Performance Of Primary Agricultural

P E R FO RM A N CE O F P RI M A R Y A G RI C UL T U RA L C O O PE R AT I VE S A ND DE T E RM N A NT S O F M E M B E R S ’ D E CI S I O N T O U S E AS M A RK E T I N G AG E N T I N A D AA L I B E N A N D L UM E DI S T RI C T S

M.Sc. Thesis

D A NI E L B E L AY

April 2006 Alemaya University

P E R FO RM A N CE O F P RI M A R Y A G RI C UL T U RA L C O O PE R AT I VE S A ND DE T E RM N A NT S O F M E M B E R S ’ D E CI S I O N T O U S E AS M A RK E T I N G AG E N T I N A D AA L I B E N A N D L UM E DI S T RI C T S

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

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 _________________ Co-advisor

________________

_______________

Signature ________________

Date _______________

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

_______________________ Internal Examiner

_______________________ External Examiner

__________________ Signature

__________________ Signature

__________________ Signature

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________________ Date

________________ Date

________________ Date

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.

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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: ________________

iv

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

v

ACRONYMS AND ABBREVIATIONS (Continued) ROTA

Return on Total Asset

TLU

Total Livestock Unit

VIF

Variance Inflation Factor

VOCA

Volunteers in Overseas Cooperative Assistance

vi

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.

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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.

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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 2.2.1. Principles of cooperative 2.2.2. Classification/ types of cooperatives

12 12 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

ix

TABLE OF CONTENTS (Continued) 2.5.1. Feudal regime (1960- 1975) 2.5.2. Derg regime (1975-1991) 2.5.3. Post 1991 period

17 18 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 3.1.1. An overview of the Oromiya regional state 3.1.2. An overview of the east Shoa zone 3.1.3. Adaa Liben and Lume Districts 3.1.3.1. Location and physical features 3.1.3.2. Socioeconomic environment 3.1.4. Agricultural extension service 3.1.5. Agricultural cooperatives 3.1.6. Cooperative organization and promotion service 3.1.7. Agricultural credit services 3.1.8. Marketing services

28 28 28 30 30 31 35 35 36 36 37

3.2. Sampling Procedure 3.2.1. Selection of study area 3.2.2. Sampling design

38 38 38

3.3. Methods of Data Collection

39

3.4. Methods of Data Analysis 3.4.1. Ratio analysis 3.4.1.1. Liquidity ratio 3.4.1.2. Financial leverage management ratio 3.4.1.3. Profitability ratio 3.4.2. Discrete regression models 3.4.3. The Tobit model 3.4.4. Specification of the Tobit model

40 40 40 41 41 42 43 44

3.5. Hypothesis and Definition of Variables 3.5.1. Dependent variable 3.5.2. The Independent variables

46 46 47

4. RESULTS AND DISCUSSION

52

4.1. Ratio Analysis 4.1.1. Liquidity analysis 4.1.2. Financial leverage management analysis x

52 52 53

TABLE OF CONTENTS (Continued) 4.1.3. Profitability analysis

54

4.2. Descriptive Analysis 4.2.1. Household characteristics 4.2.2. Land holding 4.2.3. Major crops produced and yield 4.2.4. Livestock holding 4.2.5. The cooperatives

55 55 60 61 64 66

4.3. Results from the Tobit Econometric Model 4.3.1. Factors influencing the marketing of teff through the cooperatives 4.3.2. Effects of changes in the significant explanatory variables on the intensity of marketing of teff through the cooperative

73 74 79 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

xi

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

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26. Effects of change in the significant explanatory variables on the intensity of marketing of teff through the cooperatives ...................................................................... 82

xiii

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

xiv

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

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P E R FO RM A N CE O F P RI M A R Y A G RI C UL T U RA L C O O PE R AT I VE S A ND DE T E RM N A NT S O F M E M B E R S ’ D E CI S I O N T O U S E AS M A RK E T I N G AG E N T I N A D AA L I B E N A N D L UM E DI S T RI C T S

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

xvi

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.

xvii

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.

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

2

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

3

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.

4

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.

5

Table 1. Primary cooperatives of the country by region, number of members and capital

Region

Number

Members Male

Capital

Female

(In birr)

Total

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

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

14423

1760510

3223242

4983752

474009157

Afar

Total

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).

6

Table 2. Primary cooperatives of the Oromiya region by type of cooperative, number of members and capital

Cooperative Type

Members

Number

Capital

Female

Male

Total

(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

16

6628

5

6633

414389.56

5

117

-

117

255646.21

29

1174

224

1398

908259

7

743

254

997

222962.69

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

10

269

136

405

323303.14

4

155

42

197

1056277.4

1568

1206080

1272269

1333349

119873911.4

Fishery Butchery Dairy Sugarcane Mining

Animal Husbandry Local

Seed

production Total

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.

7

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.

8

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. 9

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

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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.

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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 decisionmaking. 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 decisionmaking 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

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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.

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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).

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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

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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

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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

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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.

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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 20

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

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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

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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

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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

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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.

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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.

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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

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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 (O P E D B , 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 (O P E D B , 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 (O P E D B , 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%.

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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

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area (O P E D B , 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’-8056’N latitudes and 38058’-39022’E longitudes. It is the largest district in the zone with an area of 1576.79 km2 and cultivable land of 1261.43 km2 (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’-8050’N latitudes and 39001’-39017’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.

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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 31

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).

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Table 3. Crop production of different types in the Adaa Liben district

Type of Crop

2001/2 Area (ha)

2002/3

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

859

12885

75

370.25

3015

54270

2340

9360

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

710

8880

766

4000

2048

85560

2215

8860

-

-

165

60

Oil seed

174

897

192

576

Lin seed

174

897

57

171

Fenugreek

-

-

135

405

Others

-

-

1400.8

129584

116606

839279.6

117086.8

1307165.9

Sorghum Maize Oats

Vetch Haricot bean Others

Total

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.

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Table 4. Crop Production of Different Types in the Lume District

Type of Crop

2001/2

2002/3 Production (qt)

Area (ha)

Area (ha)

Production (qt)

Cereals

38185

488655

38415

714300

Teff

26440

264400

26500

344500

Wheat

10420

208400

10500

346500

Barley

710

12780

800

20000

-

-

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

41055

503585

41090

741050

Sorghum

Total

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 agroclimate. 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.

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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.

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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

36

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

37

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

38

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

39

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

40

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.

Current ratio =

Current asset Current liablity

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.

Debt ratio =

Total debt Total asset

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.

41

Re turn on total asset =

Net income Total asset

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

42

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)

43

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).

44

The model parameters are estimated by maximizing the Tobit Likelihood Function of the following form (Maddala, 1997).

1 Y − β X   −β X  L = ∏ f  i i i  ∏ F i i  σ  Yi∗ ≤0  σ  Yi∗ φ0 σ 

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:

Where,

∂E (Yi ) = F ( z )β i ∂( X i )

Eq (6)

βi X i is denoted by z, following Maddala, (1997) σ

2. The change in the probability of using the cooperatives as marketing agent as an independent variable Xi changes is: ∂F ( z ) β = f (z ) i ∂X i σ

Eq (7)

45

3. The change in usage intensity with respect to a change in an explanatory variable among Y  ∂E i ∗ 2   Y φ 0  f (z )   ( ) f z i   users is:   = β i 1 − Z − ∂X i F ( z )  F ( z )   

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.

46

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.

47

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.,

48

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

49

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.

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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.

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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

52

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

CR

DR

DR

ROTA

ROTA

2001/2

2002/3

2001/2

2002/3

2001/2

2002/3

Ude

1.315

1.061

0.718

0.830

-0.021

-0.002

Kajima

1.081

1.068

0.858

0.882

0.004

0.006

Kality

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

Gicegerbabo

1.003

0.965

0.963

0.976

-0.010

0.031

Hidi

1.028

0.997

0.963

0.964

-0.023

0.013

Katajara

1.033

0.986

0.958

0.992

0.021

0.026

Adulala

1.020

1.160

0.914

0.875

-0.026

-0.010

Dire

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

Yerersilassie

1.094

1.136

0.887

0.844

0.011

0.016

Kolba

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

Tulurea

1.142

1.107

0.857

0.849

0.045

0.002

Dekebora

1.124

1.071

0.868

0.869

0.007

0.037

Average

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).

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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 54

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,

55

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

Characteristic

Users

Non users

(n=77)

(n=55)

Mean

St. Dev

Mean

T-value

Total sample (n=132)

St.Dev

Mean

St.Dev .

Age (year)

48.64

13.83

44.85

11.48

1.66*

47.06

12.99

6.65

2.38

6.89

2.56

0.56

6.75

2.45

3.34

1.51

3.58

1.89

0.79

3.44

1.67

3.41

1.48

3.39

1.74

-0.08

3.40

1.59

1.09

0.30

1.00

-

-0.51

1.07

0.27

3.36

1.26

3.22

1.49

-0.58

3.30

1.36

Average family size (number) Children

<15

(number) 15-64 years (number) > 64 years (number) Active

labor

(man-equiv.)

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.

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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

Sex

Users

Non-users

Total sample

(n=77)

(n=55)

(n=132)

n

%

n

%

n

%

Male

73

94.8

54

98.2

127

96.2

Female

4

5.2

1

1.8

5

3.8

χ2-value

1.00

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).

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Table 8. Educational status of the household head

Educational Status

Users

Non-users

Total sample

(n=77)

(n=55)

(n=132)

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

T-value

3.09

3.00

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

Non users

(n=77)

(n=55)

Mean

St.Dev

Mean

St.Dev

22.38

7.69

20.55

8.40

T-value

Total sample (n=132) Mean

St.Dev

Membership (Years)

-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,

58

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

Non users

(n=77)

(n=55)

T-value

Total sample (n=132)

Mean

St.Dev

Mean

St.Dev

27.95

13.77

23.93

11.73

Mean

St.Dev

21.61

13.07

Farming experience (Years)

-1.76*

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

Income (birr)

Users

Non users

T-

Total sample

(n=77)

(n=55)

value

(n=132)

Mean

St.Dev

Mean

St.Dev

552.62

821.59

417.75

642.14

Source: Computed from the field survey data

59

-1.02

Mean

St.Dev

496.42

3.03

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

Non users

(n=77)

(n=55)

Mean

St.Dev

2.25

1.01

Mean

T-value

Total sample (n=132)

St.Dev

Mean

St.Dev

2.11

0.99

Holding Size (ha) 1.92

0.94

-1.94*

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.

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Table 13. Distribution of the sample farmers by land rent type

Rented-in Land

Farmer type

Rented-out Land

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).

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Table 14. Distribution of the sample farmers by the area of major crops

Type of crop

Users

Non users

(n=77)

(n=55)

Area

St.Dev

(ha)

Area

T-value

Total sample (n=132)

St.Dev

Area

(ha)

St.Dev

(ha)

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).

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Table 15. Distribution of the sample farmers by yield of major crops

Type of crop

Users

Non users

(n=77)

(n=55)

Yield

St.Dev

(qt)

Yield

T-value

Total sample (n=132)

St.Dev

Yield

(qt)

St.Dev

(qt)

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.

63

35.00 28.79

Percentage of the respondents

30.00

25.00 25.00 20.00

percentage of the respondents

17.42

15.00

12.12 10.61

10.00 6.06 5.00 0.00 1-5

6-10

11-15

16-20

21-25

>25

yield of teff in quintal

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.

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Table 16. Livestock ownership of the sample farmers

Particulars

Users

Non users

(n=77)

(n=55)

T-value

Total sample (n=132)

Mean

St.Dev

Mean

St.Dev

TLU

4.84

2.75

4.96

3.40

Oxen

2.55

1.36

2.60

Cows

1.21

0.14

Calf

1.47

Heifer

Mean

St.Dev

0.23

4.89

3.03

1.55

0.20

2.57

1.43

1.37

0.73

1.11

1.28

0.63

0.54

1.57

0.79

0.48

1.52

0.81

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.

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Table 17. Distribution of the sample farmers by oxen ownership

Farm oxen size (heads)

Users

Non-users

Total sample

(n=77)

(n=55)

(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

66

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

DAP (bags)

Users

Non users

(n=77)

(n=55)

Mean

St.Dev

4.83

3.15

Mean 4.36

T-value

(n=132)

St.Dev 3.15

Total sample

-0.84

Mean

St.Dev

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.

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Table 19. Quantity of Urea taken by the sample farmers from the cooperatives

Urea (bags)

Users

Non users

(n=77)

(n=55)

Mean

St.Dev

2.52

1.59

Mean 2.20

T-value

(n=132)

St.Dev 1.63

Total sample

-1.13

Mean

St.Dev

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

Non users

(n=77)

(n=55)

Mean

St.Dev

Mean

St.Dev

704.38

455.77 684.27

607.44

T-value

Total sample (n=132) Mean

St.Dev

696.00

522.22

Fertilizer credit (birr)

Source: Computed from the field survey data

68

-0.22

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 microfinancing 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

Other service

Users

Non users

Total sample

(n=77)

(n=55)

(n=132)

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%.

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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

Education

Users

Non-users

Total sample

(n=77)

(n=55)

(n=132)

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

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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

Current

Users

Non-users

Total sample

Performance

(n=77)

(n=55)

(n=132)

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.

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Table 24. Distribution of sample farmers by perception on future performance of the cooperatives

Future

Users

Non-users

Total sample

Performance

(n=77)

(n=55)

(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

72

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 Ri2 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.

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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 74

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

75

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.

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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.

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Table 25. Maximum likelihood estimates of Tobit model

Explanatory

Estimated

Variables

Coefficients

Standard error

Mean

T-ratio

Change

in

Probability ∂F ( z ) β ≈ f ( z) i ∂X i σ

Constant

-1.6638

1.7391

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 Lr (likelihood ratio) = 128.9721

-0.957

No of observation = 132

χ2 (17,114) =16.62

K= 18

Pseudo R2 = 0.71

***, **, and * represent level of significance at 1%, 5% and 10%, respectively Source: Own computation from the data.

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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.

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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.

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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.

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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

Change among the whole

of the cooperatives.

∂E (Yi ) ∂X i

∗

∂E (Yi / Yi > 0) ∂X i 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.

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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

83

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 Chisquare 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.

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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 85

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

86

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.

87

6. REFERENCES Abebe Hailegebriel, 2000. Development strategies and the Ethiopian peasantry: supply response and rural differentiation. PhD Dissertation, Institute of Social Studies, The Hague, The Netherlands. Agricultural Cooperative Development International/Volunteers in Overseas Cooperative Assistance, 2002. Restructuring agricultural cooperatives in Ethiopia. USAID, Ethiopia. Alemayehu Lerenso, 1984. State commerce and service cooperative in Kembata and Hadiya: an economic geography analysis. M.Sc. Thesis, Addis Ababa University, Ethiopia. pp. 40-44. Amemiya, T., 1981. Qualitative response models: A survey. Journal of Economic Literature. 19: 1483-1536. ALWCPO (Adaa Liben Woreda Cooperative promotion Office), 2005. Annual report for the year 2004/2005. Unpublished document, Bishoftu, Ethiopia. Asmare Hagos, 1989. The impact of farm size on efficiency of the farmers producers` cooperatives: the case of Harrer-Zuria awraja. M.Sc. Thesis, Agricultural Economics, Alemaya University of Agriculture, Alemaya, Ethiopia. Barton, D.G., T.C. Schroeder and A.M. Featherstone, 1993. Evaluating the feasibility of local cooperatives consolidation: a case study. Agribusiness. 9 (3): 281-294. Bekele Hundie, 2001. Factors influencing input loan repayment performance of smallholders in Ethiopia: the case of Oromia and Amhara national states: M.Sc Thesis, Alemaya University of Agriculture, Ethiopia. Bishop, D. and R. McConnen, 1999. Purpose of Cooperative. VOCA/ Ethiopia, Addis Ababa, Ethiopia. Black, W.E. and R.D. Knutson, 1985. Attitudes and opinions of Texas agricultural cooperative members. Report B-1483. Texas Agricultural Extension Service. USA. Black, J.R, B.J. Barnett and Y.Hu, 1999. Cooperatives and capital markets: the case of Minnesota-Dakota sugar cooperatives. American Journal of Agricultural Economics. 81:1247-1249. Bringham, E.F. and J.F. Houston, 1998. Ratio Analysis. In: Dryden Press (ed.), Fundamentals of Financial Management. The Dryden press, Orlando, Florida, U.S.A., pp. 70-93. Cain, J.L., U.C. Toensmeyer and S. Ramsey, 1989. Cooperative and proprietary firm performance as viewed by their customers. Journal of Agricultural Cooperation 4: 81-89.

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Center for Cooperatives, 2004. Working together for stronger cooperatives. University of Wisconsin, Madison, U.S.A. www. Wis. Edu/uwcc. Accessed In October 2005. Chukwu, S.K., 1990. Economics of the Cooperative Business Enterprise. Marburg, Germany. Coffey, J.D., 1993. Implications for farm supply cooperatives of the industrialization of agriculture. American Journal of Agricultural Economics. 75: 1132-1136. CSA (Central Statistics Authority), 1994. The population and housing census of Ethiopia.Vol 1: Part 4. Statistical report on population size. Addis Ababa, Ethiopia. Deininger, K., 1995. Collective agricultural production: a solution for transition economies. World Development. 23(8): 1317-1334. Dwivendi, R.C., 1996. Roles of cooperatives in rural economy. Indian Journal of Agricultural Economics. 51(4): 713-727. Ellene Kebede and F.Schreiner, 1996. Economics of scale in dairy marketing cooperatives in Kenya. Agribusiness. 12(4): 395-402. ESZFEDD (East Shoa Zone Finance and Economic Development Department), 2004. Physical and socioeconomic profile. the case of Adaa Liben district. Ziway. Ethiopia. ESZFEDD (East Shoa Zone Finance and Economic Development Department), 2004. Physical and socioeconomic profile. the case of Lume district. Ziway. Ethiopia. Fassil Teffera, 1990. The Development of peasant service cooperatives in post revolutionary Ethiopia (1974-1987). Institute of Ethiopian Studies. Addis Ababa University. FCC (Federal Cooperative Commission), 2004. Cooperative marketing information system and networking study: final requirement report. Addis Ababa, Ethiopia, pp 45. FCC (Federal Cooperative Commission), 2005. Annual report for the year 2004/2005. Unpublished document, Addis Ababa, Ethiopia. FCC (Federal Cooperative Commission), 2004. Cooperative. Annual magazine. Addis Ababa, Ethiopia. FCC (Federal Cooperative Commission), 2005. Cooperative. Annual magazine. Addis Ababa, Ethiopia. Federal Negarit Gazeta, 1998. A proclamation to provide for the establishment of cooperative society: proclamation No.147/1998. Addis Ababa, Ethiopia. Federal Negarit Gazeta, 2002. A proclamation to establish Cooperative commission: proclamation No. 274/2002. Addis Ababa, Ethiopia.

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Folsom, J., 2002. Measuring impact of cooperatives in Minnesota. USDA/ Rural Development/ Minnesota, USA. Fulton, J. and W. Adamowicz, 1993. Factors that influence the commitment of members to their cooperative organization. Canadian Journal of Agricultural cooperation. 8:39-53. Fulton, J.R. and R.P.King, 1993. Relationship among information expenditure, economic performance and size in grain marketing cooperatives in the upper Midwest. Agribusiness.19 (2): 143-157. Fulton, M.E, J.R. Fulton, J.S. Clark and C. Parliament, 1995. Cooperative growth: Is it constrained. Agribusiness. 11(3): 245-481. George, W.J. and C.P. Veerman, 2001.Marketing cooperatives: An incomplete contracting perspective. Journal of Agricultural Economics. 52 (1) 53-64. Getahun Degu (2004) Assessment of factors affecting adoption of wheat technology and its impact: the case of Hulu woreda, Ethiopia, M.Sc. Thesis, Agricultural Economics, Alemaya University, Ethiopia. Getenesh Sintayehu, 1988. Result analysis and result comparison of farmers producers’ cooperatives in highlands of Hararghe. M.Sc. Thesis, Agricultural Economics, Alemaya University of Agriculture, Alemaya, Ethiopia. Green, W.H., 2000. Econometric Analysis. Prentice Hall International, Inc, New York University, New York, U.S.A. Gujarati, D.N., 1988. Basic Econometrics, M.C. Graw Printing Press, U.S.A. Gujarati, D.N., 1995. Basic Econometrics. Third edition. United States of Military Academy, West Point. 838p. Halloways, G, C., Niccholson, C.,Niccholson, C. Delgado, S. Staal and S. Ehui,, 2000. Agroindustralization through the institutional innovation transaction costs, cooperatives and milk market development in East African highlands. Journal of Agricultural Economics.23: 279-288. Hind, A.M., 1994. Cooperatives-under performers by nature. Explanatory analysis of cooperatives and non-cooperative companies in the agribusiness sector. Journal of Agricultural Economics. 45(2): 213-219. Johnston,J. and Dinardo,J. 1997. Econometrics Methods. Fourth Edition, The McGraw-Hill Companies, Inc, New York, U.S.A. Kebebew Daka, 1978. Cooperative movement in Ethiopia. M.Sc. Thesis, Addis Ababa University.

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King, P.R., 1995. The future of agricultural cooperative in north America; discussion. American Journal of Agricultural Economics Association. 77:1160-1161. Klein, K.K., T.J. Richards and A.Walburg, 1997. Determinants of cooperative patronage in Alberta. Canadian Journal of Agricultural Economics 45:93-110. Kraenzle, C. A., 1989. Farmer cooperative: members and use. Agricultural Cooperative Society Research Report 77. USDA, Washington, D.C., U.S.A. Lang, M.G., 1995. The future of agricultural cooperative in Canada and United States: discussion. American Journal of Agricultural Economics Association 77:1162-1165. Leggesse Dadi, 2001. Adoption and intensity of fertilizer and herbicide use in the central highlands of Ethiopia. Agricon 4: 3, South Africa. LWCPO (Lume Woreda Cooperative Promotion Office), 2005, Annual report for the year 2004/2005. Unpublished document, Modjo, Ethiopia. Maddalla, G.S., 1992. Introduction to Econometrics: 2nd ed. Business Economics: University of Florida and Ohio state University, Mac Milan publishing Company, New York. Maddala, G.S., 1997. Limited Dependent and Quantitative Variables in Econometrics. Cambridge University Press. Mauget, R and F. Declerck, 1996. Structure, strategies and performance of European community agricultural cooperatives. Agribusiness. 12(3): 265-275. MORD (Ministry of Rural Development), 2002. Cooperative review, Addis Ababa, Ethiopia, 5p. Misra, S.K, D.H. Carley and S.M. Fletcher, 1993. Dairy farmers evaluation of dairy cooperatives. Agribusiness. 9(4): 351-361. Neveu, R.P., 1985. Financial statement analysis. In: South Western (ed.), Financial Management Analysis. South Western Publishing Co., Cincinnati, Ohio, U.S.A., pp 44 -76. O C P C ( Oromiya Cooperative Promotion Commission), 2004. Unpublished annual report. Addis Ababa. Ethiopia. OCPC (Oromiya Cooperative Promotion Commission), 2005. Second quarter report for the Year 2005/2006. Unpublished document, Addis Ababa, Ethiopia. O P E D B ( Oromiya Planning and Economic Development Bureau), 2000. Physical and socioeconomic Profile of 180 districts of Oromiya Region. Addis Ababa, Ethiopia.

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Owango, M, B. Lukuyu, S.J. Staal, M. Kenyanjui, D. Nujubi and W. Thorbe, 1998. Dairy cooperatives and policy reform in Kenya: effect of livestock service and milk market liberalization. Food Policy. 23(2): 173-185. Parliament, C., Z. Lerman and J. Fulton, 1990. Performance of cooperatives and investor owned firms in the dairy industry. Journal of Agricultural Cooperation.5: 1-16. Peterson, H.C. and B.L Anderson, 1996. Cooperative strategy: theory and practice. Agribusiness.12 (4): 371-383. Royer, S.J., 1995. Potential for cooperative involvement in vertical coordination and valueadded activities. Agribusiness. 11 (5): 473-481. Schroeder, L.C., 1992. Economies of scale and scope for agricultural supply and marketing cooperatives. Review of Agricultural Economics. 14: 93-103. Schroeder, B, T. Wallace and F.Mavondo, 1993. Cooperatives, statutory marketing organizations and global business strategy. Agribusiness. 9(2): 175-187. Sporleder, T.L., 1999. Capital market innovation and agricultural cooperatives. American Journal of Agricultural Economics. 81:1247-1249. Storck, H., Bezabih Emana, Birhanu Adnew, Borowiecki, A. and Shimelis W/Hawariate, 1991. Farming systems and farm management practices of smallhoders in the Hararghe highlands. Farming Systems and Resource Economics in the Tropics, Vol. 11, Wissenschaftsverlag, Vauk, Kiel, F.R. Germany. Subramani, J., 2005. Cooperative development strategy for Ethiopia: main elements. In: the Federal Cooperative Commission (ed.). Federal Cooperative Commission. Addis Ababa, Ethiopia, pp 36-37. Taimni, K.K., 2001. Cooperative in Asia: From Reform to Reconstruction. International Labor Office, Geneva, Switzerland. Techane Adugna, 2002. Determinants of fertilizer adoption in Ethiopia: the case of major cereal producing areas, M.Sc. Thesis, Agricultural Economics, Alemaya University, Ethiopia. Tefera Derbew (2004). Determinants of smallholder farmers’ demand for non-formal credit: the case of Farta woreda, M.Sc. Thesis, Agricultural Economics, Alemaya University, Ethiopia. Teferi Wondale, 2003. Trends in and determinants of fertilizer use in Gozamin woreda, Amhara region, M.Sc. Thesis, Agricultural Economics, Alemaya University, Ethiopia. Tennbark, B., 1995. Marketing cooperatives in mixed duopolies. Journal of Agricultural Economics. 46(1): 33-45. 92

Tesfaye Lemma, 1995. An analysis of cooperativisation approach to agricultural development in Ethiopia: with special attention to producers’ cooperatives. M.Sc. Thesis, University of Reading, England. Tretcher, D.D., 1999. Impact of diversification on agricultural cooperative in Wisconsin. Agribusiness. 12(4): 385-394. Wadsworth, J.J., 1991. An analysis of major farm characterstics and farmers’ use of cooperatives. . Journal of Agricultural Cooperation 6: 45-53. Wegenie Yirko, 1989. The development of agricultural producers’ cooperatives in Ethiopia: cases from Arsi region. M.Sc. Thesis, Addis Ababa University, Ethiopia. Wilkins, P.C. and T.H. Stafford, 1982, Dairy farmer evaluation of northeastern dairy cooperative. Agricultural Cooperative Society Research Report 19. USDA, Washington, D.C., U.S.A. William, J.R, S.F. Haka, M.S. Bettner and R.F. Meigs, 2003. Financial statement analysis. In: McGraw-Hill (ed.), Financial Accounting. McGraw-Hill Companies, Inc, New York, U.S.A., pp 602-645.

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7. APPENDICES

94

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

POSITION

CREDIT

COOPP

OMKAG

1

0.073

0.051

0.069

0.072

0.069

1

0.005

0.007

0.008

0.007

1

0.054

0.056

0.054

1

0.023

0.022

1

0.016

COOPP OMKAG AOS DISTRICT

AOS

DISTRICT

1

Source: Computed from the field survey

95

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

1

0.75

>13

Source: Storck et al., (1991)

Appendix table 4. Description of explanatory variables

Variables

Description

% with a

Mean ± SD

Value 1 EDUCATION

Years of formal schooling completed by

3.00 ± 3.83

household head FAMILYSIZE

Adult equivalent of the household

ONFINC

Total amount of income measured in birr that is earned from agricultural and non-agricultural

5.42±1.90 496.42±752 .36

activities MEMBERSHIP

Number of years since the farmer has been the

21.61±8.02

member of the cooperative FARMSIZE

Total area of farmland that a farmer owns in

2.11±0.99

hectare YIELD

Amount of teff the farmer obtained in quintal

15.80±13.2 6

TLSH

Total number of livestock the household own in

4.89±3.03

terms of TLU FERCREDIT

Total amount of credit the cooperative extended for fertilizer for the farmer

PATREF

696.00±522 .22

Amount of money the farmer receives from the surplus the cooperative appropriate in proportion

96

9.53±22.97

with his turnover DCFH

Distance of the cooperative from the farmer

0.33±0.51

house DDMKT

Distance of the farmer's house from the district

1.51±0.69

(main) market DISTRICT

1, if the farmer found in Adaa Liben district; 0 if

84

he found in Lume district POSITION

1, if the farmer has a position in the cooperative;

8

0 otherwise COOPP

1, if the cooperative price for teff is similar or

17

better than other marketing agents in the area; 0 otherwise CREDIT

1, if the farmer obtained credit from other micro

46

finance institution; 0 otherwise OMKAG

1, if there are other marketing agents in the area

37

of the farmer at a distance less than the cooperative; 0 otherwise AOS

1, if the farmer got other services besides supplying inputs, purchasing farm products and extending credit; 0 otherwise.

Source: Computed from the field survey data. Note: Sample Size, N= 132

97

55

Appendix table 5. Conversion factors used to estimate man-equivalent (ME)

Age Group

Male

Female

0

0

10__13

0.2

0.2

14__16

0.5

0.4

17__50

1

0.8

0.7

0.5

<10

>50 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)

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7.2. Appendix II. Survey Questionnaire Performance of Primary Agricultural Cooperatives and Determnants of Members’ Decision to Use as Marketing Agent in Adaa Liben and Lume Districts 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

99

4. Others/specify___________

6. When did you start farming for your own? (Years)_________ 7.Household membership Number

Name

Relation to Sex

Age

the HH

Main

Education

occupation

head

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

100

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 2. Shortage of ox

3. Disabled

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? ______________________________________________

101

2. Crop enterprise Crops

Area (ha)

Purpose *

Yield (Qts)

1996 1997 1996

1997

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 5. Others/ specify________________

102

3.Draft power

4.Sale

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? Crop

Total quantity sold (Qt) 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) 3. Traders in the district mkt

2. Consumers (local mkt, 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_______________________

103

7. If yes to 5, how much was the quantity sold? Crop

Total quantity sold (Qt) 1996

1997

White Teff Mixed Teff Total

II. Price for farm products 8. If yes to 2, how much was the price you received? Crop

Av. price/Qt 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? Crop

Av. price/Qt 1996

1997

White Teff Mixed Teff

104

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

105

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

106

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)

3.

Traders in the dis. mkt

2. Consumers (local mkt, dist. 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)

107

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?

108

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________________________________________

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