Agriculture is a risky business that is subject to endogenous risks. Endogenous risks caused by input utilization, input affordability and input availability may prove detrimental to the production potential of farmers. The study was aimed at examining the risk perception, risk aversion and risk management strategies of maize producers in Awi zone, which is found in the northwest part of Ethiopia. The study involved 343 respondents who produced maize under risk. Descriptive statistics, a seven-point Likert scale, the observed economic behaviour method, factor analysis and a seemingly unrelated regression model were used to process the data. The results showed that farmers have different perceptions of the endogenous risk associated with input availability and input affordability which has a different probability of occurrence and severity of damage. The observed economic behaviour method showed that farmers in the area also have different risk aversion behaviours: about 7.29% of the respondents in the study area have high risk aversion attitudes, while about 30.61% have medium risk aversion attitudes and 62.10% of them have low risk aversion attitudes. The seemingly unrelated regression model output showed that farmers’ economic, social, demographic and institutional factors, as well as their risk behaviour, determine the risk management strategies that they employ. Maize farmers in the area applied human risk management strategies, production risk management strategies, diversification, financial risk management strategies and marketing risk management strategies to tackle the endogenous risks in the area. It was deduced that maize farmers have a risk averse behaviour even if their risk aversion levels differ based on the scope of the management strategies that they employ to combat risk. Following the finding of the study, a holistic approach to risk management that encompasses all actors, such as farmers, researchers, extension services and financial institutions should be involved to make the appropriate interventions.

Though the Ethiopian economy is predominantly agriculture-based, the adoption of agricultural technologies has been very low. The results of a previous study had shown that microcredit access was one of the factors affecting the adoption of agricultural technology in Ethiopia. However, its effect has not yet been analyzed at the meta-level. Therefore, this study employed meta-analysis to understand the heterogeneous effect of microcredit access among farmers adopting agricultural technologies. We used subgroup analysis and meta-regression analysis to identify the heterogeneity level of credit access on technology adoption using the random-effects (RE) model. The study observed that there was a positive effect of microcredit access on agricultural technology adoption with a log odds ratio of 1.59. The subgroup analysis revealed a 93.2 % overall variation ($I^2$) with a p-value of 0.000, signifying a significant level of microcredit access within the between-groups heterogeneity of agricultural technology adoption studies conducted in Ethiopia. Notably, this was reflected by the adoption of improved livestock technologies, fertilizers, seed varieties, multiple agriculture, and irrigation technologies, with rates of heterogeneity of 94.9 %, 94.4 %, 94.3 %, 85 %, and 73.8 %, respectively, all with a p-value of 0.000. In addition, the meta-regression analysis results indicate that household experience, distance to the market, and income are significant moderators that affect the technology adoption decisions of farmers in rural Ethiopia. These findings suggest that policymakers should focus on improving the financial facilities and extension systems for rural farmers to enhance the adoption of agricultural technologies to increase production efficiency.

Cassava is a vital food source for Africans and is increasingly gaining status as a cash crop. However, Ethiopian farmers have yet not benefited from cassava marketing. This paper aims to explore the determinants of market participation, intensity, and channel choice of cassava producers in rural Ethiopia. Data were collected from 1040 cassava producers through three-stage random sampling techniques. Double Hurdle Model was employed to estimate the determinants affecting market participation decision and intensity and multivariate probit model (MVP) was employed to estimate the determinants of channel choice decision. The study revealed that market participation decision was positively affected by cell phone use, share of land allocated, and extension support while negatively related to access to credit and negotiating strength of farmers. The intensity of market participation is negatively related to distance to nearby markets while positively related to extension service and the quantity of cassava produced. Market channel choice was negatively affected by cell phone use, access to credit, knowledge of channels, and negotiating strength while positively affected by the share of land under cultivation and the quantity of cassava sold (log). The study suggests cassava producers consider forming an association that increases their bargaining power, increase information searching behavior while the government has to play an active role in advancing rural micro financial institutions to address financial challenge and improving access to market information to boost cassava production and marketing.

Enset is the only crop that can define food and nutrition security literally. Enset crop is closely related to food availability, access, use, stability, and nutrient balancing of densely populated communities in Wolaita and Kembata Tembaro zones. The climate smart, adaptive, productive, economical, and socially important Enset crop is the optimal way for ensuring food and nutrition security of communities. Hence, this study aims to estimate the causal effect of the level of Enset Production on farmers’ food and nutritional security in Southern Ethiopia. The survey applied structured and semi structured questionnaires for the collection of cross-sectional data from 374 sampled households in Wolaita and Kembata Tambaro Zones. Generalized Propensity Score (GPS) with multilevel treatment option was applied to deal with the impact evaluation of Production on food and nutrition security. Food and nutrition status of farming communities defined by calorie intake of households. The proxy measure of the level of Enset production was the number of Enset harvested across households in the last twelve months. The GPS method applied followed three estimation procedures such as modelling the conditional distribution of the treatment given the covariates, estimating the conditional expectation of the outcome given the treatment and GPS, and defining the dose response function. The results show that the small holder farmers that actively involved in harvesting Enset for food are significantly associated with increased level of daily energy intake. The implication of the study revealed that through the promotion level of Enset production, it is possible to have increased and balanced the energy intake of households in Southern Ethiopia. The empirical evidences illustrate that higher level of Enset harvesting is an optimal way for sustainable and better level of food and nutritious security for farming communities in southern Ethiopia.

Place-specific socioeconomic features are unique and, unlike first-nature geography, are shaped and reshaped by human and institutional interactions. In Ethiopia, however, policy thinking has not progressed much beyond first-nature geography, overlooking the multidimensional socio-spatial formations of rural areas. This study, based on nationally representative socioeconomic panel data from 2018/19 and 2021/22, used a place-based framework to explore the complex nature of rural development and its relationship with multidimensional, place-specific key determinants, namely rurality and entrepreneurial ecosystems. Indices for the key variables were developed by reducing their dimensions using Principal Component Analysis to measure multidimensional variables, including rural development, and undertake subsequent examinations. The study examines the effects of the key determinants on rural development using the Fixed Effects Instrumental Variables–Two-Stage Least Squares regression model, owing to endogeneity concerns with the key determinants. The study shows significant effects of both rurality and entrepreneurial ecosystems on rural development. It offers insights into the complex socio-spatial formations and explanatory power of rural contexts and contributes to the understanding of a place-based approach to rural development. The study also contributes to national and sub-national strategies to address rural challenges in Ethiopia and beyond.