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Purpose: This study is aimed to examine the effect of rural infrastructure on smallholders’ crop input market participation with reference to Jimma zone. Research methodology: Censored Tobit approach was employed to model relationships between the degree of household market participation from input side and rural infrastructures. Results: Distance to the nearest all-weather-road from the farm area was found important. Moreover, provision of rural credit, communication and rural market services was found to significantly foster smallholder commercialization. Unfortunately, we estimated trivial coefficient for agricultural extension. Limitation: This study is limited to a year data, where we are unable to estimate the long term impact of rural infrastructural service on rural commercialization. Contribution: Various inadequacies in the provision of services may likely be involved. The right approach for the future should consider efficiency as well as the adequacy of the services being provided. It would be better to provide smallholders with the necessary infrastructures to ensure growth as well as the transformational targets. Besides, interventions intensifying rural access to information are vital. Keywords: Censored Tobit, Commercialization, Crop input Market index, Infrastructure, Smallholder

This study was aimed to investigate the determinants of income inequality among Urban households of Nekemte Town of Ethiopia by decomposing it across subgroups of the population. Accordingly, 275 households have been drawn using a stratified sampling method, while kebele (smallest administrative unit) has been taken as a stratum. Household expenditure per adult equivalent was used as a proxy for income inequality. Inequality situation and decomposition analysis by population subgroups were performed using Distributive Analysis Stata Package (DASP) to within and between subgroups components inequality relative contribution. Furthermore, Ordinary Least Square (OLS) and Quintile Regression (QR) Models were applied for econometric analysis. High inequality relative contribution was due to the 'between subgroups inequality relative contribution' of housing condition subgroups, education levels, age, family size and occupational types of subgroups, respectively. Likewise, high inequality relative contribution was due to 'the within subgroups inequality relative contribution' of marital status, gender and remittance of subgroups, respectively. On the other hand, the QRM result confirmed that age, gender, education level, marital status, family size, dependency, occupation, housing condition and remittances were the major determinants of income inequality in the study area. The implication is that government and development actors need to intervene through family planning, empowerment of women in productive activities, providing better quality and access to higher education, ensuring better access to housing infrastructure and transforming self-employment to address the causes of income inequality in the study area.

This research aimed to critically analyze the determinants of technology adoption and the use intensity by small farm households in the study area (Masha District). Six kebeles were randomly selected from the district, and 251 sample households were proportionally and randomly identified from the selected kebeles. The data collected from the sample households have been analyzed using both descriptive as well as inferential analysis. For inferential analysis, the Double Hurdle Model was adopted to estimate the technology adoption decision as well as use intensity of small farm households in the study area.  The findings show that technology adoption decisions were associated with household-specific characteristics such as sex, education, extension, and family size, increasing the likelihood of technology adoption. In contrast, the age of the household head has a negative contribution to it. On the other hand, institutional factors such as access to extension service and access to credit facilities have a significant impact where the latter has contributed negatively to the farmers’ decision regarding technology adoption.

Rural economy remain the back bone of Ethiopian economy absorbing tremendous labor share while how these labor market behave in rural economy of Ethiopia is yet uncovered. Besides the appreciated role of rural access to basic infrastructure with reference to rural labor supply decision, the topic is not bold in domestic literature. Considering this inadequate attention to the topic, we tried to examine the impact of rural infrastructure provision on individual labor supply, and assess the implication with each component of rural services to household participation decision in the labor market, using household survey from Jimma zone. Our multinomial logit regression indicated that rural services like education, health, credit, market information and access to all-weather-road are important considerations with regard to individual labor supply decision in farm and off-farm activities. It would be better to enhance rural access to efficient agricultural extension as well as other basic services towards empowering rural livelihood, and ensuring economic transformation at large.