Commercialization of Cow Milk Production in West Hararghe Zone, Oromia National Regional State, Ethiopia

Livestock plays a vital role in the livelihood of many people in Ethiopia. However, a number of challenges hindered the development of the dairy sector along with its commercialization. Advancing commercialization of the rural generations was a foundation of the advancement and poverty reduction policies of Ethiopia. Cross-sectional data from 385 randomly selected households in Eastern Ethiopia were used in this study to assess the commercialization of cow milk producers. Descriptive statistics and the two limit Tobit econometric models were used to analyze the data. The average commercialization index was 0.434, indicating that each household sold 43.4 percent of the milk produced during the survey period. Ownership of improved breed cow, cooperative participation, access to market information, and quantity of milk produce influenced milk commercialization positively, but household size and distance to the nearest market influenced it negatively. The study suggests strengthening policies to improve rural family planning, strengthening farmer cooperatives to reinforce knowledge sharing among farmers for enhancing farmer resource endowment, and promoting improved breed varieties. The commercialization of milk producers will also expand as a result of policies that try to lower the transaction costs of accessing markets, improve the capacity of rural institutions, and encourage value addition and market links among various market players.

Determinants of Smallholder Farmers Adoption of Acacia decurrens in Northwest Ethiopia

Planting a fast-growing multipurpose Acacia decurrens (AD) tree is one of the climate-smart agricultural practices that have been promoted in Ethiopia, which is widely practiced and an important livelihood strategy in Awi zone. However, the extent of its adoption varies considerably among households in the study area. This study investigated the determinants of intensity of adoption of AD among 385 randomly selected rural households in Awi Zone. Data were gathered using a cross-sectional household survey. Descriptive statistics and Two-limit Tobit model were employed for data analysis. The result of the study shows that on average the intensity of adoption of AD was 0.43 (43% of the total cropland area), though majority of the farmers (48.8%) belong to low level of adoption. The result of the analysis shows that being male, educational level, access to seedling, experience in growing the tree, extension contact has positive and significant relationship with the intensity of adoption. Age of head of household, land holding size, livestock holding size, soil fertility status, disease emergence and road distance have negative and significant influence on intensity of adoption. These suggest that expanding road infrastructure, education, access to seedling, secure land property right, disease management, and provision of extension services related to the AD can also improve smallholder farmers’ intensity of AD adoption. The generated information provides a picture of the study area’s situation to the attention of policy makers, development practitioners and institutional service providers to formulate a better policy intervention to sustain smallholder farmers’ AD plantation.

Analysis of vulnerability and resilience to climate change induced shocks in North Shewa, Ethiopia

This article analyzes the vulnerability and resilience levels of farm households in North Shewa, Ethiopia, using a survey of 452 households. Agro ecological based classification was done to analyze vulnerability to climate change induced shocks. Integrated vulnerability analysis approach was employed to develop indexes for socioeconomic and biophysical indicators. The indicators have been classified into adaptive capacity, exposure and sensitivity to climate change impact. Then Principal Component Analysis was used to compute vulnerability index of each agro ecological zone. The result shows that farmers living in the highland areas were very much vulnerable to natural shocks compared to those living in the lowland area. In order to identify and analyse the determinants of resilience to climate change impacts, ordered probit model was used. Households were classified into three categories based on the time they take to bounce back after natural shocks. The model outputs indicate that farmers with better investment on natural resource management, access to market, better social network, access to credit, preparedness, saving liquid assets, access to irrigation and better level of education exhibited greater level of resilience during and after climate change induced shocks.