We examine the link between road accessibility and the use of maternal healthcare services in Ethiopia. Using a quasi-experimental design, we compare maternal health outcomes in villages before and after road construction alongside control villages without such infrastructure. Our analysis suggests that rural road development is associated with increased utilization of maternal healthcare services during the prenatal stage. However, we did not observe significant associations during the birth or postnatal stages. Using data collected before the commencement of the road expansion program, we confirm that the observed association between road access and maternal healthcare utilization can be attributed to the road infrastructure rather than to pre-existing conditions in the villages.

Although it is widely recognized that accounting for spillovers from higher education institutions is essential when formulating educational policy, research on these effects in developing countries is scarce. This study examines the spillover effects of Ethiopia's recent public university expansion program on the educational attainment of female adolescents in the surrounding areas. Employing an event study framework, the research demonstrates a positive association between the presence of a university in the neighborhood and the academic achievement of female students at lower educational levels.

Unlike existing studies that examined the effects of weather variability by relying on the current weather conditions disregarding the long-term influence of historical weather patterns, we jointly estimate the effects of current and past weather variability on rural households’ nutritional status. Using three waves of nationally representative panel data from rural Ethiopia, we show that the nutritional status of farming households, measured by daily intakes of micro-and macronutrients, is more sensitive to past weather variability than the current weather condition. We also find that adverse weather history can trigger responses that are linked to the deterioration of nutritional status.

New roads bring new opportunities including access to employment. However, new employment opportunities might encourage early school dropout and school absenteeism. We investigate the link between rural roads, children's labor allocation, and educational outcomes by focusing on the recent Ethiopian road construction program. In the analysis, we combine household panel data with novel road network data. To address endogeneity concerns, we combine a difference-in-difference estimation model with a matching technique. Our findings consistently show that road access does not encourage school absenteeism or school dropouts to join the labor force. The findings remain consistent across gender and age groups.

While a lot has been written on the socio-economic and welfare impacts of agricultural technologies, there has been a bias toward crop production systems to the neglect of improved livestock production methods and technologies. This paper explores the welfare impacts of improved livestock production practices and technologies using data from a low-income country. Using an econometrics technique that corrects selection bias, the paper shows that the adoption of improved livestock production practices has a positive impact on household welfare, measured by consumption expenditure and diet quality. The study also identified increased consumption of animal source foods, reducing animal death and income from the sale of animals as potential mechanisms through which such improvements in livestock production affect family welfare.

This study examines the impact of the row planting method on maize productivity and risk exposure using panel datasets from Ethiopia. A flexible moment-based production function is fitted to capture the expected yield, yield variance, and exposure to downside risk. A Mundlak-Chamberlain approach is combined with a switching regression treatment effects model to account for unobserved heterogeneity and endogeneity. The study shows that adopters of the row planting method significantly reduced exposure to downside risk while increasing expected yield. The analysis also identified some household and environmental conditions that affect the gain from the row planting method.

Abstract This study investigates the impact of climate shock on Somali households' welfare status and examines the mediating roles of formal and informal financial institutions—mobile banking and remittances—in enhancing households' coping capacity. Using representative panel data, we show that climate shock has adverse effects on multiple welfare indicators for both female-and male-headed households. However, we find that female-headed households are more likely to fall below the poverty line, have a larger poverty depth, and shift their diet due to climate shock than male-headed households. Interestingly, we find that remittances decrease following climate shock, both on average and for female-headed households, but such reduction does not have a significant adverse effect on the households' coping ability. This could be an indication that Somali households rely on other coping mechanisms to shocks than remittances. Similarly, even though we find that mobile money increases the likelihood of receiving remittances, we find no evidence that this translates into a higher coping ability to climate shock. Further investigation is needed to identify Somali households' coping strategies. JEL Classification: D14; E42; G23; I3; L96; O17; Q54

Using unique crop-specific data gathered over 7 years, we study if and how maize-producing farmers in Ethiopia adjust their land allocation decisions in response to pre-planting-season weather variations. We show that farmers adjust their land allocation decisions in response to increased temperatures early in the growing season. In addition to quantifying a substantial adaptation margin that has not been documented before, our study also reveals the presence of a weather variation-induced expansion of maize production into areas that are less suitable for maize cultivation.

Purpose This study examines the impact of access to credit on the technical efficiency (TE) of maize-producing smallholder farmers in Ethiopia and explores factors determining credit utilization. Design/methodology/approach The study relies on nationally representative data collected in 2015/2016. The data are analyzed by combining the Propensity Score Matching technique with a stochastic frontier model that corrects selectivity bias arising from unobserved variables. Findings The result shows that credit service improves TE and helps smallholder farmers to achieve the maximum possible output level from a given set of inputs used. Originality/value To the best of author’s knowledge, no study has yet measured the impact of access to credit on TE by controlling for both observed and unobserved heterogeneities. Existing research relied on a single production frontier model, assuming that credit users and non-users have similar production characteristics or ignored selection bias due to observable and unobservable characteristics.

This study investigates the impact of improved maize varieties and inorganic fertilizer on productivity and consumption expenditure of smallholder farmers in Eastern Ethiopia. The study uses primary data of maize farmers and a multinomial endogenous switching regression model to account for selection bias. The findings show that combining the two technologies boosts maize yield and consumption expenditure significantly than adopting the technologies in isolation. As a result, policies targeted at improving farm household welfare and productivity should promote the adoption of a combination of agricultural technologies rather than a single technology.

This study evaluated the technical, economic and allocative efficiency of maize production in eastern Ethiopia using cross-sectional data collected from 480 maize plots. The stochastic production function, fitted using the Cobb–Douglas production function, indicated that the amount of seed, land and DAP (Diammonium phosphate) are highly significant in determining maize production in the study area. The results of the study also indicated that the potential to improve economic efficiency of maize production in the study area relies more on allocative efficiency compared with technical efficiency. The study also identified socioeconomic and institutional factors that determine technical efficiency in the study area.

This article analyzes the impact of participation in off-farm activities on technical efficiency of maize production in eastern Ethiopia. We combined propensity score matching with a stochastic production frontier model that corrects sample selection bias resulting from unobserved factors that potentially affect both households’ decision to participate in off-farm activities and technical efficiency scores that most previous studies do not account for. The probit model results indicate that sex of the household head, literacy of the spouse, agricultural cooperative membership, family size, and access to market information had significant effect on farmers’ participation in off-farm activities. In the meantime, it was found that farmers who participated in off-farm activities have a significant technical efficiency gain compared with their non-participant counterparts.

This study evaluated the impact of agricultural cooperative membership on the wellbeing of smallholder farmers using cross-sectional data collected from the eastern part of Ethiopia. Using consumption per adult equivalent as a wellbeing indicator, we measured the impact of agricultural cooperative membership by implementing propensity score matching and endogenous switching regression estimation techniques. Both estimation methods indicate that joining agricultural cooperatives has a positive impact on the wellbeing of smallholder farmers. Furthermore, the analysis also indicates that agricultural cooperative membership has a heterogeneous impact on wellbeing among its members.

The aim of this study is to measure the impact of improved maize varieties on farm productivity and smallholders' wellbeing using data collected from the East Hararghe Zone of Ethiopia. We combined propensity score matching method with endogenous switching regression to estimate the impact on the welfare of farmers and we applied the stochastic frontier corrected for sample selection to measure the impact on farm productivity. The results show that adoption of improved maize varieties leads to significant gains in wellbeing and improves farm productivity.

The gap between demand for and supply of food in Ethiopia can be reduced by improving farm productivity through the introduction of productivity-enhancing technologies. Conversely, in Ethiopia, the adoption rates of agricultural technologies remain below the expected levels. Hence, by using multivariate probit model, this study identifies factors that motivate the adoption of a combination of inorganic fertilizer, improved seed, manure and cropping system diversification in eastern Ethiopia using multiple plot-level observations. The analysis shows that the probabilities of adoption of agricultural technologies are influenced by household, socioeconomic, institutional and plot-level characteristics. Alongside this, the paper also shows that there is a significant correlation between the selected technologies, suggesting that adoptions of technologies are interrelated. Specifically, the result indicates that there is complementarity between inorganic fertilizer and improved seed; and substitutability between inorganic fertilizer and manure. The result also indicates there is complementarity between adoption of improved seed and manure; and adoption of improved seed and crop diversification.

This research analyses factors that influence the adoption of combination of improved groundnut seed, inorganic fertilizer, and organic fertilizer in eastern Ethiopia using a cross sectional data collected from 300 sample groundnut farming households. Multivariate probit and ordered probit models are used to identify factors affecting adoption of multiple technologies. Tobit model is used to spot the determinants of intensity of adoption of improved seed. The results show a strong correlation between improved seed and inorganic fertilizer adoption, indicating the simultaneous adoption decision of farmers. Age of the household head negatively affects the adoption decision of improved seed while education, groundnut farming experience, extension contact, training and plot size are positive contributors.

The impacts of climate change are considered to be strong in countries located in tropical Africa that depend on agriculture for their food, income and livelihood. Therefore, a better understanding of the local dimensions of adaptation strategies is essential to develop appropriate measures that will mitigate adverse consequences. Hence, this study was conducted to identify the most commonly used adaptation strategies that farm households practice among a set of options to withstand the effects of climate change and to identify factors that affect the choice of climate change adaptation strategies in the Central Rift Valley of Ethiopia. To address this objective, Multivariate Probit model was used. The results of the model indicated that the likelihood of households to adapt improved varieties of crops, adjust planting date, crop diversification and soil conservation practices were 58.73%, 57.72%, 35.61% and 41.15%, respectively. The Simulated Maximum Likelihood estimation of the Multivariate Probit model results suggested that there was positive and significant interdependence between household decisions to adapt crop diversification and using improved varieties of crops; and between adjusting planting date and using improved varieties of crops. The results also showed that there was a negative and significant relationship between household decisions to adapt crop diversification and soil conservation practices. The paper also recommended household, socioeconomic, institutional and plot characteristics that facilitate and impede the probability of choosing those adaptation strategies.

The objective of this study was to identify the important factors that influence both adoption and level of use of organic fertilizer among smallholder farmers in the Central Rift Valley of Ethiopia using a primary data collected from 161 sample respondents. An independent double hurdle model was used to address the objectives of the study on the assumption that adoption and level of organic fertilizer use by are two independent decisions influenced by different factors. Empirical estimates of the first hurdle reveals that literacy status of the head, livestock holding, frequency of extension contact, distance to market and slope of the plot are statistically significant decision variables that affect the probability of adopting organic fertilizer. Meanwhile, estimates of the second hurdle revealed that, the extent of use of organic fertilizer was determined by livestock holding, access to credit distance to the market and slope of plot. This indicates that factors that affect adoption are not necessarily the same as those that influence intensity. Therefore, it is important to consider both stages in evaluating strategies aimed at promoting the adoption and use of organic fertilizer.

This study has evaluated the impact of adoption of improved groundnut seed on the well-being of the farmers of Eastern Ethiopia using a cross-sectional data collected from 301 sample households. To address this objective, both descriptive and econometric analysis methods were employed. In the econometric analysis, Propensity Score Matching was used to measure the impact of adoption of improved groundnut seeds on well-being measured as expenditure per adult equivalent. The results of the study have indicated that adoption of improved groundnut seeds has a positive and significant impact on the welfare of the farmers. Therefore, socioeconomic variables should be addressed to improve the adoption of improved groundnut seeds, which in turn increases the welfare of groundnut producing farmers.