
restaurants and cafes dairy producers/farmers………………………………………... 20
Table 3 Distribution of sample dairy farmers included in the survey by kebeles……. 21
Table 4: The explanatory verbal of related farmers in production milk deciding
participation & farm level milk product supply to the market producers......... 34
Table 5: Major means of income sources for farming households…………….…. ….. 44
Table 6: The extension service for dairy farmers per households Debere Berhan Town 46
Table 7: access of credit and information for fresh row milk for actors ….…… …….. 48
Table 8: Performance of milk marketing in different channels of the study area……… 55
Table 9: The probit regression the determinates of the milk supply to market.............. 57
Table 10: The tobit model regression the determinates of the milk supply to market…. 61

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Lists of Figure
Figure 1: Production of milk around the world by region (Average 2014 - 20118) …….. 9
Figure 2: Conceptual framework model of the factors of farmer’s market deciding
participation and farm level milk product supply to the market..………………………. 16
Figure 3: Map of the study area………………… ……………………………................. 18
Figure 4: Socio-demographic characteristics of framing households milk production (in
average, years and %)…………………………………………………………………….. 38
Figure 5: education level of milk market participant farmer of Debre Berhan………… 39
Figure 6: Number of children per HH in dairy farming in Debere Berhan town………… 40
Figure 7: Number of HH in dairy farming in urban/per- urban Debre Berhan town…… 41
Figure 8: Number Cross Breeding per of HH in dairy farming in Debre Berhan Town…. 42
Figure 9: access of credit, information and member of cooperative dairy farming per HH
in Debre Berhan town……………………………………………...................................... 45
Figure 11: Market chain map of fresh row milk of Debre Berhan town………………..... 51
Figure 12: Fresh row milk marketing channels 2020 (percentage and tons) …… ……... 52

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LIST OF APPENDIX TABLE
Appendix: Table 1. General characteristics respondent households milk production (in
average, years and %)…….……….…………………………….………………………
i
Appendix: Table 2. General characteristics respondent households milk production (in
aver., years and %)…….……………….…………………………….………………………
i
Appendix: Table 3. Number of cross breed milking cows, Price per liter offered at the
market and income sources…….…….…………………………….………………………
j
Appendix: Table 4. General characteristics respondent Wholesalers/processors, Retailers
/middleman on milk market (in average, years and %)…….………………………………
j
Appendix: Table 5. Total volume fresh row milk bought by marketing actors…….……… k
Appendix: Table 6. Result of variance inflation factors (VIF) for factors affecting of milk
market participation decision and level of milk supply to market…….…………………….
l
Appendix: Table 7. Correlation matrix of coefficients of probit model /. estat vce,
correlation….……………….…………………………….…………………………………
m
Appendix: Table 8. Correlation matrix of coefficients of tobit model/. estat vce,
correlation…….…….……………….…………………………….…………………………
n
Appendix: Table 9. Prospects and Major Constraints On Fresh Row Cow Milk Market
Value Chain….……………….…………………………….………………………………..
o

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LIST OF ACRONYMS
AGP Agricultural Growth Project
ANRS Amhara National Regional State
ASL Africa Sustainable Livestock
CR Concentration Ratio
CSA Central Statistics Agency
DBTA Debre Berhan Town Administration
FAO Food and Agricultural Organization
GMMP Gross Marketing Margin price
GTP Gross Transformation Plan
HH Households
HHI Herfindahl-Hirschman index
Km2
Kilo Mater Square
M.a.s.l Meter above sea level
MoARD Ministry of Agricultural and Rural development
NGOs Nun -Governmental Organization
NMM Net Marketing Margin
NSZTIFLD North Showa Zone Trade and Industry and fish and livestock Department
RuLIS Rural-Urban Livestock International Statistics
SCP Structure-Conduct-Performance
SNV The Netherlands Development Organization
TGMM Total Gross Marketing Margin
t t-test
X2 Chi-Square

xiii
ABSTRACT
The overall aim of this study is examine to the linkage of supply with demand, supportive
institution, price margin between terminal with producers, important role in the future
prospective increasing milk production. The general objective of this study to analyze the
market chain of milk production in Debere Berhan town. The data type was generated
quantitative and qualitative used on primary & secondary data source of farmers and actors
based on survey questionnaires and relevant document respectively. A total of 322
smallholder’s farmers and actors were simple random sample selected. The Probit & Tobit
models were employed to analyze factors affecting participation decision and level of
participation of smallholder milk producer supply milk to market. This models showed that the
results of probit model for policy implication reviled that educational level, family size, number
of cross - breed cows to effect positively and number of children under six years old, experience,
membership to milk producers’ cooperative to effect negatively per households on milk market
participation decision. Furthermore, Tobit model revealed that educational level and number
of cross - breed milking cows to affect positively and number of children under six years old to
affect negatively per households on participation to supply of milk to the market. The s-c-p of
milk market chain broadly classified into four; input suppliers; producer, marketer
(wholesalers, retailers); consumers. Hence, milk producers sold to the market about 607.14
tons (680,900) liters at time 2020/21 totally. Channel three and two was the first & second
dominant marketing channel in volume of milk supply were about 66.67% & 24.90%
respectively. This study TGMM considered producers portion ranked & the highest net profit
was found channel four 35.7%. The structure was found relatively perfect competition to an
oligopoly in case of the market share less than 28%. According to the survey the producers
and marketer faced by high price of cross- breed milking cow, shortage of feed, lack of credit,
low breed performance, season with related religion, and quality milk problem. However, the
various constraints the dairy production faced static & profitable business for the small
holders. Generally, milk products & market in the study area seems to be ineffective and
underdeveloped. So that, the government and other dairy sector development partners in
particular this study area and nationally to give attention. Such as; linkage of access
information, veterinary service & credit and promote investment on dairy production for the
purpose of skill developments or technology transfer for improve, Through short and practical
orated training Increase the knowledge and skills up the small household farmers, capacity
family planning in particular females & family division of labors forces for farmers &
marketers.
Key Words: Dairy Producers , Debere Berhan, ,Market chain analysis Probit and Tobit
Model

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CHAPTER ONE
INTRODUCTION
1.1. Background of The Study
World milk production by regions 843 million ton produce milk production at time 2018 in the
world and with compared at time 2017 increased by 2.2. This milk output increased different
global nation and union such as in India, turkey, European union, Pakistan, the USA. However,
to some extent declines in china, Ukraine and others. This increase has come in India, European
union, Pakistan, the USA and turkey Argentina with development of people and milk collection
and processes, yield per cow, dairy production systems and the size of more demand. Milk
production decrease in China and Ukraine in case of margins and price (FAO, 2019).
In Africa, milk output is estimated at 350 million tones, an increase of 1.1 percent on account
of output increases in some large milk producing countries such as Kenya, South Africa, Algeria
and Morocco, but partially offset by decreases elsewhere, especially Mali and Niger (FAO,
2019). Similarly, that Ethiopia is believed to have the largest Livestock population in Africa.
The total livestock population estimated to be about 59.9 million cattle & other 0.41-30.70
million livestock. the total population about 11.83 million are milking cows are kept for milk
production. (CSA, 2017). From the same source in the given year the total milk production from
cow is about 3.1 billion. (RuLIS dataset ;FAO ;CSA, 2014). The Ethiopian government one of
priority on GTP II period(2015-2020) increase the dairy production particularly average fresh
row cow milk annual growth rate by 15.5% , from 5,304 million litters to 9,418 million litters
(GTP, 2016). But this production and productivity is very low compared with regional other
African countries and world in average.
Although, the dairy marketing channels is assumed to provide a systematic knowledge of the
flow of dairy and its products from their production areas to their final end-users (Mesay, 2012).
The main formal marketing functions in milk major actors on value chain are processors, traders
(collectors, wholesalers, retailers and Cafe/Hotel owners), and consumers (Ketema,2016;
Abu,2016; Ali, 2017). Similarly, in Amhara region a commonly accepted figure is less than
10% enters the formal channel. Informal market, milk may pass from producers to consumers

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directly or it may pass through two or more market agents to local consumers and neighboring.
The informal system is characterized by no licensing requirement to operate, low cost of
operations, high producer price compared to formal market and no regulation of operations.
The informal (traditional) milk channel has remained dominant in Ethiopia (Feleke G. , 2003;
Land O’Lakes, 2010).
Grounded on it, this study was done for benefiting, clearing ambiguity, for researchers,
planners, policy makers, nation, non-governmental organization, for zonal and town
administration & for others to fill the linkage gaps. Such as; farmers with actors and also
producers with supportive institutions for promote investment on dairy production for the
purpose of skill developments or technology transfer and removes the price gap between
terminal and primary markets seem very large mean that the price differs 5-8 birr per liters of
fresh row cow milk. Under these condition producers have no encouragement to improve
quality fresh row cow milk product and cross breeding milking cow in this study area (CSA,
2006), (SNV , 2008).Therefore, this research study were analyzed based on three questions.
Such as, who are the key milk marketing channels, the milk market chain actors their functions
and what does marketing margins along the chain looks like? What are the factors that affect
farmers in production milk deciding participation & level milk product supply to the market?
and What are the prospects and major constraints of milk production and marketing? based on
cross-sectional data information. As this study was started on January, 2020.
1.2. Statement of the Problem
The world small farm house holders are facing the problems and supply fresh row cow milk to
the market. Those determinates similarly and related topics with interrelated this study where
Make great efforts to avoid problems based theoretical & empirical studies have been raised by
different researchers in the world in particularly Asia such as (Swarup Barua M. J., 2017) in
Chittagong district of Bangladesh; (Ravneet Singh Brar, 2018) in Punjab –Indian. Similarly,
in Africa was identified by scholars (Elly Kiptanui Kurgat, 2019) in Uasin Gishu County –
Kenya.
Although, the similar or related topic in Ethiopian smallholder dairy producers are facing by
numbers of problems or factors for participated their subsistence fresh row cow milk to the

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market. Those factors for escape were identified not the same academics show on theoretical
and empirical analysis in different potential study area of Ethiopia. The analysis of those
investigators were mention on market chain, channel and margin, factors affecting of milk
production on participation & volume supply of fresh row milk cow to the market and constraint
and prospective individually such that (Sintayehu Yigrem, 2008; Berhanu, 2012; Meryem, 2013
& Tadele Mamo, 2014; Mekonnen, 2015 Ali, 2017) on the study area Dilla, Wolaita zone,
sululta district-Oromia ,Welmera woreda west showa - Oromia, Laelay maichew woreda-
central Tigray, dessie zuria-Amhara region respectively.
This study area has milk production potential, huge demand and relatively infrastructure (road,
telephone) in urban and per urban of Debre Berhan. Therefore, on this study was mentioned the
field of demographic, economic & institutional identifies determinants such as sex (gander),
age, education level, family size, number of children of the household, land holding size,
experience milk production, access of market information, access of credit, extension serves,
number of cross breed milking cows, price per liter offered at the market, income of households
and members of cooperative (Tadele Mamo, 2014); (Tsega Lemma, 2017); (Anjani Kumar,
2010) ; (Ali, 2017) and different gapes. Such as; linkage of milk producers(farmers) with actors
and also producers with supportive institutions for promote investment on dairy production for
the purpose of skill developments or technology transfer and removes the price gap between
terminal and primary markets seem very large mean that the price differs 5-8 birr per liters of
fresh row cow milk. Under these condition producers have no encouragement to improve
quality fresh row cow milk product and cross breeding milking cow in this study area (CSA,
2006), (SNV , 2008). And also most of academic member milk producer’s cooperative not seen
member of milk producer’s cooperative with distance collective center.
So, ‘’market chain analysis of milk production: the case Debere Berhan town, Amahara region,
Ethiopia” topic to analysis based on three major questions such as (1) who are the key milk
marketing channels, the milk market chain actors their functions and what does marketing
margins along the chain looks like? (2) What are the determinants farmers in production milk
participation decisions and volume milk product supply to the market? And (3) What are the
prospects and major constraints of milk production and marketing?

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While, this study was applied in Debere Berhan town specifically in 01,06,07,08 and 09 kebeles
administration with centered on number of urban and pre- urban farmers. The sampling methods
was employed from the total 2043 sample population size only 342 sample size was selected
based on simple random procedure from farmers participate and most of milk traders in this
study area.
Moreover, mixed data types were used in the study under investigation. In order to generate
these data types, both secondary and primary data sources was used considering survey
questioners & relevant documents respectively. And also; the type of data analysis were
employed descriptive and econometrics probit and tobit model separately analysis. This method
of data analysis to the use of ratio, percentages, mean and standard deviations in the process of
examine and description socio -economic characters of milk households, traders of the study
area.
Generally, this study will be benefiting & important contributions for City administration, Dairy
Farmers, Policy makers, literature review for further research on similar topics and other related
issue Other actors in the milk -wholesalers /Processers and retailing /middleman.
1.3. Objectives of The Study
1.3.1. General Objective
The general objective of this study is to analyze the Market Chain Analysis of milk production
in Debere Berhan Town.
1.3.2. Specific Objectives
The specific objectives of the study are:
 to identify the key milk marketing channels, and margins it in Debere Berhan Town.
 to identifies determinants participation decision and level of participation of smallholder
milk producer households in milk market supply in Debere Berhan Town.
 to examine the prospects and major constraints of milk production and marketing in
Debere Berhan Town.

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1.4. Research Questions
 Who are the key milk marketing channels, the milk market chain actors their functions and
what does marketing margins along the chain looks like?
 What are the identifies determinants farmers in production milk deciding participation and
farm level milk product supply to the market?
 What are the prospects and major constraints of milk production and marketing?
1.5. Significance of The Study
This study would generate respected information on the fresh row cow milk market chain in the
study area. That might have contribution city administration and policy - makers at various
levels to make relevant decisions to intervene in the development of dairy cattle milk
production, marketing, processing and designing of appropriate policies and strategies.
Governmental and non-governmental organizations that are intervening through their programs
in the development of the dairy sub-sector are expected to benefit from the result of this study.
The findings of this study are also been useful to input suppliers, dairy farmers, traders to make
their respective decisions. It may also serve as a reference material or literature review for
further research on similar topics and other related issue.
1.6. Scope and Limitation of the Study
The study was focus and restricted in Debre Birhan town in surrounded area of 146 km² and
the data was collected only from the study area. Furthermore, the study was focused to identify
the key fresh row cow milk marketing channels, margins and costs; to identified participation
& volume supply of fresh row cow milk to market and to examine the prospective & constraints
milk producers & marketers. However, this study has limitation. The limitation of this study
were not covered fresh row cow milk value add products (Butter, cheese etc.) supply and
marketing. Moreover, the limitation of this study were used the sample area only the respective
fives Kebeles such as; out of nine kebeles was selected 01,06,07,08 and 09 kebeles
administration in Debere Berhan town due to budget and time limitations/constraints.

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1.7. Organization of The Research
this research was organized into five main sections. Chapter one is devoted to introduction of
the study and it contains the background of the study, statement of the problem, objectives of
the study, research questions, significance of the study, scope of the study and organization of
the research. Chapter two contains literature review that presents theoretical and empirical
review. In chapter three methodology of the study is presents overview of the study area, the
research design, data source and collection methods, sample size and sampling techniques and
method of data analysis and model specification and hypothesis. Chapter four presents result
and discussions. Chapter five conclusion and policy implication. Additionally, in this study was
included list of references and appendices.
1.8. Research Ethics
The study the research on the Market Chain Analysis of milk production on urban of Ethiopia:
The Case Debere Berhan Town, Amahara region. Based on the argument that the ethical
analysis should be extended to take into account more appropriate factors, such as cultural,
gender, ethnic and geographical considerations. Hence, the aim of ethical review is to protect
participants. They were a valuable part of the research process and not only a means of
accessing data. However, ethical review also helps to protect the researcher (Nancy, 2006). So
that; during the study was responsible any obstacle with legality of the research study
participant.

7
CHAPTER TWO
LITERATURE REVIEW
This chapter is discussed in to three key sections like the basic concepts of market chain,
conceptual theoretical literature & Finally, this chapter is showed conceptual frame work.
2.1. Theoretical literature
2.1.1. Basic Concepts of Market Chain
2.1.1.1. Marketing
Deferent scholars sided about market and the recent one the marketing concept in the 2000s is
a societal process by which individuals and groups obtain what they need and want through
creating, offering and freely exchanging products and services of value with others (Jordan
Gamble, 2011). The most observable features of a market are its pricing and exchange processes
and it is more than a physical place. No need to meet physically for a market to operate
especially in today’s information and communication technologies (Bain, 1988).
2.1.1.2 Marketing System
The relationships of between the society including individuals, firms, communities and
organization it Saied to be market system. marketing system different place to place and
different marketing structure such as in Africa (Fisk, 1967). Marketing system is a general term
that represents how different patterns of the flows of goods/services from producers to
consumers are culturally (uniquely) organized. theoretically marketing systems targeted on
social approach ,strategic and also it is establish ,adopted and evolution (Layton, 2015). social
mechanisms include cooperation, specialization, and self-organization, while strategic action
fields comprise the action and practices of marketing system actors in their specific roles.
Layton argues that marketing systems emerge as localized exchanges grow in scope and
become stabilized while specialization expands, and in addition, as key structures become
formalized.

8
2.1.1.3. Marketing Channel
It is business structure of inter-reliant of organization reach the product from the firs
producers to end users or consumers (Kotler, 2003). The market channels is analysis the
performance of between from the follow of milk production and end users or consumer based
on systematic knowledge. This knowledge is attained by studying the participants in the
process, i.e. those who perform physical marketing functions in order to obtain economic
benefits (Mekonnen, 2015).
2.1.1.4. Market Chain Actors
Market chain actors mean that the intermediates of in input supply, producers, marketing and
consumers on agricultural product. those middlemen to involves directly and indirectly way.
the direct involvement such as on cooperative, wholesaler /processors retailers …etc. and also
indirect involvers input suppliers such as access of credit, information and extension
agent…etc. (Mekonnen, 2015). such as,
1. Producer: It is the first link in milk market chain; the producer harvests products and
supplies to the second agent. From the moment he/she decides what to produce, how
much to grow and when to grow and sale.
2. consumer: it is the last link in the milk market chain, the participants and their
respective functions often overlap. mean that the consumers are the end users of
wholesalers/processors, retailers and directly from producers
3. Rural assembler/locale collector: Sometimes also known as farmer trader, he/she is
the first link between producer and other middlemen.
4. Wholesaler: They concentrate on the various intermediate sized loads and put the
product into large uniform units from the others intermediates.
5. Retailers: retailers one of the intermediate on the market. However; most of the time
with related others traders such as sell small amount such as fresh row milk per –
litters in super market and other.
2.1.1.5. Marketing Costs
Its refers to those costs, which are incurred to accomplish different activities
of marketing in the transportation of goods from point of production to the end consumers.

9
Marketing costs includes storage costs, handling costs (packing and unpacking, costs of
searching for exchange, screening potential trading partners to ascertain their trustworthiness,
bargaining with potential trading partners and officials to reach an agreement, transferring the
product, monitoring the agreement to see that its conditions are fulfilled, and enforcing the
exchange agreement etc. (Holloway, G. and Ehui, S., 2002).
2.1.2. Concepts of theoretical Literature
2.1.2.1. Dairy Production in The World
843 million ton produce milk production at time 2018 in the world and with compared at
time 2017 increased by 2.2. This milk output increased different global nation and union such
as in India, turkey, European union, Pakistan, the USA. However, to some extent declines in
china, Ukraine and others. This increase has come in India, European union, Pakistan, the USA
and turkey Argentina with development of people and milk collection and processes, yield per
cow, dairy production systems and the size of more demand. Milk production decrease in
China and Ukraine in case of margins and price (FAO, 2019).
Figure -1 Production of milk around the world by region (Average 2014 - 20118)
Source: (FAO, 2019).

10
2.1.2.1. Dairy Production Systems in Ethiopia
Mainstay agriculture of Ethiopian economy and its contributions to the economy of the
country accounts 72.7% employment and 36.2% to the country’s GDP (Central Intelligence
Agency, 2017) From the agricultural sector, livestock is an integral part of the agriculture and
the contribution of live animals and their products to the agricultural economy accounts 40%,
excluding the values of draught power, compost and transportation (Aleme A, 2015).
In Africa one of the largest livestock population nation is Ethiopia. The total livestock
population estimated to be about 59.9 million cattle & other 0.41-30.70 million livestock. the
total population about 11.83 million are milking cows & others 1.26-23.15 million livestock
are kept for milk production (CSA, 2017). From the same source in the given year the total milk
production from cow is about 3.1 billion. And also the other There are at least 13 million cattle
keeping households (RuLIS dataset ;FAO ;CSA, 2014).
Although, the Stakeholders have identified 4 major dairy production systems in Ethiopia. which
is including the commercial, the urban/per urban, the mixed crop-livestock, and the
pastoral/agro-pastoral systems
2.1.2.1.1. The Commercial Milking Cow
The specialized commercial dairy systems involving higher levels of investment are
concentrated in the central highland plateau. In terms of scale of operation, the small number
of farms are classified >100 milking cows for large-scale; 30–100 for medium-scale; and <30
for small-scale farms. The Milk yield 15 up to 20 litres per day per cow using purebred exotic,
high-grade or crossbred dairy animals. the fresh row cow milk is being usually sold at kiosks
or supermarkets. A small proportion are used for home consumption. Being licensed farms
with operational business plans, they are market oriented specifically targeting consumers in
urban areas. Producers tend to have a good understanding of dairy management. The
commercial dairy system is labor and input intensive relative to other systems. The animals do
not deliver draft power but their dung is used as fertilizer.
Driven by the unparalleled increase in milk demand and other dairy products, commercial dairy
is a growing sub-system in Ethiopia. However, it is constrained by shortage of inputs

11
particularly feed, genotypes, and veterinary services. Most commercial farmers are obliged to
process the milk they produce into various dairy products but not all have the financial and
infrastructural capabilities to happen such obligations (ASL, 2050).
2.1.2.1.2. The Urban/Peri-Urban
The urban/peri-urban fresh row cow milk production system is found largely plateau, invasively
in capital city of Ethiopia in Addis Ababa, and regional city readily available. The average her
size is 5 up to 10 per households and also the milk yield 10-15 liters per day per cow with
lactation period of ~200 days using high-grade or crossbred animals. The marketing of milk
production unpackaged of produced milk is sold to neighbors through informal channels or to
cafes and restaurants; a small amount is used for home consumption. It is practiced by many
landless urban and sub-urban poor households.
However, some business men and retired civil servants also keep some dairy animals
depending, wholly or partly, on hired labor. Producers are market oriented and respond to
improved technical, input supply and marketing services. This is also growing in Ethiopia.
However, it is constrained by shortage of inputs particularly feed, genotypes, and veterinary
services. Milk handling is very poor as re-used plastic bottles and jerry cans that are difficult to
clean are used for transport, and milk delivered through this system is mainly fed to infants and
children. Nowadays, urban smallholders are facing pressure from municipalities to shut down
their farms because of health and environmental issues (ASL, 2050).
2.1.2.1.3. The Mixed Crop-Livestock
Mixed crop–livestock dairy production is a subsistence oriented farming system concentrated
in the mid- and high-altitude agro-ecological zones where cereals and cash crops are dominant
on approximately 9.6 million the number farmers farm activities. Cows are the primarily
function for the need of crop production. And also the average number of cow four with the
volume of milk per cow only 1.9 litres per day, on average using indigenous typical breeds.
This production about 65 percent of the total milking cows are found in this system and produce
about 72 percent of the national annual milk output. Basically, the marketing of it smallholder
farmers either sell excess milk informally to individual consumers and milk collectors or
process it into butter and cottage cheese for sale. Dairy production in mixed crop with livestock

12
system is pivotal to supplying the bulk of milk and milk products to the Ethiopian population.
However, it is not market oriented and productivity per unit of land and per head of animal is
extremely low. At the same time, poor service delivery systems, particularly veterinary services,
makes it prone to disease outbreaks and losses due to mortality and morbidity (ASL, 2050).
2.1.2.1.4. The Pastoral/Agro-Pastoral Systems.
3.1. million Pastoral/agro-pastoral production is the major system of milk production practiced
in the lowland regions of Ethiopia where livelihoods are heavily dependent on livestock. Cattle
dominate the livestock population followed by camel, goats, and sheep. Cows constitute about
40 percent of the herd. Major pastoral areas extend from the north-eastern and eastern lowlands
(Afar and Somali) to the southern and south-western lowlands (Borana and South Omo). The
average herd size almost 10–20; large herds of >200 heads are common too, the milk yield
approximately 1.5 litres per cow per day using entirely indigenous breeds are kept typical
breeds, and dairy cattle population accounts for ~36 percent of the national herd. The marketing
of milk production for home consumption but excess milk or milk products are sold to nearby
towns or highlanders. Due to an erratic rainfall pattern an important factor that determines
availability of feed and water milk production per unit area is low and highly seasonal.
However, milk is usually produced in excess during the wet season and is either sold fresh to
nearby urban centers or processed into butter to be traded with the highlanders in the peripheral
markets for grains. The reliance of the agro-pastoral and pastoral systems on the overgrazed
natural resource base makes them most vulnerable to climate change (ASL, 2050)
2.1.2.2. Dairy Sector Policy in Ethiopia
one of priority aims of Ethiopian government are to improve the dairy production or milk
production in case of this on GPT II period from 2015- 2020 increase by 15.5 percent in
particularly improve from 5,304 million litters to 9,418 million litters. this incensement occurs
by inspiring the private organization to produce fresh row cow milk, targeting genetic
improvement increasing investment particularly commercial dairy farm in clusters of the region
Tigray, Amhara, Oromia and SNNP through selecting premium indigenous breeds and
introduction of exotic breeds (GTP, 2016).

13
2.1.2.3. Ethiopia Dairy Marketing System
The dairy market channels is regular information the movement of fresh row cow milk to the
end user consumer (Mesay Y, 2012). When to challenge constraints and access available
opportunities fresh row cow milk pass through mediators to the end users or consumers. The
main formal marketing functions in milk value chain are collection, wholesaling, processing,
retailing and consumption (Ali, 2017). and also accept this other Academics’ (Ketema M,
2016) , (KU, 2012). Moreover, the informal fresh row cow milk market system is characterized
by no licensing requirement to operate, low cost of operations, high producer price compared
to formal market and no regulation of operations. As The informal (traditional) milk channel
has remained dominant in Ethiopia (Land O’Lakes, 2010).
2.1.2.4. Value Chain Relationships in Amhara Region
In Amhara region market of dairy products are using formal and informal channels. In the
informal milk market producers directly deliver raw milk to consumers or cafes and hotels.
Most of yield of fresh row cow milk product purchased by supplier more than 3.5% in case of
full fat and trusted relationship between consumers and sellers. In the formal milk market
Cooperatives are the main actors in the collection and sales of milk in the regions. The formal
channel on fresh row cow milk market in the Amhara region less than 10%. The dairy products
are sold fresh row cow milk without being packed and branded, often using jerrycans and other
simple containers for actors as a result of check milk quality by using alcohol tests and
lactometers, visual inspection. However, consumers do not complain about milk quality as long
as they do not suspect that the fat content is reduced. Moreover, consumers purchase fresh row
cow milk from shops, kiosks through retailers or directly from producers. (AGP-LMD, 2013).
2.1.2.5. Ethiopian Prospects On Dairy Production
The future prospects of dairying seem to be bright because the challenges so far indicated and
the government is attempting them to address through polices and strategies. Based on accesses
of exception services and inputs that could help promote dairy production and productivity.
This mainly include feed and feeding, breeding services, credit extension, training veterinary
services and appropriate marketing system that address costumers demand.

14
Since dairy is labor intensive farming and to promote the government policy and its creating
employ opportunity in household level. mean that dairy production improve employment,
income and nutrition value per householders and the end users /consumers. Moreover, the
Ethiopian government is considering dairy industry the other main instrument of achieving
food security (Zegeye, 2003). The development of infrastructure like, transportation would
help change the traditional thinking of fresh milk not for sale other than exclusively intended
for human consumption among the rural population, their income will increase and be in
position to buy non-market food types in exchange and there by improve their living standard.
Since the country is an agrarian economy, dairying is much expected to be one of the major
targets of the prospective agro-processing industries in the country (Azage, 1998).
2.1.2.6. Milk Potential Commercialization Areas in Ethiopia
North showa zone districts in Amhara regional states of the country suitable for market-oriented
milk production systems or the milk shed were identified by MoARD in 2005. The major milk
shed areas to a very large extent fall within the central highlands of the country, where the milk
consumption is also higher due to higher population density and size compared to other
ecological zones. the main fresh row cow milk production district such as urban and pre urban
place and regional town. Although, this area has batter infrastructures. In the highland zones,
milk production is given priority over other livestock production systems due to ecological
conditions and the population pressure that favors dairy production and the existence of
neighboring arid-areas with a comparative advantage for specialization in beef-production
(SNV, 2008).
2.1.2.7. Determinates Participation Decision of Milk Production & Milk Supply
Many academics study has been discussed about factors that affect farmers in production milk
deciding participation & farm level milk product supply to the market was categorized in to
three such as demographic, economical and institutional factors. Such that;
2.1.2.7.1. Demographic Factors
The demographic factors such as age, women’s, number of family, education level, number of
children, and experience are the factor affecting affect farmers in production milk deciding

15
participation & farm level milk product supply to the market. The explanatory variables
affecting the positivity and negatively those dependent variables. Based on the indication
different academics such as age, women’s, number of family’s per households were illustrated
positively affecting on farmers in production milk deciding participation & farm level milk
product supply to the market (Tadele Mamo, 2014); (Tsega Lemma, 2017); (Anjani Kumar,
2010) ; (Ali, 2017) . but, anther scholars showed that being male head of a household affected
positively (Kuru, 2013) ;and (Karna, 2016).. However, number of children, experience of dairy
farmers to affected farmers in production milk deciding participation & farm level milk product
supply to the market. (Kuru, 2013). But, other academics Experience in Milk Production is
based on the fact that of different scholars when the experience of a farmer in dairy production
increases or influence positively (Swarup Barua M. J., 2017).
2.1.2.7.2. Economic Factors
The economic factors of milk market chain such as land holding size, number of cross breeding
milk cow, price liters of milk income source are appositive relation to allocated a likelihood of
getting better farm output that enables them to fulfill necessary inputs for milk business
activities. Land is very important input for fodder and pasture development to feed dairy cows;
to improving yield of milk production; farmer sees better price the probability of entering a
market and volume of milk supply is increasing; and to improving liquidity, this income makes
the household to expand production and or/ purchase from market. It also strengthens the
household position in coping with different forms of risks of it respectively. Fatherly, the
explanatory variables to affected on the dependent variables positively on farmers in
production milk deciding participation & farm level milk product supply to the market (Ali,
2017); (Berhanu Gebremedhin, 2013) (Tadele et al. and Tadele Mamo, 2014); (Burke W, 2015)
; (Benyam Tadesse, 2016). But the size of land holding increases by a hectare, the level of
participation of milk producers’ household in milk value addition decreases (Berhanu, 2012).
2.1.2.7.3. Institutional Factors
According to different scholars were found that explanatory variables access of market
information; credit; frequency of extension contact per month; members of cooperative showed
positive relationship when the variables having mobile phone and good communication with

16
milk traders; improves the financial capacity of dairy households to buy more improved dairy
cows; capacity of household’s skill in dairy production; better opportunity to bargain and get
fair price for their milk products which encourages and the collector of cooperative near to
living house of farmers. Fatherly, to affected positively the decision of participation and level
of participation in milk supply to market (Ali, 2017) ; (Benyam Tadesse, 2016) (Negassa, 2009).
However, the distance of milk collection area(place) & the farmer’s living house vary long then
the relationship between market distance and participation in dairy marketing cooperatives was
negative (Gemechu, 2016).
2.2. Conceptual Framework
Figure: 2 Conceptual framework model of the factors of farmer’s market deciding participation
and farm level milk product supply to the market.
Source: Own Reorganizing Based On Getachew Mekonnen (2015), Ali Tegegne (2017)

17
CHAPTER THREE
METHODOLOGY OF THE STUDY
This chapter contains majorly six sections. The first section presents a description of study area,
the second section describes sample methods and size, Section three, data source and collection
methods of the study, while section four explains the data analysis, fifth section model
specification and hypothesis, the sixth section pilot survey summery as follows.
3.1. Description of Study Area
3.1.1. Location
In this study, dairy marketing chains analysis for fresh row cow milk in Debre Berhan district
in in North Shewa Zone of ANRS Ethiopia. The area has high urban and per urban potential for
livestock production and has relatively better milk marketing activities due to its location
advantage in being nearer to the main road and capital city of Addis Ababa town. As Five
kebeles such as 01,06,07,08, 09 were selected for the study based the potential fresh row cow
milk production and the value chain of fresh row cow milk in market. Moreover, this study
district is found in North Shewa Zone of ANRS. It is astronomically located in an approximate
geographical coordinates bounded between latitudes 9°00’-10°00’ N and longitudes 39°00’-
40°30’ E, covering an area of 18,206 km2 (GEOtest a.s., Brno; AQUATEST a.s., Prague;
Czech Geological survey, 2018). The distance from Debere Berhan to from Addis Ababa (the
national capital) is 130 km road distance on the main highway to Dessie and/or to Mekele. The
town is bounded by such as Basona worana woreda in North Shewa Zone of ANRS which is
an indication of good potential. The density 11,000/km2
(28,000/sq. mi) to increases by 5.65
percent annually (See figure 3).

18
Figure 3: Map of the study area

19
3.1.2. Climate
Debre Berhan is one of the coolest cities found in the subtropical zone of Ethiopia with the
average elevation of 2750 (m.a.s.l). The town has a typical subtropical highland climate
(Köppen Cwb). The average annual temperature of the city during day and night hour is 20.7 °C
and 8.2 °C respectively with precipitation 964mm (Climate-Data.org, 2017).
3.1.3. Demography and Population Dynamics
Debre Berhan Town is a central Ethiopia with an estimation population of 114,652 in 2019/20,
with an average annual growth rate of 5.08 %; from this the gender ratio female 54.78% and
male 45.22% on urban and per urban Debre Berhan respectively. The population between age
0 and 14 constituted 26.11%, under age six 18.32%, the worker age between 15and 64 found
69.23 % age 65 and 80+
was found from literature 4.65%. The dependency ratio for age 0 to
15 was 28.33 percent and that of 65 and older was 4.65 percent (DBTA, 2019/20).
According to the same source data from 114,562 people was indicated that in study area of
urban and per urban Debre Berhan total farmers only 2008 from this female ration on farming
23.65 percent (DBTA, 2019/20). Moreover, the market population on fresh row cow milk such
as wholesalers/processers, retailers/middleman 12 and 23 respectively (NSZTIFLD, 2019/20).
Generally, the population size in study area (see Table 1, and 2).
Table: 1 Population Size with dairy farmer on Debre Birhan
Source: Debre Birhan town administration office, north showa zone livestock and fish
development office annual report 2019.
Age Group Urban Farmers
Both Sexes Male Female Both Sexes Male Female
114,652 51,843 62,809 2008 1533 475

20
Table:2 Milk retailing kiosks, High and medial Processers, Consumers/hotels, restaurants and
cafes dairy producers/farmers.
No- Name of town farmer
participate on dairy production , Actors
wholesalers /Processers retailing /middleman
Debere Berhan 2008 12 23
Source: North Showa Zone Trade and Industry and fish and livestock Department Annual Report ,2019.
3.2. Data Source and Collection Methods
3.2.1. Data Types and Sources
In this study was used both quantitative and qualitative data types in particularly these data types such
as secondary and primary data sources. as secondary sources include reports of ministries, journals,
books, CSA and internet browsing, national policies, zonal and town, Agricultural and Rural
Development Offices, Debere Berhan Cattle Breeding and Multiplication Center reports, & among
others. Primary data sources from urban & pre-urban farmers, actors such as milk retailing kiosks,
wholesalers/processors.
3.2.2. Method of Data Collection
On the research objectives, both primary and secondary data sources are using. Multiple data collection
strategy is more advantageous than single data collection strategy in research work. More specifically,
the selected methods to collect the necessary primary data was applied survey questionnaire, observation
and A secondary data was assessed and collect basic information dairy farming to considering about
globally, nation, region, zonal.
3.3. Sample Methods and Size
The sampling methods was employed Firstly, from 9/nine administration Kebele must be
selected only five sample pre- urban administrative kebeles such as 01,06,07,08 and 09 in the
study area based on milk producer kebeles. Secondly, to selected representative sample farmers
from these five kebeles with simple random sampling procedure. Additionally, most of

21
participant on milk traders such as Wholesalers /Processors, Milk retailing kiosks/middlemen
and consumers/neighbor or Cafes/Hotels was engaged in the study district area.
The sample size was used two stage samples procedure applied. the first stage sample size
based on 2008 population of farmers per households located (Yamane Taro, 1967). Such as;
The sample methods and size
n=
𝑁
1+𝑁(𝑒)2
− − − − − − − −eq(1 )
Where,
 n = sample size =307
 N = population size =2008
 A 95% confidence level
 e = level of precision or error margin. it is expressed in percentage points (±5).
And the second sample size was used milk traders or actors to considering the numbers of
organization such as 12(100%) Wholesalers/Processors and 23(57%) retailing /middleman.
Generally, from the total population size 2043 was applied only 325 sample size. Hence, the
sample size of each participant farmers, Wholesalers/Processors and retailing /middleman were
applied 303,12,10 respectively (see Table 3).
Table: 3 Distribution of sample dairy farmers included in the survey by kebeles
N
o.
Item
Populati
on
Plan of Sample size
(Number and %)
Performance of
sample size (Number
and %)
Number % Number %
1 Total(01,06,07,08 & 09
Kebeles) milk produce farmers
2008 307 15.3% 303 98.7%
2 Name of milk market
intermediary(2.1.,2.2.)
35 25 71.4% 22 88%
2.
1.
Wholesalers/processors 12 12 100% 12 100%
2.
2.
retailing /middleman 23 13 56.5% 10 76.92%
Total (1+2) 2043 332 16.25% 324 97.6%
Source: North Showa Zone Trade and Industry and fish and livestock Department Annual Report ,2019.

22
3.4. Research Design and Rationale
A cross-sectional study design was employed to study the key milk marketing channels, and
margins it, factors that affect farmers in production milk deciding participation and farm level
milk product supply to the market in Debere Berhan District. Firstly, five sample administrative
kebeles in study area were be selected by number of farmers on it. Secondly, to select
representative sample households from these five kebeles, simple random sampling procedure
was employed for household farmers from the list provided by kebeles administration.
However, most of milk traders present in the study area was included in the sample. As the
number of milk traders in the study area is small, their most of population was used as a sample
size.
3.5. Method of Data Analysis
After collection of relevant data from various milk producers and other respective milk trader’s
respondent in the study area was managed by coded and entered in to computers through key
informant interviews and analyzed by software program STATA version 12.0, software.
Ratios, percentages, mean and standard deviations were used in the process of examining and
describing socio-economic characteristics of milk households and traders of the study area.
3.5.1. Description Statistics
3.5.1.1. Analysis of Structure Conduct and Performance
The model examines the fundamental relationships between market structure, conduct and
performance along with them, and was referred to as the S-C P model. Therefore, in this study
was used S-C-P model to evaluate milk market.
3.5.1.2. Market Concentration Ratio
Market concentration ratio is the numerical index or Herfindahl-Hirschman index (HHI) widely
used by industrial organizations for measuring the size of firms in market. if we want to compute
the market ratio such as concentration between 0% to 40% to prefers or categorized on perfect
competition to an oligopoly, Medium concentration between 40% to 70%. An industry in this
range is likely an oligopoly, High concentration between 70% to 100% and lastly 100% means
an extremely concentrated oligopoly. So in this study were found the category ranges from an

23
oligopoly to monopoly (London economics in association with global energy decisions, 26
February 2007). Hence, the market concentration ratio, which refers to the number and relative
size of buyers in the market. Based on, different academics (Meryem, 2013). So in this study
was described the dominancy and competitive of buyer(actors) on milk producer’s farmer’s
product based on the amount of product handled by buyer (each actors) from farmers (milk
producers). such as,
Si =
Vi
∑ Vi
− − − − − − − − − − − − − − − − − eq( 2)
Where:
 𝑆𝑖= Market share of buyer i
 𝑉𝑖 = Amount of product handled by buyer i
 ∑ 𝑉𝑖 = Total amount of product handled
C = ∑ Si
r
i=1
i = 1.2.3.4 … r
Where:
 C = concentration ratio
 Si = the percentage market shares of the ith firm and
 r = is the number of largest firms for which the ratio is going to be calculated.
3.5.1.3. Marketing Margin
All managers of business to consider budgets and for projection use calculate margin and
analyze the business (Farris, Bendle, Pfeifer, & Reibstein, 2010) and (Hailegiorgis, 2015). As
in case of observation every actor on this study area without value add the row milk commonly
gate 5-8 Ethiopian birr from sale between end buyer and first seller prices so to assure the truth
was used the Total Gross Marketing Margin (TGMM). Such as;
TGMM =
End buyer price − First seller price
End buyer price
X 100 − − − − − eq (3)

24
It was useful to introduce the idea of farmer’s Gross Marketing Margin (GMMP) which is the
portion of the price paid by the consumer that goes to the farmer. The farmer’s margin is
calculated as;
GMMP =
End buyer price − Gross Marketing margin
End buyer price
X 100 − − − −eq(4)
Moreover, the net marketing margin (NMM) was the percentage of the final price earned by
the
intermediaries as their net income after their marketing costs was deducted. The percentages
of net income that can be classified as pure profit (i.e. return on capital), depends on the
extension to such factors as the intermediaries’ own (working capital) costs. The equation tells
us the marketing margin of fresh row cow milk selling and marketing cost with end buyer price
such as;
NMM =
Gross margin − Marketing cos
End buyer price
X 100 − − − − − eq(5)
3.5.2. Econometric Models
This section tried to cover model specification part for the analyzing to understanding factors
that affect farmers in production milk deciding participation and farm level milk product supply
to the market in the study areas. It also devoted to describe the data nature and variable working
to estimate the specified models for this study. Hence, Firstly following (Aldrich, 1984) the
probit model estimation for factors that affect farmers in production milk deciding
participation. In case of dummy dependent variable that represent the probability of milk market
participation by milk producers. The variable represented the value of one if milk producer
participates in milk market supply and zero otherwise. The second model was analyzed tobit
models (Tobin’s probit) the econometrics literature by Tobin (Tobin, 1958). It was also
known as a censored normal regression model because on 𝑌∗
(those for which 𝑌∗
> 0 those
for which positive volume of market supplied to market and also some observations on 𝑌∗
≤ 0 ) was censored( we are not allowed to see them). Our objective is to
estimate the parameters 𝛽 𝑎𝑛𝑑 𝜎 ). In this study the factors affecting the supply of milk to the
market is estimated using tobit model. It was specified as 𝑌2 =

25
𝐹(𝑥1, 𝑥2, 𝑥3, 𝑥4, 𝑥5, 𝑥6, 𝑥7, 𝑥8, 𝑥9, 𝑥10, 𝑥11, 𝑥12 𝑥13, 𝑥14 ) because it is continuous dependent
variable measured in liters indicating the actual volume of milk supplied to the market per
household per day. However, it must be hypothesis/ diagnostic tests before analyzing.
3.5.2.2. Econometric Model for Deciding Participation
As the dependent variable Milk market participation decision to participation is a qualitative
with response of “yes” or “no” type. Hence, it is a dummy dependent variable that represent the
probability of milk market participation by milk producers. The variable represented the value
of one if milk producer participates in milk market supply and zero otherwise. regression is
specified as
𝑌𝑖
∗
= 𝛽0 + 𝛽𝑖 𝑥𝑖 + 𝑈𝑖 … … … … … … … . .6
𝑌𝑖 = {
1 𝑖𝑓 𝑌𝑖
∗
> 0
0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
Where,
 𝑌𝑖 Is not observable variable, 𝑌𝑖 =1 when, 𝑌𝑖 >0 (Participated), 𝑌𝑖 =0 Otherwise (Not
participated)
 𝐷𝑖 is explanatory variables listed under, i.e. =x1, x2, x3, x4 … 𝑒𝑡𝑐
 β_i=a vector of parameters to be estimated, i.e.= β1, β2, β3, β4 …etc.
 U = disturbance term
In this study the factors that affect farmers in production milk deciding participation is estimated
using the probit model. Moreover , different academics such as (Sintayehu Yigrem, 2008);
(Anjani Kumar, 2010); (Berhanu, 2012) ; (Berhanu Gebremedhin, 2013) & (Tadele Mamo,
2014) were used Probit and Tobit Model. So, those were adopted to identify the most
important factors that are associated with the deciding participation of by producer households
in the area, and hence it enables to estimate how the included variables are related. The

26
estimated coefficients indicate the effect of a change in the independent variables on the
dependent variable (Aldrich, 1984). Quantity/volume of milk supply
𝑌1= 𝐹(𝑥1, 𝑥2, 𝑥3, 𝑥4, 𝑥5, 𝑥6, 𝑥7, 𝑥8, 𝑥9, 𝑥10, 𝑥11, 𝑥12 𝑥13, 𝑥14 ) (See Table 4).
Prediction of Effects of Changes in The Explanatory Variables: After estimating the
parameters 𝛽𝑖, we would like to know the effects of changes in any of the explanatory variables
on the probabilities of any observation belonging to ether of the two groups. This effects are
given by
𝜕𝑃 𝑖
𝜕𝑥 𝑖𝐽
= 𝛽, ∅( 𝑍𝑖 ) … … … … … … … … … 7
for the probit model
Where; 𝑍𝑖 = 𝛽0 + ∑ 𝛽𝑖 𝐷𝑖𝑗
ላ
𝑖=1
And , ∅(. ) is the density function of the standard normal
3.5.2.1. Market Supply Econometric Model
Let y denotes the dependent (quantity/volume of milk supply) variable that is linearly related
to k independent (or explanatory) variables x1, x2, x, x4 … 𝑒𝑡𝑐 through the parameters
𝛽1, 𝛽2 , 𝛽3 … 𝑒𝑡𝑐 and we write
𝑌𝑖
∗
= 𝛽𝑖 𝑥𝑖 + 𝑈𝑖 … … … … … … … … … 8
𝑌𝑖 = {
𝑌𝑖
∗
= 𝛽𝑖 𝑥𝑖 + 𝑈𝑖 𝑖𝑓 𝑌𝑖
∗
> 0 𝑣𝑜𝑙𝑚𝑒 𝑜𝑓 𝑚𝑎𝑟𝑘𝑒𝑡 𝑠𝑢𝑝𝑝𝑙𝑖𝑒𝑑 𝑡𝑜 𝑚𝑎𝑟𝑘𝑒𝑡
0 𝑖𝑓 𝑌𝑖
∗
≤ 0 𝑛𝑜𝑡 𝑣𝑜𝑙𝑚𝑒 𝑜𝑓 𝑚𝑎𝑟𝑘𝑒𝑡 𝑠𝑢𝑝𝑝𝑙𝑖𝑒𝑑 𝑡𝑜 𝑚𝑎𝑟𝑘𝑒𝑡
𝑈𝑖~𝐼𝑁(0, 𝜎2
)
Where,

27
 Yi = Volume of milk supplied to market
 xi = a vector of explanatory variables, i. e = x1, x2, x3, x4 … 𝑒𝑡𝑐
 𝛽𝑖 = a vector of parameters to be estimated, i. e = 𝛽1, 𝛽2 , 𝛽3 … 𝑒𝑡𝑐
 U = disturbance term
This is known as the tobit models (Tobin’s probit) and was first analyzed in the econometrics
literature by Tobin (Tobin, 1958) it is also known as a censored normal regression model
because some observations on 𝑌∗
≤ 0 ) are censored( we are not allowed
to see them). Our objective is to estimate the parameters 𝛽 𝑎𝑛𝑑 𝜎 ). In this study the factors
affecting the supply of milk to the market was estimated using tobit model and similar topic
(Gemechu, 2016) was used it. Therefore, this was adopted to identify the most important factors
that are associated with the amount of milk supplied to market by farmer in the study area.
Marginal Effects in The Censored(Tobit) Regression Model : After estimating the
parameters 𝛽𝑖, we would like to know the effects of changes in any of the explanatory variables
on the probabilities of any observation belonging to ether of the two groups. This effects are
given by
𝜕𝐸[
𝑦 𝑖
𝑥 𝑖
]
𝜕𝑥 𝑖
= 𝛽 × 𝑝𝑟𝑜𝑏[ 𝑎 < 𝑦∗
< 𝑏] … … … … … … … … .9
Where: a and b are constants
𝜕𝐸[
𝑦 𝑖
𝑥 𝑖
]
𝜕𝑥 𝑖
= 𝛽 ∅(
𝛽′ 𝑥 𝑖
𝜎
)
where,
 𝑦𝑖 is dependent variables, 𝑥𝑖 is vector of independent, 𝛽 is a vector of tobit maximum
likelihood estimate and
𝜕𝐸[
𝑦 𝑖
𝑥 𝑖
]
𝜕𝑥 𝑖
is the cumulative standard normal distribution function,
And ∅(. ) is the density function of the standard normal (Cong, 2000).

28
To detect different appropriate tested basically between dependent and explanatory variables
and also explanatory variables each other’s. Similarly, that, in this study were tested such as;
the testing Goodness of fit(R2
) on probit model and, Wald test of liner hypotheses fit model on
tobit, T-test, Confidence interval testing, Standard Error test(SE), Heteroscedasticity test,
according to Gujarati (2003), Multicollinearity refers to a condition where it becomes difficult
to identify separate effect of explanatory variables on dependent variable due to the existence
of strong correlation among them. VIF used to test Multicollinearity among continuous
variables whereas contingency coefficient (CC) used to test Multicollinearity between dummy
independent variables. As a rule of thumb, if the value of VIF is less than 10 (the null hypothesis
accepted mean that no Multicollinearity ) and if the
value of CC greater than 0.75, then the variables are said to be collinear (Gujarati, 2003) and
VIF for continuous variables computed as follow:
VIFxi = (1 − Rj
2
)−1
… … … … … … … … … … .10
Where,
 Rj
2
is the squared multiple correlation coefficients between independent variables, the
larger the value of Rj
2
, the higher the value of VIFxi causing severe collinearity problem
in xi .
 The value of CC ranges between 0 and 1 and 0 indicates no association between the
variables and the value close to 1 indicates a high degree of association between
variables.
𝐶𝐶 = √
𝑋2
𝑁+𝑋2 … … … … … … … … … … … … … … … … … … … … 11
Where,
 CC is contingency coefficient,
 𝑋2
is chi-square test and
 N is total sample

29
And also; Auto coloration test, and the parameter estimates of the coefficients of the
independent variables may not be BLUE (Best Linear Unbiased Estimator). Hence, to overcome
the problem, Robust standard error probit and tobit models (See Table 10 and 11), (see annex
6,8 and 9).
3.5.3. Variables Description and Hypothesis
Any one inform my research proposal operational definition with related to determinates of the
participation decision and volume of milk supplied to the market and their effects are
hypothesizing as follow:
3.5.3.1. Dependent Variables
The dependent variables which are assume to be influence by explanatory variables are:
 Decision of participation in milk market supply ( 𝑌1): which was a dummy dependent
variable that represent the probability of milk market participation by milk producers.
The variable represented the value of one if milk producer participates in milk market
supply and zero otherwise.
 Volume of milk supplied to the market ( 𝑌2): was continuous dependent variable
measured in liters indicating the actual volume of milk supplied to the market per
household per day.
3.5.3.2. Independent Variables
The explanatory variables which are hypothesize to influence decision of participation and level
of participation in milk market supply are the following:
Sex of the household head (𝑆𝑒𝑥ℎℎ)was a dummy variable and assumed to influence the
households decision to participate in milk market supply. women are expected to contribute
more labor especially for value addition and supply of milk and other dairy products. therefore,
in this study, being male household head was expected to affect negatively on farmers in
production milk deciding participation & farm level milk product supply to the market (Anjani
Kumar, 2010). but, anther scholars showed that being male head of a household affected

30
farmers in production milk deciding participation & farm level milk product supply to the
market positively (Meryem, 2013).
Age of the household (𝐴𝑔𝑒ℎℎ) was a continuous variable measured in year and hypothesize to
have a positive relationship with milk market supply. age can affect experience, wealth and
decision making which in turn affect how one works and hence can influence individual
productivity positively the farmers in production milk deciding participation & farm level milk
product supply to the market (Tadele Mamo, 2014). This may be due to the fact that, aged
households have experience of dairy production, wise in resource use, have more milking cows
and increasing milk production. It is expected to have a positive affected on farmers in
production milk deciding participation & farm level milk product supply to the market.
Educational level of the household(Eduhh): It was a continuous variable measured in number
of years/grade of schooling and hypothesize to have a positive relationship with market supply.
Education can improve the knowledge and skills of milk producers and empowers them to
perform the farming activities accurately, efficiently and accordingly. Formal education
enhances the information sharing and technology implementation abilities of the farmer,
thereby improving the quality of decision making, and also educational level of the HH is from
different academic’s farmers in production milk deciding participation & farm level milk
product supply to the market showed positive association (James, 2013) (Tadele et al. and
Tadele Mamo, 2014).
Family size of the household (Famhh) was a continuous variable measured in number and
assumed to influence participation of household in milk market supply positively. This was
assumption due to the fact that when the number of family size increases, the availability of
work force per household increases and directly relation of farmers in production milk deciding
participation & farm level milk product supply to the market (Ali, 2017).
Number of children under six years old(𝑁𝑢𝑐ℎ𝑖𝑙) was a continuous variable measure in number
and hypothesize to influence negatively participation decision and level of participation for
milk market supply by smallholder milk producers. This was due to the assumption that; mostly
milk was a major food for children and its importance in children growth was widely accepted
and recognized both in rural and urban areas. children have natural priority in consumption of

31
milk in the household, and increase in the number of children in this age category usually
decreases the marketable surplus and reduces the ability of the smallholder in market
participation (Meryem, 2013). whereas the other academic that the positive relationship of the
number of children less than 6 years age (Berhanu, 2012).
Land holding size of the household(𝐿𝑎𝑛𝑑ℎ𝑜𝑙𝑑) was continuous variable measured in hectare
and propos to influence positively the decision of participation and volume of market supply
by milk producers. When the land holdings of a household increases, farmers have a likelihood
of getting better farm output that enables them to fulfill necessary inputs for milk business
activities. Land was very important input for fodder and pasture development to feed dairy
cows. Therefore, it was assumed that as the size of landholding increases, the proportion of land
allocated for fodder and pasture development increased and thereby the farmers in production
milk deciding participation & farm level milk product supply to the market (Ali, 2017). But
the size of land holding increases by a hectare, the level of participation of milk producers’
household in milk value addition decreases (Berhanu, 2012).and also similar this study was
found negative impact.
Experience in milk production(𝐸𝑥𝑝𝑚𝑖𝑝𝑟𝑜)was a continuous variable measured in years and
assumed to influence positively the decision of participation and level of participation of milk
producers in milk market. This assumption is based on the fact that of different scholars when
the experience of a farmer in dairy production increases, the skill to perform milk business in a
better way also increases. This indicated that experience of dairy farm has been found to
influence positively farmers in production milk deciding participation & farm level milk
product supply to the market (Swarup Barua M. J., 2017). This assumption was opposed based
Year of dairy experience negatively related the level of milk production. This indicates that
ceteris paribus, increase in dairy experience of farmer by one year results in decrease the milk
yield per day. The reason behind may be that less productivity of dairy farmers discourages
them to give continuity of this profession. (Karna, 2016).
Access to credit(𝐴𝑐𝑐𝑐𝑟𝑒):Access to credit is measured as a dummy variable taking a value of
one if the household has access to credit and zero otherwise. This variable was expected to
influence the marketable supply of milk and milk market entry decision by dairy household

32
positively on the assumption that access to credit improves the financial capacity of dairy
households to buy more improved dairy cows, thereby increasing farmers in production milk
deciding participation & farm level milk product supply to the market (Benyam Tadesse, 2016).
Extension service per month(𝐸𝑥𝑡𝑠𝑒𝑟): it was continuous variable hypothesize to have a
positive relationship on milk market farmers in production milk deciding participation & farm
level milk product supply to the market. It is expecting that extension visit is directly related
to capacity of household’s skill in dairy production hence, it has positive impact on milk market
farmers in production milk deciding participation & farm level milk product supply to the
market (Ali, 2017).
Access to market information(𝐴𝑐𝑐𝑚𝑎𝑖𝑛𝑓) was a dummy variable taking the value of one if a
household has access to market information and 0 otherwise. Having mobile phone and good
communication with milk traders can provide access to market information. according scholars
found that market information showed positive relationship with decision of participation and
level of participation in milk market supply. Therefore, this variable is hypothesized to
influence positively farmers in production milk deciding participation & farm level milk
product supply to the market (Ali, 2017).
Membership of milk producers’ cooperative (𝑀𝑒𝑚𝑚𝑖𝑝𝑟𝑜𝑐𝑜𝑜): is dummy variable taking the
value of one if a household was member to milk producers cooperative and zero otherwise and
hypothesized to have a positive/negative relationship with milk market supply participation.
Members. Hence, Members of cooperative have better opportunity to bargain and get fair price
for their milk products which encourages them to participate in milk market supply when fresh
row milk cooperative center near to fresh row milk producer living farmer home (Negassa,
2009).. However, between distance of the cooperative milk collection center & the farmer’s
living house vary long then the relationship between market distance and participation in dairy
marketing cooperatives was negative (Gemechu, 2016).
Number Of Cross Breed Milking Cows(𝑁𝑢𝑐𝑟𝑜𝑏𝑟𝑒𝑚𝑖𝑐𝑜𝑤) was measure in number which is
hypothesis to affect positively the decision of participation and level of participation. When
number of cross breed milking cows per household increases, the tendency of household to
participate in milk market rather than value addition increases as cross breed cows produce less

33
content of fat during milk processing than local breed one. The result of different academics
conducted that number of cross breed milking cows affected positively on farmers in production
milk deciding participation & farm level milk product supply to the market (Meryem, 2013)
(Tadele et al. and Tadele Mamo, 2014).
Price per liter offered at the market (𝑃𝑟𝑖𝑐𝑒𝑝𝑒𝑟𝑙𝑖𝑡𝑚𝑖𝑙𝑘): It was a continuous variable Birr (ETB)
and expected to influence market participation and supply decisions positively. As farmer sees
better price the probability of entering a market and volume of milk supply is increasing.
Farmers’ marketing decisions are based on market price information, and poorly integrated
markets may convey mistaken price information, leading to inefficient product movement. a
unit increase in price paid to dairy farmers by a cooperative significantly raised the probability
of selling to market (Burke W, 2015).
Income from the non-dairy sources(𝐼𝑛𝑐𝑜𝑚𝑠𝑜𝑢𝑟𝑐𝑒𝑠) It was continuous variable measured in
Birr (ETB). The variable represents income originating from different sources and obtained by
the sample household. Through improving liquidity, this income makes the household to
expand production and or/ purchase from market. It also strengthens the household position in
coping with different forms of risks. Thus, income from non-dairy source was hypothesized to
affect farmers in production milk deciding participation & farm level milk product supply to
the market positively (Benyam Tadesse, 2016).
Generally, different academics the explanatory variables to relate with dependent variables of
farmers in participation decision of milk production & farm level milk product supply to the
market were used sex age, education level, family size number of children under six age, land
holding size, experience milk production, access of credit, extension serves ,access of market
information, membership of milk producers’ cooperative number of cross breed milking cows
per households and categorized in to three item demographic, economical and institutional (See
Table 4).

34
Table: 4 The explanatory variables of related farmers in production milk deciding participation
& farm level milk product supply to the market of milk producers.
Source: own computation from survey data (2020)
Description
Notatio
n
Variable
type
Unit
Expect
edsign
Dependent variables
 Milk market participation
decision
 Volume of milk supplied to
the market
𝑌1
𝑌2
Dummy
Continuous
(1=participate,0
=otherwise)
Liter
Explanatory variables
Sex of the household 𝑆𝑒𝑥ℎℎ Dummy 0=male,1=female -ve
Age of the household 𝐴𝑔𝑒ℎℎ Continuous Year + ve
Education level of the household Eduhh Categorical Educational status +ve
Family size of the household Famhh Continuous Number +ve
Number of children of the
household≤ 𝟔
𝑁𝑢𝑐ℎ𝑖𝑙 Continuous Years -ve
Land holding size(Hr.) 𝐿𝑎𝑛𝑑ℎ𝑜𝑙𝑑 Continuous Hr. +ve
Experience milk production 𝐸𝑥𝑝𝑚𝑖𝑝𝑟𝑜 Continuous Year -ve
Access of credit 𝐴𝑐𝑐𝑐𝑟𝑒 Dummy 1=Yes 0=no +ve
Extension serves 𝐸𝑥𝑡𝑠𝑒𝑟 Continuous Number day +ve
Access of market information 𝐴𝑐𝑐𝑚𝑎𝑖𝑛𝑓 Dummy 1=Yes, 0=no +ve
Membership of milk producers’
cooperative
𝑀𝑒𝑚𝑚𝑖𝑝𝑟𝑜𝑐𝑜𝑜 Dummy 1=Yes,0=no -ve
Number of cross breed milking cows 𝑁𝑢𝑐𝑟𝑜𝑏𝑟𝑒𝑚𝑖𝑐𝑜𝑤 Categorical Average milking
cow size
+ve
Price per liter offered at the market 𝑃𝑟𝑖𝑐𝑒𝑝𝑒𝑟𝑙𝑖𝑡𝑚𝑖𝑙𝑘 Continuous Birr/coefficient
variation%
+ve
Income from the non-dairy sources 𝐼𝑛𝑐𝑜𝑚𝑠𝑜𝑢𝑟𝑐𝑒𝑠 Continuous Birr +ve

35
3.6. Pilot Survey Summery
The pilot survey questionnaires were done at march, 2020. The topic on market chain analysis
of milk production on urban of Ethiopia: The Case Debere Berhan Town, Amahara region. The
aim of pilot research aimed: To detect possible flaws in measurement procedures (including
instructions, time limits, etcetera) and in the operationalization of independent variables,
identify unclear or ambiguous items in a questionnaire, The non-verbal behavior of participants
in the pilot study may give important information about any embarrassment or discomfort
experienced concerning the content or wording of items in a questionnaire and check and
threatening about where the main research project can fail. Using the specific objectives of the study
such as identify the key milk marketing channels, and margins it in Debere Berhan Town,
analyze factors affecting participation decision and level of participation of smallholder milk
producer households in milk market supply and assess the prospects and major constraints of
milk production and marketing.
So after the adviser was reviewed the survey questions relating to its language; wording and
relevance. At this point in the development more than one question was modified accordingly
due to format; instructions; enumerators; the boundary objectives and additional objective;
parameter; additional question about volume of milk production, consumption and selling of it;
and rearranged the regular milk value chain (Producer- wholesaler/processer-retailer -
consumer) on leading question
Then after adviser review, i was selecting the participants from milk producers and related
actors such as 17 and 10 respectively. Farther more, the interviews ranged in time between
approximately 25 and 30 minutes. The interview should not exceed 90 minutes to consider other
commitments of participants (Jacob, 2012).moreover, I was adjusted additional errors in
measurement procedures (procedures (including instructions, time limits, etcetera), unclear or
ambiguous items in Amharic questionnaire such as spelling and words errors on milk producers
and actors survey question and improve, adjusted and deleted discomforted phrases on survey
question producers of milk on dependent variable frequency of participation and also
independent variable education, children, land, accesses of information factors, Number of
cross breed milking cows, Market Concentration Ratio (CR),Market Channel and Marketing

36
Margin of Fresh Raw milk respectively ( Annex 1). Additionally, based on the selectees on the
pilot survey respondents were check independent Compute interitem correlations
(covariance’s) and Cronbach’s alpha as follows,
Test scale = mean (standardized items)
Reversed items: x3, x4, x11, x13
Average interitem correlation: 0.2144
Number of items in the scale: 14
Scale reliability coefficient: 0.7926
The scale derived from our somewhat arbitrarily chosen market chain analysis of milk
production items (variables) appears to be reasonable because the estimated correlation between
it and the underlying factor it measures is √0.7926 ≈ 0.8903 and the estimated
correlation between this battery of fourteen items and all other fourteen-item batteries from the
same domain is 0.7926. Because the “items” are not on the same scale, it is important that
standardized was specified so that the scale and its reliability were based on the sum of
standardized variables (Cronbach, 1951).

37
CHAPTER FOUR
RESULTS AND DISCUSSION
This part contains results of descriptive and econometric data analysis of the study.
Descriptive analysis were used to describe general background of the household, Influences of
demographic characteristic, Influences of institutional, and Economic factors on milk
Production of respondent households, the key milk marketing channels, and margins production
and actors , the asses of prospects and major constraints of milk production and marketing and
econometrics data was analysis on factors affecting participation decision and level of
participation of smallholder milk producer households in milk market supply with regard to
their performance of in the study area.
4.1. Results of descriptive Analysis of Milk Producer
For the descriptive statistics, sampled smallholder dairy producer householders were analyses
the participations level with considering the measurement of mean frequency, percent of milk
marketing by section. The descriptive statistical analysis was run to assess the Influences of
demographic characteristic, institutional, Economic factors on milk Production.
4.1.1. The Influences of Demographic Characteristic
4.1.1.1. Participant, Age, Gender/Sex, Experience and Land
The sampled population of household participated in milk market during the survey data from
303 populations was participated from five kebeles such as 01,06,07,08 and 09 totally only
the participation on milk market supply was found to be 75.58% ± 2.47 range experience in
year 3 up to 25 years respectively so that the variable experience dairy farmers households
statistically Significant on participated in milk market. However, The survey data gender/sex,
age, and land and experience mean value were found 60.01% ± 2.8 , 1.93 Hec ± 0.41,11.62
± 0.31years and 7.59 years ± 0.24 ranged respectively. The chi-square or t-test showed that
there was statistically significant difference at P>|t| at 1% probability level between age, land
holding, and experience level, participants and non-participants of milk market supply which

38
implies that age, land, and experience level affected significantly the participation of
households (See Figure 4).
Figure-4: Socio-demographic characteristics of framing households milk production (in
average, years and %)
The sex ,age ,land, experience ,χ2/t-test 2.3, −35.18∗∗∗
, −2.89∗∗∗
−28.82∗∗∗
*** indicate
statistical significance (P>|t|) at 1% and otherwise not.
4.1.1.2. Education
When formal Education could improve the knowledge and skills of milk producers and
empowers them to perform the farming activities, efficiently and accurately. Due to that, the
educational background of the sample per household one of factor affecting of the readiness of
household heads to accept new ideas and innovations. So that, the sample households were in
five kebeles illiterate, joined first level primary, first level full cycle primary, secondary school
9-12, certificate-diploma and degree and above in urban/per urban of Debre Berhan town milk
Mean Std.Err Mean Std.Err Mean Std.Err
total Participate Non-Participate
Participate per HH 75.58 2.47
sex participant per HH 60.01 2.8 58.01 3.25 67.57 5.78
Age of participant per Hh 11.62 0.31 11.37 35.8 12.34 0.58
Land/Hec of participant per HH 1.93 0.41 1.53 0.05 3.13 1.67
Experience of participant per HH 7.59 0.24 7.11 0.24 9 0.58
0
10
20
30
40
50
60
70
80
%,Year&Hec.
Mean Value
On Fresh Row Milk production participate,Female,Age,Land,& Experience
on Per HH Debere Berhan Town
Obs. 303
Participate per HH sex participant per HH
Age of participant per Hh Land/Hec of participant per HH
Experience of participant per HH

39
market participate frequency and percent were found such that 115(37.95%) ,58(19.14)
,64(21.12%) ,32(10.56%), and 29(9.57%), and 5(1.65%) respectively. However, most of the
milk product 62% and above was educated from grade one up to high level of education Degree
and above. The t-test showed that there was statistically significant difference P>|t| at 1%
probability level between education level per grade, participants and non-participants of milk
market supply which implies that education level affected significantly the participation of
households (See figure 5).
Figure 5: education level for milk market participant farmer of urban/per urban Debre Berhan
The education level based on t-test 4.14***, *** indicate statistical significance (P>|t|) at 1%
Freq. % Freq. % Freq. %
total Participate Non-Participate
Illiterates 115 37.95 65 28.14 51 68.92
1-4 grade 58 19.14 44 19.05 14 18.92
5-8 grade 64 21.12 63 27.27 1 1.35
9-12 grade 32 10.56 28 12.12 5 6.76
Certificate –diploma grade 29 9.57 26 11.26 3 4.05
Degree and above grade 5 1.65 5 2.16
0
20
40
60
80
100
120
140
Freq.,%
Total,particpate,Non- participate
Education level for Milk market participant per- hh of urban/per urban in
Debre Berhan Obs.303

Market chain analysis of milk production 5 final

Market chain analysis of milk production 5 final

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