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Rural Development and Agricultural Extension Thesis and Dissertations
2020-10-14 DETERMINANTS OF RURAL LIVELIHOOD DIVERSIFICATION STRATEGIES: THE CASE OF LIBO KEMKEM DISTRICT, SOUTH GONDAR
Melkamu, Mengie http://hdl.handle.net/123456789/11394 Downloaded from DSpace Repository, DSpace Institution's institutional repository
BAHIR DAR UNIVERSITY COLLEGE OF AGRICULTURE AND ENVIRONMENTAL SCIENCE
POSTGRADUATE PROGRAM
DEPARTMENT OF RURAL DEVELOPMENT AND AGRICULTURAL EXTENSION
DETERMINANTS OF RURAL LIVELIHOOD DIVERSIFICATION STRATEGIES: THE CASE OF LIBO KEMKEM DISTRICT, SOUTH GONDAR
M.Sc Thesis By Melkamu Mengie
Submitted in partial fulfillment of the requirements for the degree of Master of Science in rural development management
July 2020
Bahir Dar, Ethiopia DECLARATION I Melkamu Mengie, hereby declare that the thesis entitled “Determinants of Rural Livelihood Diversification strategies in Libo kemkem District, Ethiopia” submitted in partial fulfillment of the requirements for the award of the degree of Master of Science in Rural Development Management to the Graduate Program of College of Agriculture and Environmental Sciences, Bahir Dar University, through the department of rural development and agricultural extension my original work and the matter embodied in this thesis has not been submitted earlier for the award of any degree or diploma to the best of my knowledge and belief.
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BIOGRAPHY The author was born from his father Ato Mengie Zemene and his mother W/ro Beletie Fekadu on 10 November 1984, in Amhara Regional State, South Gondar zone (Libo Kemkem woreda). He attended elementary school at Michael Debir from 1995-2003 and his secondary education school at Addis Zemen from 2004-2007. He then joined Wollo University to study Agriculture in 2015 and graduated in B.Sc. Degree in Rural Development and Agricultural Extension in July 7, 2010.
After graduation, he offers a scholarship to study MSc in Rural Development Management at Bahir Dar University in 2011-2012 EC.
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ACKNOWLEDGMENT Above all, I am glad my innumerable praise to the Almighty GOD for giving me the opportunity, capacity, and guidance throughout my life.
I am grateful to my supervisor for Dr. Benebru Assefa and co-advisor Mr. Birhanu Melesse for their valuable and constructive comments, suggestions, and the overall assistance from the early stage to the completion of this study. Without their supports and guidance, this paper wouldn’t have materialized. I would like to thank Bahir Dar University for offering a scholarship to study MSc in Rural Development Management at Bahir Dar University. The skills and knowledge acquired from Bahir Dar University help me to plan my future and many thanks to all the teachers who taught me.
I would like to allow my heart-felt thanks to my father Mengie Zemene and mother Beletie Fikadu for their moral support, encouragement and being with me in the completion of this study. Without taking their responsibility in cost covering for this study, would not be completed without their support.
Finally, respondents also deserve special thanks for their cooperation in responding to questions, warm hospitability, and because they kindly shared their views and made this work possible. Moreover, I would like to thank the leader of the two kebeles for facilitation during the during data collection period.
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TABLE OF CONTENT DECLARATION ...... i BIOGRAPHY ...... ii LIST OF TABLE ...... vii ACRONYMS AND ABBREVIATIONS ...... ix ABSTRACT ...... x CHAPTER 1. INTRODUCTION ...... 1 1.1 Background of the Study ...... 1 1.2 Statement of the Problem ...... 3 1.3 Objective of the Study ...... 5 1.3.1 General Objective ...... 5 1.3.2 Specific Objective ...... 5 1.3.3 Research Question ...... 6 1.4 Significance of the Study ...... 6 1.5 Scope and Limitations of the Study ...... 6 CHAPTER 2. LITERATURE REVIEW ...... 7 2.1 Concepts and Definitions of Key Terms ...... 7 2.2 Concept of Livelihood Diversification Strategy ...... 8 2.3. Sustainable Livelihood Framework ...... 9 2.3.1 Vulnerability Context ...... 10 2. 3.2 Livelihood Asset ...... 11 2. 3.3 Policy, Institution, and Processes ...... 12 2. 3.4 Livelihood Strategies ...... 12 2.3.5 Livelihood Outcome ...... 12 2.4 Type of Livelihood Diversifications strategies in Ethiopia ...... 13 2.5 Challenges and Opportunities of Rural Livelihood Diversification ...... 14 2.6 Empirical Studies on Determinants of Rural Livelihood Diversification ...... 14 2.7 Conceptual Frameworks ...... 16 CHAPTER 3. RESEARCH METHODOLOGY...... 17 3.1. Description of the Study Area ...... 17 3.2 Research Design ...... 18 3.3 Sampling Methods and Sampling Techniques ...... 18 3.4 Sample Size Determination ...... 19
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3.5 Method of Data Collection ...... 19 3.6 Method of Data Analysis ...... 20 3.7 Operational Definitions of the Variables ...... 22 3.7.1 Dependent Variables ...... 22 3.7.2 Independent Variables ...... 22 CHAPTER 4. RESULTS AND DISCUSSION ...... 27 4.1 Result of descriptive statistics...... 27 4.1.1 Human capital ...... 27 4.1.1.1 Sex of household head ...... 27 4.1.1.2 Education level of the household head ...... 28 4.1.1.3 Age of household head ...... 29 4.1.1.4 Marital status of the household head ...... 30 4.1.1.5 Family size of the households ...... 31 4.1.1.6 Dependency ratio of households ...... 32 4.1.1.7 Access to training...... 33 4.1.2 Financial capital ...... 34 4.1.2.1 Annual incomes of the household head ...... 34 4.1.2.2 Access to credit ...... 35 4.1.3 Natural capital ...... 36 4.1.3.1 Farm land size in a hectare ...... 36 4.1.4 Physical capital ...... 37 4.1.4.1 Livestock holding ...... 37 4.1.4.2 Market distance ...... 39 4.1.4.4 Agricultural input users of households ...... 40 4.1.5 Social Capital ...... 41 4.1.5.1 Membership in cooperatives ...... 41 4.2 Challenges and Opportunities of Livelihood Diversification Strategy ...... 41 4.2.1 Major Challenges that hinder households to diversify their livelihood ...... 41 Source field survey: 2020 ...... 42 4.2.2 Opportunities of Houshols to Diversifing TheirLivelihood ...... 42 4.2.3 Reasons for Diversification ...... 43 4.3 Determinants of Rural Livelihood Diversification Strategies ...... 44
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4.3.1 Econometric Model Results ...... 44 CHAPTER 5. Conclusion and Recommendation ...... 49 5.1 Conclusion ...... 49 5.2 Recommendation ...... 49 REFERENCE ...... 51 APPENDIX...... 56
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LIST OF TABLE
Table 1 Definition of Model Variable ...... 25 Table 2 Distribution of household’s livelihood diversification strategies in table form...... 27 Table 3 Sex composition of the household head ...... 28 Table 4 Education level of household head ...... 29 Table 5 Age composition of the household head ...... 30 Table 6 Marital status of the household head...... 31 Table 7 Family size of the households ...... 32 Table 8 Dependency ratio of the households ...... 33 Table 9 Access to training of the households ...... 34 Table 10 Annual incomes of the households ...... 35 Table 11 Access to credits of the households ...... 36 Table 12 Farm land size of the households ...... 37 Table 13 Total number of livestock holding ...... 38 Table 14 Market distance of the households in the hour ...... 39 Table 15 Agricultural input users of households ...... 40 Table 16 Member of cooperatives...... 41 Table 17 Major challenges of the household to diversification livelihood strategies ...... 42 Table 18 Opportunities of the households for livelihood diversification ...... 43 Table 19 Reason for household head’s livelihood diversification ...... 43 Table 20 Multinomial logistic reparation result of household livelihood diversification strategies ...... 45
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LIST OF FIGURE
Figure 1 Sustainable livelihood diversification strategies ...... 10 Figure 2 Conceptual frameworks of livelihood diversification strategies ...... 16 Figure 3 Map of the study area Libo kemkem, Amhara ...... 17 Figure 4 Sampling procedure ...... 18
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ACRONYMS AND ABBREVIATIONS ANOVA Analysis of Variance
ANRS Amhara National Regional State
BDU Bahir Dar University
CSA Central Statics Agency
DA Development Agent
DFID Department for International Development
FAO Food and Agricultural Organization
FGDS Focus Group Discussions
GDP Growth Domestic Product
HH House Holds
KIIs Key Informants Interview
MNL Multinomial Logit Model
MoE Ministry of education
MoFED Ministry of Finance
ODI Overseas Development Institute
SLA Sustainable Livelihood Approach
SSA Sub-Saharan Africa
TLU Tropical Livestock Unit
WB World Bank
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ABSTRACT This study examines rural households’ livelihood diversification strategies in Libo kemkem District South Gondar Zone, Ethiopia. Data were gathered employing a household survey conducted on 180 sampled households using a semi-structured household survey questionnaire. Focus group discussion and key informant interviews were also conducted to gather information on the major determinants factor and major type of livelihood diversification strategies. Multi-stage sampling techniques were used to select the study area and sample respondents. The alternative livelihood strategies used by the study households were agriculture alone, agriculture + off-farm, agriculture + non-farm, and the combination of agriculture + off-farm + non-farm activities. Descriptive statistics indicate that more than half of sample respondents (61.1%) pursue agriculture alone and agriculture + off-farm activities such as selling of firewood, charcoal and wage labor, agriculture + non-farm activities such as selling of food and a local drink, petty trading, hand crafts, and combination of agriculture + off-farm + non-farm comprise 8.3%, 27.2%, and 3.3% of households was used as livelihood strategies respectively. Multinomial logit model was employed in identifying the determinants of rural livelihood diversification strategies. From 14 hypothesized explanatory variables, seven variables were found to be a significant in determining the diversification of households’ livelihood strategies. The higher total annual incomes of household, number of household size, and access to credits have positive effect on choice of livelihood diversification strategies. However, the research result revealed that farm land size, access to fertilizer, access to training, and distance from the nearest market have bottle-necks for livelihood diversification strategies. Therefore, to solve these problem policy makers should give due attention and incorporate determinant factors of livelihood diversification in planning rural development strategies and policies. Micro finance institution should be integrate and facilitate access to credit and training create awareness for the rural households’ livelihood diversification.
Keywords: livelihood, livelihood diversification strategies, rural household, multinomial logit, on-farm, non-farm and off-farm
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CHAPTER 1. INTRODUCTION
1.1 Background of the Study Agricultural activity is an important sector for the majority of the rural populations’ livelihood in developing countries. It has been the major activity for most rural households in sub- Saharan Africa (SSA) which offers a strong option for spurring growth, overcoming poverty and improving food security (WB, 2008). Farmers in sub-Saharan Africa participate in livelihood diversification activities to increase household’s income and to maintain livelihood facing increasing climatic and economic risk (Enchebiri et al., 2017; Prowse, 2015).
Livelihood diversification is a norm in which individuals and households diversify assets, incomes and activities due to push and pull factors for realization of strategic complementarities between activities (Barrett et al 2001). This is used to restrict risk and uncertainty (Sharma, 2010). It is the process of caring out activities by rural households to serve and improve their standard of living (Weldegebriel and Prowse, 2013). In addition, Ellis (2000) also conceptualized as livelihood diversification in various ways an increases the number of income source a switch from subsistence food production to commercial agriculture, expand the importance of non-farm income on which non-farm includes both off- farm wage labor and non-farm self-employment.
Diversification of livelihood is a strategy to cope with the economic, environmental shock, and an instrument to ease poverty reduction and to reduce the household income difference, reduce the adverse impact of seasonality and provide additional income (Alobo, 2015).
In Ethiopia, agriculture serves as the primary means of rural households’ livelihood which contributes 41% of GDP, more than 80% of employment opportunities created and 90% of the foreign exchange earning of the country (MoFED 2016). Nevertheless, farming as a primary source of income has become failed to guarantee sufficient livelihood (Babatunde, 2013).
Like the other world, rural peoples in Ethiopia diversify their asset, income, and activity due to push and pull factors. They diversify their livelihood through on-farm, non-farm, and off- farm income generating activity. On-farm income is income generated from crop and
1 livestock on owners' of farm land and off-farm income is temporary wage or exchange labor on other farms within agriculture (Weldegebriel and Prowse, 2013).
Furthermore, livelihood diversification is believed to be a solution, and an effective strategy for the reduction of poverty and food insecurity in rural Ethiopia (Yenesew, et al., 2015). Enhancing crop production is considered as a solution at all levels to improve the lives of rural people so that effort and intervention of the community to ensure food security focuses on agriculture sector.
However, farming on its own is increasingly unable to provide a sufficient means of survival in a rural area. Hence families tend to diversify occupation buffer the risk of bad weather, land constraint, and other problem that affect both crop and livestock production. They are usually engaged in multiple activities both with agriculture and non-farming sectors (Demisse and Workneh, 2004). Rural households engage and practice various non-farm livelihood activities to cope with vulnerability and risks such as drought Gebiru (2012).
Non-farm activities have the potential to support households reduce poverty by offering them a form of insurance against the threat of farming and minimizing reliance on natural resource. In most developing countries, the importance of non-agricultural activity is increasing and is estimated to account for 30-50% of rural incomes Haggblade (2010).
In Ethiopia, an empirical study found that estimated from non-farm income account for 40- 45% of the average household income Bezabih (2010). In addition to this, empirical study consistently shows that diversification to non-farm livelihood strategies enables farm household to have better incomes, enhances food security, and increase agricultural production by smoothing capital constraints and help to cope with environmental stress WB (2014).
Amhara is the second largest region next to Oromia in Ethiopia. Its population is largely dependent on agriculture about 85% of rural populations are engaged in agricultural activities as a primary occupation. Only 15% of populations were participated in non-agricultural activity Beleynew et al (2018).
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According to Libo Kemkem district agricultural office report (2017), the livelihoods of rural households in Libo Kemkem district are primarily based on subsistence agriculture. This subsistence has been and is facing a challenge such as drought, insects, population growth, shortage of arable land, and less access to irrigation. In this area, farmers are mainly engaged in mixed farming systems and also rely on the production of rain-fed cereal crops such as (barley, wheat, sorghum, been, finger millet, potato, Teff, and flax) and livestock production as a major livelihood strategy.
1.2 Statement of the Problem Ethiopia, a country with famine prone agriculture in sub-Saharan Africa has a long history of famine and food shortage. The food insecurity situation of the country has been increasing and the estimated number of food-insecure people increased from 5.6 million in 2016 to 8.5 million in 2017 ( FAO, 2017).
Regularly, Ethiopian people are occupied in agriculture as a means of livelihood and account for 31.19% of the GDP WB, (2018). However, the sector has been continually failed to meet the growing food need of the rural population. A major number of people suffer from food shortages and poverty. The cause of food insecurity for Ethiopia is drought, population growth, environmental degradation, the small size of land holding, lack of improved technology, and lack of credit access, and absence of livelihood diversification to the non- farm and off-farm activity (Tezera, 2010).
In Ethiopia, policy makers were favoring agriculture as a means of rural economic development for a long time, which excludes rural non-farm activities from much attention and support, there by ignoring an important source of livelihood. Tassew (2002), Reta, (2010). Lack of access to non-farm and off-farm activities are possibly a major cause for low coping and adaptive capacities of households in times of food security crises. Livelihood diversification is viewed as a response to the failure of agriculture to provide an adequate livelihood for a significant share of rural inhabitants. So, diversification remains crucial for tackling food insecurity irrespective of the form it may take either farm-based, off-farm/non- farm or mixed (Allison, 2004).
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According to Melese et al., (2019) study in East Gojjam Zone, the determinants of rural households livelihood diversification strategies were access to credit service, total annual income and total household size have a positive effect on choices of livelihood diversification strategies; while market distance, age, total livestock holding and dependency ratio of the household head have a negative effect on choices of livelihood diversification strategies. However, the study was not included access to training of the households, memberships of cooperatives, access of agricultural input, and the marital status of the household heads. These factors were determined the livelihood diversification of rural households in the study area.
According to Ambachew et al., (2016) empirical examine the determinants of rural households livelihood diversification strategy in South Gondar Zone were determined by gender, education, dependency ratio, credit access, proximity to town and market, agro- ecological zone, and access to electricity positively and age, cultivated land size, and extension agent training and frequency of contact also negatively determined Geremew et al., (2017). Both Ambachew and Geremew was studied the determinants of livelihood diversification strategies at zonal level which was not looked at a specific area. Thus emphasized the determinants of livelihood diversification strategies at zone level and didn’t classify determinants of livelihood diversification according to socio-economic variables, land characteristics, and demographic variables. This classification is very important because the variables in each classification vary from place to place or community to community.
Agriculture is the dominant economic activity and the primary source of livelihoods for the rural households in the study area with its problems of high population growth, diminishing farm land size, erratic nature of drought, failing of agricultural production through over time. According to Libo Kemkem woreda food security office (2018) reported that the woreda has 33 rural kebeles. Out of 33 rural kebeles, 23 kebeles are food insecure and the most vulnerable among others that are classified as drought-prone and highly food insecure. Particularly, the chronic food insecure population of the woreda has included under productive safety net program.
The livelihood of the rural households in the study area is primarily based on the subsistence stage, vulnerable, diverse, and risk-prone. It is also characterized by severe drought, small land holding, high population growth, lack of irrigation accesses, and highly dependent on
4 rain-fed cereal crop productivity which has low economic returns and unable to feed round their household members Arega et al., (2013).
The food security situation in the study area is disturbing. Majority of subsistence households faced five moths food insecurity in nearly all staples every year, especially around Jun when all crops would have planted. Ironically the time in the year where subsistence households undergo a lot of hard work in land preparation and weeding on their farm coincides with the time they have less to eat, making them vulnerable to disease which comprises their ability to labor and its attendant effect on low yields and incomes. The resultant effects of ill-health, low income, and food insecurity have three dimensional effect on the livelihoods of subsistence farmers which entrench them in poverty. In the face of these numerous challenges subsistence farmers adopt several livelihood diversification strategies to ensure their survival and improved standard of living.
The empirical evidence shows that the determinants of livelihood diversification strategy in the study area were less researched. According to Mossa, (2013) studied the poverty and livelihood strategies of female headed households in the study area. However, the studies have not seen the older households’ livelihood strategies. The elder households are mainly observed that more exposed to food shortages and vulnerability to chronic poverty. Therefore, the study contributes to filling these gaps by focusing on the major type of livelihood diversification and determinants of livelihood diversification strategies in Libo Kemkem district. The ultimate goal of livelihood diversification is, therefore bringing sustainable livelihood outcomes such as securing more income, improved food security, reduced vulnerability, and increase the wellbeing of households.
1.3 Objective of the Study
1.3.1 General Objective The general objective of the study is to assess rural livelihood diversification strategies in Libo Kemkem district.
1.3.2 Specific Objective To identify the factors of rural livelihood diversification strategies in the study area
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To assess the challenges and opportunities of rural livelihood diversification strategies in the study area
To assess the types of livelihood diversification strategies in the study area
1.3.3 Research Question What are the determinants factors of rural livelihood diversification strategies in the study area?
What are the major challenges and opportunities for rural livelihood diversification strategies in the study area?
What are the types of rural livelihood diversification strategies in the study area?
1.4 Significance of the Study This study will help to identify the determinant factors of the households in livelihood diversification strategies and could improve the coping mechanism of farmers. The study should provide basic information about the existing challenges in the development of rural livelihood diversification strategies in the study area. Besides, institutions or individuals who will be interested to know the utilization of the rural livelihood diversification strategies in the study district can use the document as a reference.
1.5 Scope and Limitations of the Study
The researcher tried to investigate the practice of rural livelihood diversification strategies in Libo Kemkem Woreda in South Gondar Zone. The study concentrates to the determinant factors, types of livelihood diversification strategies, and about challenges in the study area.
In Libo Kemkem Woreda, there are 33 rural Kebeles. However, due to limited resources (finance and time), the study was restricted to only two rural Kebeles. Hence, the researcher was limited to sample household heads from the two Kebeles for household survey, inquiry of the problem, and time constraint. These studies focused on the determinants of rural livelihood diversification strategies in the study are.
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CHAPTER 2. LITERATURE REVIEW
2.1 Theoretical Review Livelihood is defined as adequate stocks and flow of food and cash to meet basic need. Security refers to secure ownership of, or access to, resource and income earning activities including reserves and asset to offset risk, case shock and meet contingencies. A household may be enabled to gain sustainable livelihood security in many ways through ownership of land, livestock or tree, right to grazing, fishing, hunting or gathering through stable environment with adequate remuneration Robert et al, (1991).
Livelihood diversification is one of the rural livelihood strategies. Different academics and development agents define the term livelihood diversification differently. According to Hussein and Nelson (1998), livelihood diversification refers to attempts by individuals and households to find new ways to raise incomes and environmental risk, which differs sharply by the degree of freedom of choice (to diversify or not), and the reversibility of the outcomes.
2.2 Concepts and Definitions of Key Terms A livelihood comprises the capabilities, assets (stores, resources, claims, and access) and activities required for a means of living. A livelihood is sustainable which can cope with and recover from stress and shocks, preserve and enhance its capabilities, assets, and provide sustainable livelihood opportunities for the next generation; and which contributes net benefits to other livelihoods at the local and global levels and in the short and long term (Chamber and Conway, 1992). Livelihood activity diversification is vital to the survival strategy for rural households in developing countries like Ethiopia. Although agriculture still has a central role in the economy, farming is on its own increasingly unable to provide a sufficient means of survival in the most rural areas. Briefly, one could livelihood as a combination of the resources used and the activities are undertaken to live. The members of a household combine their capabilities, skills, and knowledge with the different resources at their disposal to create activities that will enable them to achieve the best possible livelihood for themselves.
The concept of livelihood is widely used in contemporary writings on poverty and rural development, but its meaning can often appear elusive either due to vagueness or to different definitions being encountered in different sources (Ellis, 2000). A livelihood comprises
7 incomes in cash and in-kind, the social relation and institution that facilitate individuals or family standard of living, and access to social and public services that contribute to the well- being of the family. Everything that goes towards creating that livelihood can be thought of as a livelihood asset the major livelihood assets are human capital like age, education, sex, family size and dependency ratio, etc. Physical capital comprises the basic infrastructure and producer goods needed to support livelihood social capital refers to the network and connectedness. Financial capital like saving, credit, and remittance from family members working outside the home and natural capital which are the natural resource stock that are land, water, air, etc.
2.2 Concept of Livelihood Diversification Strategy In this study, livelihood diversification refers to a means attempts any one individual and households to find new ways to raise their incomes and reduce environmental risk as well as shapely by the degree of freedom of choice (to diversify or not). Therefore, strategies are including on-farm, non-farm, and off-farm activities which support to generate income additional to that of the main household agricultural activities, via the production other agricultural and non-agricultural goods and services, the sale of waged labor, or self- employment in small firms, and other strategies undertaken to spread risk (Delil, 2001). Individuals and households that can be diversified livelihood portfolio in different ways.
Several classifications of activities included in rural livelihood portfolio have been proposed by (Ellis, 2000; Reardon and Webb, 2002). Focus on different criteria (farm vs. non-farm, on- farm vs. off-farm activities, local vs. migratory, and self-employment vs. wage labor). All these classifications are useful to make sense of nature of choices entailed by rural livelihoods diversification.
In this classification, a labor force payment refers to the provision of agriculture wage work or non-agricultural activities owned by non-household employers. So sometimes employment opportunities are available local and practiced as part of a rural livelihood diversification strategy in the type of wage labor seldom entail a full remittance of the rural worker. Remittances of temporary or part-time rural wage labor very often complement an insufficient on-farm production in ensuring the satisfaction of household consumption need (Alain De Janvry 1981). Rural self-employment enterprise refers to activities undertaken by mobilizing
8 labor plus other household capital asset (saving, land, etc). Rural agricultural enterprise is based on innovative on-farm agricultural activities. On the other hand, rural non-agricultural activities are focus on activities such as processes of agricultural or forestry commodities, petty trading, and hand craft, etc.
2.3. Sustainable Livelihood Framework Sustainable livelihood is built on five principle categories of livelihood assets, the pentagon to emphasize their interconnections and the fact that livelihood depends on a combination of assets of various kinds and not just one category. An important part of the analysis is to find out peoples access to different types of assets (physical, human, financial, natural, and social) and their ability to put these to productive use. In standing of this framework offers a way of assessing how the household head, individuals and communities are form livelihoods, both by determining who gains access to which type of asset, and defining what range of livelihood strategies are open and attractive to people (Carney, 1998). The value of using a framework like this, according to Department for International Development (DFID), is that it encourages users to take a broad and systematic view of the factors that cause poverty whether these are shocks and adverse trends, poorly functioning institutions and policies, or a basic lack of assets and to investigate the relations between them. It does not take a sectoral view of poverty but tries to reconcile the contribution made by all the sectors to building up the stocks of assets upon which people draw to sustain their livelihoods. The aim is to do away with preconceptions about what exactly people seek and how they are most likely to achieve their goals and to develop an accurate and dynamic picture of how different groups of people operate within their environment’ (DFID 1999).
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Figure 1 Sustainable livelihood diversification strategies
Key H = Human Capital S = Social Capital N = Natural Capital P = Physical Capital F=financial capital Livelihood assets Livelihood
Structure outcome Vulnerabil F Level of Livelihood More ity context H governme Diversification S nt Strategies outcomes Shocks Privet Agriculture Improve sector food Trends only, non - farm P Law security N & off- ffarm Policies Seasonality Reduce Culture vulnerabilit
y
Source: DFID (2000) developed the widely accepted sustainable livelihood framework (SLF).
2.3.1 Vulnerability Context Vulnerability context refers to seasonality, trends and shock that affect people’s livelihood and have a direct impact on people’s asset status and the option that are open to them in pursuit of beneficial livelihood outcomes. Both exposures to unfavorable development like rainfall or livestock loss would cause considerable harm to livelihood as well as the lack of means to cope with losing the households' livelihood base (DFID, 2000). The vulnerability context relates to the external environment can affect the susceptibility to poverty and consequently the potential for livelihood sustainability. It is described in term of shock (sudden death, drought, and conflict, and wars, accidents, Underling the SLA is the theory that people draw on arrange of a capital asset to further their livelihood objective (DFID, 1999; FAO, 2002). flood, etc), trend (in this cause change in populations, diseases,) and seasonality. All of this describes circumstances in which people exist and over which they have limited FAO, (200).
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2. 3.2 Livelihood Asset Underling the SLA is the theory that people draw on arrange of a capital asset to further their livelihood objective (DFID, 2002:3). Assets are categorized into social (social network and relationships of trust), human (skill, knowledge, age and labor), natural (natural resource stock) physical (transport, shelter, water, and energies) and financial (saving, credit, and income), etc.
Natural capital: natural capital is the term used for the natural resource stock (soil, water, air, genetic resources, etc.) and environmental services (hydrological cycle, pollution sinks, etc) from which resource flows and services useful for livelihoods are derived.
Human capital: human capital is education, skill, knowledge, ability to work and good health important for the successful pursuit of livelihood strategies (Ellis, 2000). The major human capital determinants of livelihood diversification were sex, age, family size, education level, agricultural extension visits and access to training.
Physical capital: physical capital comprises the basic infrastructure and tools and equipment needed to be productive in buildings infrastructures, distance from nearest to market (Ellis, 2000).
Financial capital: it is cash; credit /debit and saving or financial assets are organizational income, access to credit grant, or saving. Financial capitals are financial resources includes the deposited in a bank or liquid assets such as jewelry, livestock, and financial institution (Davidson et al., 2014).
Social capital: the social resources (networks, social claims, social relations, affiliations, associations) upon which people draw when pursuing different livelihood strategies requiring coordinated actions. To create livelihoods, therefore, people must combine the ‘capital’ endowments that they have access to and control over. These may be made up of personal capabilities, tangible assets (e.g. stores and material resources), and intangible assets (claims and access) (Conway 1992).
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2. 3.3 Policy, Institution, and Processes Policy and institutions represent an important source of external factor that influence the livelihood of people, through influencing access to asset and reducing vulnerability to shocks, positive livelihood outcomes can be produced (FAO, 2009). For instance, institutions that influence livelihood outcomes include formal membership organizations (cooperatives and registered groups), informal organizations (exchange labor groups or rotating savings groups), political institutions (parliament, law and order or political parties), economic institutions (markets, private companies, banks, land rights or the tax system), and socio-cultural institutions (kinship, marriage, inheritance or religion) (FAO 2009).
2. 3.4 Livelihood Strategies According to Scoones (1998:7), livelihood strategies are classified into three broad clusters in the sustainable livelihood framework.
These include agricultural intensification/extensification, Livelihood diversification, and migration. As option for rural people are either to gain more livelihood activities from agriculture through the process of intensification (more output per unit area through capital investment or increase labour inputs) and extensification (more land under cultivation), and to diversify a range of off-farm income-earning activities and they move away and seek a livelihood either temporary or permanently elsewhere.
2.3.5 Livelihood Outcome Livelihood outcomes is the results in rural household’s livelihood strategies to feed back into the vulnerability context and asset bases, with successful strategies allowing them to build asset bases as a buffer against shocks and stresses, as opposed to poor livelihood outcomes which deplete asset bases, thereby increasing vulnerability (ODI, 2002).The most basic livelihood outcomes relate to satisfaction of elementary human needs, such as food, water, energy, shelter, clothing, sanitation, and health care. The ultimate outcome is to achieve the preservation of the households and to provide the next generation with desirable quality life (DFID, 2000).
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2.4 Type of Livelihood Diversifications strategies in Ethiopia According to Ellis (2000:3) livelihood activity can be categorized into three types namely, on- farm, off-farm, and non-farm. On-farm activities are activities, which are directly related to agricultural production focused on both crop production and animal husbandry activity. Non- farm activities are activities that tack place outside agriculture (non-agricultural wage, self- employment, rent income transfer, and remittance).
An off-farm activity refers to agricultural activities a person who, engaged in agricultural wage apart from his own farm land (mainly, charcoal and extraction of natural resource and selling). Ethiopian people are a rural and agrarian society where nearly 85% of the populations are directly dependent on agriculture and livestock for their livelihood. Agriculture is the base of the economy and it accounts for about 51% covered in the total foreign exchange earnings (MoFED, 2010).
The main types of farming activities are crop production, livestock husbandry and mixed farming. Mixed farming is the dominant type of farming system and includes both crop production and animal husbandry. In Ethiopian, agricultural productivity is found to be low even though the country has implemented various agricultural policies. These policies formulated so far do not incorporate non-agricultural livelihood strategies under the policy framework as they have focused on merely agricultural development and strategy (Geremew et al 2017).
Policy focus is also to increase agricultural productivity and farm income to attain food self- sufficiency at a national, regional, and household level. significant resources has been spent on agricultural research and extension to alleviate food shortage in the nation while research and extension activities have not been done adequately on the issues related to off-farm and non-farm employment (Blaineh, 2013).
Nonetheless, due to many reasons rural livelihood and rural communities could pursue alternative livelihood strategies to ensure the income and food security of their household member. The increasing population growth in rural Ethiopia obliged households to cultivate and make their living on the extremely small size of land. Unlike many studies that show their
13 strict focus on agricultural intensification and extensification, there is a growing literature dealing with rural non-farm livelihood issue in Ethiopia Demisse and Workneh, (2004).
According to Woldehana and Oskam (2001), increasing the availability of off-farm and non- farm activities and improving the wage rate received by farm households can expand and economic activity of the Tigray Regional State. Hence the underlying factors that hider participation in non-farm activities such as credit constraint and technical training.
According to Tenaw and Mengistu (2016), major livelihood diversification activities were crop and livestock production, petty trading and remittance. Besides making charcoal, daily laborer, contraband trading, wage, and handcraft were livelihood diversification activities of rural households.
2.5 Challenges of Rural Livelihood Diversification According to different literature for example (Tassew, 2001; Mulat, 1997; Josef, et al 2008; Weldebrhan, 2013) the challenges include technological, institutional, infrastructural (the low quality and insufficient supply of roads, electrical power, and telephone lines), lack of sufficient initial capital, lack of adequate start-up skills, lack of raw materials and absence of market demand for products and cultural factors are existing.
2.6 Opportunities of Rural Livelihood Diversification According to Brhanu (2016), there is no consensus on factors that affect participation decisions in off-farm activities in Ethiopia. In poor rural areas, some households will make a positive choice to take advantage of opportunities in the nonfarm livelihood economy, taking into consideration the wage differential between the two sectors and the riskiness of each type of employment. Rising incomes and opportunities off-farm then reduce the supply of labor on-farm. However, other households are pushed into the non-farm sector due to a lack of opportunities on-farm, for example, as a result of drought or the small size of land holdings. This may result in a similar pattern of rising non-farm incomes.
2.7 Empirical Studies on Determinants of Rural Livelihood Diversification In Ethiopia, different determinants of rural livelihood diversification strategies were identified. Those determinants were revolved around five livelihood assets namely, human,
14 financial, social, natural, and physical capital. Various scholars distinguish different determinant factors, which influence livelihood diversification strategies based on their inferential statistics results. Nevertheless, some of the scholars did not reason out why different determinants affect farmer‟s livelihood diversification.
For instance, (Devereux 2000) found out that most Ethiopians are “subsistence farmers” who have been forced to diversify into off-farm incomes to bridge their annual consumption gap, while some are effectively landless and depend entirely on non-agricultural sources of food and income, including food aid. The typical rural livelihood strategy combines crop and livestock agriculture, off-farm income-generating. Ellis identifies seasonality, risk, labor markets, credit substitution, and asset strategies (investment to enhance future livelihood prospects e.g. developing networks, education) as factors that might induce voluntary motives for the adoption of diverse livelihoods (Ellis, 2000).
According to Wondim (2018), in Ethiopia identify the determinants that affect rural livelihood diversification were land holding size, sex, age, education level, agricultural extension visit, farmer association, access to credit, and market distance. However, there were contradictory findings on the determinants of livelihood diversification. In addition, some of the scholars did not reason out model outputs on livelihood diversification. Some of the major challenges which affect rural livelihood diversification were lack of capital, poor infrastructures, lack of access to credit service, lack of access to market and marketing service, lack of job opportunities, and farm land scarcity. However, most of the studies lack detailed information on each diversification strategy rather than generalization on livelihood diversification strategies.
According to Baharu (2016), study in the case of Kembata Tambaro Zone, make out small farm land size and market distance have a strong influence on rural livelihood diversification. The econometric analysis demonstrated that the education of household head, increased number of non-farm activities, credit facilities, and market distance enhanced livelihood diversification.
According to Dessalegn (2016), in Hadiyya Zone generally, the determinants of household participation in diversified livelihood activities in the area were: total land holding, education
15 level of the households, remittance-receiving, and regularity of development agents’ contact, total households size, dependent family size and access to credit determined livelihood diversification. Rural livelihood diversification has generally occurred as a result of increased importance of off-farm wage labor in household livelihood portfolios or through the development of a new form of on-farm production of non-marketable commodities.
2.7 Conceptual Frameworks Figure 2 Conceptual frameworks of livelihood diversification strategies
Natural capital Farm land size Social capital Human capital, age, sex,
membership of education level, family cooperatives size, marital status, Livelihood access to training and diversification strategies dependency ratio
Only agriculture
Ag + non-farm Physical capital Financial capital Ag +off-farm agriculture input access of credit and (fertilizer and improve annual income Ag+ non-farm +off-farm seed), market distance and livestock holding
Source developed from DFID s sustainable livelihood framework (1999).
As it is shown in the above Figure, the study was identifies the challenges, determinant factors and the major types of livelihood diversification in a rural households. The determinants were livelihood assets such as human capital (skill); financial capital (credit access), physical capital (infrastructure), natural capital (farm land size), and social capital takes place in the rural households to understand the decision to diversify their livelihoods into off/non-farm activities. In the context of this study, off-farm and non-nonfarm livelihood diversification is the engagement of households on the non-farm sector for different purpose to produce income, self-employment and waged-employment.
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CHAPTER 3. RESEARCH METHODOLOGY
3.1. Description of the Study Area
Figure 3 Map of the study area Libo kemkem, Amhara Source: Libo Kemkem Woreda land administration office, 2020
Libo kemkem Woreda is one of the words in South Gondar administrative Zone, Amhara regional state. Geographically, the woreda is located from 11057′44.6"N-12025′32.6"N and 37 034′4.89"E-3803′30.9"E (Askebir, 2006). The Woreda is bordered by West Belessa Woreda in the North, Ebenat Woreda in the East, Fogera Woreda in the South, and Lake Tana and Gondar Zurie Woreda in the West. The total area of the Woreda is 1081.57km2 sub- divided by 33 Kebeles, of which 29s rural Kebeles. Addis-Zemen town, the administrative center of the Woreda, is located on the main road of Addis Ababa-Gondar and is far 67kms from south Gonder administrative zone, 85 km from Bahir Dar and 645Kms from Addis Ababa. According to Libo Kemkem district plan commission office (2012) reported that the
17 district has a total population of 233, 311 out of which 118,109 were males and 115,202 were females.
3.2 Research Design This research is a cross-sectional study. The study is aimed at collecting data at one point in time and describing the study population rather than showing the patterns of change that might be witnessed over time.
3.3 Sampling Methods and Sampling Techniques Sampling technique is a system of sample selection from a large population to get information about those large populations from the sample observation by statistical technique. Multi- stage stratified sampling technique was used for this study to get good representative sample. In the first stage, based on Libo Kemkem Woreda food security office information, the researcher stratified the district Kebeles into two such as food secure and insecure kebeles based on traditional agro-ecological zone. In the second stage, from-food insecure Kebeles two of them were selected randomly based on traditional agro-ecological zone such as Mantogera (Qolla agro-ecology) and Maytad (Dega agro-ecology). In the third stage, based on random sampling methods with the help of the list of household heads that are found in each selected Kebeles Agricultural development agent (DA) office, the respondent were selected randomly by using lottery methods.
Figure 4 Sampling procedure
Libo kemkem woreda has 33 rural kebeles
23 kebeles are food insecure
Maytad kebele Dega agro ecology Mantogera kebele Qolla agro ecology N2= 657 HH N1= 821 HH
=80 100 180= sample
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3.4 Sample Size Determination The total sample size was determined according to the sampling formula provided by Yamane (Yamane, 1967:886). The formula will be used for sample determination:
n = n = = 180 ( ) ( . )
The 180 respondents were selected by using proportionate sampling technique from the two sample kebeles.
× × Maytad kebele = = =100
× × Mantogera kebele = = =80
Where: n= Sample size, N= Population size and e = error margin (0.07) desired level of precision for a 95% confidence level
3.5 Method of Data Collection To conduct this study, both primary and secondary source of data were used to achieve its core objectives. The nature of the data is both qualitative and quantitative.
The sources of primary data were sample household head, key informants (KIIs), and focus group discussion (FGD). The primary data were collected through personal and face-to-face interview using schedule. It was designed to collect data on demographic, socioeconomic, physical, financial factor related to the household’s livelihood diversification strategy in the study area.
Qualitative data were collected through focus group discussion and key informant interview. Two group discussions (8, 8 individuals in each group and two FGDs for each Kebele) were carried out in the two Kebeles. The discussions were focused on the major types of livelihood strategies and the determinant factors of livelihood diversification strategies. Key informant interviews (KIIs) were conducted with four different Kebele officials. Two of them were the voluntary agricultural extension workers in the two Kebeles and two Kebeles chair person. The discussions were focused on the major challenges to diversify, the major type of
19 livelihood diversification strategy, and the vulnerability of the alternative livelihood diversification.
Secondary data were collected from books, articles, research journals, and different reports. These grasp the background information, descriptions of the study area, and experiences that could be supported to look and understand the issues under inquiry.
Key informants were selected outside of the total respondents. It includes in the survey samples that warm and trustful relationships were established with these individuals and information gathered through individual interviews. The working language in the region is Amharic and the researcher is a speaker of the language, there was no problem during the time of communicating with them to record the data and to understand their idea in the field of the study. The field survey was conducted from January 15, 2012, to february15, 2012, E.C.
3.6 Method of Data Analysis Both descriptive statistics and econometrics methods of data analysis were used to achieve the objective of the study. Descriptive statistics were used to compare and contrast different categories of sample unite concerning desired characteristics. The methods used for quantitative data analysis were mean, percentage, t-test, f-test, and one way ANOVA, used for continuous variable while the chi-square test was used for categorical variable.
For econometrics analysis a multinomial logit model was used. To analyses the second objective the determinant factors of rural livelihood diversification strategies. Moreover, based on the work of Tassew and Oskam (2001), the maximum utility model of households from different activity diversification can be specified as follows:
Let Uij denotes the utility that the household i gets from choosing alternative livelihood activity j and
= + = + …………………………………………………… (1)
Where j= the coefficient of covariates which varies across alternatives
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j= the covariates which remain constant across alternatives; and
= a random disturbance term, and unobserved attributes of alternatives.
Let the jth livelihood activity that the ith household chooses to diversify its value could take the value 1 and 2 otherwise. Therefore, J category of livelihood diversification strategies of the ℎ household for this study is categorized as follows
1 = Agriculture only (crop production and livestock rearing) as reference outcome
2= Agriculture + Off-farm activity (which includes agriculture plus daily labor work (wage), renting of asset (land, ox), firewood wood sale and trading of livestock)
3= Agriculture + Non-farm activity (which includes hand craft, small business trade and remittance (from abroad)
4= Agriculture + Off-farm + Non-farm (which includes all above livelihood strategy).
The probability a household with characteristics x chooses the livelihood diversification j, modeled as multinomial logit. The model is selected because the responses of households for livelihood diversification will be expected to be polytomous. Logistic regression can be extended to handle polytomous responses. Therefore, the probability, Pij is modeled as: Then multinomial logit model can be written as:
exp(x′iβj) Pij= exp (xi j) pij = j …………………………………………………… (2) j 0 exp (x′iβj)
With the requirement of ∑ 0 Pij = 1 for any i Where Pij = probability representing the respondent’s chance of diversifying into livelihood activity j
X = Predictors of response probabilities
j = Covariate effects specific to ℎ response. Then through normalization the model, it is assumed that 1 =0 (this arises because probabilities sum to 1, so only J parameter vectors are needed to determine the J + 1 probability), (Galab et al 2002, as cited in Dessalegn 2016:34)
21 so that exp (Xi 1) =1, implying that the generalized equation (2) above is equivalent to
( ) 1 = 3 , for (j = 1, 2, 3,) and 1 = ………….. (3) 1 exp (x′i j) 1 1 1 exp (x′i j)
3.7 Operational Definitions of the Variables
3.7.1 Dependent Variables The dependent variable is livelihood diversification strategies. Multinomial logit model is used in the study classifying smallholder farmers’ livelihood diversifications strategies into four (Agriculture only, Agriculture + off-farm, Agriculture + non-farm and Agriculture +non-farm + off-farm).
Agriculture only: are activities, which are directly engaged in agricultural production focused on both crop production and animal husbandry activity.
Agriculture + Non-farm activity is an activity, which includes hand craft, small business trade and remittance besides agriculture.
Agriculture + Off-farm activity refers to agricultural activities, plus engagement in agricultural wages apart from his farm land (agricultural plus daily labor work, renting of asset, firewood sale and trading of livestock).
Agriculture + Non-farm+ Off-farm (which includes all above livelihood strategies)
3.7.2 Independent Variables The independent variables of this study were family size, age of household, sex of household, education level, dependency ratio, size of farm land, livestock holding, market distance, access to training, marital status of the household, membership of cooperative, input use, total household income and access to credit explanatory variables were hypothesized as a factor to determine farmers decision to participate in different livelihood diversification is explained as follows.
Land size: land size is the basic asset for the majority of rural livelihoods. Farm households having more farm land size were forced to follow agricultural extensification rather than diversification (Yizengaw et al, 2015). Farm land size is hypothesized negatively impact on livelihood diversification strategies (Anshiso, 2016).
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Access to fertilizer and improve seed: this variable is one of the determinant factors to diversify livelihood diversification strategies in rural household. It expected to hypothesize negatively correlation with response variable Said, (2016). Because, farmers could use different agricultural inputs such as fertilizer and improve seed to increase the productivity of crops and generate more income, so that they satisfy their family requirements.
Household size: due to the presence of large families to practice multiple activities as a household laborer to diversify their livelihood strategies. Family size is expected to have positive effect on livelihood diversification strategies Melesse, (2018).
Education level: education level influenced positively the household’s livelihood diversification, since they may have better skilled (Debela and Desta, 2016).
Age of household: as the age of household head increased, the farmer will getting older and could not be capable of diversifying and more likely to concentrate on-farm activities for their subsistence. According to Asfir (2016), age affects livelihood diversification negatively since old farmers were well established, more experienced in agricultural production, more resistant to new ideas and information hence less likely to diversify their livelihood.
Sex of household: sex is one of the determinants of livelihood diversification. Men and women have different access to resources and opportunities (Ellis, 2000). As expected sex of headed is positive effects on livelihood diversification strategies Ambachew, (2016).
Access to training: trainer farmers have better skills, knowledge, and experience to improve agricultural production and productivity for fulfilling their family requirements (Asfir, 2016). It had a negative effect on livelihood diversification strategies.
Marital status: marital status is one of the determinant factors that affect households to diversify their livelihood to the non-farm activities. Most of the time female headed households had a better engagement in non-farm activities selling of local drink and cooked food. While male household head have seen to choose Agriculture and off-farm activity diversification to fulfill basic need of the house. It has a positive effect on livelihood diversification strategies.
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Access to credit: access of credit is one of the important institutional factors that have a positive effect on livelihood diversification. Hence, providing credit for resource poor farmers will enhance livelihood diversification (Debele and Desta, 2016).
Tropical: this is one of the determinant factors and a negative effect on livelihood diversification. Hence farmers with a large number of tropical livestock units were less likely to diversify livelihood than those who own small number of TLUs due to better opportunity to earn more income from livestock production (Asfir, 2016).
Annual income: total annual income affects household livelihood diversification positively (Gecho, 2017). Therefore, households having large cash income were more likely to diversify livelihood into non/off-farm activity.
Market distance: market distance negatively affected households’ income diversification activity. As market distance increase from home, farmer’s non/off-farm income diversification will be discouraged (Gecho, 2017). The farmers having near market possibility to selling out their labor to the nearest market maximize their income and to smooth their annual consumption during the slack crop production period, promote rural-urban linkage and develop the entrepreneurial skill of farm households to diversify their livelihood.
Dependency ratio: It determines the participation of individuals in the labor market, the expenditure and investment in the social sector. The existence of a large number of children below 15 ages and above 65 ages of the households could affect poverty. Children may necessitate greater income to support their basic needs and elders also need greater labor than contributing directly to the productive role. Therefore, the dependency ratio was hypothesized to negatively affect household decision to participate in existing livelihood strategies Desalegn, (2016).
Membership to cooperatives: it represents whether household head is members to cooperatives or not. Cooperatives worldwide are committed to the concept of mutual self- help. This makes them natural tools for social and economic development, and provides significant additional benefit to communities and social systems. Formal as well as informal associations, such as indigenous cooperation groups, enforcing widely agreed standards of behavior, and uniting people with bonds of community solidarity and mutual assistance.
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Membership to cooperatives also will increase households’ access to services that might be granted by being member. This variable was expected to be positively related to livelihood diversification and means for obtaining different employment opportunities (Asfir, 2016).
Table 1 Definition of Variable
No Definition of dependent variable Code Measure Unordered categorical variable ment 1 Livelihood diversification strategies Agriculture alone 1 No of participa nts Ag+Off- farm 2 Ag+Non-farm 3 Ag+Off 4 farm+Non-farm 2 Definition of Explanatory Variable Character Expected sign 1 Sex of HH Dummy Male=1 + Female=2 2 Access to a credit utilization of HH head Dummy Yes =1 + No =2 3 Membership of cooperatives Dummy Yes=1 + No=2 4 Input users of HH (fertilizer and improve Dummy Yes=1 - seed) No=2 5 Access to training of the HH head Dummy Yes=1 - No=2 6 Marital status of the HH head Categorical 0=single + 1=married 2=divorced 3=widowed 7 Education level of the HH head Categorical 0=no read & + writ 1=grade 1-4 2=grade 5-8 3=grade 9- 12 8 Age of the HH head Continuous Number of - years
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9 Family size of the HH Continuous Number of + family members 10 Dependency ratio of the HH Continuous Number of - dependents 11 Farm land size Continuous Hectare - 12 Distance from the market Continuous Hour - 13 Total livestock holding Continuous No of - livestock 14 Annual income Continuous in birr +
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CHAPTER 4. RESULTS AND DISCUSSION
4.1 Result of descriptive statistics In the study area, there are four types of livelihood diversification strategies that rural households have adopted to achieve their livelihood outcome. Especially, as it is shown in table 2, the categories that households pursue in the study area. Based on the focus group discussion and key informant interviews results indicate that only agriculture (crop and livestock production) livelihood strategy is the most commonly used in the study area. Generally, the households responses was in the surveying studies, in which about 61.1%, 8.3%, 27.2%, and 3.3% of sample respondents are engaged in agriculture alone, agriculture + off-farm, agriculture + non-farm and all the combination of agriculture + non-farm + off-farm livelihood strategies respectively.
Table 2 Distribution of household’s livelihood diversification strategies in table form
Livelihood diversification strategies Frequency Percent
Only agriculture 110 61.1 Agriculture off-farm 15 8.3 Agriculture + non-farm 49 27.2 Agriculture + non-farm + off- farm 6 3.3 Total 180 100 Source: Field survey (2020)
4.1.1 Human capital
4.1.1.1 Sex of household head Among the total respondents, 72.8% and 27.2% of them are male headed and female-headed respectively. The survey result indicates that 48.3%, 8.3%, 13.9% and 2.2% of male headed respondents have better engaged than female-headed in agriculture alone, agriculture + off- farm, agriculture + non-farm and combination of agriculture + non-farm + off-farm activities respectively. Female-headed households are focusing to diversify Ag + non-farm activities selling of local drink and cocked food than agriculture + off-farm. The chi-square test result indicates that there was a statistically significant difference in a female household headed and male household headed between four livelihood diversification strategies at 1% of confidence level.
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Table 3 Sex composition of the household head
Livelihood diversification strategies Sex of household head Male Female Total P-value
Only agriculture N 87 23 110 .000***
% 48.3 12.8 61.1
Agriculture + off -farm N 15 0 15
% 8.3 0.0 8.3
Agriculture + non -farm N 25 24 49
% 13.9 13.3 27.2
Agriculture + non -farm +off- N 4 2 6 farm % 2.2 1.1 3.3
Total N 131 49 180
% 72.8 27.2 100
*** Significant at 1%
Source: Field survey (2020)
4.1.1.2 Education level of the household head
The survey result indicates that 89.4% of households were under cannot be read and write category whereas 10.6% of the household head literate. Among those who can be read and write households 6.7%, 2.8%, and 1.1% completed grade 1-4, grade 5-8 and grade 9-12. As it is shown in (table 3) 57.8% of household head who cannot be read and write have been engaging in agriculture alone use as a livelihood strategy. Agriculture + non-farm livelihood diversification strategy was the second option to illiterate households, there was 20.6% of households engaged in agriculture + non-farm activity. More educated households (6.7%) were located under the category grade 1-4 completing have better engagement in non-farm activities than 2.8% and 1.1% under the category grade 5-8 and 9-12 education levels respectively. The one way ANOVA test indicates that there were statistically significant
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among four livelihood diversification strategies with regard to education level at less than 5% of confidence level.
Table 4 Education level of household head livelihood No Grade Grade Grade Total Mea SD F- P- diversification read & 1-4 5-8 9-12 n value value strategies write
Only N 104 4 2 0 110 1. 6 0.95 3.0 0.03** agriculture % 57.8 2.2 1.1 0.0 61.1 Ag + off- N 14 1 0 0 15 2.2 0.96 farm % 7.8 0.6 0.0 0.0 8.3 Ag + non- N 37 7 3 2 49 2.2 1.09 farm % 20.6 3.9 1.7 1.1 27.2 Ag+ non- N 6 0 0 0 6 3.0 0 farm +off- % 3.3 0.0 0.0 0.0 3.3 farm Total N 161 12 5 2 180 1.7 0.97 % 89.4 6.7 2.8 1.1 100 ** Significant at 5%
Source: Field survey (2020)
4.1.1.3 Age of household head The age of household head has direct effects to engage in different types of livelihood diversification strategies. The study result indicated that in Table 5 the older household head is more focused on agricultural alone livelihood than others from non-farm and off-farm livelihood diversification strategies. From the table below it could be seen that majority (88.3%) of the respondents were engaged within the age group of 28-64 years. This age range is regarded as the economically productive section of the population, which implies that the households were engaged in non-farm activities to ensure households food security. Out of which 52.4%, 7.9%, 24.4%, and 3.3% were engaged in Agriculture alone, Agriculture + off- farm, Agriculture + non-farm and Agriculture + non-farm + off-farm livelihood diversification strategies, while 11.7% of sample households included at above 65 age of
29 years. The mean age of the households occupied in agriculture alone, Ag + off-farm, Ag + non-farm, and Ag + non-farm + off-farm livelihood strategies were 48.4, 45.6, 42.8, and 37.5 respectively. This implies that households, whose age is relatively younger, could be pushed to engage more in Ag + off-farm + non-farm, Ag + non-farm, and Ag + off-farm activities than the base category of agriculture alone respectively. The one way ANOVA result showed that, there was statistically significant among four livelihood diversification strategies at less than 5% of confidence level.
Table 5 Age composition of the household head livelihood diversification 28- 64 > 65 Tota Mean S D F- p- strategies age age l value value
Only agriculture N 95 15 110 48.4 11.2 1.70 .014** % 52.8 8.3 61.1 Agriculture + off -farm N 14 1 15 45.6 8.6 % 7.8 0.6 8.3
Agriculture + non-farm N 44 5 49 42.8 10.3 % 24.4 2.8 27.2 Agriculture + non-farm N 6 0 6 37.5 5.1 + off –farm % 3.3 0.0 3.3 Total N 159 21 180 46.3 11.0 % 88.3 11.7 100 ** Significant at 5%
Source: Field survey (2020)
4.1.1.4 Marital status of the household head The marital status distribution of the household heads illustrates that out of four categories of marital status such as single, married, divorced and widowed, the majority of the households 71.7% of households were married. Only 0.5, 17.3, and 10.0 percent of households were single, divorced, and widowed respectively. The study results shown that 48.3%, 8.3%, 13.3%, and 1.7% of households were engaged in Agriculture alone, Agriculture + off-farm, Agriculture + non-farm, and Agriculture + off-farm + non-farm respectively. These, married
30 households have seen more diversifying into Ag + off-farm and Ag + non-farm livelihood strategies than unmarried households. Because, the households was diversifying in to the non- farm activities to fulfill basic need of household member. The chi-square result indicates that there was statistically significant difference among four livelihood diversification strategies at 1% of confidence level.
Table 6 Marital status of the household head livelihood diversification marital status of the household strategies Single Marriage divorced widowed Total P-value Only agriculture N 0 87 12 11 110 0.001*** % 0.0 48.3 6.7 6.1 61.1 Agriculture + off – N 0 15 0 0 15 farm % 0.0 8.3 0.0 0.0 8.3 Agriculture + non – N 1 24 17 7 49 farm % 0.6 13.3 9.4 3.9 27.2 Agriculture + non - N 0 3 3 0 6 farm +off- farm % 0.0 1.7 1.7 0.0 3.3 Total N 1 129 32 18 180 % 0.6 71.7 17.8 10.0 100 *** Significant at 1% confidence level
Source: Field survey (2020)
4.1.1.5 Family size of the households The study result indicates that household family size has great roles to engage for farm and non-farm activities. The data regarding family size was collected and presented in Table 7. Accordingly, 22.2% of households have family size between the range of 1-3 members and 72.8 % of households have family size in the range of 4-7 members. Only 5.2% of households have family members of the household were above 8 members. Households, that have higher number of family size was better engagement in non-farm activities than the small size of family members. Accordingly, household head choosing for agriculture + off-farm and agriculture + non-farm activities were the mean of 5.86 and 5.0 respectively. The survey result indicates that family size had some variation between livelihood diversification strategy
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were 4.9, 5.86, 5.0, and 4.66 of households engaged in agriculture alone, agriculture + off- farm, agriculture + non-farm and agriculture + off-farm + non-farm respectively. The households engaged in Ag + off-farm and Ag + non-farm activities have the higher of the mean than agriculture alone. This implies that, households have increase by one numbers of family members pushing to diversify their livelihood strategies. The one way ANOVA test showed that there were statistically insignificant among four livelihood diversification strategies.
Table 7 Family size of the households
livelihood diversification Family size of the household strategies 1-4 4-7 8-11 Total Mea SD F- P- n value value Only agriculture N 27 79 4 110 4.9 1.55 0.4 0.88 % 15 43.9 2.2 61.1 Agriculture + off – N 1 12 2 15 5.86 1.35 farm % 0.6 6.7 1.1 8.3 Agriculture + non – N 11 35 3 49 5.0 1.6 farm % 6.1 19.4 1.7 27.2 Agriculture + non - N 1 5 0 6 4.6 1.36 farm +off- farm % 0.6 2.8 0 3.3 Total N 40 131 9 180 5.0 1.56 % 22.2 72.8 5.0 100
Source: Field survey (2020)
4.1.1.6 Dependency ratio of households The dependency ratio means the number of dependent family members that are found less than 18 years and above 65 years was taken as a determinant variable for livelihood diversification strategy in sample households. When the dependent member of the family was high the income of households is low. There were 47.8% of households have 1-2 number of dependent and 52.2% of household’s dependence was under 3-5 number of dependents. Even if, households had more economically active with high dependent family members that share the total income of household’s were found to be low saving. Households have high number
32 of dependent family members forced to push diversifying their livelihood activities to feed the dependent members. The study result showed that the mean of 2.86 and 2.6 dependency ratio were engaged in agriculture + off-farm and agriculture + non-farm activities respectively. The statistical analysis shows that there was not statistically significant between four livelihood strategies.
Table 8 Dependency ratio of the households
Livelihood Dependency ratio diversification 1-2 No of 3-5 No of Total Mea SD F- P- strategies dependent dependent n value value Only agriculture N 59 51 110 2.54 0.94 0.79 0.52 % 32.8 28.3 61.1 Agriculture + off – N 2 13 15 2.86 0.63 farm % 1.1 7.2 8.3 Agriculture + non N 22 27 49 2.6 0.90 –farm % 12.2 15.0 27.2 Agriculture + non N 3 3 6 2.5 0.5 -farm +off- farm % 1.7 1.7 3.3 Total N 86 94 180 2.59 0.90 % 47.8 52.2 100 Source: Field survey (2020)
4.1.1.7 Access to training Obtaining any types of training is the most important to jointed that different asset and can create livelihood strategies. In the study area, most households located nearby the town have good communicating. But, rural households have not enjoyed training regarding modern income-generating activities. They remain engaged with their traditional activities because the training mainly focuses on agriculture-related issues. Integrating agricultural training with non-farm enterprise training can help HHs to manage and market their farm production more effectively, to take advantage of new agricultural opportunities. The study result showed that 37.2% of household head has provided the training and 62.8% of households have not obtained respectively. The households were engaged in agriculture alone, agriculture + off-
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farm, agriculture + non-farm and both the combination of agriculture + non-farm + off-farm activities were by 25.0%, 1.7%, 25.0% and 1.7% of households were tacking the training respectively. The chi-square test indicates that, there was no statistically significant difference among the four livelihood diversification strategies Table 9 Access to training of the households livelihood diversification Yes No Total Mean F- P-value strategies value
Only agriculture N 45 65 110 1.59 0.56 0.33 % 25 36.1 61.1 Agriculture + off -farm N 3 12 15 1.8 % 1.7 6.7 8.3 Agriculture + non -farm N 16 33 49 1.67 % 25 18.3 27.2 Agriculture + non -farm N 3 3 6 1.50 +off- farm % 1.7 1.7 3.3 Total N 67 113 180 1.63 % 37.2 62.8 100
Source: Field survey 2020
4.1.2 Financial capital
4.1.2.1 Annual incomes of the household head In the study site, households that practiced different livelihood activities have better total annual income. Farmers are more likely to diversify their livelihood strategies through agricultural activities, agriculture + off-farm, agriculture + non-farm, and combination of agriculture + off-farm + non-farm livelihood strategies. These households are having better options to survive the natural hazard and vulnerability than those undiversified households. Therefore, diversified households have obtained higher annual income under the category of Ag + non-farm + off-farm, Ag + non-farm, and Ag + off-farm livelihood diversification strategies were the means 21383.3 birr, 21083.0 birr, and 12536.0 birr compared with the result of the base category of agriculture alone respectively. Since, households choosing to
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diversify other livelihood strategies besides agriculture alone, in cause of les farm land size. The one way ANOVA result indicated that there was a statistically significant difference between four livelihood strategies at less than 5% of significant level. Table 10 Annual incomes of the households
Livelihood Annual income of the households diversification <1000 1000- >500 Tota Mean SD f- p- strategies 5000 0 l value value only N 8 43 59 110 10905.5 10802.2 1.53 .041** agriculture % 4.4 23.9 32.8 61.1 agriculture + N 3 12 15 12536.0 9465.9 off-farm % 0.0 1.7 6.7 8.3 agriculture + N 0 7 42 49 21083.0 18768.2 non –farm % 0.0 3.9 23.3 27.2 agriculture + N 0 1 5 6 21383.3 9655.13 non-farm % 0.0 0.6 2.8 3.3 +off- farm Total N 8 54 118 180 14161.2 14025.8 % 4.4 30.0 65.6 100 ** Significant 5% level of confidence
Source: Field survey (2020)
4.1.2.2 Access to credit The survey results from (Table 11) indicated that households obtained access to financial credit were 31.4% while others 68.3% of households cannot obtain access to credit for different reasons such as collateral type, loan repayment period. (Table 11) showed that the comparison made by their livelihood diversification strategies 13.3%, 2.2%, 13.9%, and 2.2% households were received credit in agriculture alone, agriculture + off-farm, agriculture + non- farm, and agriculture + off-farm + non-farm received credit respectively. In the categories of only agriculture and agriculture + non-farm pursue households has a better provision of credit access, but the majority of households were not provided access to credit in agriculture alone category. Households that offering better access to credit have enhanced pushed to diversify
35 their livelihood strategies into Ag + non-farm and Ag + off-farm+ non-farm activities. The chi-square test indicated that there was statistically significant at 1% of confidence level in terms of access to credit.
Table 11 Access to credits of the households
Livelihood diversification strategies Access to credit Yes no Total P-value only agriculture N 24 86 110 0.001*** % 13.3 47.8 61.1 agriculture + off –farm N 4 11 15 % 2.2 6.1% 8.3 agriculture + non –farm N 25 24 49 % 13.9 13.3 27.2 agriculture + non -farm +off- N 4 2 6 farm % 2.2 1.1 3.3 Total N 57 123 180 % 31.7 68.3 100 *** Significant at 1% of confidence level
Source: Field survey (2020)
4.1.3 Natural capital
4.1.3.1 Farm land size in a hectare Most sample households have farm land size holding in the ranges between 1-3 hectare with an overall mean of 1.67 and a standard deviation of 0.85. The mean of farm land size were 1.91 sampled households have relatively large size of land holding in agriculture alone would not be enforced to diversify more, since the productivity they got from the cultivable land is enough to endure the livelihood of their families. However, the mean land holding size of sampled households who diversify their livelihood strategies were 0.83 ha, 1.0 ha, and 1.41 ha engaged in agriculture + non-farm + off-farm, agriculture + off-farm, and agriculture + non- farm activities respectively. This implies that, households who have small area of land to cultivate have more diversified their livelihood strategy. Because they would be forced to get
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additional income beside agriculture to sustain their livelihood, since the productivity gained from cultivating small land is not enough. The one way ANOVA analysis has shown statistically significant difference among four livelihood diversification strategies concerning farm land size at 1% of confidence level.
Table 12 Farm land size of the households
Livelihood farm land size of the household in a hectare diversification strategies <1 1-3 3.5-7 Total Mea SD F- P-value ha ha ha n value Only agriculture N 1 95 14 110 1.91 0.86 4.6 .000*** % 0.6 52.8 7.8 61.1 agriculture + off N 0 15 0 15 1.0 0.17 -farm % 0.0 8.3 0.0 8.3 agriculture + non N 4 42 3 49 1.41 0.75 -farm % 2.2 23.3 1.7 27.2 agriculture + non N 2 4 0 6 0.83 0.25 -farm +off- farm % 1.1 2.2 0.0 3.3 Total N 7 156 17 180 1.67 0.85 % 3.9 86.7 9.4 100 *** Significant at 1% of confidence level
Source: Field survey (2020)
4.1.4 Physical capital
4.1.4.1 Livestock holding In order to identify the quantity of livestock ownership status of households, a question was asked to the respondents to mention the number of livestock they have. In the study area, the listed livestock includes ox, cow, sheep, goat, donkey, chicken, mule, and beehives. Farmers use the livestock as the options in livelihood strategies to coping up of the shock during the time of food shortage. To determine the household livestock holdings the total number of livestock possessed by sample households was converted into a tropical livestock unit (TLU)
37 using conversion factor estimated by (Freeman et al 1996 as cited in Menkir 2018:61). The survey result indicates that 11.1%, 67.2%, and 21.7% of households own livestock in the ranges of <1, 1-4, and 4-8 TLU respectively. The total average livestock holding in TLU for the sample respondents were 2.97 TLU with a standard deviation of 1.41. The average mean of livestock size of sample households measured in TLU for agriculture alone, agriculture + off-farm, agriculture + non-farm, and both the combination of agriculture + off-farm + non- farm livelihood diversification strategies were 3.08, 2.81, 2.47, and 2.57 respectively. The mean of livestock holding in agriculture alone were 3.08 is greater than other livelihood strategies. As indicated in the Table 13 the average mean were 2.47, 2.57, and 2.81 in TLU owned by Ag + non-farm, Ag + non-farm + off-farm, and Ag + off-farm activities pursue were relatively low as compared to the base category of agriculture alone respectively . Therefore, households those have small size of livestock holding diversifying to the non-farm livelihood strategies. However, there were no statistically insignificant among the four livelihood diversification strategies. Table 13 Total number of livestock holding
Livelihood diversification Total number of livestock holding strategies <1 1-4 4-8 Total Mean SD F- P- value value Only agriculture N 10 75 25 110 3.08 1.43 0.98 0.51 % 5.6 41.7 13.9 61.1 Agriculture + off – N 2 8 5 15 2.81 1.45 farm % 1.1 4.4 2.8 8.3 Agriculture + non – N 7 34 8 49 2.47 1.45 farm % 3.9 18.9 4.4 27.2 Agriculture + non - N 1 5 0 6 2.57 1.17 farm +off- farm % 0.6 2.8 0.0 3.3 Total N 20 122 38 180 2.97 1.41 % 11 67.8 21.1 100 Source: Field survey (2020)
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4.1.4.2 Market distance Too long distance accesses of the market have less opportunity for farmers traveling to participate in livelihood diversification strategies. A place where shorter to distance in the nearest town (market) farmers shared information about livelihood diversification strategies and it relatively reduces the transaction cost. But, 59.4% of households were walked on foot from one up to three hours about 33.6% of households were walked on foot from three to six hour. Therefore, households’ access of market was low the diversification of non-farm activities were decreased. The mean of market distance in Hour were 1.36, 1.06, 1.1, and 0.83 choosing the agriculture alone, Ag +off-farm, Ag + non-farm, and Ag + off-farm + non-farm livelihood diversification strategies respectively. Accordingly, the one way ANOVA analysis showed that there were statistically significant differences between four livelihood diversification strategies.
Table 14 Market distance of the households in the hour
Livelihood Market distance of the households in Hour walked on foot diversification strategies <1hr 1-3hr 3-6hr Total Mean SD F-value P-value only agriculture N 6 59 45 110 1.36 0.58 3.92 0.02** % 3.3 32.8 25.0 61.1 agriculture + off - N 2 10 3 15 1.06 0.59 farm % 1.1 5.6 1.7 8.3 agriculture + non - N 4 33 12 49 1.1 0.55 farm % 2.2 18.3 6.7 27.2 agriculture + non - N 1 5 0 6 0.83 0.40 farm +off- farm % 0.6 2.8 0.0 3.3 Total N 13 107 60 180 1.26 0.97 % 7.2 59.4 33.3 100 ** Significant at 5%
Source: Field survey (2020)
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4.1.4.4 Agricultural input users of households Input supplies are one of the key elements for improving agricultural product and productivity. Hence households are expected to use these inputs to enhance the productivity of their farm land. However, according to the study site households face difficulties in covering the costs of this farm inputs. In this case, households diversifying other livelihood options to generate income that can help them to cover costs modern farm implements and other house expenses. The survey results showed that 82.2% and 17.8% of sample households were agricultural input users and non-user respectively. Input users are 54.4%, 6.1%, 20.0% and 1.7% of households were agriculture alone, agriculture + off-farm, agriculture + non-farm and agriculture + off-farm + non-farm activities respectively. The chi-square test result indicated that there was statistically significant between in four livelihood diversification strategies at 5% of confidence level.
Table 15 Agricultural input users of households
Livelihood diversification strategies Agricultural input use of the households Yes No Total P-value only agriculture N 98 12 110 0.011** % 54.4 6.7 61.1 agriculture + off –farm N 11 4 15 % 6.1 2.2 8.3 agriculture + non –farm N 36 13 49 % 20.0 7.2 27.2 agriculture + non -farm +off- N 3 3 6 farm % 1.7 1.7 3.3 Total N 148 32 180 % 82.2 17.8 100 ** Significant at 5%
Source: Field survey (2020)
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4.1.5 Social Capital
4.1.5.1 Membership in cooperatives Households who participate a member of cooperatives, have better skill, knowledge, experience and providing access to credit in an easy way, which helps to diversify their livelihood into the non-farm activities. The survey result indicates that from the total households 76.1% of households were members in cooperatives. Thus 47.2%, 5%, 21.1%, and 2.8% of household were engaged in only agriculture, agriculture + off-farm, agriculture + non-farm and agriculture + off-farm + non-farm livelihood diversification strategies respectively. The chi-square result showed that there was no significant statistical difference between in four livelihood diversification strategies. Table 16 Member of cooperatives
Livelihood diversification strategies Member of cooperatives of the household Yes No Total P-value only agriculture N 85 25 110 0.48 % 47.2 13.9 61.1 agriculture + off –farm N 9 6 15 % 5.0 3.3 8.3 agriculture + non –farm N 38 11 49 % 21.1 6.1 27.2 agriculture + non -farm +off- farm N 5 1 6 % 2.8 0.6 3.3 Total N 137 43 180 % 76.1 23.9 100 Source: Field survey (2020)
4.2 Challenges and Opportunities of Livelihood Diversification Strategy
4.2.1 Major Challenges that hinder households to diversify their livelihood Given the fact that rural livelihood diversification activities are heterogeneous by their nature, the challenges also have varying characteristics. Therefore, this study is emphasizing on the major challenges of livelihood diversification identified by the study households. Survey
41 respondents and study participant had put and list down several specific and general challenges for livelihood diversification strategies. However, for analytical purposes, greater emphasis is given on the major one identified by households. The following table illustrates the major challenges of diversification identified in frequency of the sample respondents in the study sites. As it is shown in (table 17) the households that hinders to diversify their livelihood to the non-farm sector, 39.4% of households indicates that lack of access to credit as a major challenge that limits livelihood diversification strategies. While the other 32.8%, 20.0%, 5.6% and 2.2% of households identified lack of financial capital, poor infrastructure, lack of training and timing of loan repayment as the second and third challenges of livelihood diversification strategies, respectively.
Table 17 Major challenges of the household to diversification livelihood strategies
Major challenges of livelihood diversification Frequency Percent lack of financial capital 59 32.8 lack of access to credit 71 39.4 lack of training 10 5.6 timing of loan repayments 4 2.2 poor infrastructure 36 20.0 Total 180 100
Source field survey: 2020
4.2.2 Opportunities of Houshols to Diversifing TheirLivelihood Rural households were asked to mention the existing opportunities for non-farm livelihood diversification strategies in their locality, thus the responses of households in both kebeles are similar. The household prioritized the opportunities in their locality for livelihood diversification of non-farm income-generating activities as follows: the first is households’ interest to get involved in these activities, skill training, technical support, access to transport and credit. As it is shown in table 18 the opportunities of households to diversify their livelihood into the non-farm sector that household heads have their own skill, technical support, access to credit and transport were 68.3%, 13.9, 9.4% and 8.3% of household have opportunities to diversify their livelihoods respectively.
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Table 18 Opportunities of the households for livelihood diversification
Opportunities to diversification Frequency Percent Access to credit 17 9.4
Access of own skill to diversify 123 68.3
Access to transport facility 15 8.3 Technical support 25 13.9 Total 180 100.0 Source: field survey 2020
4.2.3 Reasons for Diversification Rural households were asked their reasons for selecting the non-farm activities, almost 61.1% of household engaged in agriculture alone households reported that replied that they do have the interest to diversify their livelihoods situation. Survey result showed that 61.1% of household heads reported that have required to diversifying their livelihood activities in case of small farm land size. The remaining 17.2%, 13.3%, and 7.9% of respondents have reported that, diversifying to the non-farm activities by the reason low productivity and poor soil fertility; provide additional incomes and shortage of food respectively.
Table 19 Reason for household head’s livelihood diversification
Reason Frequency Percent Shortage of food 15 8.3
Shortage of farm land size 110 61.1
Low productivity and poor soil fertility 31 17.2 Provide additional income 24 13.3 Total 180 100.0 Source: field survey 2020
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4.3 Determinants of Rural Livelihood Diversification Strategies
4.3.1 Econometric Model Results Multinomial logit regression was utilized to identify the determinants factors of livelihood diversification strategies in rural household. This model was used to analyze the relationship between independent variable and response variable. Among 14 hypothesized explanatory variables, 5 variables were found to be significant on livelihood diversification strategies such as Ag + off-farm, agriculture + non-farm, and agriculture + off-farm + non-farm livelihood strategies. These include the number of family size, access to credit of the households, annual income of the households, farm land size of the households, and the market distance of from the households residency were positively and negatively determined to diversify livelihood strategies.
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Table 20 Multinomial logistic reparation result of household livelihood diversification strategies
Predictor variable Livelihood diversification strategies
Ag + off-farm Ag + non-farm Ag+ off-farm+no-farm Sig Exp Sig Exp Sig Exp
(B) (B ) (B) Sex of household head 14.0 0.97 1240 -.919 .256 .399 -.216 .914 1.24 Age of household head .013 .79 1.01 -.006 .885 .996 -.147 .338 .864 Education level of the -23.7 .99 4.8 -13.0 .995 5.32 3.65 .997 38.5 household head household 1size .822 .098* 2.78 .054 .886 1.05 0.005 .994 .995 Access to training -2.29 .064* .100 -.331 .515 .718 -.54 .705 .583 Dependency ratio -.264 .718 .768 .221 .588 .802 .533 .677 1.70 Farm land size -6.89 .002*** .001 .081 .752 1.08 -6.2 .055* .001 Total livestock unit .012 .975 1.01 -.238 .215 .788 -.716 .218 .489 Market distance -2.00 .02** .135 -.821 .071 .44 -2.47 .087* .084 Access to credit -2.15 .108 .115 1.02 .052** 2.7 -.121 .942 .886 Marital statues 12.0 .984 1695 .02 .986 1.02 13.5 .987 794 cooperative members -.24 .838 1.27 -.286 .662 .752 .75 .68 2.12 Input use -2.9 .054** .13 .032 .967 1.03 1.55 .47 4.71 Annual income .000 .887 1.00 .00 .001*** 1.0 .000 .144 1.00 Base categories Only agriculture No of observations 180 Likelihood 216.45 Chi-square 167.8 p-value 1.000 Pseudo R2 0.605 ***, **, * Significant at 1%, 5%, and 10% confidence level Source: field survey 2020
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Farm land size: as expected farm land size is found to be negative and significantly influences the diversification into agriculture + off-farm and agriculture + non-farm + off- farm activities at 1% and less than10% probability level respectively. The negative coefficients indicate that the households have better farm land size, their option was agriculture alone than other livelihood strategies. Holding the other factors constant, the likelihood of rural household’s participation and getting their livelihood within agriculture + off-farm and agriculture + non-farm +off-farm livelihood diversification strategies were decreased by a factor of 0.001 and 0.001 for each 1 hectare increase at 1% and less than 10% probability level respectively. On the contrary more land tends to follow and divot more time to agricultural intensification rather than diversification. This is in line with Ambachew (2015) the land owner and rural dweller considered off-farm activities as a last job opportunities and low paying activity. Market distance: as expected distance to market center was found to have negative relationship and statistically significant at p<5% and p<10% probability level with households likelihood of livelihood diversification into Ag + off-farm and Ag + off-farm + non-farm activities respectively. Household heads lived far from the nearest market location have a negative effect and less likely to engaged in agriculture plus off-farm and agriculture plus off- farm plus non-farm livelihood diversification strategies. The other variables holding constant, a unit increases in the time taken from the nearby market distance increased the probability of choosing Ag + off-farm and Ag + non-farm + off-farm activities decreased by a factors of 0.135 and 0.84 as the distance from the households home to market center increased by one hour. FGD discussions held with respondents also emphasize that access of market is one of the determinant factors for rural households have and one of the reason for farmers to diversify their livelihood to the non-farm activities. It is clear that the more households are distant from market center, the more disadvantaged from diversifying their livelihood into non-farm options. This is in line with the study by Tariku (2019), Gebrhiwot (2018). Access to credit: access to credit services has positively significance association with the probability of choosing Agriculture + Non-farm livelihood diversification strategies at 5% probability level. Focus group discussions made with households, the discussant showed that lack of financial capital is one of the core determinates to diversify their livelihood strategies while some others emphasized how access to credit improve their livelihoods. Therefore, the
46 analysis indicates that as the households who get credit access the probability of choosing in agriculture + non-farm activity besides agriculture were raised by a factor of 2.7. This might be true, if households especially those who have less farm land size easily access the financial credit can diverse their income source. Keeping all other variable constant, access to credit increased in some unit, the alternative livelihood diversification of Ag + non-farm increased by 2.7 relative to the base category of agriculture alone. This finding is in line with Ambachew et al (2016), credit access is found have appositive impact on likelihood choosing agriculture + non-farm activates. Total annual income (income): the income variables have positive and significant influence on household’s to participate in Agriculture + non-farm livelihood diversification at 1% significant level. This means that households have with large annual incomes are more likely to engage in agriculture + non-farm livelihood diversification strategies while those farmers with low income are less likely to diversify to the non-farm activities. Keeping the effect of all other variable in the model constant, the model results reveal that the probability of households have favoring to diversify Ag + non-farm livelihood activities increased by a factor of 1.0 compared to those with the base category agriculture alone. This result is in line with Melesse, (2018).
Number of family size: this variable showed that positively and significant correlation with household decision to pursue Ag + off-farm livelihood strategies at p<10%. A one person increase in the family can increase by a factor of 2.78. Those household have an opportunity of pursuing Ag + off-farm activities. Because, households with large family size have a better chance to allocate their labor force in to different farm and non-farm livelihood strategies. The result of this study is in line with Mezgebu, (2019).
Access to training: it is found to have a negative and significant effect on agriculture +off- farm activities at p<10% significant level. Training is mechanism of promoting farmers knowledge, technical information for new technology, and skill about the production and adoption of improve seed which increase farmer’s decision making ability. Therefore, respondents were provided access to training in agricultural production system to improve their crop product and productivity. Holding other variable constant, the engagement of Ag + off-farm activities was decreased by a factor of 0.1 as households provided the training. Since,
47 respondents focused on agriculture alone. The result is in agreement with Sintayehu et al (2017).
Agricultural inputs: The inputs are contributes to an increase in agricultural productivity and their application also noticeable as rural households have increased volume of crop production (CSA, 2017). This variable has a negative significant effect on Ag + off-farm activities that household heads were used different agricultural inputs. Holding the other variable constant, the use of agricultural inputs increase in a unit of 0.054 there were a choosing of Ag + off-farm activities decreased by a factors of 0.13. Since, the respondents more focused in agriculture alone to improve agricultural productivity. This study is opposed with Gebrehiwot, (2018).
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CHAPTER 5. Conclusion and Recommendation
5.1 Conclusion
Based on the finding subsistence farmer in the study area were characterized by higher level of uneducated, relatively beggar household size and the overarching problem of ill-health which are symptomatic of poverty. Their livelihoods were friendly in agriculture alone with a households growing crops and keeping livestock raring. An average annual income of subsistence farm households pursuing in agriculture alone were overly low as compared to diversified households around 61.1% of subsistence farmers earned 10905.5 ET birr in agriculture alone.
Rural households in the study area engaged into different combination of livelihood diversification strategies to ensure their food needs. Livelihood diversification strategies in the study area were positively determined by number of household size, access of credit, and annual income of the household heads use of agriculture + off-farm and Ag + of-farm + non- farm activities respectively. The coefficient of farm land size, market distance, access to training, and utilization of improve seed and fertilizer has a negative significant on Ag + off- farm and Ag + non-farm + off-farm livelihood diversification strategies. This indicates that households have better farm land size more engaged in agricultural alone, but less likely to choose Ag + off-farm and Ag + non-farm + off-farm livelihood strategies in the study area.
5.2 Recommendation Based on the research finding the following recommendations are put forward. Though households need to involve in livelihood diversification strategies, financial constraint is one of the obstacles to do so. This is because; there is no well developed and evenly distributed provision of credit in the study area. Increase credit access and strength the institutional arrangement to improve the livelihood of rural households. Solve financial problem through increasing and strengthening financial institution and promoting better income-generating options.
Having good infrastructure is a back bone for any development. But, in the study area infrastructure development is low. For instance, it is difficult to reach the market place due to
49 poor road and network. This can be negatively affecting the tendency of livelihood diversification strategy in the study area. Therefore expand the infrastructure and input-output market in the rural area and fill the market information gaps.
The government and other related organizations give attention and motivation to rural credit and saving programs in order to be function according to the plan of credit tacking.
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REFERENC Allison, E. (2004). Livelihood diversification and natural resource access food and agriculture organization of the United Nations, livelihood support programme working paper overseas development quintile, University of East Anglia, January. Retrieved January 2004, Alobo, L. S. (2015). Rural livelihood diversification in sub-Saharan Africa: a literature review. J Dev Stud 2 015; 51(9):1125–38. Ambachew, M. D., Ermiyas, A. (2016). Determinants of rural household livelihood diversification strategy in South Gondar zone, Ethiopia. Journal of Agricultural Economics, Extension and Rural Development: ISSN2360-798X, Vol. 4(8): pp, 548- 560.
Arega, B., Woldeamlak, B., and Melanie, N. (2013). Rural households’ livelihood assets, strategies and outcomes in drought-prone areas of the Amhara Region, Ethiopia: Case Study in Lay Gaint District
Asfir, S.(2016). Determinants of rural household livelihood strategies: evidence from western Ethiopia. Journal of economics and sustainable development 7(15):103-109. Ayalew, D., Tesfaye, K. (2012). Vulnerability to rainfall and its current trends in Amhara Region Ethiopia, Journal of Agricultural Research 7(10):1475-1486. Babatunde, R. O. (2013). On-farm and off-farm works: complements or substitute? Evidence rural from Nigeria contributed paper for the 4th international conference of the African association of agricultural economists September 22-25, 2013. Hammamet, Tunisia. URL: Economists, Septehttp://ageconsearch.umn.edu. Accessed on June 10, 2014 Baharu, G. (2016). Determinants of livelihood diversification: the case of Kembata Tambaro Zone, Southern Ethiopia. Journal of poverty investment and development, Vol23, ISSN 2422-846X. Barrett, C.B, T. Reardon and P.Webb (2001). "Nonfarm income diversification and household livelihood strategies in rural Africa: Concepts, dynamics, and policy implications." Food Policy 26(4): 315-331. Beleynew, A.M., Getaneh, M.A., Bedilu, Y. A., & Getnet, A.T. (2018). Collaborative study by College of Business and Economics, Bahir Dar University and Amhara Region Chamber of Commerce and Sectoral Associations (ARCCA) with support from the Swedish international Development Agency (SIDA). No.25. Bezabih M., Kohlin G. and Mannberg A. (2010). Trust insecurity and land certification in rural Ethiopia. journal of socio economics, 40:833-843. Brhanu T. (2016). Rural Non-Farm Livelihood Diversification among Farming Households in Saharti Samre Woreda, Southeastern Tigray June, 2016 Addis Ababa, Ethiopia.
51
Chambers, Robert. Gordon, C. (1992). Sustainable Rural Livelihoods: Practical concepts for the 21st Century. IDS Discussion Paper 296, IDS, Brighton. CSA, (2017). Farm management practice (private peasant holdings, Meher season). V.3. Ethiopia, Addis Ababa. De Janvry, A. (1981).The agrarian question and reformism in Latin America. Baltimore: john Hopkins University press. Delil, H. (2001). The Determinants off-farm Employment & its role in rural poverty Alleviation, The case of Oromia Regional State, School of Graduate studies, AAU. The fifth annual conference on the Ethiopian economy, Addis Ababa. Demisse, D., & Workneh, N.(2004). Determinants of rural livelihood diversification: Evidence from Southern Ethiopia. Quarterly Journal of International Agriculture V 43 No: 209-267. Dessalegn, A. (2016). Determinants of rural livelihood diversification: the case of rural households in Lemmo District, Hadiyya Zone of Southern Ethiopia: Journal of Economics and Sustainable Development Vol.7, (5), pp.32-39. Devereux S, Sharp K, Yared A (2003). Destitution in Ethiopia’s northeastern highlands (Amhara National Regional State). Institute of Development Studies of the University of Sussex, Brighton. DFID, (1999). Natural resources systems programme: annual report 1998/99, RNRKS, DFID, London Ellis, F. (2000). The determinants of rural livelihood diversification in developing countries. Journal Agric Econ.; 51, No.2, 89–302. Enchebiri, R., Onwusiribe, C., & Nwaogu, D. (2017). Effects of livelihood diversification in food security status of rural farm households in Abia State Nigeria. Scientific papers series management, economic engineering in agriculture and rural development 17(1):159-166 FAO, (2009). Overview of the livelihood assessment tool-kit. Analyzing and responding to the impact of disasters on the livelihoods of people: methodological and conceptual overview.Vl.1. FAO, (2017). Severe food insecure in southern Somali Region due to prolonged drought. Gebrehiwot, W., Hyacinth, E. (2018). Determinants of Livelihood Diversification Strategies in Eastern Tigray Region of Ethiopia. Gebru, G. W., & Beyene, F. (2012). Rural household livelihood strategies in drought‑ prone areas: a case of Gulomekeda District, eastern zone of Tigray National Regional State, Ethiopia. J Dev Agric Econ; 4(6):158–68.
52
Gecho, Y. (2017). Rural farm households‟ income diversification: the case of Wolaita Zone, Southern Ethiopia. Social sciences 6(2):4556. Doi: 10.11648/j.ss.20170602.12. Geremew, W.K., Sangho, K (2017). Determinant factors of livelihood diversification: evidence from Ethiopia. Environmental studies research article. 3: 1369490.13. Haggblade, S., Hazell, P., & Reardon, T. (2010). The rural non-farm economy: prospects for growth and poverty reduction. Hussein, k. and Nelson, J. (1998). Sustainable Livelihoods and Livelihood Diversification, IDS Working Paper 69. Libo Kemkem district Office of agriculture and rural development. (2017). Libo Kemkem Woreda agriculture and rural development office general agricultural activities reports. Unpublished. Libo Kemkem district plan commission office, (2012). Unpublished report. Melese. A.T., Getaneh. M. A., and Gemechu. S.O (2019). Determinants of Rural Households Livelihood Diversification Strategies in Kuarit District, West Gojjam Zone of, Amhara Region, Ethiopia. International Journal of Economic Behavior and Organization. 2018; 6(3): 61-68. Doi: 10.11648/j.ijebo.20180603.11. Mengistu, S. (2016). Challenges of livelihood diversification in pastoral lands of Ethiopia: evidence from South Omo pastoralists. International journal of scientific and technology research 5(9):147153. Mezgebu, A., Habtamu, M., Mohamed, A. (2019). Rural non-farm activity income diversification among smallholder farmers in Debre Elias Woreda, Amhara regional stat, Ethiopia. American journal of environment and Resource Economics 2019, 4(2):84-91. MoFED, (2016). Federal democratic republic of Ethiopia. Food Security Programme 2010 – 2014. Addis Ababa, Ethiopia.
Mossa, E. A. (2013). Poverty and livelihood strategies of female headed households in rural Ethiopia: the case of libo kemkem woreda, south Gondar. ODI, (2002). Overseas Development Institute 111 Westminster Bridge Road London SE1 7JD UK. Prowse, M. (2015). The Determinants of Non-Farm Income Diversification in Rural Ethiopia. Journal of Poverty Alleviation and International Development 6(1):109-130.
Robert, C., Gordon, R. (1991). IDS Discussion paper 296: sustainable rural livelihood practical concepts for the 21th century. Scoones, (2000). Sustainable Rural Livelihoods: a framework for analysis. IDS Working Paper no. 72, Brighton: Institute for Development Studies.
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Scoones, I. (1998). Sustainable rural livelihoods: A framework for analysis. Ids working paper no. 72, Brighton: institute of development studies, June. Sharma R (2010). Diversification in Rural Livelihood Strategies: A Macro-Level Evidence from Jammu and Kashmir. Working Papers 439. Available at: www.cds.edu. Sintayehu, S., & Belayneh, L. (2017). Rural Livelihood Diversification Strategies in Sodo Zuria woreda. Journal of economics and sustainable development. Vol.8, No. 5, 2017 Tariku, L. (2019). The Determinants of Livelihood Diversification Strategies in Qecha Bira Woreda Kambata Tambaro Zone, Southern Ethiopia. Journal of Economics and Sustainable Development.Vol.10, No.9, 2019. Tassew W. and Oskam A. (2001). Income diversification and entry barriers: evidence from the Tigray Region of Northern Ethiopia. Food Policy 26(4):351–365. Tezera, M. (2010). Determinants of rural household livelihood diversification: the case of libo kemkem woreda, Amhara region. Addis Ababa: AAU. Tilahun, A., Teklu, B., & Hoag, D. (2017). Challenges and contributions of crop production in agro-pastoral systems of Borana Plateau, Ethiopia. Pastoralist: Research Policy and Practice 7(2):2-8. DOI 10.1186/s13570-016-0074-9 Weldegebrial, G. (2018). Determinants of livelihood diversification strategies in eastern Tigray Region of Ethiopia. Weldegebriel Zerihun and Prowse, M., 2013. Climate-change adaptation in Ethiopia: To what extent does social protection influence livelihood diversification? Development Policy Review, 31(11): 035–056.
Wondim, A. K. (2018). Determinants and challenges of rural livelihood diversification in Ethiopia: Qualitative review. Journal of agricultural extension and rural development. Vol.11(2), pp. 17-24 February 2019 DOI: 10.5897/JAERD2018.0979. World Bank, (2008). Agriculture for development policy Washington D.C; World Bank. PP 177-179. World Bank, (2014). Income diversification patterns in rural sub-Saharan Africa: reassessing the evidence. Washington. Yamane, T. (1967). Statistics: An Introductory Analysis,2nd Ed., New York: Harper and Row. Yenesew, S. Y., Eric, N. O., & Fekadu, B. (2015). Determinants of livelihood diversification strategies: The case of smallholder rural farm households in Debre Elias Woreda, East Gojjam Zone, Ethiopia. African journal of agricultural research, 10, 1998-2013. Doi: 10.5897/ajar2014.9192 Yizengaw, S., Okoyo, E., & Fekadu, B. (2015). Determinants of livelihood diversification strategies: The case of smallholder rural farm households in Debre Elias Woreda, East
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Gojjam Zone, Ethiopia. African Journal of Agricultural Research 10(19):1998-2013 DOI: 10.5897/AJAR2014.9192
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APPENDIX Appendix 1 Melticolinarity test for categorical variable
Variable Sex Marita Educati Coopera Agricultural Access Access l status on level tives impute use to to member credit training Sex 1 0.707 -0.059 0.067 0.271 -0.067 0.109 marital status 0.707 1 -0.092 0.137 0.263 -0.068 0.051 Education level -0.059 -0.092 1 -0.044 0.058 -0.217 -0.036 Cooperative members 0.067 0.137 -0.044 1 0.353 0.157 0.081 Agriculture impute use 0.271 0.263 0.001 0.058 1 -0.152 0.118 Source field survey 2020 Appendix 2 Multicolinerality test for continuous variable
Independent continuous variable Tolerance VIF age of household 0.76 1.315 number of family size 0.422 2.37 dependency ratio of the household 0.43 2.325 farm land size 0.673 1.486 annual income of the household 0.941 1.063 livestock holding 0.817 1.224 market distance from the residency 0.923 1.084 Source field survey 2020 Appendix 3 Conversion factors used to estimate Tropical Livestock Unit (TLU)
Type of livestock TLU Type of livestock TLU
Cow/ox/bull 1.0 Chicken 0.013
Calf 0.4 Donkey 0.5
Heifer 1.0 Hours/mule 1.10
Sheep 0.10 Goat 0.10
Source: freeman et al. (1996) as cited in Menkir 2018:61.
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Annex: A
Introduction
Dear respondents, the purpose of this questionnaire is to assess the determinants of rural livelihood diversification among farming households in Libo Kemkem district. The following questions will allow the researcher to obtain information about the challenges, determinants and the major types of livelihood activities. This study is conducted as a requirement for the Masters of degree in Rural Development Managements. Thus, your genuine response for the following questions is required.
General information
Your information will be kept confidential
Select the answer from the given alternative
Use the space provided for open ended questions.
Section I: Demographic factors of the Households
1. General characteristics of the household
No 1.1 sex 1.2 1.3 Marital 1.4 cod of the 1.5 family size 1.6 Education Level 1.7 Dependency of HH Age status 0=single kebele 0=1-3member 0=no read and write ratio 1=male of 1=Married 1=Maytad (dega) 1=4-7member 1= Elementary (1-8) 1=below 18 2=fema HH in 2= Divorced 2=Mantogera ( 2=8-11member 2= High school (9- 2=18-64 le year 3=Widowed qolla) 3=above 12) 3=above 65 4=Others 3=above grade 12 1 1.8 What is your major livelihood? (Multiple response are possible) 1=Farm only, 2=Livestock rearing 3=both crop production and animal husbandry, 6=Blacksmith, 4=Hand craft, 5=Petty trading. 6=Daily labor, 7=other specify------
1.9 Do you diversify your livelihoods to the non-farm sector? Yes=1, No=2
1.8 What is your major livelihood? (Multiple response are possible) 1=Farm only, 2=Livestock rearing 3=both crop production and animal husbandry, 6=Blacksmith, 4=Hand craft, 5=Petty trading. 6=Daily labor, 7=other specify------
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1.9 Do you diversify your livelihoods to the non-farm sector? Yes=1, No=2
1. 10 If your answer for Q. No. 1.9 is ‘Yes’, what are the non-farm activities you mostly engaged in? (Multiple responses) 0=Wage labor, 1=Hand Crafts, 2=Trade, 3=Sal of cooked food and local drinks, 4=Charcoal selling, 5=wood selling, 6=if others specifies______
1.11 For what purpose does use the income you got from the non-farm activities? 1=to repay previous credit, 2= to buy farm implements, 3=for asset building, 4=to fulfill basic needs of HH Section II. Questions about livelihood asset
1. Natural capital
1. Do you have plots own farm land? 1=Yes, 2=No
2. If your answer for Q. No. 1.1 is ‘Yes’, what is your farm land holding size? (in Hectare)______
3. How did you obtain your current farm land? 1=inherited, 2=from kebele administration, 3=crop sharing, 4=clearing forest land, 5=other specifies______
4. If your answer for Q. No. 1.1 is ‘Yes’, for what purpose you use it? 1= cultivation, 2=grazing, 3=uncultivated, 4=other specify______
5, is there potential for irrigation cultivation in your kebele? 1=Yes, 2=No
6. If your answer for Q. No. 1.5 is ‘Yes’, do you produce using irrigation? 1=Yes, 2=No
2. Social capitals
1.1 Do you have social relationship? 1=Yes, 2=No 1.2 If your answer for question No 2.1 is yes in which social network? 1= member of Idir/mehaber, 2= member of equb, 3= saving and credit, 4=other specify______1.3 Are you a member of cooperatives? 1=Yes, 2=No
2.3 Agricultural extension visits
2.2.1 Did you participate in the new extension program in this year? 1=Yes, 2=No
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2.2.2 If your answer for question No 2..2.1 is yes in what agricultural technology did you participate? 1=in fertilizer, 2=pesticides, 3=improve seed, 4=if others specify______
3. Financial capital
3.1 Access to credit
3.1.1 Have you ever accessed financial credit? 1= Yes, 2= No
3.1.2 If your answer for Q. No. 3.1.1 is ‘Yes’, what is/are the source of credit? 1=Government, 2=NGOs 3=Idir/Mahber, 4= Relative and friend, 5= others specify______
3.1.3 If your answer for Q. No. 3.1.1 is ‘Yes’, what type of credit you get? (Multiple response)
0=improve seed credit, 1=fertilizer credit, 2=livestock credit 3= if others specifies
3.1.4 If your answer for Q. No. 3.1.1 is ‘Yes’, for what purpose you used it? 0= to fulfill household basic necessity, 2= to purchase farm implements, 3=to fatten livestock, 4=engaged in non-farm activities, 5= other specifies______
3.2 Annual income of household
3.2.1 What are the major sources of income? 1=only agriculture, 2=agriculture plus off-farm,
3= agriculture plus non-farm, 4= agriculture plus non plus off-farm
3.2. 2 in the year 2011/2012 list the income from agricultural product, non-farm and off-farm activities?
Livelihood Livelihood diversification Total production in (qt) Total annual family Unit Total Annual diversificati activity consumption in (qt) price in sell in income on strategy (birr) (qt) Agriculture Major Crop production Total production in (qt) only Wheat Barley Teff
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Maize Figure-millet (dagusa) Sorghum Been 2 Major livestock Total production in No Consumption in production birr
Ox cow Donkey Sheep Goat chicken animal product Milk Egg Honey Cheese Butter off-farm Selling fuel wood wage labor charcoal selling sand selling selling of grasses Non-farm Grain millet black smiz Hand craft Petty trading Weaving Total annual income
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Butter off-farm Selling fuel wood wage labor charcoal selling sand selling selling of grasses Non-farm Grain millet black smiz Hand craft Petty trading Weaving Total annual income 3.2.3 Do you have any livestock your own? 1=Yes, 2=No
3.2.4 If your answer for question No 3.2.3 is ‘Yes’ how many livestock you have? 0=No livestock, 1=oxen, 2=cows, 3=calves, 4=sheep, 5=chicken, 6=donkey, 7=other specify______
3.2.5 Do you have sold livestock in the past one year? 1=Yes, 2=No
3.2.6 If your answer for question No 3.2.5 is ‘Yes ‘how many income have you earned from sale of livestock (Birr)? ___
3.2.7 If your answer for question No 3.2.5 is ‘Yes ‘in what purpose you sell? 1=to purchase 1agricultural input, 2=to purchase food consumption 3= to purchase cloths, 4= to purchase ox, 5 to pay tax, 6=other specify) ______
4. Human capital (skills, training)
4.1 Have you ever received any type of trainings? 1=Yes, 2= No
4.2 If your answer for question No 4.1 is ‘Yes’, which type of training? 1= model farmer training, 2= micro entrepreneur training, 3=if others specifies______
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4.3 If your answer for question No 4.1 is ‘Yes’, on which livelihood strategy? 1=farm activities,
2= Non-farm activities, 3= both farm and non-farm, 4=if others specify______
4.4 Who provided you the training? 1=Agricultural extension workers, 2=NGOs, 3=If others specify______
4.5 Do you have labor shortage problems? 1=Yes, 2=No
4.6 If your answer for question No 4.5 is ‘Yes’, for which of the following activities?
1= for Farm activities, 2= for Non-farm activities 3= on both farm and non-farm activities
7. Do you believe the trainings benefit for you? 1=Yes, 2=No
5. Physical capital
5.1 market accesses information
5.1.1 Where is market place for your farm product? 1=mini market in kebeles, 2=district towns market, 3=sub-district towns market 4=others specify______
5.1.2 What is the distance (in hour) to sale the product in a nearby market and come again?
By walk on foot______(hours) by transport______(hours)
5.1.3 Did the market distance affect to you diversify in non-farm activity? 1=Yes, 2=No
5.1.4 Do you have market price information for your farm product? 1=Yes, 2=No
5.1.5 If your answer for question No 5.1.3 is yes for which product? 1=for farm product, 2=livestock product, 3=non-farm product, 4=other specify______
5.2 Household’s access to infrastructure
Availability of services to 1=if available in the village Distance per hour from household 2= if available in tabia HHs home to the services 3= if available in neighboring tabiya
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4= if available only in woreda town 5=if other specify Primary school Secondary school All weather road Nearest market (local market) Main market Animal health center Residency of extension agent Section .III Key challenges and opportunities of rural livelihood diversification
18. Select and prioritize the major problems that hinder you from diversifying your livelihood to non-farm activities ;( multiple responses are possible).
No Major type of no- Reason for Challenges to diversify non- Opportunities Rank farm activity diversificat farm activity 1=access to credit major ion 1= Lack of capital 2=access to skill training livelihoo 2=lack of access to credit 3=access to transport facility d 3=lack of training 4=technical support 4=Timing of loan repayment 5=other specify 5=poor infrastructure (road, electricity) 1 Livestock trading 2 Grain trading 3 Weaving 4 Sand extracting and selling
Annex B: Interview Guides for FGDs and KIIs
Personal information: name - ______age______sex______
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1. What are the major livelihood diversifications of farmers? 2. What are the main determinants factors that limit household to diversify their livelihood activities? 3. What do you think are the main reasons that initiate people to engage in nonfarm livelihood activities? 4. What do you think about the outcomes of non-farm livelihood diversification? 5. On what types of livelihood activities do farmers mostly engaged in? Why?
Interview guide for key informant interview with agricultural extension workers
Annex B: Interview Guides for FGDs and KIIs
Personal information: name - ______age______sex______
6. What are the major livelihood diversifications of farmers? 7. What are the main determinants factors that limit household to diversify their livelihood activities? 8. What do you think are the main reasons that initiate people to engage in nonfarm livelihood activities? 9. What do you think about the outcomes of non-farm livelihood diversification? 10. On what types of livelihood activities do farmers mostly engaged in? Why?
Interview guide for key informant interview with agricultural extension workers
1. What do you think the major livelihood of farming households?
2. In what way farming households diversify their livelihood activities?
4. What do you think the major challenges of farmers to engage in livelihood diversification?
Interview guide for Key Informant Interview with Kebele Administration chairpersons
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1. Are households encouraged to diversify their livelihoods other than agriculture? How and why? 2. What are the major challenges of farming household to diversify their livelihood? 3. What do you think the trends of production in the kebele especially?
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