performance of primary agricultural
TRANSCRIPT
PERFORMANCE OF PRIMARY AGRICULTURAL
COOPERATIVES AND DETERMNANTS OF MEMBERS’
DECISION TO USE AS MARKETING AGENT IN ADAA
LIBEN AND LUME DISTRICTS
M.Sc. Thesis
DANIEL BELAY
April 2006
Alemaya University
PERFORMANCE OF PRIMARY AGRICULTURAL
COOPERATIVES AND DETERMNANTS OF MEMBERS’
DECISION TO USE AS MARKETING AGENT IN ADAA
LIBEN AND LUME DISTRICTS
A Thesis Submitted to the Department of Agricultural Economics
School of Graduate Studies
ALEMAYA UNIVERSITY
In Partial Fulfillment of the Requirements for the Degree of
MASTER OF SCIENCE IN AGRICULTURAL ECONOMICS
BY
Daniel Belay
April 2006
Alemaya University
ii
SCHOOL OF GRADUATE STUDIES
ALEMAYA UNIVERSITY
As Thesis research advisor, I hereby certify that I have read and evaluated this Thesis
prepared, under my guidance, by Daniel Belay, entitled Performance of Primary
Agricultural Cooperatives and Determinants of Members’ Decision to Use as Marketing
Agent in Adaa Liben and Lume Districts. I recommend that it be submitted as fulfilling the
Thesis requirement.
_________________ ________________ _______________
Major Advisor Signature Date
_________________ ________________ _______________
Co-advisor Signature Date
As member of the Board of Examiners of the MSc Thesis Open Defence Examination, we
certify that we have read, evaluated the thesis prepared by Daniel Belay and examined the
candidate. We recommended that the thesis be accepted as fulfilling the Thesis requirement
for the degree of Master of Science in Agricultural Economics.
_______________________ __________________ ________________
Chairperson Signature Date
_______________________ __________________ ________________
Internal Examiner Signature Date
_______________________ __________________ ________________
External Examiner Signature Date
iii
DEDICATION
This thesis manuscript is dedicated to my mother, Shege Tulu and my father the late Belay
Tesfaye (may Lord put his soul in peace), who had committed with strong prayer for the
betterment and in general success of my life.
iv
STATEMENT OF THE AUTHOR
First of all, I declare that this thesis is my work and that all sources of materials used for this
thesis have been duly acknowledged. This thesis has submitted in partial fulfillment of the
requirements for M.Sc. degree in Agricultural Economics at the Alemaya University and is
deposited at the University Library to be made available to borrowers under rules of the
Library.
Brief quotations from this thesis are allowable without the special permission provided that
accurate acknowledgment of source is made. Requests for permission for extended quotation
from or reproduction of this manuscript in whole or in part may be granted by the head of the
major department or the Dean of the School of Graduate Studies when in his or her judgment
the proposed use of the material is in the interests of scholarship. In all other instances,
however, permission must be obtained from the author.
Name: Daniel Belay Signature: ________
Place: Alemaya University, Alemaya
Date of Submission: ________________
v
ACRONYMS AND ABBREVIATIONS
AAU Addis Ababa University
ACDI Agricultural Cooperative Development International
AE Adult Equivalent
ALWADO Adaa Liben Wereda Agricultural Development Office
ALWCPO Adaa Liben Wereda Cooperative Promotion Office
AU Alemaya University
AUA Alemaya University of Agriculture
CR Current Ratio
CSA Central Statistical Authority
DA(s) Development Agent(s)
DAP Di- Ammonium phosphate
DR Debt Ratio
ESZFEDD East Shoa Zone Finance & Economic Development
Department
FCC Federal Cooperative Commission
Ha Hectare
ICA International Cooperative Alliance
LIMDEP Limited Dependent Variables
LWADO Lume Wereda Agricultural Development Office
LWCPO Lume Wereda Cooperative Promotion Office
masl Meter above Sea level
ME Man Equivalent
MoRD Ministry of Rural Development
NGO Non Governmental Organization
OLS Ordinary Least Squares
OPEDB Oromiya Planning and Economic Development Bureau
OCPC Oromiya Cooperative Promotion Commission
PA(s) Peasant Association(s)
Qt Quintal
vi
ACRONYMS AND ABBREVIATIONS (Continued)
ROTA Return on Total Asset
TLU Total Livestock Unit
VIF Variance Inflation Factor
VOCA Volunteers in Overseas Cooperative Assistance
vii
BIOGRAPHY
The author was born in Addis Ababa in October 1976 of his father Belay Tesfaye and his
mother Shege Tulu. He completed his primary and junior secondary school education in Atse
Tewodros Public School and his secondary education at Nefas Silk Comprehensive Secondary
School of Addis Ababa. After successfully passing the Ethiopian School Leaving Certificate
Examination (ESLCE), he joined the Alemaya University of Agriculture and graduated on
July 11, 1998 with B.Sc degree in the field of Agricultural Economics.
After his graduation, he was employed in Kembata Alaba Tembaro zone Planning and
Economic Development Department as junior economist in Economic Development Section
where he served for two years. Then after, he was employed in Ardaita Agricultural Technical
Vocational Educational Training College of the Ministry of Agriculture as junior instructor
until he joined School of Graduate Studies, Alemaya University, in October 2003.
viii
ACKNOWLEDGMENT
No one is like you, the Almighty God. Thank you for giving me the chance to enjoy the fruits
of my endeavour. No one is righteous, God alone. Thank you, for giving me courage and
endurance to withstand all the problems and troubles.
Words fail to convey my deepest thanks to my advisor Dr. Gezahegn Ayele for his
willingness to advice and guiding me with understanding throughout the course of the
research. It is my sublime privilege to express my deepest sense of gratitude and indebtedness
for his scientific guidance and ceaseless support throughout the course of the research work in
addition to restructuring and editing the thesis, that is obviously tiresome.
.
My deepest overwhelming acknowledgment goes for my mother Shege Tulu, Lord, make me
not to forget her commitment and scarify to bring me to this stage. I would also like to convey
my thanks to my sisters Yeshi, Zena and Mekdes, my brothers Samuel and Yoseph and my
uncle the late Tulu Debele (the one I lost while I was undertaking this research) for being
compliant and standing by me when the going got rough. Seyoum Nigatu and Solomon Tulu
also deserve special thanks for their unforgettable encouragement.
My warm thanks are extended to Dr. Assefa Admassie and Dr. Edilegnaw Wale for their keen
and genuine moral and material support. I am very indented to my colleagues Aschalew
Feleke and Melaku Gorfu for their generous deeds and unfailing encouragement. Alemayehu
Abebe, Ketema Feye, Yonas kidane, Sileshi Girma, Daniel Shiferaw, Sisay Temesgen,
Zemene Koyelign and all other friends also deserve thanks for their encouragement.
Finally, I indebted to all individuals and institutions for their support and encouragement in
the entire work of the research.
ix
TABLE OF CONTENTS
STATEMENT OF THE AUTHOR iv
ACRONYMS AND ABBREVIATIONS v
BIOGRAPHY vii
ACKNOWLEDGMENT viii
LIST OF TABLES xii
LIST OF FIGURES AND MAPS xii
LIST OF TABLES IN THE APPENDIX xv
ABSTRACT xvi
1. INTRODUCTION 1
1.1. Background 1
1.2. Statement of the Problem 8
1.3. Objectives of the Study 9
1.4. Significance of the Study 9
1.5. Scope and Delimitation of the Study 10
1.6. Organization of the Thesis 11
2. LITERATURE REVIEW 12
2.1. The Definition of Cooperative 12
2.2 Review of Basic Issues Concerning Cooperatives 12
2.2.1. Principles of cooperative 12
2.2.2. Classification/ types of cooperatives 14
2.3. Major Benefits of the Cooperation 16
2.4. Farmers’ Attitude on the Performance of the Cooperative 16
2.5. Historical Development of Agricultural Cooperatives in Ethiopia 17
x
TABLE OF CONTENTS (Continued)
2.5.1. Feudal regime (1960- 1975) 17
2.5.2. Derg regime (1975-1991) 18
2.5.3. Post 1991 period 20
2.6. Elements for the Development of Cooperatives in Ethiopia 21
2.7. Studies on Cooperatives in Ethiopia 22
2.8. Empirical Studies on the Performance of Agricultural Cooperatives 24
3. RESEARCH METHODOLOGY 28
3.1. Description of the Study Area 28
3.1.1. An overview of the Oromiya regional state 28
3.1.2. An overview of the east Shoa zone 28
3.1.3. Adaa Liben and Lume Districts 30
3.1.3.1. Location and physical features 30
3.1.3.2. Socioeconomic environment 31
3.1.4. Agricultural extension service 35
3.1.5. Agricultural cooperatives 35
3.1.6. Cooperative organization and promotion service 36
3.1.7. Agricultural credit services 36
3.1.8. Marketing services 37
3.2. Sampling Procedure 38
3.2.1. Selection of study area 38
3.2.2. Sampling design 38
3.3. Methods of Data Collection 39
3.4. Methods of Data Analysis 40
3.4.1. Ratio analysis 40
3.4.1.1. Liquidity ratio 40
3.4.1.2. Financial leverage management ratio 41
3.4.1.3. Profitability ratio 41
3.4.2. Discrete regression models 42
3.4.3. The Tobit model 43
3.4.4. Specification of the Tobit model 44
3.5. Hypothesis and Definition of Variables 46
3.5.1. Dependent variable 46
3.5.2. The Independent variables 47
4. RESULTS AND DISCUSSION 52
4.1. Ratio Analysis 52
4.1.1. Liquidity analysis 52
4.1.2. Financial leverage management analysis 53
xi
TABLE OF CONTENTS (Continued)
4.1.3. Profitability analysis 54
4.2. Descriptive Analysis 55
4.2.1. Household characteristics 55
4.2.2. Land holding 60
4.2.3. Major crops produced and yield 61
4.2.4. Livestock holding 64
4.2.5. The cooperatives 66
4.3. Results from the Tobit Econometric Model 73
4.3.1. Factors influencing the marketing of teff through the cooperatives 74
4.3.2. Effects of changes in the significant explanatory variables on the intensity of 79
marketing of teff through the cooperative 79
5. SUMMARY AND CONCLUSION 83
5.1. Summary 83
5.2. Conclusion and Recommendations 84
6. REFERENCES 88
7. APPENDICES 94
7.1. Appendix I. Tables 95
7.2. Appendix II. Survey Questionnaire 99
xii
LIST OF TABLES
Table Page
1. Primary cooperatives of the country by region, number of members and capital ................. 6
2. Primary cooperatives of the Oromiya region by type of cooperative, number of members
and capital .......................................................................................................................... 7
3. Crop production of different types in the Adaa Liben district ............................................. 33
4. Crop Production of Different Types in the Lume District ................................................... 34
5. Financial ratios of the multi-purpose agricultural cooperatives........................................... 53
6. Characteristics of the sample households ............................................................................ 56
7. Distribution of the sample farmers by sex of the household head ...................................... 57
8. Educational status of the household head ............................................................................ 58
9. Characteristic of the sample farmers by years of membership ............................................ 58
10. Characteristic of the sample farmers by years of farming experience ............................... 59
11. Characteristic of the sample farmers by income from off/non-farm activities .................. 59
12. Distribution of the sample farmers by the available land holdings.................................... 60
13. Distribution of the sample farmers by land rent type......................................................... 61
14. Distribution of the sample farmers by the area of major crops.......................................... 62
15. Distribution of the sample farmers by yield of major crops .............................................. 63
16. Livestock ownership of the sample farmers....................................................................... 65
17. Distribution of the sample farmers by oxen ownership ..................................................... 66
18. Quantity of DAP taken by the sample farmers from the cooperatives .............................. 67
19. Quantity of Urea taken by the sample farmers from the cooperatives............................... 68
20. Distribution of the sample farmers by fertilizer credit extended from the cooperatives ... 68
21. Distribution of the sample farmers by other services from the cooperatives..................... 69
22. Distribution of the sample farmers by education from the cooperatives ........................... 70
23. Distribution of the sample farmers by perception on the current performance of the
cooperatives...................................................................................................................... 71
24. Distribution of sample farmers by perception on future performance of the cooperatives 72
25. Maximum likelihood estimates of Tobit model ................................................................. 78
xiii
26. Effects of change in the significant explanatory variables on the intensity of
marketing of teff through the cooperatives ...................................................................... 82
xiv
LIST OF FIGURES AND MAPS
Figures Page
1. “Map” of Oromiya Regional State....................................................................................... 29
2. “Map” of East Shoa Zone Containing Adaa Liben and Lume Districts .............................. 31
3. Yield of teff in quintal by sample farmers ........................................................................... 64
xv
LIST OF TABLES IN THE APPENDIX
Appendix Tables Page
1. VIF of the continous explanatory variables (Xi) hypothesized for the study....................... 95
2. Contingency coefficients of the hypothesized discreet explanatory variables.................... 95
3. Conversion factors employed to compute adult equivalent (AE) ........................................ 96
4. Description of explanatory variables ................................................................................... 96
5. Conversion factors used to estimate man-equivalent (ME) ................................................. 98
6. Conversion factors used to estimate tropical livestock unit (TLU) ..................................... 98
xvi
PERFORMANCE OF PRIMARY AGRICULTURAL
COOPERATIVES AND DETERMNANTS OF MEMBERS’
DECISION TO USE AS MARKETING AGENT IN ADAA
LIBEN AND LUME DISTRICTS
ABSTRACT
When the issue of economic growth and development of the country is raised, one has to take
into account the performance of the smallholder farmers. Reducing the challenges they are
facing and utilizing their potentials can help to accelerate the agricultural sector and
economic development of the country as a whole. Agricultural cooperatives are an ideal
means for self-reliance, higher productivity level and promotion of agricultural development.
Therefore, the major concern of this study is empirically analyzing the performance of
agricultural cooperatives found in the Adda Liben and Lume districts.
Both primary and secondary data were taken for this study. A two-stage random sampling
procedure was adopted to select 11 agricultural cooperatives and a total of 132 sample
respondents from Adaa Liben and Lume districts. Primary data pertaining to the years
2003/4 and 2004/5 was collected from selected respondents through structured questionnaire.
Of the total respondents, about 58% and 42% were users and non-users of the cooperative as
marketing agent for their farm produce (teff) respectively. Secondary data of the cooperatives
for the years 2001/2 and 2002/3 was also taken to examine the financial performance.
Ratios were analyzed taking the two years financial data (2001/2 and 2002/3). The liquidity
analysis showed that the cooperatives under investigation were below the satisfactory rate
(current ratio of less than 2.00). The financial leverage ratio (debt ratio) showed that the
cooperatives under investigation used financial leverage (financed more of their total asset
with creditors’ fund).The profitability ratio of the cooperatives showed that the profitability of
xvii
the cooperatives was weak. The cooperatives earn return on their asset below the interest
rate the financial institution extend credit (7%).
Descriptive statistics were used to compare the socio-economic, the attitudes towards their
cooperatives, services rendered by the cooperatives and other institutional characteristics of
the users and non-users of the cooperative as marketing agent for their teff. Testing
differences between two samples were done using T-test and Chi-square test. The comparison
revealed that there is a significant difference between the two groups of sample farmers
regarding their age, farming experience, land holding, yield obtained from wheat, provision
of different services and perception on future performance of the cooperatives.
Tobit econometric model was employed to identify the factors influencing the marketing of teff
through the cooperative in the two districts. A total of 17 explanatory variables were
included in the model in which 10 variables were found to be significant. Of these, seven
explanatory variables namely district (DISTRICT), position in the cooperative (POSITION),
farm size (FARMSIZE), yield of teff (YIELD), patronage refund (PATREF), cooperative price
for teff (COOPP), distance of the district market from the farmer’s house (DDMKT) were
found to influence the marketing of teff and its intensity through the cooperatives positively.
Implications of this study are improving the financial as well as management performance of
the cooperatives to face the market competition in the area especially in purchasing farmers’
produces, increasing the participation of the farmers in the cooperative through provision of
different services and benefits, appropriation of surplus in the form of patronage refund,
increasing the productivity and specialization of the farmers, continuation of distribution of
fertilizer in credit to the farmers and above all continuous education and enlightenment of the
farmers about cooperative and its benefits are the utmost priority areas of interventions to
improve the performance of the cooperatives in the area.
1. INTRODUCTION
1.1. Background
Cooperatives have existed in some form for thousands of years. Hunting wild animals for
food called for collective effort primitive man lived. The history of cooperation dominated by
rural examples, probably because of the nature of rural life. The history of modern
cooperation traced to the impact of industrial revolution that brought immense wealth to the
capitalists and poverty to unorganized labor. The first man to conceive of an economic
association for the benefit of the members was P.C.Plockboy, a Dutchman, living in England
(Kebebew, 1978). He encouraged agriculturalists, artisans and other professionals to form
their own associations to which they were to contribute capital and work. Dr. William King
was also another pioneer in the field of cooperatives, stressed on self-help as opposed to
patronage from the rich.
The first modern cooperative, the Rochdale society, was established in England in 1844
(Chukwu, 1990). It started with twenty eight members who purchased one share of stock. The
members consisted of craftsmen such as weavers or shoemakers. The members decided to
join forces to work together, sell their products under one roof, and use a part of earnings to
purchase supplies in quantity at economical price, another portion of the earnings would be
reinvested in growth of the society, and the remainder would be returned to the individual
member in the form of refunds.
Cooperative movement in Germany evolved in response to the economic crisis. Both farmers
and town dwellers were on the verge of starvations in 1846 (Kebebew, 1978). In agricultural
area of western Germany the disastrous year of 1846, inspired Fredrick Wilhelm Raiffeisan,
to take some action to alleviate the problem of hunger. He believed that farmers could
improve their condition by eliminating moneylenders and middlemen. The government
formed a local committee in Raiffeisan‘s district that is responsible for the initiation of an
agricultural credit society.
2
In Ethiopia, the formation of cultural and traditional associations (e.g.`Edir`, `Ekub`, `Debbo`,
etc) was dated many years ago. The peasants long realized the value of cooperation for
improved productivity and for the task that require collective effort. For example, ‘Debbo’ is
one of the traditional self-help organizations prevailing in agricultural communities of
Ethiopia. The people living in a given particular geographical boundary help one another in
ploughing, weeding, harvesting, house construction etc.
It was after 1960 that those modern cooperatives societies came to birth (MoRD, 2002). These
cooperatives were established during the Feudal regime (1960 to 1975), Derg regime (1975 to
1990) and now after 1990. It was unfortunate that those cooperatives that were established
during the previous two governments were not successful because they were used as political
tools and member’s willingness was not given priority it deserves. It is even very difficult to
get rid of those bad images of cooperatives printed in the minds of farmers for the
establishment of similar voluntary associations such as cooperative societies in order to
enhance bargaining power, raise sales and purchase, transaction volumes and so on.
The study conducted by Tesfaye (1995) on producers’ cooperatives confirmed the above idea.
Cooperatives failed in the past because of some predictable and controllable factors. The Derg
regime formed these organizations in a hurry with out any sufficient preparation and
feasibility study. The regime violated the very basic principle of cooperation (open and
voluntary membership). Farmers were forced both directly and indirectly to join cooperatives
with out their interest. In addition, the regime had intervened in their affairs and used them for
its own political ends.
Agricultural cooperatives have been used for implementing agricultural development policies
directed specifically towards smallholders of the country as smallholders’ agriculture is an
important component of the rural sector and its contribution has a significant place in the
national economy of the country. These cooperatives are introduced as the major rural
institutions to increase efficiency of the marketing system and to promote agricultural
development in the rural sector of the country’s economy. They are also organized to render
3
economic benefits such as economies of scale, market power, risk pooling, coordination of
demand and supply and guaranteed access to input and output markets to these smallholders.
And all these allow farmers to extend their economic power beyond the farm gate.
Agricultural cooperatives enable farmers to own and democratically control their business.
Farmers are organized to help themselves rather than rely on the government. And this allows
them to determine services and operations that will maximize their profits. They increase the
income of the farmers by raising the general price level through increasing bargaining power
for the products sold and by lowering the costs of supplies of purchased input. They also
increase the farm income of the farmers by reducing per unit handling costs (economies of
size), by distributing the net savings made in handling, processing and selling operations, by
up grading the quality of supplies or farm products and by developing new markets for
products.
Agricultural cooperatives provide a kind of farm supplies that will maximize returns and
market farm products of the farmers based on grades and standards for quality. They are
dependable source of reasonably priced supplies especially important during periods of
shortage. Agricultural cooperatives introduce desirable competition that raises market prices
for the farmers’ products. They also expand and capture a greater share of the existing market
by pooling specified grade or quality and this helps to meet the needs of large scale buyers.
Government support to agricultural cooperatives is essential for their diversification,
expansion and sustainability and above all to protect the interest of the people with limited
means. Liberalization doesn’t prohibit this support. In fact, the World Bank and UN
specialized agencies emphasize government support for the cooperatives development with
out impairing in any way their cooperative character i.e. governments have to be committed
for the support by accepting the Sydney declaration of conference of ministers of cooperation
of Asia and Pacific countries organized by ICA (Dwivendi, 1996).
The current government of Ethiopia has been taking bold decisions to create favorable
conditions for the development of cooperatives such as monetary support, creating healthy
4
and conducive environment for the cooperatives to grow and work smoothly and giving
freedom and autonomy by replacing the existing cooperative laws on the pattern
recommended by ICA. The government legislated the cooperative society act by the
proclamation No. 147/1998 (Federal Negarit Gazeta, 1998). The proclamation states the
necessity of establishing cooperative societies which are formed by individuals on voluntary
basis and who have similar needs for creating savings and mutual assistance among
themselves by pooling resources, knowledge and property. It also states the necessity of
enabling the cooperative societies to actively participate in the free market economic system.
In general, it becomes imperative to issue a comprehensive legislation by which cooperative
societies are organized and managed in order to achieve their objectives.
Government assistance was provided through the Federal Cooperative Commission that was
established by the proclamation No. 274/2002 (Federal Negarit Gazeta, 2002). The
Commission has a vision of seeing the Ethiopian cooperative societies enhancing the
livelihood of the communities. It is responsible for formulating policies and preparing draft
laws suitable for the activities and development of the cooperative societies, encourages the
organization of cooperative society. It is also responsible for registering, supporting and
supervising cooperative societies at federal level, conducting research and rendering training
and other technical support. There are also other duties and responsibilities the commission
established for. In addition to this, trainings and technical assistance of other governmental
and NGOs was provided through regional cooperative bureaus, zonal and wereda offices of
cooperative organizations and promotion. Because of the importance given to the
cooperatives in the rural development process, activities of the agricultural cooperatives are
organized in the development plans of the country.
The proclamation No. 147/1998 stated that the capital that enables the primary cooperatives1
to expand its work activities is obtained from paid up shares of each member in accordance of
the decision of the general assembly. The cooperatives may sell additional shares if it is found
1 Primary cooperatives are the smallest individual units in the set up of hierarchy of cooperatives and usually
cover a more limited area of operation. They have in most cases individual persons as members.
5
necessary to promote the financial capacity of the cooperatives subject to the decision of the
general assembly. However, no member in the cooperative should hold more than 10% of the
total paid up share capital. Every member, regardless of the number of shares he/she holds,
has only one vote at the meeting of the cooperative and he/she needs to be present at the
meeting of the cooperative to cast a vote.
In Ethiopia the development of primary cooperatives has shown a good progress. There are
14,423 primary cooperatives across the country operating in different sector of the national
economy in 2004/5 (Table 1). They have 4,983,752 members and capital of birr 474,009,157
(FCC, 2005a). Their number has shown almost double increase in the last two years. There
were 7,740 primary cooperatives in 2002/3 and out of these 4,183 were agricultural
cooperatives (FCC, 2004a). Most of the cooperative operate in the agriculture sector of the
national economy. They involved in grain marketing, input supply, credit service, irrigation,
dairy, livestock and coffee marketing etc. There are also a few numbers of primary
cooperatives that involved small-scale industry.
The Oromiya regional state has 1,568 primary cooperatives which operate in various sectors
in the region (Table 2). They have 1,333, 349 members and a capital of birr 119,873,911.40
(OCPC, 2004). Most of the cooperatives involved in the agriculture sector. Multi-purpose
agricultural cooperatives are the largest in number among the agricultural cooperatives and
they engaged in more than one field of activity. They market farmer’s product, supply input
and extend credit to the farmers.
6
Table 1. Primary cooperatives of the country by region, number of members and capital
Members Region Number
Male Female Total
Capital
(In birr)
Amhara 2114 1290476 154656 1445132 85211401
Oromiya 2720 145302 1453018 1598320 135766940
Debub 1480 108332 935719 1044051 140637880
Benishangul 63 589 6804 7393 1931940
Harari 71 779 2380 3159 838989
Gambela 38 2067 2527 4594 300000
Afar 113 154 922 1076 693520
Tigray 1215 85633 341167 426800 54903066
Addis Ababa 6035 122163 307876 430039 41734692
Dire Dawa 327 2748 9648 12396 6179304
Somale 247 2267 8525 10792 5811425
Total 14423 1760510 3223242 4983752 474009157
Source: Federal Cooperative Commission, Annual Report 2004/2005
(Unpublished Amharic Version)
Adda Liben and Lume districts found in east Shoa zone of the Oromiya regional state. In
Adda Liben districts, there are 26 multi-purpose agricultural cooperatives which have 21,914
members and a capital of birr 2,489, 306 (ALWCPO, 2005). In Lume district, there are also
12 multi-purpose agricultural cooperatives with 11,483 members and 2,134,912.27 birr as
capital (LWCPO, 2005).
7
Table 2. Primary cooperatives of the Oromiya region by type of cooperative, number of
members and capital
Members Cooperative Type Number
Male Female Total
Capital
(In birr)
Multi-purpose 898 1165689 116739 1282428 105232674.71
Irrigation 90 5778 156 5934 4558313.38
Saving and credit 416 19267 9037 28304 5446149
Fishery 16 6628 5 6633 414389.56
Butchery 5 117 - 117 255646.21
Dairy 29 1174 224 1398 908259
Sugarcane 7 743 254 997 222962.69
Mining 53 3450 86 3536 516233.77
Consumers 9 650 224 874 283536.32
Handicrafts 20 485 98 583 220121.25
Bee keeping 5 92 1 93 69733
Electricity 4 1583 267 1850 366442
Animal Husbandry 10 269 136 405 323303 .14
Local Seed
production
4 155 42 197 1056277 .4
Total 1568 1206080 1272269 1333349 119873911 .4
Source. Oromiya Cooperative Promotion Commission, Second
Quarter Report 2004/2005. (Unpublished Amharic Version)
This research focuses on the analysis of performance of the multi-purpose agricultural
cooperatives found in the two districts focusing on their financial condition and identifying
those factors influencing farmers’ marketing of farm produces through the cooperatives.
8
1.2. Statement of the Problem
Research results and statistical data have revealed that Ethiopia is among the poorest countries
in the world. Despite that agriculture is the main sector of the national economy and the
development of the country is correlated with progress in it, the methods and techniques of
production and distribution are traditional and, therefore, the level of its productivity is
exceedingly low.
Economic development of the country is the outcome of several factors of which improving
the performance of economic organization is of importance. Agricultural cooperatives are the
means to an economic development. They are indispensable for self-reliance, higher
productivity level, promotion of industrial development raising the communities economic
and social consciousness, and for launching an attack on a common enemy i.e. poverty.
Some authors have presented investigations on the performance of agricultural cooperatives.
Getenesh (1988) studied farmers producers’ cooperative and found size in terms of members
and area doesn’t contribute significantly to explain the performance differences in most cases,
in contrast to wide spread assumption of this to be so. Asmare (1989) showed that factors of
production employed in the farmer producers’ cooperatives were inefficiently used.
Inefficiency includes underutilization of labor, fertilizer and capital expenses and partly over
utilization of land.
The performance of agricultural cooperatives have drawn much attention and resulted in
different findings. Hind (1994) studied the performance of cooperatives and non-cooperatives
in the agricultural business and indicated that on the basis of profitability and liquidity, there
was no significant difference between the two groups. Fulton and king (1993) found that the
performance of grain marketing cooperatives is influenced by a complex interaction of size,
number of locations, grain handling facilities and information expenditure. Mauget and
Declerck (1996) showed that specialized cooperatives of the European union didn’t perform
better than multi-purpose agricultural cooperatives.
9
Agricultural cooperatives are promoted by Ethiopian government as a means to increase
efficiency of marketing of farm produces and supply of farm inputs and hence agricultural
development in the rural sector of the country’s economy. Knowledge about their
performance thus is of major importance for better understanding of this policy. This is why
the present study takes up on performance analysis focusing on their financial condition and
identifying those factors influencing marketing of farm produces through the multi-purpose
agricultural cooperatives.
1.3. Objectives of the Study
The specific objective of this research is to investigate the performance of the multi-purpose
agricultural cooperatives with emphasis on their financial condition and identifying those
factors that influence farmers’ marketing through the cooperatives in the study area. In detail
the objectives of the study are the following
1. To examine financial performance of agricultural cooperatives
2. To identify factors that influence farmers’ marketing of farm produces through the
cooperatives
3. To study farmers’ attitudes towards agricultural cooperatives
1.4. Significance of the Study
When the issue of economic growth and development of the country is raised, one has to take
into account the performance of the smallholders. Reducing the challenges they are facing and
utilizing their potentials can help to accelerate the agriculture sector and economic
development of the country as a whole. Multi-purpose agricultural cooperatives are an ideal
means for the improvement of the livelihood of smallholder farmers. More than four million
farm households are the members of these cooperatives (FCC, 2005a). The production and
income of the farmers are dependent on the performance of the cooperatives in which they are
member.
10
Financial analysis provides ways of improving cooperative’s performance by pinpointing the
weakness and strength of key areas by use of ratios i.e. identifying the financial strength and
weakness of a cooperative by properly established financial statements. This analysis allows
managers and other concerned bodies to reach conclusion about the recent status of the
cooperatives.
Agricultural cooperatives have been organized to render economic benefits to their farmers.
One of the aims of establishing agricultural cooperatives in the rural area is to increase
efficiency of the marketing system and to promote agricultural development in the rural sector
of the country’s economy. Hence, identifying those factors that influence the marketing of
farm produces through the multi-purpose agricultural cooperatives and the attitudes of the
farmers towards these cooperatives will also provide beneficial information to the managers
and other stakeholders to know the effectiveness of the cooperatives operation in the
marketing of farmers’ produces.
1.5. Scope and Delimitation of the Study
Among the several areas in the country where cooperative movement is high, the study area is
the front-liner in the set up and organization of agricultural cooperatives. The reason for the
study to be confined in these two weredas is that the prevailing resource limitation does not
allow encompassing other areas in the study.
The first objective of this study focuses on the financial statements of the cooperatives.
However, some cooperatives in the two districts were not audited in yearly bases due to
shortage of auditors in the zone and wereda offices. Cooperatives that were properly audited
for the year 2001/2 and 2002/3 were selected to meet the first objective of the study.
By comprising the required budget and time a total of 132 farmers, who are a members of
eleven multi-purpose agricultural cooperatives, were interviewed to meet the second and third
11
objectives of the study. These cooperatives primarily supply farm inputs especially fertilizer
through credit to the farmers. They also purchase farmers’ teff. The study area is also well
known for its teff production in the country and almost all farmers primarily produce different
grades of teff besides other crops. Hence, teff is taken for the analysis of factors influencing
marketing through the cooperatives.
1.6. Organization of the Thesis
This thesis constitutes five major sections. In the first and introductory sections subtopics that
are discussed includes, background, statement of the problem, objectives of the study,
significance of the study and scope and delimitations of the study. The second section
elaborates a review of some theoretical and practical conceptualizations with respect to the
agricultural cooperatives. A brief description of the study area and a thorough explanation of
the methodologies used for the study are presented in section three. The findings of the study
are presented in the result and discussions part in section four. Finally section five deals the
summary and conclusions that are drawn from the study.
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2. LITERATURE REVIEW
This section discusses the definition, principles and classification of cooperatives and
highlights the major benefit of cooperation, farmers’ attitudes on the performance of
cooperatives, historical development of cooperatives in Ethiopia and elements for
development of cooperatives in Ethiopia. Reviews of theoretical and empirical studies on the
performance of cooperatives in Ethiopia and other parts of the world are also presented.
2.1. The Definition of Cooperative
Center for Cooperative (2002) defined cooperative as a private business organization that is
owned and controlled by the people who use its products, supplies or services. Although
cooperatives vary in type and membership size, all were formed to meet the specific
objectives of members, and are structured to adapt to members’ changing needs. Chukwu
(1990) considered cooperative as a democratically controlled business i.e. it is owned and
controlled by the members. It also gives benefit to the members. It is often supplemented with
the six principles adopted by ICA.
2.2. Review of Basic Issues Concerning Cooperatives
2.2.1. Principles of cooperative
There are certain basic principles of cooperatives that are recognized by ICA. These
principles go back to the Rochdale pioneers and their original attempt started in 1844
(Chukwu, 1990). The principles define cooperative organizations, give them strength and
provide the cause and rationale for their public support. They also make it possible for
cooperatives to serve their members more efficiently. According to Chukwu (1990) and
Taimni (2000), the principles are summarized below.
13
The first principle is open membership. It encourages free entry into and exit from
membership of the cooperative. This principle disapproves unjustifiable restrictions or
discrimination against membership by persons who need and can benefit from the services of
the cooperative. According to this principle members who wish to terminate their membership
must be free to terminate their membership. However, in our country this basic principle was
violated in Derg regime. Farmers were forced to be a member with out their interest
especially in producers’ cooperatives.
Democratic management and control is the second basic principle of cooperative. It
emphasizes that members must be independent, participative and supreme in decision-
making. In the process of decision-making open, democratic and objective procedures
(voting) should be adopted. In general, this principle emphasizes members should be directly
or indirectly control and supervise the affairs of their cooperative. Farmers’ participation in
decision-making in the affairs of their cooperatives was minimum in the last two regimes.
Boards of directors and managers appointed by the governments were supreme in decision-
making process in the cooperatives.
The third principle is patronage refund. It is the most distinguishing feature of cooperatives. It
means that the proceeds of a cooperative, usually called savings, are returned to members in
proportion to their use of the cooperative (the amount they bought or sold to the cooperative).
Most agricultural cooperatives in Ethiopia use this method (patronage refund) in the
appropriation of surplus to their members.
Limited return (interest) on equity capital is the fourth principle and it limits the level of the
returns on the share capital paid by the members to rates which, if to be paid at all, are
considered reasonable, as high as the current market rate. In Ethiopia, this kind of surplus
appropriation takes place in saving and credit cooperatives.
The fifth principle is continuous education of the members. It emphasizes that cooperative
should give continuous education to their members in order to equip them with skills,
knowledge and confidence that make them use, participate and control the cooperative more
14
effectively. The type and extent of education offered might depend on the specific roles each
member is expected to play in the cooperative. This is what it lacks in agricultural
cooperatives in our country. Farmers don’t get continuous education from their cooperatives.
The last principle of cooperative is cooperation among cooperatives which intensifies the
basic cooperative idea of people working together in any given cooperative society to the
relationship between cooperatives of the same and/ or different sectors, on the same and/ or
on different organizational level and with in one country and/or internationally. In our
country, primary agricultural cooperatives started cooperation among themselves (forming
secondary cooperatives). There are 104 secondary cooperatives (FCC, 2005a).
Any business organization can be defined in terms of three basic interests: ownership, control
and beneficiary (Folsom, 2002). Only in the cooperative are all three interests vested directly
in the hands of the user i.e. the cooperative owned by the people who use it, it is controlled by
the people who use it and the benefits generated by the cooperative accrue to its users on the
basis of their use. These interests are commonly referred to as the contemporary cooperative
principles
In general, the above basic principles define cooperative organizations, give them strength,
and provide the cause and rationale for their public support, in terms of taxation, anti-trust
considerations, public education and promotion.
2.2.2. Classification/ types of cooperatives
Chukwu (1990) presented different criteria of classifying cooperatives that have been adopted
by different authors and some of the criteria for classification are summarized as follows. One
of the classifying criteria is the area of operation of the cooperative. Urban cooperatives are
those operating in the urban areas. There are housing, credit and saving etc. cooperatives
operating in the urban area of our country. Rural cooperatives are those operating in the rural
areas. Most of the cooperatives in our country fall in this category. There are grain, livestock,
dairy, coffee marketing cooperatives in different rural areas of the country.
15
Cooperatives can also be classified based on their organizational level. The smallest
individuals set up in the cooperative organizational level are primary cooperatives. They
usually cover a limited area of operation. They have individual person as member. Their
working capital is obtained from paid up shares of each member of the cooperatives. The
other organizationally higher cooperatives work in the interest of these cooperatives. In our
country there are 14,423 primary cooperatives operating in different sectors of the economy
(FCC, 2005a). Cooperatives in the second layer of the organizational set up are secondary
cooperatives. They usually formed by the number of primary cooperatives. Their working
capital is obtained from paid up shares of the constituent primary cooperatives. Their area of
operation covers the total area of the given constituent primary cooperatives. There were 104
secondary cooperatives operating in the different sectors of the economy (FCC, 2005a). The
third layers in the organizational set up are the tertiary cooperatives. They usually formed by
the secondary cooperatives and their working capital is obtained from paid up shares of the
constituent secondary cooperatives. So far these kinds of cooperatives are not formed in our
country.
The other classification criterion of cooperatives is the sector in which the cooperative
engaged. Cooperatives that engaged in the agriculture sector are classified as agricultural
cooperatives. There are many agricultural cooperatives operating in the different sub sector of
the economy. Industrial cooperatives (small scale industry) engaged industry sector. They are
emerging in different areas of the country. There are 78 handicraft cooperatives in the country
(FCC, 2004a). Service cooperatives are those engaged in the service sector of the economy.
They usually engaged in the banking, insurance, transport, health, electricity etc. There are
many saving and credit cooperatives and one newly established bank (Oromiya Cooperative
Bank) representing this sector (FCC, 2005b).
The number of operation in which the cooperative engaged is another classification criteria of
cooperatives. There are single purpose cooperatives which have only one field of activity (one
purpose e.g. marketing). There are also multi-purpose cooperatives which have more than one
field of activity (two or more purpose e.g. credit and marketing).
16
2.3. Major Benefits of the Cooperation
The theory of cooperative organization provides several reasons why farmers join the
cooperatives. According to Schroeder (1992) cooperatives provide quality supplies and
services to the farmers at the reasonable cost. By purchasing supplies as a group, the farmers
offset the market power advantage of other private firms providing those supplies. The farmer
can gain access to volume discounts and negotiate from a position of greater strength for
better delivery terms, credit terms, and other arrangements. Suppliers will also be more
willing to discuss customizing products and services to meet farmers’ specifications if the
cooperative provides them sufficient volume to justify the extra time and expense.
Increased farmers bargain power in the market places is the other advantage of the
cooperative (Douglas and McConnen, 1999). Marketing on a cooperative basis permits
farmers to combine their strength and gain more income. The farmers can lower distribution
costs, conduct joint product promotion, and develop the ability to deliver their products in the
amounts and types that will attract better offers from purchasers.
According to Parliament et al. (1990) a cooperative gives farmers a means to organize for
effective political action. Farmers can meet to develop priorities and strategies. They can send
representatives to meet with legislators and regulators. These persons will have more
influence because they will be speaking for many, not just for themselves.
According to Folsom (2002) having a businesses owned and controlled on a cooperative basis
helps farmers’ entire community. Cooperatives generate jobs and business earnings for local
residents. They pay taxes that help finance schools, hospitals, and other community services.
2.4. Farmers’ Attitude on the Performance of the Cooperative
The cooperative is usually one alternative form of business organization that can offer good/
service to the farmers. If the other business organizations are regarded as dishonest, inefficient
17
or exploitive, farmers will be predisposed to use the cooperative (Chukwu, 1990). On the
other hand if the other business organizations are offering good/ service efficiently, honestly
and at fair price, the farmers more likely to be less interested in the cooperative.
According to Klein et al. (1997) the performance of the cooperative will also affect the
possibilities of having more farmers as member. If the cooperative is seen as inefficient, its
functionaries corrupt and not prepared to listen its members, the prospective members
(farmers) will not have a good attitude towards the cooperative.
Cooperatives cannot be free of risks as they undertake speculative business activities
(chukwu, 1990), for example, in our country agricultural cooperatives purchase teff, coffee
and other farm produces from the farmers in the harvesting season speculating that the price
rises in the latter seasons. These risks are usually high for the average cooperative farmers
who in most cases belong to the lower economic class of the society. Furthermore, decision
making in the agricultural cooperative is known to be traditionally relatively low, whereas
speculative business activities require flexible and speedy action. If there is repeated loss in
the cooperative, farmers will be disappointed with performance and be less interested in the
cooperative.
2.5. Historical Development of Agricultural Cooperatives in Ethiopia
In Ethiopia, though the formation of similar cultural and traditional associations (example
‘Edir’, ‘Ekub’, ‘Wonfel”, etc) was dated many years ago, it was after 1960 that those modern
cooperatives came to birth (MoRD, 2002).
2.5.1. Feudal regime (1960- 1975)
The Feudal regime proposed cooperatives as instruments for the mobilization of rural
resources in Ethiopia for the first time. Decree 44/1960 and proclamation 241/1966 provided
18
the legal ground for the development of cooperatives in Ethiopia in that period (Alemayehu,
1984).
The decree was necessitated by the creation of proper framework for the establishment of
cooperatives enterprises which contribute measurably towards the acceleration of
development of agriculture sector. The cooperatives that were anticipated to be organized in
accordance with the provision of the decree were in general to have, as their principal purpose
and objective, the promotion of the economic interest of the country and of their members.
The decree also had various provisions on rights, duties, privileges and responsibilities of
members. Membership in general was to entitle everyman to a proportionate share in the net
profit of the cooperative, to attend the general meeting, to elect administrative bodies and to
vote on all questions.
Societies that were organized under this proclamation were to have as their principal purpose
and objective the promotion of better living, better business and methods of production.
According to Alemayehu (1984) five types of cooperatives were established through
proclamation 241/66. Multi-purpose, thrift and credit, consumers’, artisans’ and farm
workers’ cooperative societies were established and 700 peoples enrolled as a member of
these societies and contributed about birr 25,000 towards purchase of share.
When we overview the regime, it was in this period that modern cooperative came into birth.
Though there was little or no awareness in the people, the regime laid down the legal ground
for the development of the cooperatives taking into account their significance to mobilize the
resources the country had.
2.5.2. Derg regime (1975-1991)
The legal ground for the establishment and development of agricultural cooperatives was first
provided by the proclamation 71/1975 (Wegenie, 1989). The Derg regime established an
extensive network of socialist agricultural cooperatives throughout Ethiopia to organize the
peasants, control agricultural prices, levy taxes, and extend government control to the local
19
level. Farmers came to view the cooperative with mandatory membership, quotas for grain to
be delivered to the government, and boards of directors and managers appointed by the ruling
party as a synonym for government oppression (ACDI/VOCA, 2002). The development of
cooperatives was anticipated to proceed in four stages
1. Service cooperatives (credit and marketing)
2. First stage producers’ cooperatives
3. Advanced producer’ cooperatives
4. Commune
Later on in 1978 the regime necessitated the establishment of different cooperative societies
for combating exploitation of workers and peasants by enabling theme secure services, to
safeguard the economic, political and social rights of peasants by securing goods and services
and ensuring the participation of the broad mass (Wegenie, 1989). The objectives of the
cooperative societies at that time were the following
- to develop self-reliance and promote the interest of the members
- to put the means of production under the control of the cooperative
- to increase production
- to expand industries
- to conduct political agitation
- to eliminate reactionary culture and customs
With the above objectives producers’, thrift and credit, service and housing cooperative
societies were established.
When we overview the regime, there was the understanding of the significance of the
cooperatives for the development of the country but there were problems in implementing
them. As indicated by Tesfaye (1995), ACDI/VOCA (2002) and Subramani (2005) the regime
violated some of the internationally recognized basic principles and values of cooperatives
and it made cooperatives a platform for conducting political agitation rather ignoring their
political neutrality. It also violated the very basic principles of cooperatives (open and
voluntary membership). In some places farmers were forced to be the member of the
cooperative through external pressure especially in the farmers producers’ cooperatives.
20
Cooperatives were administered by the government cadres and untrained manpower. There
were corruptive practices in the cooperatives. In general, the regime misused cooperatives for
its political ends violating the underlying principles of cooperative.
2.5.3. Post 1991 period
Subramani (2005) indicated that emphasis that deserve for cooperatives was not given in the
transition period. Some of the above problems of the Derg regime repeated in this period.
Cooperatives were administered by untrained manpower. There were corruptive practices due
to poor record keeping system. There were also other unhealthy practices in the area of the
cooperatives. The bad track record of the cooperatives couldn’t get rid of the mind of the
people in these years.
It was after the proclamation 147/1998 (Federal Negarit Gazeta, 1998) that people centered
cooperatives came into existence. This proclamation paved a conducive environment for the
development of cooperatives. To speed up the cooperative movement in the country, the
government established the Federal Cooperative Commission by the proclamation 274/2002
(Federal Negarit Gazeta, 2002). According to FCC (2005) the commission is established to
undertake the following responsibilities
- to formulate policies and prepare draft laws suitable for the activities and development of
cooperative societies and follow up their implementation
- to direct and supervise cooperatives’ training institute to be set up at federal level
- to make the values, principles, organization and benefits of the cooperatives be further
known by the society and educational establishments
- to promote the product of the cooperative societies so that they made find market, and
facilitate conditions in order to bring consumers and producers to direct communication
in the home market.
- to provide professional and technical support to process agricultural products of the
cooperative societies to industrial products so that they will have better added-values
- to facilitate means to provide support for the societies in collaboration with regions by
21
studying and preparing projects suitable for the development of the cooperative societies and
- to provide technical and professional assistance for regional bureaus in setting up
cooperative societies.
The government has also given more emphasis to agricultural cooperatives as they are a
means to implement agricultural development policies directed specifically towards
smallholders. The number of primary cooperatives increased from 7,740 in 2003 (FCC,
2004a) to 14,423 in 2005 (FCC, 2005a). This increment can be evidence to the attention given
to the development of cooperatives. Efforts are also being made to keep the basic principles
and ideas of cooperation while organizing the cooperatives.
2.6. Elements for the Development of Cooperatives in Ethiopia
Wegenie (1989) and Abebe (2000) indicated that rural institution such as agricultural
cooperatives should form the basis of future development endeavors in the country as they are
best instrument for the mobilization of rural resources. However, Abebe (2000) emphasized
that they should take into account local perceptions and realities, as well as built on the spirit
of self and mutual help.
Subramani (2005) pointed out certain elements, which deserve attention in an integrated
development of cooperatives in Ethiopia. The first element that he proposed was the choice
of sectors wherein cooperatives operate. Nowadays the agricultural sector of the country
needs much attention as it is the backbone of the country and the majority of the population
engaged in it. This is also true from the point of view of the policy (agricultural development
led industrialization) the country adopted.
Defining the rights and responsibilities of the cooperative at a macro level is the second
element in the development of cooperatives in Ethiopia. It has a key place as it constitutes a
prime factor in determining the overall role to be played by the cooperative movement in the
national planning and development programs. The existing government of Ethiopia has
22
already legislated the cooperative society act by the proclamation No. 147/1998 (Federal
Negarit Gazeta, 1998) and rules to define the rights and responsibilities of the cooperative.
The third element that is proposed in the development of cooperatives is the choice of the
organizational pattern. In Ethiopian case the development of primary cooperatives should
deserve prior attention. After organizing and strengthening primary cooperatives, efforts
should be made to link these vertically and horizontally. These linkages help to improve their
competency and operational efficiency.
Education, capital, management skills and training facilities are the fourth element to be given
attention in the development of cooperatives. These inputs are important to get effective
output from the cooperatives. The government of Ethiopia has given emphasis for these
inputs. It has been launching different training programs across the country. According to
FCC (2004b) four universities already launched cooperative training program at the level of
bachelor degree. Ardaita ATVET College, the former Yekatit 25 cooperative institute, is also
giving middle level (diploma level) training program in the fields of cooperative. In order to
avoid the capital shortage of the cooperatives, the government is establishing cooperative
banks (e.g. the Oromiya Cooperative Bank) and other financial rural institution in the country.
He finally concluded that if the four elements of cooperative development properly handled,
no doubt they would serve as four pillars to firmly hold the entire structure of the national
cooperative movement for the better accomplishment of the desired national expectations.
2.7. Studies on Cooperatives in Ethiopia
In his study of cooperative movement in Ethiopia, at early days Kebebew (1978) emphasized
that the state commitment for collective agriculture to flourish. This commitment manifested
by the material and technical investment accompanied by educational programs designed to
raise the social and political consciousness of the peasants. State investment in agriculture
23
designed to modernize the methods of agricultural production is likely to tract those peasants
who are dubious about the success of collective production.
A study conducted by Alemayehu (1984) in Kembata and Hadiya on service cooperatives
revealed that most of the service cooperatives safeguarded the peasants against price
exploitation by private traders. However, he noted that cooperatives’ attempt to serve their
members have been hampered by the cooperative poor spatial organization which necessitated
the re-organization of some of the cooperatives based on physical geographic factors and on
the size of the PA membership.
Getenesh (1988) used some performance measures such as liquidity ratio, net capital ratio,
debt ratio etc. in her comparison of farmers’ producer cooperatives in the highlands of
Hararge. The result showed that size in terms of members and area didn’t contribute
significantly to explain the performance differences in most cases, in contrast to wide spread
assumption of this to be so.
Asmare (1989) investigated the efficiency of resource use in producers’ cooperatives in
Harar- Zuria awraja giving special attention to size effects. Using the marginal productivity
and partial productivity methods, he displayed inefficient use of resources in both small and
large sized producers’ cooperatives groups. However, relatively the larger sized producers’
cooperatives group allocated its resources more efficiently. Inefficiency includes under
utilization of labor, fertilizer and capital expenses and partly over utilization of land.
Wegenie (1989) evaluated the performance of cooperatives both at micro and macro level and
the problems of development of cooperatives. Macro level study indicated that the
performance of cooperatives was poor when compared to the individual and state farms in
terms of yield. The performance evaluation of the cooperatives at the micro level was
specifically directed at looking their allocative efficiency using the linear programming
model. Comparison of the actual with the optimal pattern indicated sub optimality in their
cropping pattern. In all cases his result suggested a reallocation of land away from the two
basic products of the region i.e. wheat and barely to other crops. Land, in his optimal solution
24
was found to be the limiting factor in all the cooperatives and he suggested that for an
appropriate land holding and land allocation policy for each of the cooperatives which take
resource availability of the cooperative into account. His study also indicated input-output
pricing system, declining income of members, forced membership and absence of democracy
in decision-making process as a problems development of cooperatives.
A study conducted by Fassil (1990) showed that inspite of the several tasks bestowed upon
peasant service cooperative, they were mainly engaged in the supply of consumer goods to
members followed by grain purchase and sale activities. Even in the activities they engaged,
they have lower share compared to those of state and other bodies. The problems of the
cooperatives were manifested in the sphere of marketing and management, which includes the
problems in the supply of both consumer goods and agricultural inputs, participation in
purchase and sale of products especially grain, shortage of skilled manpower and financial
management.
Tesfaye (1995) in his study of producers’ cooperatives found that these organizations failed in
the past not because of failure inherent in collective management but because of forced
membership with out the interest of the farmers and formation of the cooperatives in hurry
without any sufficient preparation and feasibility study. The problem of intervention of the
Derg regime in the affairs of these organizations i.e. using them for its political ends and the
largeness and complexity of the organizations for the managerial capacity of the farmers were
also a reason for the failures of the cooperatives.
2.8. Empirical Studies on the Performance of Agricultural Cooperatives
Misra et al. (1993) used the ordered probit model to analyze the factors influencing farmers’
degree of satisfaction with the overall performance of milk marketing cooperatives. As
satisfaction level of dairy farmers is a discrete qualitative variable, they used this model
instead of the OLS as the latter would result in biased and inefficient estimate. Their result
showed that dairy farmers perceive cooperatives’ ability to hold down operating and
25
marketing costs, to provide higher prices and competent field services and the assurance of a
market for their milk as important attributes of dairy marketing cooperatives.
Hind (1994) studied the Performance of 31 agricultural cooperatives and 82 non-cooperatives
in agribusinesses in United Kingdom. He determined first, the mean, standard deviations and
t-test of differences in means for the two businesses of the selected performance indicators
such as sales turnover, return on asset, sales/working capital, debt ratio, etc. Then, he used
the linear multiple regression analysis to determine if there were significant relationships
between the performance indicators and business form using dummy variables for the
business form. The findings of his research revealed that cooperatives do not perform
differently to non-cooperatives, despite being required to balance members needs with the
attainment of their goals.
Mauget and Decklerck (1996) examined a sample of European community agricultural
cooperatives annual reports including financial results such as value-added/turnover,
operating activities/turnover, (net income+ depreciation) /turnover, labor cost/turnover etc. in
order to find key factors of success. Their data years were 1990 and 1991. The result showed
that in general specialized cooperatives didn’t perform better than multi-purpose cooperatives.
Specialized cooperatives were most successful in Denmark while multipurpose cooperatives
did better in Ireland.
A logit regression analysis was used by Tretcher (1996) to analyze the factors associated with
diversification on agricultural cooperatives in Wisconsin. He found that the impact of
diversification upon measures of cooperative performance (profitability, patronage refund and
equity redemption) was relatively minor i.e. diversification on agricultural cooperatives was
not statistically associated with profitability, increases in patronage dividends or increases in
equity revolvement. The result also showed that diversification on agricultural cooperatives
was an important factor in determining membership size i.e. diversified cooperatives enjoyed
larger membership.
26
Harris and Fulton (1996) found that agricultural cooperatives performed at least as well as
their proprietary business competitors in terms of their liquidity, asset management efficiency,
debt coverage and profitability. However, for many farmers, financial performance was
secondary to the “competitive yardstick” role of cooperative, or the role that they play in
improving the rural economy.
The technical efficiency and scale economies of the dairy marketing cooperatives were
estimated by Ellene and Schreiner (1996) in Kenya. They used the maximum likelihood
technique to estimate a stochastic cost frontier function and determined technical efficiency
and scale economies. The estimated long–run average cost curve indicated that scale
economies, but most of the scale economies are exhausted for the average size of cooperatives
in the sample. In general, the result indicated that the dairy marketing cooperatives were
technical efficient for the observed technology. They also suggested that cooperatives can
reduce unit costs by expanding volume of milk handled, either through existing members or
new member, including merging with other cooperatives.
Klien et al. (1997) used tobit model to analyze the amount business conducted with different
type of cooperatives. They revealed that relatively larger sized farms did a great proportion of
grain marketing and chemical purchases through the cooperatives and bought more of their
fuel from the cooperatives. Older farmers patronized all types of cooperatives more than
younger farmers except for farm chemical. At the highest level of off-farm income, grain
farmers used the cooperative more intensively. The perception of competitive price leaded to
a higher rate of patronage.
The tobit econometric model was used by different researchers in similar studies. Teferi
(2003) used this model in identifying the determinants of fertilizer use. His result showed that
health of the respondent, education level, credit access, extension contact, labor, availability,
livestock holding, age, distance from the road and use of improved seed were found to
determine the use of fertilizer.
27
Getahun (2004) used tobit model to in assessing factors affecting adoption of wheat
technology. His analysis showed that fertilizer use, income and credit influenced the
probability of adoption and intensity of improved wheat varieties.
Tefera (2004) also used tobit model to in identifying the determinants of smallholder farmers’
demand for non-formal credit. The result showed that gender of the household head, number
of children below fourteen years of age, fertilizer use and interest rate on the credit were
found to determine the demands for non-formal credit
28
3. RESEARCH METHODOLOGY
The information discussed in this session includes the features of the study area where the
research was conducted and the methodologies adopted in the sampling and data analysis. The
information collected includes both primary data from sample households and secondary data
(financial data) of the cooperatives from the wereda cooperative organization and promotion
offices.
3.1. Description of the Study Area
3.1.1. An overview of the Oromiya regional state
The Oromiya regional state lies in the central part of the country with larger protrusions
towards the south and west directions. It has an area of 353,690 km2 (OPEDB, 2000). The
region has 12 administrative zones and 180 districts. The population of the region was 20
million, of which the economically active population (15-64) accounted for 50.0% and the
total average household size was estimated at 4.8 person (CSA, 1994). The estimated
livestock population was 41.6 million. The total estimated arable land was 30.7% of the
region and average land holding per farmer household was about 4.3 ha (OPEDB, 2000).
Teff, wheat, maize barley, sorghum, bean, pea, lentil etc. are some of the widely cultivated
crops in the region.
3.1.2. An overview of the east Shoa zone
East Shoa zone has an area about 14,050 km2 that is divided into 12 districts (OPEDB, 2000)
including the Adaa Liben and Lume districts. According to the same source the estimated
population of the zone in 2003/4 was about 1,800,000 and the economically active age group
(15-64) was about 52.4%.
29
Figure 1. “Map” of Oromiya Regional State
The average family size per household was about 4.8 person (CSA, 1994). The zone has an
estimated livestock population of about 5.3 million and arable land of about 44.0% of the total
30
area (OPEDB, 2000). Teff, maize barley, sorghum, bean, pea, fruits, vegetables etc. are
some of the widely cultivated crops in the zone.
3.1.3. Adaa Liben and Lume Districts
3.1.3.1. Location and physical features
The location of Adaa Liben is 8022’-8
056’N latitudes and 38
058’-39
022’E longitudes. It is the
largest district in the zone with an area of 1576.79 km2 and cultivable land of 1261.43 km
2
(80%) of the district area (ESZFEDD, 2004a). Bishoftu (Debrezeit) is capital of the district.
Currently, the district is divided into 42 PAs. The largest relief feature of the district is
dominated by flat land that is broken by undulating and rolling plateaus. Elevation of the
district ranges between 1500–2300 m.a.s.l. The largest portion (95%) of the district has
Woinadega agro-climate and the remaining portion (5%) has Dega agro-climate (ESZFEDD,
2004a). According to the same source the annual temperature for the two agro-climatic zones
is 15-20 0c and 10-15
0c respectively and the major soil type of the district is Vertisol which
covers about 988.44 km2 (62.7% of the district).
The location of the Lume district is between 8012’-8
050’N latitudes and 39
001’-39
017’E
longitudes. It is the second smallest district in the zone with an area of 730 km2 and divided
into 35 PAs (ESZFEDD, 2004b). Modjo is the capital of the district. Most parts of the district
has an elevation ranges of 1500–2300 m.a.s.l. About 44%, 31% and 25% of the district has
Woinadega, Dega and hot agro-climatic zones respectively (ESZFEDD, 2004b). According to
the same source the average annual temperature range between 15-20 0c and 10-15
0 c for
Woinadega and Dega agro-climatic zones of the district respectively and the average annual
rainfall of the district is between 700-800mm. Vertisol is the major soil type and covers the
largest area of the district.
31
Figure 2. “Map” of East Shoa Zone Containing Adaa Liben and Lume Districts
3.1.3.2. Socioeconomic environment
The estimated population of Adaa Liben district was 187,330 of which 51.7% and 48.3%
were males and females respectively (ESZFEDD, 2004a). The economically active population
(15-64) accounted for 50.4% (CSA, 1994). According to the same source the district has the
highest level of population in the zone with total average family size of 5 persons. The crude
32
population density and agricultural density are 119 and 158 persons/km2 respectively. The
estimated population of Lume district was 117,051 of which 51.1% and 48.9% were males
and females respectively (ESZFEDD, 2004b). The economically active population (15-64)
accounted for 53.5%. The crude population density of the district was 160 persons/km2 (CSA,
1994).
Adaa Liben is one of the most known agriculturally rich districts of the zone and it is most
popular in farming activities. Its agro-climatic conditions (sub-tropical) and major soil
(vertisols) made it suitable for the production of cereals and pulses. According to ESZFEDD
(2004) the district has 42 PAs that have 28,448 farmers, 80% cultivable area and livestock
population of 606,037 including poultry. The Lume district like the Adaa Liben district is
known for its cereals and pulses. According to ESZFEDD (2004b) the district has 35 PAs that
have 11483 farmers, 56.2% cultivable area and livestock population of 186,333 including
poultry.
The farming calendar of the Adaa Liben district is from March to January. Rain-fed
agriculture is its main crop production system. The agro-climatic conditions (Woinadega and
Dega) of the district are conducive for the production of various types of crops. The major
crops that are produced in the district are cereals, pulses and oil seeds. As shown in Table 3,
the total area of land cultivated in 2001/2 and 2002/3 was 116,606 and 117,086.8 ha
respectively and the yield obtained was 8,392,796 and 13,071,659 qts respectively. Teff
occupied the largest cultivated area out of the crops grown in the district. The major crops that
grow in the Lume district are cereals and pulses. The crop production is rain-fed one and it
takes place once in the year (Meher).
33
Table 3. Crop production of different types in the Adaa Liben district
2001/2 2002/3 Type of Crop
Area (ha) Production (Qt) Area (ha) Production (Qt)
Cereals 97142 8161213 96781 1066745.9
Teff 59898 723753 59417 513602
Wheat 30646 820590 33005 528080
Barley 2645 42320 1883 15089.6
Sorghum 859 12885 75 370.25
Maize 3015 54270 2340 9360
Oats 79 395 61 244
Pulses 19290 230686 18713 110260
Lentils 2105 18945 1800 7200
Horse beans 6580 24576 6420 38520
Chick peas 4375 61470 3367 31720
Field peas 3472 31255 3980 19900
Vetch 710 8880 766 4000
Haricot bean 2048 85560 2215 8860
Others - - 165 60
Oil seed 174 897 192 576
Lin seed 174 897 57 171
Fenugreek - - 135 405
Others - - 1400.8 129584
Total 116606 839279.6 117086.8 1307165.9
Source: ESZFEDD Physical and Socioeconomic Profile report for Adaa Liben district, 2004.
As shown in Table 4, the total area under different crops in 2001/2 and 2002/3 was 41,055
and 41,090 ha respectively and the yield obtained was 503,585 and 741,050 qts respectively.
34
Table 4. Crop Production of Different Types in the Lume District
2001/2 2002/3 Type of Crop
Area (ha) Production (qt) Area (ha) Production (qt)
Cereals 38185 488655 38415 714300
Teff 26440 264400 26500 344500
Wheat 10420 208400 10500 346500
Barley 710 12780 800 20000
Sorghum - - 15 300
Maize 615 3075 600 21000
Pulses 2870 14930 2675 26750
Lentils 185 925 200 2000
Horse bean 620 3100 600 6000
Chick peas 710 3550 635 6350
Vetch 440 2325 240 2400
Haricot beans 310 1550 300 3000
Field peas 605 3480 700 7000
Total 41055 503585 41090 741050
Source: ESZFEDD Physical and Socioeconomic Profile report for Lume district, 2004.
The Adaa Liben district has a diversified livestock population that largely rear on its agro-
climate. It has a total of 606,037 livestock and cattle stands first in terms of population (63%)
followed by goat (15.3%) (ESZFEDD, 2004a). Livestock are a means of draft power,
transport and source of income directly and indirectly. Though they are gradually declining,
pasture, bushes and shrubs are used as major livestock feed. Crop residues and industrial by
products are also used as feed. The Lume district also has a livestock population of 186,333
(ESZFEDD, 2004b). Livestock are a means of draft power, transport and also serve as an
asset. In the district the grazing and browsing area are diminishing in size. In addition to
pasture, crop residues and industrial by products are used as feed.
35
3.1.4. Agricultural extension service
In order to realize the desired development in those countries where agriculture is the major
means of survival, every effort towards growth should focus on the rural farming community.
In this context extension services play a vital role in channeling the appropriate know-how to
the farmers.
In the Adaa Liben and Lume districts there are 39 and 24 DAs respectively that are
responsible for providing the necessary technical supports required by the farmers. To
upgrade the skill and learning capacity of the farmers the country revised the extension policy
in the year 2001. The plan revised gives priority in establishing farmers training centers (FTC)
and assigning three DAs who have a diploma in specialized fields of agriculture in each
kebele. This would enable farmers to get in touch and make use of new ideas and technologies
on a variety of subjects to improve their livelihood. Taking this into consideration during the
last three years a number of DA’s have been recruited and enrolled in TVET (Technical
Vocational Education and Training) to acquire the required skills.
3.1.5. Agricultural cooperatives
In Adaa Liben district there are 26 multi-purpose agricultural cooperatives (ALWCPO, 2005).
And they have 22,583 farmer members (19892 males and 2691 females) in 2002/3. The total
capital of the cooperatives was birr 2,682,812.86. The cooperatives provide primarily
fertilizer and other farm inputs. One of the fascinating attributes of agricultural cooperatives is
extending fertilizer in credit. They also market farm produces especially teff. Some of the
cooperatives render tractor and grain mill service. There are 12 multi-purpose agricultural
cooperatives in Lume district with members of 11,483 farmers (10,731 males and 752
females) in 2002/3 (LWCPO, 2005). The total capital of the cooperative was birr
2,134,912.27. The cooperatives provide farm inputs especially fertilizer in credit to the
members, market cereals especially teff, provide tractor and mill service to the farmers.
36
3.1.6. Cooperative organization and promotion service
The current government of Ethiopia is establishing, promoting and organizing cooperatives in
the rural community, as they are a means to development. In the Adaa Liben and Lume
districts there are cooperative organization and promotion office that are responsible for
providing the necessary technical supports required by the cooperatives. As these offices are
newly organized, the support they are giving is not satisfactory. The offices also face shortage
of qualified personnel in the area of cooperative to meet their objectives.
The government of Ethiopia is working to mitigate the qualified manpower needs of the
cooperatives. Four Universities launched training program in the first-degree level and
diploma level training is taking place in the Ardaita agricultural TVET College. During the
last three years a number of students enrolled in the departments of cooperatives. The
cooperative offices as well as the cooperatives themselves in the two districts are expected to
benefit from this in the coming few years.
The other problem in the cooperative organization and promotion in the two districts is the
shortage of capital. This makes the cooperatives unable to compete in the market especially in
the purchasing of farmers’ produces. In order to solve this problem, the Oromiya regional
government has already established a cooperative bank (Oromiya cooperative bank) which is
primarily established to extend credit for the cooperatives.
3.1.7. Agricultural credit services
Formal and informal institutions are the two main sources of credit in the study districts.
Credit from informal sources such as friends, relatives and neighbors are used to cover family
consumption requirements such as food purchases, medical expenses and sometimes to pay
taxes. Interest charged on credit from friends, relatives and neighbors is nil in most cases.
However, local moneylenders, who charge high interest rate, are found in the study areas.
There are also formal micro finance institutions that provide credits for the farmers. Farmers
receive credit from these institutions for the prepayment to be paid for the cooperatives to
37
obtain fertilizer in credit, fattening livestock, contracting land and ox and for other social
obligation. The cooperatives also extend credit for the farmers i.e. they distribute fertilizer in
credit for the farmers. Almost all farmers, who are the member of the cooperatives, take this
credit.
3.1.8. Marketing services
Availability of efficient marketing system raises farmers' income. It has considerable
importance in improving the productivity of agriculture by providing incentives to farmers. It
also enables the farmers to produce a particular crop or livestock species, which may provide
the best advantage. It is possible to say that if increased production is the door for
development, marketing should be the key to open the door.
There are a total of 38 primary agricultural cooperatives in the area where this study
conducted. They are organized under two Union (Erer and Lume-Adama). The Unions are
participating in the fertilizer market and distribution. The union purchase fertilizer by biding
method from suppliers at wholesale price and retail to the primary cooperatives after adding
minimum retail margins. Finally the cooperatives distribute the fertilizer to the farmers after
adding minimum retail margins. The cooperatives distribute the fertilizer in credit to their
members with some prepayment. Besides benefiting the farmers, the cooperatives also
enabled to reach remote areas. There were no other private enterprises competing with the
cooperatives in supplying farm inputs especially fertilizer to the farmers in the study area.
However, there are some proprietary firms in the district markets that sell in retail.
Agricultural product market in the study area is less developed and there is a seasonal price
variation. In areas where three of the cooperatives studied, there are local markets whereas in
other areas where the cooperatives operate there are no local markets. In some areas there are
assemblers especially in harvesting seasons. They purchase teff from the farmers. In most of
the cases, when farmers want to sell some of their farm produces they have to travel long
distances to district market place using their pack animals. Though it is not strong as
marketing of fertilizer, cooperatives also participate in purchasing farm produces especially
38
teff from the farmers. Due to locational accessibility to the district markets and other market
outlets, farmers also use these markets for their farm produces.
3.2. Sampling Procedure
3.2.1. Selection of study area
Adaa Liben and Lume districts, as a case study area, are selected purposively for several
reasons. Among the several areas in the country where cooperative movement is high, the
study area is the front-liner in the set up and organization of agricultural cooperatives.
Primary agricultural cooperatives in these two districts are relatively well organized and
developed. The development is favored by locational accessibility to markets and transport
routes. In addition to this, the cooperatives in these districts are relatively near to Addis Ababa
and can get support both from government and NGOs easily. The cooperatives primarily
supply fertilizer through credit and other farm inputs, purchase farmers’ teff and extend credit.
3.2.2. Sampling design
Cooperatives in the two districts were not audited in a yearly base due to shortage of auditors
in the zone. Hence, cooperatives, that were audited for the periods 2001/2 and 202/3, were
taken purposively to examine their financial performance. To meet the last two objectives of
the study, a two-stage random sampling procedure was adopted for the selection of the sample
farmers from the cooperatives in the two districts.
In the first stage, considering the number of primary cooperatives (26 in Adaa Liben district
and 12 in Lume district) as well as financial and time limitations, eleven primary cooperatives
were randomly chosen from the two districts i.e. seven from Adaa Liben district and four
from Lume district. In the second stage, the farmers were selected randomly by using the list
of the cooperatives’ member files. The number of farmers selected from each primary
39
agricultural cooperative was 12, totaling 132 farmers. For the sampling, the number of
household head in the cooperative file was divided by twelve and by the interval of the ratio
the farmer will be selected starting from any number between 1and 9 randomly. If the
respondent obtained thus was migrated to other area leaving the cooperative or other
inconveniences exist for the interview, the sample frame was updated before the selection.
The numbers of respondents were limited to 132 by compromising the required budget and
time.
3.3. Methods of Data Collection
Both primary and secondary data were used in the analysis of this study. To accomplish the
first objective of the study, the financial performance of the fifteen agricultural cooperatives
i.e. the financial statements of the cooperatives for the periods 2001/2 and 2002/3 were taken
from the wereda cooperative offices. The primary data pertaining to the year 2003/4 and
2004/5 were collected from sample respondents through a structured questionnaire, which
was designed to generate data on some social and economic variables about the farmer, the
total quantity of fertilizer taken from the cooperatives, the total quantity of teff marketed
through the cooperatives, the credit the farmer got from the cooperative, the attitude of the
farmer towards the cooperative and other variables that were supposed to be important for the
study.
The enumerators who speak the local language (Oromiffa) were recruited from the study
districts and were trained on methods of data collection and interviewing techniques.
Moreover, the researcher explained the contents of the questionnaire to the enumerators. Field
trips were made before the actual survey to observe the overall features of the selected
cooperatives and to select farmers to be interviewed using lists taken from respective
cooperatives. The questionnaire was pre-tested and its contents were refined on the basis of
the results obtained during the pre-test. With regard to the collection of primary data, it was
done in two different ways: trained enumerators held interview with sample farmers using the
structured questionnaire; and the researcher made personal observations and informal
40
discussions with farmers, cooperative officials and employees in the cooperatives on issues
related to the cooperatives and their performance. Continuous supervision was also made to
reduce error during data collection and to correct possible errors right on the spot.
Information such as the number and type of the cooperatives in the country and Oromiya
region, the number of members and the capital amount etc. were obtained from various
sources such as reports of Federal Cooperative Commission, Oromiya Cooperative Promotion
Commission. Similar data concerning the two districts was also obtained from Adaa Liben
Wereda Cooperative Organization and Promotion office and Lume Wereda Cooperative
Organization and Promotion office. Other published and unpublished information which were
found to be relevant for the study were also collected from wereda offices of agriculture in the
two districts, Central Statistics Authority, other governmental and non governmental
organizations.
3.4. Methods of Data Analysis
3.4.1. Ratio analysis
To meet the first objective of the study, different financial ratios were used. Financial ratios
can be designed to manage cooperative’s performance. Ratios can be used as one tool in
identifying areas of strengths or weakness in cooperatives. Financial ratios enable to make
comparison of cooperative’s financial conditions over time or in relation to other
cooperatives. Ratios standardize various elements of financial data for differences in the size
of a series of financial data when making comparisons over time or among cooperatives.
3.4.1.1. Liquidity ratio
A cooperative intends to remain viable business entity must have enough cash on hand to pay
its debts as they come due. In other words, the cooperatives must remain liquid. One way to
determine whether this is the case is to examine the relationship between a cooperative’s
41
current assets and current liabilities. Liquidity ratios are quick measure of cooperative’s
ability to provide sufficient cash to conduct business over the next few months. According to
Nevue (1985); Bringham and Houston (1998) and William et al.(2003) one of the most
commonly used liquidity ratio is the current ratio that is computed by dividing current asset
by current liabilities.
liablityCurrent
assetCurrentratioCurrent = Eq (1)
3.4.1.2. Financial leverage management ratio
Whenever a cooperative finance a portion of asset with any type of financing such as debts,
the cooperative is said to be using financial leverage. According Bringham and Houston
(1998) and William et al. (2003) financial leverage management ratio measures the degree to
which a firm is employing financial leverage. According to these authors, of the several types
of financial leverage ratios, debt ratio is commonly used. It measures the portion of a firm’s
total asset that is financed with creditors fund. It is computed by dividing total debt by total
asset.
assetTotal
debtTotalratioDebt = Eq (2)
3.4.1.3. Profitability ratio
Profitability is the net effect of a number of policies and decisions. Profitability ratios measure
how effectively a firm’s management was generating profits on sales, total assets, most
importantly stockholders’ investment (Nevue, 1985; Bringham and Houston, 1998; William et
al., 2003). These authors also suggested that the most commonly used profitability ratio is
return on total asset, which is computed by dividing net income by total asset.
42
assetTotal
incomeNetassettotalonturn =Re Eq (3)
3.4.2. Discrete regression models
Discrete regression models are models in which the dependent variable assumes discrete
values. The simplest of these models is that in which the dependent variable Y is binary (it
can assume only two values denoted by 0 and 1) (Amemiya 1981; Gujarati, 1988; Maddala,
1997). According to these authors, the three most commonly used approaches to estimating
such models are the linear probability models (LPM), the logit Model and the probit models.
The linear probability model is the model, which expresses the dichotomous dependent
variable (Y) as a linear function of the explanatory variable (X). Because of its computational
simplicity, LPM has been used in econometrics applications especially during and before the
1960s. However as indicated by Amemiya (1981), Maddala (1997) and Gujarati (1988) the
linear probability model has an obvious defect in that the estimated probability values can lie
out side the normal 0-1 range. The fundamental problem with the LPM is that it is not
logically a very attractive model because it assumes that the marginal or incremental effect of
explanatory variables remains constant, that is Pi= E (Y=1/X) increases linearly with X
(Maddala, 1997; Gujarati, 1988).
The defects of the linear probability model suggest that there is a need to have an appropriate
model in which the relationship between the probability that an event will occur and the
explanatory variables is nonlinear (Amemiya, 1981; Gujarati, 1988 and Madalla, 1997). These
authors suggested that the sigmoid or S-shaped curve, which very much resembles the
cumulative distribution functions (CDF) of random variable, is used to model regressions
where the response variable is dichotomous taking 0-1 values. The cumulative distribution
function (CDF’s), which is commonly chosen to represent 0-1 response models, is the logit
(logistic CDF) model and the probit (normal CDF) model. Logit and probit Models are the
convenient functional forms for models with binary endogenous variable (Johnston and
Dinardo, 1997). These two models are commonly used in studies involving qualitative
43
choices. To explain the behavior of dichotomous dependent variable we will have to use a
suitably chosen cumulative distribution function (CDF).
The logit model uses the cumulative logistic function. But this is not the only CDF that one
can use. In some applications the normal CDF has been found useful. The estimating model
that emerges from normal CDF is popularly known as the probit model (Gujarati, 1995). The
logistic and probit formulations are quite comparable; the chief difference being that the
logistic has slightly flatter tails that is the normal curve approaches the axis more quickly than
the logistic curve. Therefore, the choice between the two is one of mathematical convenience
and ready availability of computer programs (Gujarati, 1988).
3.4.3. The Tobit model
The study of marketing of teff through the cooperatives based up on dichotomous regression
models have attempted to explain only the probability of using the cooperative as marketing
agent or not rather than the extent and intensity of usage. Knowledge that a farmer is
marketing his teff through the cooperative may not provide much information about the
quantity of teff he/she marketed through the cooperative. A strictly dichotomous variable
often is not sufficient for examining the intensity of usage for such problems.
There is also a broad class of models that have both discrete and continuous parts. One
important model in this category is the Tobit2. Tobit is an extension of the Probit Model and it
is really one approach to dealing with the problem of censored data (Johnston and Dinardo,
1997). Some authors call such models Limited Dependent Variable Models because of the
restriction put on the values taken by the regressand (Gujarati, 1995).
Even though the Tobit Model is better than the Discrete Regression Model in explaining the
usage of a cooperative as marketing agent for farm produces and the intensity of usage, still it
2 Tobit Model was first studied by Tobin (1958). His Model was nick named the Tobit Model (Tobins Probit) by Goldberger (1964)
44
uses Limited Dependent Variables. It measures between 0 and continuous dependent
variables.
3.4.4. Specification of the Tobit model
The econometric model applied for analyzing factors influencing the marketing of teff
through the cooperatives is the Tobit model shown below in equation (4). This model was
chosen because it has an advantage over other discrete models (Logistic and Probit) in that; it
reveals both the probability of marketing through the cooperative and the intensity of
marketing.
Following Maddala (1992), Johnston and Dinardo (1997) and Green (2000), the Tobit model
can be defined as:
Yi* = βXi+ Ui i=1,2,…, 132 Eq (4)
Yi= Yi*if Yi > 0
Yi= 0 if Yi*< 0
Where,
Yi= the observed dependent variable, in this case a quintal of teff marketed through the
cooperative
Yi*= the latent variable which is not observable
Xi= vector of factors influencing the marketing of teff through the cooperative
βi= vector of unknown parameters
Ui= residuals that are independently and normally distributed with mean zero and a common
variance δ2
Note that the threshold value in the above model is zero. This is not a very restrictive
assumption, because the threshold value can be set to zero or assumed to be other value
(Green, 2000). The Tobit Model shown above is also called a Censored Regression Model
because it is possible to view the problem one where observations of Yi* at or below zero are
censored (Johnston and Dinardo, 1997 and Green, 2000).
45
The model parameters are estimated by maximizing the Tobit Likelihood Function of the
following form (Maddala, 1997).
∏∏≤∗∗
−
−=
00
1
ii Y
iiiii
Y
XF
XYfL
σβ
σβ
σφ
Eq (5)
Where f and F are respectively, the density function and cumulative distribution function of
Yi*, ∏yi*>0 means the product over those i for which yi*>0, and ∏yi*≤0 means the product
over those i for which yi*≤0.
An econometric software known as "LIMDEP" was employed to run the Tobit model. It may
not be sensible to interprete the coefficients of a Tobit in the same way as one interprets
coefficients in an uncensored linear model (Johnston and Dinardo, 1997 and Green, 2000).
Hence, one has to compute the derivatives of the estimated Tobit model to predict the effects
of changes in the exogenous variables.
As cited in Maddala (1997) and Johnston and Dinardo (1997), proposed the following
techniques to decompose the effects of explanatory variables into usage and intensity effects.
Thus, a change in X (explanatory variables) has two effects. It affects the conditional mean of
Yi* in the positive part of the distribution, and it affects the probability that the observation
will fall in that part of the distribution. Similar approach is used in this study.
1. The marginal effect of an explanatory variable on the expected value of the dependent
variable is: ( )( )
( ) i
i
i zFX
YEβ=
∂
∂ Eq (6)
Where, σβ iiX is denoted by z, following Maddala, (1997)
2. The change in the probability of using the cooperatives as marketing agent as an
independent variable Xi changes is:
( ) ( )
σβ i
i
zfX
zF=
∂
∂ Eq (7)
46
3. The change in usage intensity with respect to a change in an explanatory variable among
users is: ( )( )
( )( )
−−=
∂
∂ ∗ 2
10
zF
zf
zF
zfZ
X
Y
YE
i
i
i
i
βφ
Eq (8)
Where, F(z) is the cumulative normal distribution of z, f(z) is the value of the derivative of the
normal curve at a given point (i.e., unit normal density), z is the z score for the area under
normal curve, β is a vector of Tobit maximum likelihood (ML) estimates and σ is the standard
error of the error term.
Using descriptive statistics it is also possible to clearly compare and contrast different
characteristics of the sample households along with the econometric model. Hence,
descriptive statistics such as mean, percentage and standard deviation were computed to
analyze the collected data. T-test and χ2- test were also employed.
3.5. Hypothesis and Definition of Variables
In the course of identifying factors influencing the marketing of teff through the cooperative,
the main task is to analyze which factors influence the usage of the cooperative by the farmers
as marketing agent for their teff. Therefore, potential variables, which are supposed to
influence marketing of teff through the cooperative, will be explained next.
3.5.1. Dependent variable
The Tobit Model uses censored values as a dependent value. As observed in different
empirical studies, this variable can be expressed in terms of ratio, actual figure and
logarithmic form depending on the purpose of the study. For example, Klein et al. (1997)
used the amount of business conducted with several types of cooperatives. In this study, the
total quantity of teff (in quintal) the farmer marketed through the cooperative in 2004/5 was
taken as the dependent variable.
47
3.5.2. The Independent variables
Farmers' decision to market his teff through the cooperative was hypothesized to be
influenced by a combined effect of various factors such as household characteristics,
socioeconomic characteristics, cooperative characteristics and other institutional
characteristics in which both the farmer and the cooperative operate. Based on the brief
literature review, in this study a total of 17 variables were hypothesized to explain the
dependent variable. Brief explanation of the selected explanatory variables is presented
below.
District (DISTRICT): This is a dummy variable taking a value 1 if the district in which the
farmer found is Adaa Liben cooperative, 0 if he is in Lume cooperative. There is performance
variation among cooperatives in different place (Misra et al., 1993). Therefore, this variable is
expected to influence the marketing of teff through the cooperative positively or negatively
depending on the performance of the district in which the farmer found.
Education level (EDUCATION): It is a continuous variable and refers to the number of
years of formal schooling the farmer attended. The higher the education level, the better
would be the knowledge of the farmer towards the cooperative and acquire news and
education about the benefits of the cooperative easily (Kraenzle, 1989; Klien et al., 1997).
Hence, those farmers with higher formal education are in a better position to know the
benefits of cooperative and are more likely to market their teff through the cooperatives. So
this variable is expected to influence the marketing of teff through the cooperatives positively.
Family size (FAMILYSIZE): This variable is a continuous explanatory variable and refers
to the total number of family the household has in terms of adult equivalent (AE). It is
assumed that household with larger family size consume more of what is produced in the
house and little will remain to be marketed. Therefore, the variable expected to have negative
influence in marketing of teff through the cooperative.
48
Number of years of membership (MEMBERSHIP): This variable is a continuous variable
and it refers to number of years since the farmer has been the member of the cooperative.
Farmers having longer years of membership are in a better position to know the benefits of
the cooperative than farmers with shorter years of membership (Cain et al., 1989). In this
study, this variable is hypothesized to influence the marketing of teff through the cooperative
positively.
Off/non-farm income (ONFINC): It is a continuous variable. It refers to part of the total
amount of income measured in birr that is earned from activities which are related to
agriculture and activities which are not related to agriculture. There are two hypothesis
regarding this variable. The first is that farmers that are engaged in theses activities have little
time to consider alternative market outlets uses the cooperative as their marketing agent due
to its convenience. The second is that these activities help farmers to earn additional income.
This additional income improves the farmers’ financial position that in turn enables them to
invest in purchasing the needed amount of farm inputs especially fertilizer and renting land.
This increases the yield to be marketed. At a highest of level off-farm income, grain farmers
tend to use the cooperative more intensively (Klein et al., 1997). Therefore, in this study it is
hypothesized that off/non-farm income affects the marketing of teff through the cooperative
positively.
Position in the cooperative (POSITION): It is a dummy variable taking a value 1 if the farmer
has a position (in the management (board of director) or employment) in the cooperative, and 0 if
he is ordinary member. Having a position in the cooperative increases the attachment of the farmer
to the cooperative than the ordinary member and help to realize the benefits of the cooperative.
Thus, their usage of the cooperative as marketing agent is better than the ordinary member.
Therefore, having a position in the cooperative is expected to influence the marketing of teff
through the cooperative positively.
Farm size (FARMSIZE): This variable is a continuous variable and it refers to the total area of
farmland that a farmer owns in hectare. The usage of the cooperative as marketing agent requires
substantial economic resources of which land is the principal one (Wadsworth, 1991; Klein et al.,
49
1997). It is assumed that the larger the total area of the farmland the farmer owns, the higher
would be the output. Farmers with higher level of output expected to use the cooperative than
those who have not. Therefore, it is expected that this variable would have positive influence on
the marketing of teff through the cooperative.
Yield of teff (YIELD): This is a continuous variable and refers to amount of teff the farmer
obtained in quintal in the study year. It is assumed that the marketing of teff by the farmer is
positively related to the amount of output they get. The higher the output the farmer obtained, the
higher would be the amount marketed through the cooperative. Therefore, this variable is
expected to influence the marketing of teff through the cooperative positively.
Total livestock holding (TLSH): This variable is a continuous variable and refers to the total
number of livestock the household own in terms of TLU. It is assumed that household with
larger TLU have better economic strength and financial position to purchase sufficient
amount of fertilizer (Techane, 2002; Teferi, 2003) that boost his production of teff. Livestock
may also serve as a proxy for oxen ownership in the area, which is important for farm
operations especially in the production of teff. Therefore, this variable has positive association
with the usage of the cooperative as marketing agent for teff.
Cooperative price for teff (COOPP): This is a dummy variable taking a value 1 if the
cooperative price for the farmer’s teff is similar or better than other marketing agents in the
area and, 0 otherwise. The price effect is one form of cooperative effect that the cooperative
passes on the farmer’s economy (Chukwu, 1990). Therefore, if the cooperative charge
competitive price for teff in the area, the farmers market their teff through the cooperative
(Wilkins and Stafford, 1982; Fulton and Adamowicz, 1993; Misra et al., 1993; Klein et al.,
1997). Therefore, cooperative price influence the marketing of teff through the cooperative
positively.
Patronage refund (PATREF): It is a continuous explanatory variable and refers to the
amount of money the farmer receives from the surplus the cooperative appropriate in
proportion with his/her use of the cooperative (patronage). It is assumed that farmers will be
50
encouraged to market more of his teff through the cooperative if there is surplus appropriation
in the form of patronage refund (Black and Knutson, 1985; Fulton and Adamowicz, 1993).
Thus, patronage refund assumed to influence the marketing of teff through the cooperative
positively.
Credit (CREDIT): This is a dummy variable which takes a value 1 if the farmer obtained
credit from other micro finance institution operating in the area, 0 otherwise. Credit helps the
farmer in paying the prepayment to the cooperative in order to get the sufficient amount of
fertilizer. It also helps in renting land and purchasing other inputs that increase production. In
general, it plays an important role in using fertilizer (Techane, 2002; Teferi, 2003) and other
inputs that increase productivity. This in turn leads to an increase in the amount to be
marketed. Therefore, it is expected that this variable would have positive influence on the
marketing of teff through the cooperative.
Availability of other marketing agents (OMKAG): This is a dummy variable taking a value
1 if there are other marketing agents in the area of the farmer at a distance less than the
cooperative and doing similar activity (purchasing teff), 0 otherwise. Farmers will get
alternative market outlet to sell their teff if there are other marketing agents in their area.
Cooperatives face market competition if there are other marketing agents in the area of the
farmer performing similar activity with them (Bishop and McConnen, 1999). Therefore, this
variable is expected to influence the marketing of teff through the cooperative negatively.
Availability of other services (AOS): This is a dummy variable taking a value 1 if the farmer
gets other services from the cooperative besides supplying inputs, purchasing farm products
and extending credit, 0 otherwise. Farmers’ usage and connection with the cooperative
increases if they are beneficiary from different services it extends (Wilkins and Stafford,
1982; Black and Knutson, 1985; Misra et al., 1993; Fulton and Adamowicz, 1993; Klein et
al., 1997). Therefore, this variable is expected to influence the marketing of teff through the
cooperative positively.
51
Fertilizer credit (FERCREDIT): It is a continuous variable and refers to the amount of
fertilizer credit (in birr) the cooperative extended for the farmer. This credit is paid to the
cooperative in installment. Farmers are assumed to sell their teff to the cooperative and pay
the credit they get for fertilizer there in the cooperative. Black and Knutson (1985) Texas
survey showed credit is one of the most important reasons for the cooperative patronage.
Thus, fertilizer credit is hypothesized to influence the usage of the cooperative as marketing
agent for teff positively.
Distance of the cooperative from the farmer house (DCFH): It is a continuous variable
measured in hours. It refers to the distance of the cooperative from the farmer house. The
proximity of the cooperative for the farmer house reduces the cost of time and labor that the
farmer spent in searching for a buyer for his teff. The other advantage is that as the farmer is
close (near) to the cooperative, they will have more knowledge about the cooperative and its
benefits (Bishop and McConnen, 1999). Therefore, in this study the distance of the
cooperative from the farmer house is expected to influence the marketing of teff through the
cooperative negatively.
Distance of the district market (main market) from the farmer house (DDMKT): It is a
continuous variable measured in hours and refers to distance of the farmer's house from the
district (main) market. The proximity of district (main) market to the farmer’s house shows
access to the main market system to sell output (Legesse, 2001). It also shows access to easy
transportation facility to sell farm produces in this market. Thus, this variable is expected to
influence the marketing of teff through the cooperative positively.
52
4. RESULTS AND DISCUSSION
This chapter presents the findings from ratio, descriptive and econometric analysis. The ratio
analysis made use three ratios i.e. current, debt and return on total asset to examine the
performance of the cooperatives found in Adaa Liben and Lume districts. And the descriptive
analysis made use of tools such as mean and percentage. T-test and χ2- test were also
employed. Econometric analysis was employed to identify the most important factors that
influence the marketing of teff through the cooperatives.
4.1. Ratio Analysis
4.1.1. Liquidity analysis
The satisfactory rate of current ratio that is accepted by most lenders as condition for granting
or continuing commercial loan is 2.00. With this yardstick when the reference years (2001/2
and 2002/3) are observed, all cooperatives in the two districts performed below the desirable
standard. In 2001/2 the average current ratio for the fifteen selected cooperatives in the two
districts was 1.11 (Table 5). The highest ratio was 1.36, which was scored by Kolba and the
lowest was 1.00, which was scored by Gicegerbabo. In 2002/3 the average current ratio was
1.02 (Table 5). The highest ratio was 1.16, which was scored by Adulala and Kolba and the
lowest ratio was 0.97, which was scored Gicegerbabo. In this year there were four
cooperatives in Adaa Liben district, which in general couldn’t liquidate i.e. their ratios were
below 1.00.
When we observe the performance of the cooperatives, their liquidity ratio decreased in
2002/3 as compared to the 2001/2 except Adulala. This implies that their current liabilities are
rising faster than their current assets. Though the cooperatives got credit from financial
institution in most cases the government being their collateral, the ability to get cash (credit)
by their own to meet their short-term demand for money (to purchase farmers’ teff) is
53
endangered. Lenders may not be willing to extend short-term loan to these cooperatives i.e.
lenders require current ratio to remain at or above 2.00 as a condition for granting loan.
Table 5. Financial ratios of the multi-purpose agricultural cooperatives
Cooperatives CR
2001/2
CR
2002/3
DR
2001/2
DR
2002/3
ROTA
2001/2
ROTA
2002/3
Ude 1 . 315 1 . 061 0.718 0.830 - 0 .021 -0.002
Ka j ima 1 . 081 1 . 068 0.858 0 . 882 0.004 0.006
Ka l i t y 1 . 080 1 . 012 0.919 0 . 963 0.020 0.013
Dankaka 1 . 073 0 . 977 0.862 0 . 967 -0.002 0.007
G i cege rbabo 1 . 003 0 . 965 0.963 0 . 976 -0.010 0.031
H id i 1 . 028 0 . 997 0.963 0 . 964 -0.023 0.013
Ka t a j a r a 1 . 033 0 . 986 0.958 0 . 992 0.021 0.026
Adu l a l a 1 . 020 1 . 160 0.914 0 . 875 -0.026 -0.010
D i r e 1 . 135 1 . 058 0.880 0 . 911 0.028 0.007
Dukem 1 . 176 1 . 066 0.843 0 . 888 0.012 0.011
Ye re r s i l a s s i e 1 . 094 1 . 136 0.887 0 . 844 0.011 0.016
Ko lba 1 . 357 1 . 160 0.827 0 . 737 0.049 0.044
Tede 1 . 007 1 . 001 0.974 0 . 967 0.047 0.031
Tu l u r ea 1 . 142 1 . 107 0.857 0 . 849 0.045 0.002
Dekebo ra 1 . 124 1 . 071 0.868 0 . 869 0.007 0.037
Ave r age 1 . 112 1.015 0.886 0 . 901 0 . 012 0 . 015
Source: own computation
4.1.2. Financial leverage management analysis
All of the cooperatives in the two districts used financial leverage (finances a portion of assets
with debts). The cooperatives under investigation in the two districts financed more of their
total asset with creditors’ fund. In 2001/2 the average debt-asset ratio was 88.6% (Table 5).
54
This implies that 88.6% of the total asset of the cooperatives was financed with creditors’
fund. In 2002/3 the average debt-asset ratio increased to 90.1%. Only three of the Lume
district and two of Adaa Liben district cooperatives has shown slight decrease in debt-asset
ratio in 2002/3 as compared to the previous year.
When we observe the two years data of how the cooperatives were financed, creditors have
supplied on overage more than 85% of the cooperatives finance. The smaller the proportion
(in most cases <50%) of the total asset financed by the creditors, the smaller the risk that the
firm unable to pay its debt (William et al., 2003). Having higher proportion of asset financed
by the creditors fund may lead the cooperatives to the risk of bankruptcy if the management
seek to increase the debt any further by borrowing additional funds.
4.1.3. Profitability analysis
The profitability ratios demonstrate how well the firm is making investment and financing
decisions. According to William et al. (2003) firms need to earn return on their asset that
enables them to pay the interest of the money they borrowed i.e. they need to have return on
their asset which is equal or better than the interest rate of the money they borrowed.
One can observe from Table 5, the profitability ratios of the cooperatives under investigation
were so much low. When we look at the earning of the cooperatives under investigation in
2001/2, the highest was 4.9%, which was scored by Kolba and the lowest was -2.6%, which
was scored by Adulala. In 2002/3 the highest ratio was 4.4%, which was scored by Kolba and
the lowest was -1.0%, which was scored by Adulala. In 2001/2 the average profitability of the
cooperatives under investigation was 1.2% and five of the cooperatives were not profitable. In
2002/3 the average ratio increased to 1.5% and only two of the cooperatives were not
profitable. The average profitability ratio for the two years was 1.3%.
Even though there was improvement in profitability ratio in 2002/3, the cooperatives had less
effective operation as the profitability ratio show combined effects of liquidity, asset
management and financial management. Even they couldn’t achieve the profitability ratio
55
which is equal or better than the interest rate (7%) with which they borrowed money from the
financial institutions. The plausible reasons for the difference in profitability among the
cooperative lies on how effectively the cooperative management is generating profit on sales,
total assets, money they borrowed and most importantly members’ investment (share capital).
4.2. Descriptive Analysis
In order to understand the socioeconomic, the cooperatives and farmers attitude towards them
and other institutional characteristics of the user and non-user farmers of the cooperative as
marketing agent for their teff, descriptive analysis is summarized and discussed.
4.2.1. Household characteristics
Out of the sample farmers interviewed, 58.3% of the farmers marketed teff through the
cooperatives (users of the cooperative as their marketing agent for their teff) while 41.7% of
the farmers didn’t market teff through the cooperatives (non-users of the cooperative as their
marketing agent for their teff) in the year 2004/5.
The average age of the sample farmers was about 47.06 years. The corresponding figure for
the cooperative users and non-users was about 48.64 and 44.85 years respectively (Table 6).
There is statistical significant difference between cooperative users and non-users in age. The
users are more aged than the non-users.
The average family size of the sample households was 6.75 persons, with maximum and
minimum family size of 12 persons and 1 person, respectively. The average family size of the
sample households that used the cooperative was 6.65 persons, with maximum and minimum
family size of 11 and 2 persons, respectively. The corresponding figure for the non-users was
6.89 persons, with maximum and minimum family size of 12 persons and 1 person,
56
respectively. The average number of children who were less than 15 years old was 3.37
persons and it was 3.34 and 3.58 persons for the users and non-users, respectively.
Table 6. Characteristics of the sample households
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Characteristic
Mean St. Dev Mean St.Dev
T-value
Mean St.Dev
.
Age (year) 48.64 13.83 44.85 11.48 1.66* 47.06 12.99
Average family
size (number)
6.65
2.38
6.89
2.56
0.56
6.75
2.45
Children <15
(number)
3.34
1.51
3.58
1.89
0.79
3.44
1.67
15-64 years
(number)
3.41
1.48
3.39
1.74
-0.08
3.40
1.59
> 64 years
(number)
1.09
0.30
1.00
-
-0.51
1.07
0.27
Active labor
(man-equiv.)
3.36
1.26
3.22
1.49
-0.58
3.30
1.36
Source: Computed from the field survey data.
* Represent level of significance at less than 10%
Based on the assumption of CSA (1996), the average number of economically active family
members (15-64) was 3.40 persons whereas the average number of elderly (>64) family
member was 1.07 persons for the sample households. The average number of economically
active family members (15-64) and average number of elderly (>64) family members for the
users of the cooperatives was 3.41 and 1.09 persons, respectively. The corresponding figure
for the non-users was 3.39 persons and 1.00 person, respectively.
57
Economically active family labour force (known as man equivalent) was calculated for the
sample households. The average number of active labour force for the whole sample was 3.30
ME (Table 6). If this result is compared with the average family size (6.75), on the average
only 48.89% of the family member provides labour force and actively engaged in an
economic activity. Economically active family labour force (man-equivalent) for the
cooperative users was 3.36 ME and the figure for the non-users was 3.22 ME (Table 6). If
these results are compared with the average family sizes of the two groups (6.65 and 6.89), on
the average only 50.53% of the cooperative users and 46.73% of the cooperative non-users
family member provides labour force and actively engaged in an economic activity.
Out of the total sample farmers studied 96.2% were male headed and 3.8% were female
headed (Table 7). The majority of the members of the cooperatives in the study area are male.
Most of the sample farmers (90.9%) are married while 0.8%, 3% and 5.3% are single,
divorced and widowed, respectively.
Table 7. Distribution of the sample farmers by sex of the household head
Users
(n=77)
Non-users
(n=55)
Total sample
(n=132)
Sex
n % n % n %
χ2-value
Male 73 94.8 54 98.2 127 96.2 1.00
Female 4 5.2 1 1.8 5 3.8
Source: Computed from the field survey data.
The average number of years of formal schooling completed by the sample farmers was 3.00
years. Among the sample farmers, 9.9% had not received any education, while 43.9% could
only read and write. The rest attended from elementary to high school level. More
specifically, 22.7%, 10.6% and 12.9% of the sample farmers had attended elementary school,
junior secondary and high school, respectively (Table 8).
58
Table 8. Educational status of the household head
Users
(n=77)
Non-users
(n=55)
Total sample
(n=132)
Educational Status
n % n % n %
Illiterate 7 9.1 6 10.9 13 9.9
Read and Write 33 42.8 25 45.5 58 43.9
Elementary (1-6) 20 26.0 10 18.2 30 22.7
Junior (7-8) 8 10.4 6 10.9 14 10.6
High School (9-12) 9 11.7 8 14.5 17 12.9
Mean 2.97 3.09 3.00
T-value 0.11
Source: Computed from the field survey data
The average years of membership of the sample farmers in the cooperative was 21.61 years,
with maximum and minimum years of membership of 29 years and 1 year, respectively
(Table 11). The average years of membership for users of the cooperative was 22.38 years
while the corresponding figure for non-users was 20.55 years.
Table 9. Characteristic of the sample farmers by years of membership
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
Membership
(Years)
22.38
7.69
20.55
8.40
-1.30
21.61
8.02
Source: Computed from the field survey data.
As to their farming experience, the average years of farm experience of the sample farmers
was 26.27 years with maximum and minimum years of farming experience of 65 and 2 years,
59
respectively (Table 10). The cooperative users had on average 27.95 years of farming
experience whereas the non-users had on average 23.93 years of farming experience. There is
statistical significant difference between cooperative users and non-users in years of farming
experience. The users have more years of farming experience than the non–users.
Table 10. Characteristic of the sample farmers by years of farming experience
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
Farming experience
(Years)
27.95
13.77
23.93
11.73
-1.76*
21.61
13.07
Source: Computed from the field survey data
* Represent level of significance at less than 10%
Out of the total households interviewed, 65.2% involved in different off/non-farm activities
and generated an average estimated income of birr 496.42 (Table 11). The cooperative users
generated an average estimated income of birr 552.62 from off/non-farm activities whereas
the non-users generated an average estimated income of birr 417.75 from these activities.
Table 11. Characteristic of the sample farmers by income from off/non-farm activities
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-
value
Mean St.Dev
Income (birr) 552.62 821.59 417.75 642.14 -1.02 496.42 3.03
Source: Computed from the field survey data
60
4.2.2. Land holding
Land is the basic asset of the sample farmers. In the study area on the average 2.11 ha of land
was available per household for cultivation. The corresponding figure for cooperative users
and non-users was 2.25 ha and 1.92 ha, respectively (Table 12). There is statistically
significant difference in land holding size between the users and non-users. The available land
per household for cultivation was greater for users than the non-users.
Table 12. Distribution of the sample farmers by the available land holdings
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
Holding Size (ha)
2.25
1.01
1.92
0.94
-1.94*
2.11
0.99
Source: Computed from the field survey data.
* Represent level of significance at less than 10%
On the other hand 53.8% of the sample farmers involved in renting systems indicating that
sample farmers in the study area derive a part of their income from contractual land tenure
arrangements (Table 13). Accordingly those engaged in rented-in and rented-out being 40.9%
and 12.9% respectively, having an average size of 1.39 ha and 0.93 ha, respectively. The basic
reasons for renting-in land were shortage of land, availability of extra labor in the house and
the desire to have better economic position whereas aged farmers who are unable to make use
of their farm land and shortage of farm implements and inputs were found to be the basic
reasons for renting-out land.
61
Table 13. Distribution of the sample farmers by land rent type
Rented-in Land Rented-out Land Farmer type
n % n %
Users (n=77) 29 37.7 11 14.3
Non-users (n=55) 25 45.5 6 10.9
Total sample (n=132) 54 40.9 17 12.9
Mean size (ha) 1.39 0.93
Source: Computed from the field survey data.
4.2.3. Major crops produced and yield
Adaa Liben and Lume districts are among the most known agriculturally rich districts and
they are popular in farming activities especially in crop production. The sample farmers grew
cereals and pulses as main food crops and for sale to meet their cash requirements. Teff was
produced by the sample farmers for the purpose of both consumption and sale. It held the
largest share in terms of cultivated area (62.5 %) (Table 14) and yield obtained from crops
(58.5 %) (Table 15).
The average area used by the sample farmers for the production of teff was 1.65 ha. The
sample farmers that marketed teff through the cooperatives used an average area of 1.61 ha.
The corresponding figure for the non-users was 1.72 ha (Table 14).
62
Table 14. Distribution of the sample farmers by the area of major crops
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Type of crop
Area
(ha)
St.Dev Area
(ha)
St.Dev
T-value
Area
(ha)
St.Dev
Teff 1.61 1.00 1.72 1.39 0.52 1.65 1.17
Wheat 0.49 0.41 0.39 0.30 -1.20 0.45 0.37
Bean 0.09 0.14 0.10 0.17 -0.65 0.09 0.15
Lentil 0.15 0.14 0.09 0.12 -0.11 0.12 0.13
Pea 0.07 0.25 0.08 0.18 1.52 0.07 0.22
Others 0.18 0.22 0.18 0.30 0.82 0.26 0.26
Source: Computed from the field survey data
The average yield of teff obtained by the sample farmers was 15.80 qt. The cooperative users
obtained an average yield of teff of 15.44 qt whereas the non-users obtained an average yield
of 16.30 qt (Table 15).
The sample farmers also produced other crops besides teff. Wheat was produced by 90.9% of
the sample farmers. The corresponding percentage of farmers that produced bean, lentil, pea
and other crops was 2%, 35.0%, 23.5% and 53.3%, respectively. The average area used for
the production of wheat, bean, lentil, pea and other crops was 45, 0.09, 0.12, 0.07 and 0.26 ha
respectively (Table 14).
63
Table 15. Distribution of the sample farmers by yield of major crops
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Type of crop
Yield
(qt)
St.Dev Yield
(qt)
St.Dev
T-value
Yield
(qt)
St.Dev
Teff 15.44 10.50 16.30 16.46 0.37 15.80 13.26
Wheat 6.78 5.2 4.95 4.10 -1.85* 6.02 4.85
Bean 0.96 1.37 1.10 1.14 -0.28 1.02 1.28
Lentil 1.63 1.79 1.14 1.65 0.37 1.42 1.73
Pea 0.67 2.85 0.55 2.38 -0.28 0.62 2.67
Others 2.16 3.07 2.01 2.87 0.20 2.11 2.98
Source: Computed from the field survey data
* Represent level of significance at less than 10%
The yield obtained from wheat, bean, lentil, pea and other crops was 6.02, 1.02, 1.42, 0.62
and 2.11 qt respectively (Table 15). There is statistically significant difference between
cooperative users and non-users in the yield obtained from wheat. The users obtained greater
yield from wheat when compared to the non-users.
64
10.61
28.79
25.00
17.42
6.06
12.12
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
1-5 6-10 11-15 16-20 21-25 >25
yield of teff in quintal
Percentage of the respondents
percentageof therespondents
Figure 3. Yield of teff in quintal by sample farmers
4.2.4. Livestock holding
Farm animals serve several purposes in rural economy. They are sources of cash income,
draught power and animal dung (as an organic fertilizer and fuel). In addition farm animals
serve as a measure of wealth and prestige in rural areas.
Based on Storck et. al. (1991), the livestock population number was converted into Tropical
Livestock Unit (TLU), so as to facilitate comparison among the sample farmers. On the
average a household had 4.89 TLU (Table 16). The average holding of livestock of the
cooperative users was 4.84 TLU. The corresponding figure for the non-users was 4.96 TLU.
65
Table 16. Livestock ownership of the sample farmers
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Particulars
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
TLU 4.84 2.75 4.96 3.40 0.23 4.89 3.03
Oxen 2.55 1.36 2.60 1.55 0.20 2.57 1.43
Cows 1.21 0.14 1.37 0.73 1.11 1.28 0.63
Calf 1.47 0.54 1.57 0.79 0.48 1.52 0.81
Heifer 1.16 0.37 1.38 0.51 1.38 1.25 0.44
Sheep 3.29 2.23 4.36 2.16 1.22 3.76 2.22
Goat 4.00 2.05 3.14 1.77 -0.89 3.65 1.93
Horses 1.00 - 1.00 - - 1.00 -
Mules 1.00 - 1.00 - - 1.00 -
Donkey 1.77 0.99 1.81 1.07 0.18 1.79 1.02
Source: Computed from the field survey data.
The cooperative users who owned no ox, one ox, two oxen and more than two oxen
represented 2.6%, 16.9%, 49.4% and 31.2% of the sample farmers respectively (Table 17).
The corresponding figures for the non-users were 9.1%, 14.5%, 50.9% and 25.5%
respectively. The figures show that the great majority of the sample farmers (about 78.8%)
owned at least a pair of oxen.
66
Table 17. Distribution of the sample farmers by oxen ownership
Farm oxen size (heads) Users
(n=77)
Non-users
(n=55)
Total sample
(n=132)
n % n % n %
No ox 2 2.6 5 9.1 7 5.3
One ox 13 16.9 8 14.5 21 15.9
Own 2 oxen 38 49.4 28 50.9 66 50.0
>2 oxen 47 31.2 14 25.5 51 28.8
Source: Computed from the field survey data
4.2.5. The cooperatives
All of the cooperatives under study were multi-purpose agricultural cooperatives. They render
the services of marketing of farm produces, supplying farm inputs and extending credit (kind
credit i.e. fertilizer in credit) for the farmers. Some of the cooperatives render other services
such as mill, tractor services etc. in addition to the above services.
The cooperatives primarily purchase teff as it is primarily produced and sold by most of the
farmers in the study area for their cash requirement. The cooperatives pay cash for the farmers
on delivery. The duration of their purchasing ranges from December to May. In 2003/4, 53%
of the sample farmers marketed teff through the cooperatives. This figure increased to 58.3%
in 2004/5.
Out of the sample farmers, 58.3% marketed teff through the cooperatives. These farmers were
asked for the important attributes of cooperative purchasing of teff in the area. And 29.9% of
the farmers pointed out that selling to the cooperative has an advantage of genuine
measurement (no cheating in the weight) and 37.7% of the farmers pointed out both genuine
67
measurement and patronage refund3 as important attributes. Genuine measurement and
introduction of desirable competition were pointed out by 14.3% of the farmers. The
corresponding figures for patronage refund and introduction of desirable competition were
2.6% and 6.5% respectively.
The cooperatives were a source of fertilizer for 94.7% of the sample farmers. The average
quantity of DAP and Urea taken from the cooperatives were 4.64 and 2.39 bags respectively.
The sample farmers that used the cooperative as their marketing agent for their teff took an
average quantity of 4.83 bags of DAP (Table 18) and 2.52 bags of Urea (Table 19). The
corresponding figures for the non-users were 4.36 bags of DAP and 2.20 bags of Urea.
Table 18. Quantity of DAP taken by the sample farmers from the cooperatives
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
DAP (bags) 4.83 3.15 4.36 3.15 -0.84 4.64 3.14
Source: Computed from the field survey data
Out of the sample farmers, 81.8% of the farmers used other farm inputs such as pesticide,
herbicide and improved seeds. The cooperatives were a source of these farm inputs for 56.1%
of the sample farmers.
3 Patronage refund is a surplus distributed to members in proportion to the patronage/turnover of the individual
member with the cooperative.
68
Table 19. Quantity of Urea taken by the sample farmers from the cooperatives
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
Urea (bags) 2.52 1.59 2.20 1.63 -1.13 2.39 1.60
Source: Computed from the field survey data
Credit is very important to resource poor farmers who cannot finance agricultural input
especially fertilizer from their own savings. The majority of the sample farmers (89.3%)
couldn’t purchase the quantity of fertilizer they need without credit. The cooperative extended
fertilizer in credit for 94.7% of the sample farmers. The credit was extended with
preconditions. The preconditions were membership, personal guarantee and certain amount of
prepayment. The farmers got an average 696.00 birr of fertilizer in credit from the
cooperatives (Table 20). Though the prepayment differed from cooperative to cooperative,
the farmers paid an average prepayment of 422.39 birr to get fertilizer in credit. The farmers
that used the cooperative as their marketing agents received an average 704.38 birr of
fertilizer in credit and the corresponding figure for the non-users was 684.27 birr of fertilizer
in credit. The reason for the sample farmers (99.2%) taking fertilizer from the cooperative
was getting it in credit.
Table 20. Distribution of the sample farmers by fertilizer credit extended from the
cooperatives
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Mean St.Dev Mean St.Dev
T-value
Mean St.Dev
Fertilizer credit
(birr)
704.38
455.77
684.27
607.44
-0.22
696.00
522.22
Source: Computed from the field survey data
69
There were also other micro finance institutions extending credit in the study area. The
Oromiya saving and credit S.C., Buussa Gonofaa micro-financing S.C. and Gasha micro-
financing S.C. were operating in the study area. Out of the sample farmers, 45.5% received
credit from these sources for the purpose of prepayment, fattening livestock, contracting land
and ox and for other social obligations. But the interest rate with which these institutions
extended credit was so much high when compared to the interest rate the cooperatives charge
(7%). For example, Oromiya saving and credit S.C., from which the majority of the sample
farmers took credit, charge an interest rate of 11.5% and this was the minimum interest rate
charged by the micro finance institution operating in the area. In addition to this, there are
restrictive procedures to get credit from these sources.
Besides supplying farm inputs, purchasing farm produces and extending credit, some
cooperative provide other services to the farmers. The cooperatives gave tractor service, mill
service, and other services. Out of the sample farmers, 41.7% were beneficiary from these
services. The corresponding figures for those that used the cooperative as their marketing
agent and for those that didn’t use were 55.8% and 21.8% respectively (Table 22). There is
statistically significant difference between cooperative users and non-users in getting these
services. The significant χ2 test indicates that more of the sample farmers who used the
cooperative as their marketing agents were beneficiary from the services mentioned above.
Table 21. Distribution of the sample farmers by other services from the cooperatives
Users
(n=77)
Non users
(n=55)
Total sample
(n=132)
Other service
n % n % n %
No 34 44.2 43 78.2 77 58.3
Yes 43 55.8 12 21.8 55 41.7
χ2-value 15.28***
Source: Computed from the field survey data
*** Represent level of significance at less than 1%.
70
In addition to the economic effects, there are also social effects that the cooperative brought in
the area. Community spirit, democratic way of decision-making in the cooperative, which is
one of the internationally recognized principles of the cooperative, and reduction of
exploitation of the farmers by moneylenders are among the effects. Out of the sample farmers,
81.8% recognized that they feel sense of community spirit by joining the cooperative, 40.2%
also learned the democratic way of decision making, and 69.7% recognized that the
cooperative (by extending fertilizer in credit) mitigate their exploitation by money lenders.
The type and extent of educational activities of the cooperatives in the study area was weak.
Most of the cooperatives gave education to the farmers once in the year. Continuous
education of the farmers help equip the farmers with the skill, knowledge and confidence to
enable them use, participate in and control the cooperative more effectively and to be more
cooperators. Out of the sample farmers, 51.5% got education from their cooperative in prior
year of this study and the corresponding figure for users and non-users were 53.2% and 49.1%
respectively (Table 23). There is no statistically significant difference between cooperative
users and non-users in getting education from the cooperative. Out of those sample farmers
that got education from the cooperative, 97.1% got education on the benefits of the
cooperative, 75.4% on the members’ commitment to the cooperative and 12.9% on principles
of the cooperative.
Table 22. Distribution of the sample farmers by education from the cooperatives
Users
(n=77)
Non-users
(n=55)
Total sample
(n=132)
Education
n % n % n %
No 36 46.8 28 50.9 64 48.5
Yes 41 53.2 27 49.1 68 51.5
χ2-value 0.22
Source: Computed from the field survey data
71
Most of the sample farmers (93.2%) feel that the cooperative didn’t solve their major common
problems currently (Table 24). These farmers were asked to rank their major common
problems and 92.4% of the farmers raised the supply of household consumable items such as
salt, soap, cloths etc as their major common problem to be solved by the cooperatives. Some
of the sample farmers mentioned that they sell their farm produces in the district markets in
search for these items there. The cooperatives were supplying these items in Derg regime and
the farmers need the cooperatives to resume this activity. The farmers that raised credit in
cash and inadequate supply of other farm inputs (pesticide, herbicide and improved seed) as
their major common problem were 85.3% and 31.8% respectively. Most of the farmers also
raised the price of fertilizer, which is beyond the capacity of the cooperatives, as a problem.
Table 23. Distribution of the sample farmers by perception on the current performance of the
cooperatives
Users
(n=77)
Non-users
(n=55)
Total sample
(n=132)
Current
Performance
n % n % n %
Not good 74 91.6 49 89.1 123 93.2
Good 3 3.9 6 6.9 9 6.8
χ2-value 2.48
Source: Computed from the field survey data
More than half of the sample farmers (59.8%) believed that the cooperatives will enable them
to overcome their major common problems in the future whereas 40.2% of the sample farmers
don’t think so (Table 24). Out of these pessimist farmers, 84.9% mentioned lack of
responsibility for the common work as the first reason for not the cooperative enable them to
overcome their major common problems, 22.1% raised the misuse of the cooperative by
management body and other employees in the cooperative and 26.6% raised the lack of
commitment of the members for the cooperative as reasons.
72
Table 24. Distribution of sample farmers by perception on future performance of the
cooperatives
Future
Performance
Users
(n=77)
Non-users
(n=55)
Total sample
(n=132)
n % n % n %
Not good 37 48.1 16 29.1 53 40.2
Good 40 51.9 39 70.9 79 59.8
χ2-value 4.80*
Source: Computed from the field survey data
** Represent level of significance at 5%
The significant χ2 test indicates that despite not participated in using the cooperative as their
marketing agent, the non-users have better hope on the cooperatives in enabling them to
overcome their major common problems in the future. In general, most of the sample farmers
have hope on the cooperatives in improving their life if the cooperatives organized and
managed properly.
All the sample farmers agreed that the cooperatives need improvement in their performance.
And 74.2% of the sample farmers were willing to contribute money to improve the
performance of the cooperatives and 25.8% of the sample farmers were not willing to
contribute due to various reasons. The first reason (for 70.6% of the sample farmers) that was
given for not contributing was distrust in the management body of the cooperatives. The other
reason (for 29.4% of the sample farmers) was inability to contribute.
All of the sample farmers want to continue their membership for the reason of supply of
fertilizer in credit. The other reason that is given by the farmers (56.8%) for continuation was
the purchase of the farm produces by the cooperatives. Some farmers (10.6%) mentioned that
the other services and benefits besides supplying of inputs and purchasing of farm produces
73
make them continue membership. None of the sample farmers give external pressure as
reason for continuation of membership.
4.3. Results from the Tobit Econometric Model
Entering the data obtained into the program LIMDEP version 7, imported from SPSS 10,
Tobit model was analyzed. Prior to the analysis, the explanatory variables were checked for
multicollinearity and hetroscedasticity.
Very often data we use in regression analysis cannot give decisive answers to the question we
pose. This is because the standard errors are very high or the t-ratios are very low. This
situation occurs when the explanatory variables display little variation and/or high
intercorrelations. The situation where the explanatory variables are highly intercorrelated is
referred to as Multicollinearity (Maddala, 1992).
Before running the model all the hypothesized explanatory variables were checked for the
existence of multicollinearity problem. There are two measures that are often suggested to test
the existence of multicollinearity. These are: Variance Inflation Factor (VIF) for association
among the continuous explanatory variables and Contingency Coefficients (CC) for dummy
variables.
According to Maddala (1992), VIF can be defined as: VIF (Xi) = 1/1-R2 where Ri
2 is the
squared multiple correlation coefficient between Xi and the other explanatory variables. A
statistical package known as SPSS 10 was employed to compute the VIF values. Once R2
values were obtained the VIF values can be computed using the formula. The VIF values
displayed in Appendix 1 have shown that all the continuous explanatory variables have no
serious multicollinearity problem. Similarly, contingency coefficients were computed for
dummy variables. The values of the contingency coefficients were also shown in Appendix 2.
Based on the above test both the hypothesized continuous and dummy variables were retained
in the model.
74
One of the assumptions in regression analysis is that the errors Ui have a common variance σ2.
If the errors do not have a constant variance we say they are hetroscedastic (Maddala, 1992).
In the general linear model, OLS estimates are consistent but not efficient when the
disturbances are hetroscedastic. In the case of the limited dependent variable Models (such as
Tobit), the estimate of the corresponding regression coefficient is upward biased in the
presence of hetroscedasticity. But nothing can be said about the other coefficients and the
direction of the bias. It is more practicable to make some reasonable assumptions about the
nature of hetrotcedasticity and estimate the model than just to say that Maximum Likelihood
Estimates are inconsistent if hetroscedesticity is ignored (Maddala, 1997).
In this study hetroscedasticity was tested for all variables by running hetroscedastic Tobit
using an Econometric Software (LIMDEP). There was no serious problem of
hetroscedasticity in the model. And hence all the important variables were included in the
analysis of marginal effect and marketing through the cooperative probability in the present
study.
4.3.1. Factors influencing the marketing of teff through the cooperatives
The estimates of parameters of the variables expected to influence the marketing of teff
through the cooperative are displayed on Table 26. Seventeen explanatory variables of which
6 are dummy variables were taken for the analysis. The result of the model analysis showed
that 10 variables were found significant. The impact of these variables on the dependent
variable is discussed below.
District (DISTRICT) is significant at 10% level showing that farmers in Lume district more
used their cooperative as marketing agent for their teff than farmers in Adaa Liben district.
Though the cooperatives in the two districts are working in a homogeneous agro-ecological
environment, it was observed during data collection that the cooperatives in Lume district are
well organized than the Adaa Liben in terms of provision of different services and benefits,
asset etc. Hence, these enabled them to perform in relatively better position in being
marketing agent for their farmers. Had the farmer been in Lume district cooperatives, the
75
probability of marketing of teff through the cooperative and its intensity increases by 0.11 %.
Misra et al. (1993) also found that there is performance variation among dairy marketing
cooperatives in different places in United States.
Position in the cooperative (POSITION) influenced positively the probability of marketing
and marketing intensity of teff through the cooperative (significant at 1%). Having a position
(in the management (board of director) or employment) in the cooperative increases the
probability of marketing of teff through the cooperative and its intensity by 0.23%. Having
position in the cooperative increases the attachment of the farmer to the cooperative than the
ordinary members and helps them to realize the benefits of the cooperative. So their
participation in the marketing of teff through the cooperative is better than the ordinary
members.
Family size (FAMILYSIZE) influenced negatively the probability of marketing and
marketing intensity of teff through the cooperative (significant at 10%). As the family size
increases by one adult equivalent (AE), the probability of marketing of teff through the
cooperative and its intensity decreases by 0.13%. This result shows that households with
larger family size consume more of what is produced in the house and small amount is left to
be marketed through the cooperatives.
Yield of teff (YIELD) influenced positively the marketing of teff through the cooperative and
its intensity as expected by the hypothesis (significant at 5%). Each additional quintal of teff
produced increases the probability of marketing of teff through the cooperative and its
intensity by 0.16%. The implication is that farmers’ usage of the cooperative as marketing
agent is positively related to the yield obtained.
Farm size (FARMSIZE) influenced the marketing of teff through the cooperatives and its
intensity positively (significant at 10%). Each additional hectare of land increases the
probability of marketing of teff through the cooperative and its intensity by 0.13%. The
implication is that farmers with larger farm size more used the cooperative as marketing agent
76
than farmers with smaller farm size. Wadsworth (1991) and Klein et al. (1997) also found that
farm size influences the usage of the cooperative.
Cooperative price for teff (COOPP) influenced the marketing and the intensity of marketing
of teff through the cooperative positively (significant at 1%). Charging competitive price for a
quintal of farmer’s teff increases the probability of marketing of teff through the cooperative
and its intensity by 0.24%. The implication is that as there are other marketing agents in the
study area purchasing farmers’ teff, the cooperatives have to charge a competitive price so as
to be a marketing agent for the farmers. The result was in conformity with the earlier studies
(Wilkins and Stafford, 1982; Fulton and Adamowicz, 1993; Misra et al., 1993; Klein et al.,
1997).
Patronage refund (PATREF) also influenced the marketing of teff through the cooperatives
and the marketing intensity positively (significant at 1%). A patronage refund of one birr for a
quintal of teff given to the farmer increases the probability of marketing of teff through the
cooperative and its intensity by 0.60%. The implication is that farmers are encouraged to
market their teff through the cooperative if they get patronage refund. Similar result was also
found by Black and Knutson, 1985; Fulton and Adamowicz, 1993.
Fertilizer credit (FERCREDIT) influenced the marketing of teff and intensity of marketing
through the cooperatives negatively in the contrary to the hypothesized expectation
(significant at 5%). As it has been pointed out in the descriptive analysis part, 94.7% of the
sample farmers got credit for fertilizer from the cooperatives as they couldn’t afford money
for the quantity they need in that time (mid May). Getting the required amount of fertilizer
and other farm inputs increase the productivity (yield) of the farmers. And increased
productivity (yield) mean in most cases increase in the amount to be marketed. However, the
farmers’ usage and participation in the cooperative as their marketing agent for teff was not as
they got credit for fertilizer from the cooperative i.e. farmers paid this credit to the
cooperatives after selling to other marketing agents in the contrary to the hypothesized
expectation (selling to the cooperatives). That is why the result showed negative sign.
77
Distance of the cooperative from the farmer’s house (DCFH) influenced the marketing of
teff through the cooperatives and intensity of marketing negatively (significant at 1%).
Farmers who are relatively nearer to the cooperative more marketed teff through the
cooperatives. As the house of the farmer is far by an hour from the cooperative, the
probability of marketing of teff through the cooperatives and its intensity decreases by 0.27%.
The plausible reasons for this are proximity of the cooperative for the farmer reduces the costs
of time and labor that the farmer spent in searching for the buyer and closeness (nearness) of
the farmer to the cooperative also helps in having more knowledge about the cooperative and
its benefits.
Distance of the district market from the farmer’s house (DDMKT) influenced the
marketing of teff through the cooperatives and the marketing intensity positively (significant
at 5%). As the house of the farmer is far by an hour from the district (main) market, the
probability of marketing of teff through the cooperatives and its intensity increases by 0.80%.
The implication is that farmers who are nearer to the district market have access to district
(main) market system to sell their teff. They have also easy access to transportation facility to
sell their teff in the district (main) market.
In general, the marketing of teff through the cooperatives was influenced by district, family
size, position in the cooperative, farm size, yield of teff, cooperative price for teff, patronage
refund, fertilizer credit, distance of the cooperative from the farmer’s house and distance of
the district market from the farmer’s house. However, district, position in the cooperative,
farm size, yield of teff, cooperative price for teff, patronage refund and distance of the district
market from the farmer’s house influenced the marketing and intensity of marketing of teff
through the cooperatives positively.
78
Table 25. Maximum likelihood estimates of Tobit model
Explanatory
Variables
Estimated
Coefficients
Standard error Mean T-ratio Change in
Probability
σβi
i
zfX
zF)(
)(≈
∂
∂
Constant -1.6638 1.7391 -0.957
DISTRICT -1.5515* 0.9530 0.6364 -1.899 -0.0011
EDUCATION -0.0306 0.0981 3.0027 -0.302 -0.0002
FAMILYSIZE -0.3634* 0.1974 5.4187 -1.805 -0.0013
MEMBERSHIP 0.0416 0.0565 21.6136 0.731 0.0005
ONFINC 0.0006 0.0004 496.4242 1.442 0.0011
POSITION 3.7553*** 1.1267 0.0758 3.217 0.0023
FARMSIZE 0.7884* 0.4138 2.1116 1.898 0.0013
YIELD 0.0834** 0.0363 15.7973 2.284 0.0016
TLSH 0.0492 0.1475 4.8908 0.319 0.0002
COOPP 2.5990*** 0.7723 0.1667 3.172 0.0024
PATREF 0.1120*** 0.0130 9.5303 8.273 0.0060
FERCREDIT -0.0017** 0.0006 696.0008 -2.152 -0.0020
CREDIT -0.1390 0.5998 0.4545 -0.220 -0.0002
OMKAG -0.7605 0.8631 0.3636 -1.053 -0.0006
AOS 0.4974 0.7350 0.4167 0.664 0.0005
DCFH -3.2007*** 0.8180 0.3258 -3.386 -0.0027
DDMKT 1.3101** 0.1143 1.5125 2.365 0.0080
Log Likelihood function = -221.2451 No of observation = 132 K= 18
Lr (likelihood ratio) = 128.9721 χ2 (17,114) =16.62 Pseudo R
2 = 0.71
***, **, and * represent level of significance at 1%, 5% and 10%, respectively
Source: Own computation from the data.
79
4.3.2. Effects of changes in the significant explanatory variables on the intensity of
marketing of teff through the cooperative
The results of the Tobit model can be used to identify the effects of changes in explanatory
variables on the intensity of marketing of teff through the cooperatives. The effect of
marginal changes (derivatives) in significant explanatory variables on the intensity of
marketing of teff through the cooperatives among the farmers that marketed teff through the
cooperative and among the entire sample farmers is presented in Table 27. The result of the
marginal changes (derivatives) in significant explanatory variables on the intensity of
marketing of teff through the cooperatives is discussed below.
District (DISTRICT): Though the cooperatives in the two districts are working in a more or
less similar agroecological environment, there is performance variation among them. The
study showed that cooperatives in Lume are performing better than the Adaa Liben in being
marketing agent for the farmers. It was also observed during data collection that cooperatives
in Lume are well organized in terms of asset, provision of different services etc. Had the
farmer been the member of the Lume district cooperatives, the quantity of teff marketed
through the cooperatives increase by 1.30 qts among users and 1.00 qts by the whole sample.
Family size (FAMILYSIZE): Increasing the family size on limited resource (land) obviously
bring economic pressure on the household i.e. the family consume more of what is produced
and little remain to be marketed. Increasing the family size by one adult equivalent (AE)
decreases the marketing of teff through the cooperatives by 0.30 qts among users and 0.24 qts
by the whole sample.
Position in the Cooperative (POSITION): Farmers that have position in the cooperative used
the cooperative better than the ordinary members as their marketing agent for their teff.
Having a position in the cooperative helps them to realize the benefits the cooperative bring to
the area. Thus, having a position in the cooperative (either in the management (board of
director) or employment) increases the quantity of teff marketed through the cooperatives by
3.13 qts among users and 2.43 qts by the whole sample.
80
Farm size (FARMSIZE): The usage of the cooperative as marketing agent requires substantial
economic resources of which land is the principal one. The study also confirmed that farmers
with larger farm size used more the cooperative as marketing agent than those with smaller
farm size. Increasing the farm size increases the quantity of teff marketed through the
cooperative. An increase in farm size by 1 ha increases the quantity of teff marketed through
the cooperative by 0.66 qts among users and 0.51 qts by the whole sample. However the
availability of additional arable land in the study area is almost nil.
Patronage refund (PATREF): Farmers encouraged marketing their teff through cooperative if
there is surplus appropriation in the form of patronage refund. A patronage refund of one birr
for a quintal of teff increases the quantity of teff marketed through the cooperatives by 0.09
qts among users and 0.07 qts by the whole sample.
Cooperative price for teff (COOPP): Price effect is one form of cooperative effect that the
cooperative passes on the farmer’s economy. So charging similar or better price for farmer’s
teff increases marketing through the cooperative. It increases the quantity marketed by 2.17
qts among users and 1.68 qts by the whole sample.
Yield of Teff (YIELD): This study showed that the quantity of teff marketed through the
cooperative is positively related to the yield obtained. An increase in the yield of teff of the
farmer by 1qts increases the quantity of teff marketed through the cooperatives by 0.07 qts
among users and 0.05 qts by the whole sample.
Distance of the Cooperative from the Farmer’s House (DCFH): This study showed that as
farmers become away from the cooperative, their usage of the cooperative as marketing agent
decreases i.e. farmers who are relatively nearer to the cooperative more marketed teff through
the cooperatives than those who are far away from the cooperative. An increase in the
distance of the farmer’s house from the cooperative by an hour reduces the quantity of teff
marketed through the cooperatives by 2.67 qts among users and 2.07 qts by the whole sample.
81
The distance of the district (main) market from the farmer house (DDMKT): Farmers who are
nearer to the district market have access to the main market system to sell their teff. They
have also easy access to transportation facility to sell their output. So the farther the farmer
from the district (main) market, the higher the quantity of teff marketed through the
cooperatives. An increase in the distance of the farmer house by an hour from the district
market increases the quantity of teff marketed through the cooperatives by 1.09 qts among
users and 0.85 qts by the whole sample.
82
Table 26. Effects of change in the significant explanatory variables on the intensity of
marketing of teff through the cooperatives
Explanatory Variables Change among users
of the cooperatives.
i
ii
X
YYE
∂
>∂ ∗)0/(
Change among the whole
i
i
X
YE
∂
∂ )(
DISTRICT -1.2950 -1.0035
EDUCATION -0.0255 -0.0198
FAMILYSIZE -0.3034 -0.2351
MEMBERSHIP 0.0347 0.0269
ONFINC 0.0005 0.0004
POSITION 3.1344 2.4290
FARMSIZE 0.6581 0.5100
YIELD 0.0696 0.0539
TLSH 0.0411 0.0318
COOPP 2.1693 1.6811
PATREF 0.0935 0.0725
FERCREDIT -0.0014 0.0011
CREDIT -0.1160 -0.0899
OMKAG -0.6347 -0.4918
AOS 0.4151 0.3217
DCFH -2.6714 -2.0703
DDMKT 1.0935 0.8474
Log Likelihood Function = -221.2451
Sigma (δ)= 24.9077 f(z) = 0.0007
z = 1.41 F(z) = 0.8416
Source: Own computation from the data.
83
5. SUMMARY AND CONCLUSION
5.1. Summary
Multi-purpose agricultural cooperatives operate in the agricultural sector of the national
economy and they are supposed to increase efficiency of the marketing system and promote
agricultural development in the rural area. They are also organized to render economic
benefits such as economies of scale, market power, risk pooling, coordination of demand and
supply and guaranteed access to input and output markets to the smallholders.
In this study, the financial performance of agricultural cooperatives, identifying factors
influencing farmer’s marketing through agricultural cooperatives and attitudes of farmers
toward the cooperatives were analyzed in Adda Liben and Lume districts of the East Shoa
Zone of the Oromiya Region. The study was based on primary (cross section data) from the
farmers and secondary data obtained from the Wereda cooperative offices.
The financial performance of the cooperatives is examined using the financial ratios. Current
ratio, debt ratio and return on total asset ratio indicators were used to examine the financial
performance of the cooperatives. Statistical software called "SPSS 10 version” was employed
to analyze the descriptive statistics of the sample farmers. Econometric software called
“LIMDEP 7 version" was also employed to estimate the tobit model with the aim to identify
factors influencing farmers’ marketing of teff through cooperatives and the intensity of
marketing. The model was selected or chosen since it has advantage in revealing the objective
of the study cited above.
Ratios were analyzed taking the two years financial data (2001/2 and 2002/3). The liquidity
analysis showed that the cooperatives under investigation were below the satisfactory rate (a
current ratio of less than 2.00) for the two years. All of the cooperatives under investigation in
the two districts use financial leverage (financed more of their total asset with creditors fund
i.e. on average 89.35% of the assets of the cooperatives was financed with creditors fund in
84
the two years). The profitability ratio of the cooperatives under investigation in the two
districts showed that the profitability of the cooperatives was weak. All the cooperatives earn
return on their asset below the interest rate the financial institution extend credit.
The descriptive statistics and econometric model were also used for analyzing the data in
addition to the ratio analysis. T-test was used to compare the mean values of the continuous
explanatory variables and examine the existence of statistically significant differences
between the cooperative users and non-users. The T-test showed significant difference in the
age of the farmers, farming experience, land holding and yield obtained from wheat between
the two groups at less 10% probability level. Discrete variables were also compared using
Chi-square test to see if there is statistically significant difference between the two. The Chi-
square test also revealed that the discrete variables (provision of different services, perception
on future performance of the cooperatives) showed significant differences between the two
groups at less than 10% probability level.
To identify the factors influencing farmers’ marketing of teff through the cooperatives in the
study districts, Tobit regression model was used. The model results revealed that among
seventeen explanatory variables included in tobit model, ten were found to be significant at
less than 10% probability level. More specifically, these variables include district, family size,
cooperative price for teff, position in the cooperative, farm size, yield of teff, patronage
refund, fertilizer credit, distance of the cooperative from the farmer’s house and distance of
the district (main) market from the farmer’s house were found to be significantly related to the
farmers’ marketing of teff through the cooperatives. And among these significant variables
district, Cooperative price for teff, position in the cooperative, farm size, yield of teff,
patronage refund and distance of the district market from the farmer’s house were found to be
significantly and positively related to the farmers’ marketing of teff through the cooperatives.
85
5.2. Conclusion and Recommendations
On the basis of this study, the following points are suggested for consideration in improving
the performance of the agricultural cooperatives in the study districts. These may be broadly
viewed as improving the financial condition of the cooperatives, identifying the factors that
influence farmers’ marketing of farm produces through the cooperatives and changing the
attitudes of the farmers towards the cooperatives.
1. The study has shown that the liquidity ratio (current ratio) of the cooperatives in the study
area is below the desirable rate. The cooperatives’ current asset base is its members i.e. the
cooperatives should make the members contribute certain amount of money as additional
share capital (Chukwu, 1990). And this money, which is contributed as additional share
capital, will improve the cooperatives liquidity position. In the mean time, the contribution
also improves the operating/working capital of the cooperatives rather than depending on
external sources.
2. The debt ratio shows the financial risk i.e. as debt becomes an increasing percentage of the
cooperatives’ financing source, the cooperatives face inability to meet debt obligations. This
ratio showed that the cooperatives have shortage of their own capital to meet their objective of
rural development so the government should be their source of capital until they strengthen
and this is common in most developing countries (Chukwu, 1990; Taimni, 2000) as the
government is the major initiator of cooperatives. Government support for the cooperatives
development should be with out impairing in any way their cooperative character (Dwivendi,
1996). The capital can be given in the form of grant or loan. Grants are usually non-repayable
and loan may have interest payment or not. If it has interest payment, it has to be subsidized
when compared to other financial institution i.e. the loan has to have a concessional rate of
interest.
3. The profitability ratio measures how effectively the cooperatives’ management is
generating profits on sales, total assets, money they borrowed and members’ investment
(share capital). The cooperatives in the study area perform below the desirable rate i.e. even
86
their profitability ratio couldn’t reach bank interest rate with which they borrowed money
from financial institution. Increasing the qualified manpower in the field, upgrading the
management capacity of the cooperatives’ management body (board of directors and other
employed workers) through education and trainings, improving the financial capacity of the
cooperatives and the participation of the farmers in the cooperative are among the possible
solutions.
4. Farmers’ usage of the cooperative as marketing agent for farm produces increase if the
cooperative provide them with different services such as grain mill service, tractors service
etc. and other benefits. Hence, provision of different services and benefits indispensable
means in increasing the participation of the farmers in marketing their farm produces through
the cooperatives.
5. Farmers sell their teff for other marketing agents in their area. They also travel long
distance to main market (district market) in search for better price. The cooperatives need to
charge competitive price for the farmers’ teff so as to be a marketing agent.
6. One of the aims of establishing cooperatives in the rural area is to increase the efficiency of
marketing system. For this to be so, first the farmer has to get good yield i.e. produce surplus.
The cooperatives are performing a significant role in increasing the productivity of the
farmers by supplying farm inputs especially fertilizer in credit. Other development partners
should also give due emphasis with regard to this issue. Appropriate and effective extension
services should be continued in the area in order to enhance the productivity of the farmer.
The other issue to be concerned is the specialization of the farmer. As the cooperatives in the
study area encourage and purchase white teff, farmers should be encouraged to produce this
item. According to Klien et al. (1997) with specialization comes an increased polarization of
the demands on cooperatives.
7. According to the proclamation 147/1998, 70% of the surplus the cooperative earned in the
year should be appropriated to the members. This study revealed that appropriation of surplus
in the form of patronage refund motivates the farmers to market their farm produces through
87
the cooperative. So cooperatives need to appropriate surplus in the form of patronage refund
to the farmers.
8. One of the fascinating features of agricultural cooperatives in the study districts is their
distribution of fertilizer in credit for the farmers with some prepayment. The credit is
extended with bank interest rate (7%) and paid in installment. Farmers pay this credit in the
harvesting seasons i.e. starting from December. Fertilizer is distributed to the farmers staring
mid May. As it is known, this time is a critical time for most farmers i.e. they are in short of
money to pay for the amount of fertilizer they need. Had the cooperatives not extended credit
for fertilizer, the only options for most farmers would have been either to sell their assets or
lend from other micro finance institutions or local money lenders with a higher interest rate.
Hence, this function of cooperatives in the study area should be strengthened and continued.
9. Above all, changing the attitudes of the farmers towards their cooperatives is a crucial
factor in improving the performances of the cooperatives in the study area. Most of the
sample farmers need only immediate economic advantages from the cooperatives i.e. getting
fertilizer in credit. They don’t pay attention to the sum total of the different advantages they
can get in the long-run if they actively participate and strengthened their cooperatives. The
concerned bodies should create awareness about a cooperative and the agricultural
development it can bring to the area in the long-run. Continuous education and enlightenment
of the farmers will have a positive impact on their attitudes towards the cooperatives.
88
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7. APPENDICES
95
7.1. Appendix I. Tables
Appendix table 1. VIF of the continous explanatory variables (Xi) hypothesized for the
study
Variables Ri2 Variance Inflation Factor (VIF)
DDMKT 0.140 1.163
EDUCATION 0.384 1.623
FAMILYSIZE 0.395 1.653
ONFINC 0.105 1.117
MEMBERSHIP 0.527 2.114
FARMSIZE 0.333 1.499
YIELD 0.610 2.564
TLSH 0.609 2.558
DCFH 0.222 1.285
FERCREDIT 0.509 2.037
PATREF 0.140 1.163
Source: Computed from the field survey.
Appendix table 2. Contingency coefficients of the hypothesized discreet explanatory
variables
POSITION CREDIT COOPP OMKAG AOS DISTRICT
POSITION 1 0.073 0.051 0.069 0.072 0.069
CREDIT 1 0.005 0.007 0.008 0.007
COOPP 1 0.054 0.056 0.054
OMKAG 1 0.023 0.022
AOS 1 0.016
DISTRICT 1
Source: Computed from the field survey
96
Appendix table 3. Conversion factors employed to compute adult equivalent (AE)
Age Group Male Female
< 10 0.6 0.6
10-13 0.9 0.8
>13 1 0.75
Source: Storck et al., (1991)
Appendix table 4. Description of explanatory variables
Variables Description % with a
Value 1
Mean ± SD
EDUCATION Years of formal schooling completed by
household head
3.00 ± 3.83
FAMILYSIZE Adult equivalent of the household 5.42±1.90
ONFINC Total amount of income measured in birr that is
earned from agricultural and non-agricultural
activities
496.42±752
.36
MEMBERSHIP Number of years since the farmer has been the
member of the cooperative
21.61±8.02
FARMSIZE Total area of farmland that a farmer owns in
hectare
2.11±0.99
YIELD Amount of teff the farmer obtained in quintal 15.80±13.2
6
TLSH Total number of livestock the household own in
terms of TLU
4.89±3.03
FERCREDIT Total amount of credit the cooperative extended
for fertilizer for the farmer
696.00±522
.22
PATREF Amount of money the farmer receives from the
surplus the cooperative appropriate in proportion
9.53±22.97
97
with his turnover
DCFH Distance of the cooperative from the farmer
house
0.33±0.51
DDMKT Distance of the farmer's house from the district
(main) market
1.51±0.69
DISTRICT 1, if the farmer found in Adaa Liben district; 0 if
he found in Lume district
84
POSITION 1, if the farmer has a position in the cooperative;
0 otherwise
8
COOPP 1, if the cooperative price for teff is similar or
better than other marketing agents in the area; 0
otherwise
17
CREDIT 1, if the farmer obtained credit from other micro
finance institution; 0 otherwise
46
OMKAG 1, if there are other marketing agents in the area
of the farmer at a distance less than the
cooperative; 0 otherwise
37
AOS 1, if the farmer got other services besides
supplying inputs, purchasing farm products and
extending credit; 0 otherwise.
55
Source: Computed from the field survey data.
Note: Sample Size, N= 132
98
Appendix table 5. Conversion factors used to estimate man-equivalent (ME)
Age Group Male Female
<10 0 0
10__13 0.2 0.2
14__16 0.5 0.4
17__50 1 0.8
>50 0.7 0.5
Source: Bekele Hundie (2001)
Appendix table 6. Conversion factors used to estimate tropical livestock unit (TLU)
Livestock Type TLU (Tropical Livestock Unit)
Calf 0.20
Weaned Calf .34
Heifer .75
Cows/Oxen 1
Horse/Mule 1.10
Donkey .70
Donkey (Young) .35
Sheep/Goat .13
Sheep/Goat (Young) .06
Camel 1.25
Chicken .013
Source: Storck et al., (1991)
99
7.2. Appendix II. Survey Questionnaire
Per f ormance o f Pr imary Agr i cu l tura l Coopera t i v es and Determnan ts o f
Members ’ Dec i s i on t o Use as Market ing Agen t i n Adaa L iben and Lume
D i s t r i c t s
Instructions for the interviewers
• Introduce yourself with the selected person
• Circle the letter for the closed questions
• Write interview questions clearly
• Use only pencil
Notice: this questionnaire is used only for the academic purposes. Thank you for your
cooperation.
A. General information
1. Name of the enumerator_______________________________
2. Date ______________________
3. Name of the district_____________________________
4. Name of the cooperative ___________________________
5. Distance of the cooperative from the district center (Kms)__________
6. Name of the respondent ___________________________________
7. Signature of the enumerator_________________________________
B. Farmer/ Household information
1. Age_______ (years)
2. Gender
1. Male 2. Female
3. Martial Status
1. Married 2. Single 3. Divorced 4. Widowed
4. Educational level
1. Illiterate 2. Basic education (Religion based)
3. Primary education. Number of years _______
4. Secondary education. Number of years _______
5. Religion
1. Orthodox 2. Muslim 3. Protestant 4. Others/specify___________
100
6. When did you start farming for your own? (Years)_________
7.Household membership
Number Name Relation to
the HH
head
Sex Age Main
occupation
Education
8. Did the household involve in any off/non-farm activities in 1996 E.C.?
1. Yes 2. No
9. If yes, in what type of activity?
1. Petty trade (poultry & egg, milk & milk products, hides & skins, crop residue, honey)
2. Casual work
3. Handicraft
4. Others /Specify______________________________________________________
10. What was the estimated amount of income for the year? _____Birr
11. How long have you been the member of this cooperative? (Years)__________
12. What was your position in the cooperative in the last two years?
1. Chairman
2. Ordinary member
3. Board of director
4. Others/ specify ____________________________
C. Farm characteristics
1. Land
1. How much is your farm size in hectares (own land)? ______
2. Did the household rented in /shared in someone land?
1. Yes 2. No
101
3. If yes, what was the size of the land rented in/ shared in (ha)
__________ and __________
4. If yes to 2, what was/ were the reason (s) for renting in/shared in?
1. Availability of fertilizer and other farm inputs
2. Because of land shortage
3. Because of the extra labor I had
4. 4. Others/ specify _______________
5. If yes to 2, type of agreement
1. In birr 2. In grain
6. If it was in birr, how much it was? ______Birr
7. If it was in grain, how much quintal and what type of grain it
was? ___________________________________
8. Have you rented out/shared out land to other farmers?
1. Yes 2. No
9. If yes, what was the size of the land rented out/ shared out?
__________ and __________(ha)
10. If yes to 8, what was the reason for renting out/ sharing out?
1. Shortage of money to buy fertilizer and other inputs 3. Disabled
2. Shortage of ox 4. Others/ specify____________________
11. If yes to 8, type of agreement?
1. In birr 2. In grain
12. If it was in birr, how much it was? ______Birr
13. If it was in grain, how much quintal and what type of grain it
was? ______________________________________________
102
2. Crop enterprise
Area (ha) Yield (Qts) Crops
1996 1997 1996 1997
Purpose *
White Teff
Mixed Teff
Wheat
Peas
Beans
Lentils
Maize
Others/ specify
* Purpose 1. Consumption 2.Sale 3. Others/ specify____________
3. Livestock enterprise
Type Number Value of each Purpose of
keeping *
Oxen
Cows
Calves
Heifers
Sheep
Goat
Mule
Donkey
Horse
Others/
specify
* Purpose of keeping 1.Milk production 2.Consumption 3.Draft power 4.Sale
5. Others/ specify________________
103
D. The Cooperatives and their members
1. Purchasing activity and Price for teff
I. Purchasing activity
1. Did you sell teff to the cooperative in the last two years?
1. Yes 2. No
2. If yes, how much was the quantity sold?
Total quantity sold (Qt) Crop
1996 1997
White Teff
Mixed Teff
Total
3. Which of the following do you think are important attributes of cooperative
purchasing?
1. Genuinely measures (no cheating in the weight)
2. It has patronage refund
3. Introduced desirable competition that raises market prices
4. Others/ specify__________________
4. Did you sell teff to other marketing agents in 1997 E.C.?
1. Yes 2. No
5. If yes, to which marketing agents you sold?
1. Local assemblers (local mkt, main road) 2. Consumers (local mkt, district mkt)
3. Traders in the district mkt 4. Others/ specify____________
6. If yes to 5, why you sold to these agents?
1. The cooperative was not ready to purchase
2. Lack of coincidence (the day you sold and the purchasing day of the cooperative
couldn’t coincide)
3. Price difference/the cooperative didn’t charge competitive price
4. Others/ specify_______________________
104
7. If yes to 5, how much was the quantity sold?
Total quantity sold (Qt) Crop
1996 1997
White Teff
Mixed Teff
Total
II. Price for farm products
8. If yes to 2, how much was the price you received?
Av. price/Qt Crop
1996 1997
White Teff
Mixed Teff
9. If yes to 1, did you know the price for a quintal of your teff in the nearby market?
1. Yes 2. No
10. If yes to 9, which one was better?
1. The cooperative price
2. The nearby market price
3. They are the same
4. Others/ specify___________________________
12. If yes to 4, how much was the price you received?
Av. price/Qt Crop
1996 1997
White Teff
Mixed Teff
105
2. Supply of farm inputs
I. Supply of fertilizer
1. From where you get fertilizer in 1996 E.C?
1. Cooperative 2. Retailers 3. Others/ specify________
2. What was the amount of fertilizer you get from the cooperative?
DAP __________bags
Urea__________bags
4. What was/ were the possible reason (s) for buying fertilizer from the cooperative?
1. Extend it in credit
2. No other sources provide in sufficient amount
3. Relatively lower price
4. Others/ specify ________________________________
5. Had you not get fertilizer from the cooperative, what you were going to do?
1. Stop using inputs (I couldn’t buy from other sources).
2. Purchase from other sources but minimize the amount used.
3. Continue using inputs by purchasing from other sources
4. Others/ specify___________________________________________
II. Supply of other farm inputs
1. Did you use other farm inputs last year?
1. Yes 2. No
2. If yes, which farm inputs you used last year?
1. Pesticide 2. Herbicide
3. Improved seeds 4. Others/ specify____________________
3. From where you got these farm inputs?
1. Cooperative 2. Retailers 3. Others/ specify________
4. If you didn’t get inputs from the cooperative, which input it was?
1. Pesticide 2. Herbicide
3. Improved seeds 4. Others/ specify____________________
3. Credit
1. Did you get fertilizer in credit from the cooperative?
1. Yes 2. No
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2. If yes, how much was the prepayment you paid in order to get this kind credit?
___________ Birr
3. What were the preconditions to obtain this kind credit?
1. Membership
2. Personal guarantee
3. Prepayment
4. Agricultural land
5. Others/ specify____________________
4. If Yes to 1, how much was the credit you get from the cooperative?_________ birr
5. Had you not get fertilizer in credit, do you have the capacity to buy in cash the amount
you needed?
1. Yes 2. No
6. Do you know other credit agencies that extend cash credit in your area?
1. Yes 2. No
7. If yes, which agency?
1. Oromiya saving and credit S.C.
2. Buussa Gonofaa Micro-financing S.C.
3. Gasha Micro-financing S.C.
4. Others/ specify__________________________
7. If yes to 5, did you take credit from this/ these sources?
1. Yes 2. No
8. If yes, for which purposes you take the credit?
1. For purchasing farm inputs and prepayment of fertilizer
2. For fattening livestock
3. For contracting land/ox
4. For other social obligations
5. Others/ specify___________________________________
9. If Yes to 8, what kind of collateral did you provide to obtain this loan?
1. Signature, personal guarantee
2. Agricultural land
3. Group lending
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4. Others/ specify__________________________
10. If No to 5, why not you take credit from these credit agencies?
1. Shortage of supply 2. High interest rate
3. Restrictive procedure 4. No need to take
5. Others/(specify)________
4. Distances of the respective marketing agents to which the farmer sold teff
1. How many hours you need to travel to get the following (on foot)
1. Cooperative ______ hours
2. Local market (if there is) ______ hours
3. Local assemblers (if there is) _______hours
4. The district market _____ hours
2. Did you sell teff to the cooperative?
1.Yes 2. No
3. By what means you usually take your produces when you sell?
1. Carrying by own 4. Using carts
2. Using donkey 5. Others/ specify_______________
3. Using trucks
4. If Yes to 2, on average how many hours the farmer spent in a journey in selling a
quintal of teff to the cooperative?
________ Hours
5. Did you sell teff to other marketing agent(s)?
1.Yes 2. No
6. If Yes, to which agent(s) you sold?
1. Local assemblers (local mkt, main road) 2. Consumers (local mkt, dist. mkt)
3. Traders in the dis. mkt 4. Others/ specify____________
7. Where could (did) you get them?
1. At the farm level 4. At the district market
2. At the local market 5. Others/ specify______________________
3. On the main road (A.A to Nazareth)
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8. If yes to 5, on average how many hours the farmer spent on the journey in selling a
quintal of teff to other marketing agents?
________ Hours
5. Surplus appropriation
1. Did the cooperative appropriate surplus to the members in 1996 E.C?
1.Yes 2. No
2. If Yes, did you get money as patronage refund/ dividend from the cooperative?
1.Yes 2. No
3. If Yes, how much it was? _______ birr
4. If No, do you know the possible reasons?
1. Didn’t market products through the coop.
2. The general meeting decided to be reinvested in the coop.
3. The cooperative didn’t make surplus
4. The cooperative didn’t purchase farm products
5. Others/ specify________________________________
5. Do you know that if you market your produces through or buy inputs from the
cooperative, you will get money as patronage refund/ dividend?
1.Yes 2. No
6. Other benefits of the multipurpose agricultural cooperative
1. Did you get other services besides distributing inputs and purchasing
your grains in 1996 E.C?
1.Yes 2.No
2. If yes, which services did you get?
1. Tractor service
2. Grain mill service
3. Employment opportunity
4. Others/ specify________________________________________________
3. Did the cooperative involve in any local development activities?
(To be asked the management body of the cooperative)
1.Yes 2.No
4. If yes to 4, did the farmer or his family get this secondary benefit of the cooperative?
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1.Yes 2.No
5. In view of you, what are the social contributions of the cooperative in your area?
1. Community spirit (one for all and all for one)
2. Democratic way of decision making (one member one vote)
3. Reduction of exploitation by money lenders
4. Others/ specify_________________________________
7. Education/ training
1. Did you get education/ training from the cooperative in 1996 E.C.?
1.Yes 2. No
2. If Yes, on what points it gave you education/ training?
1. The benefits of the cooperative
2. The need of the members commitment to the cooperative
3. The principles of the cooperative
4. Others/specify_____________________________________
3. Did you get any training or education about the cooperative from any other sources?
1.Yes 2. No
4. If yes, which sources give you that education/ training?
1. The woreda cooperative promoters and organizers
2. The union
3. NGO such as VOCA
4. Others/ specify________________________________________
8. Other issues on the long-term success of the cooperative
1. Did the you believe that the cooperative is doing a good job in solving the problems the
farmers are facing these days?
1.Yes 2. No
2. If No, what is/are the major commonly felt problems that isn’t/aren’t solved by the
cooperative in your area?
1. Household consumable items (such as salt, soap, oil, cloths, etc)
2. The farm inputs aren’t provided in sufficient amount
3. The credit demand
4. Farm equipments
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5. Others/ specify___________________________
3. In general, do you believe that the farmers will overcome their commonly felt
problems by working together such as establishing cooperative in the future?
1.Yes 2.No
4. If No, what is/ are the possible reasons?
1. Lack of responsibility for common work
2. Misuse of the cooperative by some individuals
3. Lack of commitment by the members
4. Political influence/ intervention
5. Others specify_______________________
5. Would you be willing to contribute money to improve the performance of the
cooperative?
1.Yes 2.No
6. If No, what are the possible reasons?
1. I don’t trust the management body
2. I can’t afford
3. The government should improve it
4. Others/ specify___________________________________________
7. Do you want to continue your membership of the cooperative?
1. Yes 2.No
8. If Yes, what is/are the possible reason(s)
1. I get goods and services (fertilizer) which are not available elsewhere
2. It purchases (assures a market for) our products
3. I don’t want to isolate from other farmers
4. There is external pressure
5. Others/ specify________________________________________