The tomato had nutritional, economic and health benefits to the societies, however, its production and productivity were low in developing countries and particularly in Ethiopia. This might be due to technical inefficiency caused by institutional, governmental, and farmers related factors. Therefore this study tried to investigate the factors that affecting technical efficiency and estimating the mean level of technical efficiency of tomato producers in Asaita district, Afar Regional State, Ethiopia. Both primary and secondary data sources were used; the primary data was collected from 267 tomato producers from the study area cross-sectional by using a multistage sampling technique. The single-stage stochastic frontier model and Cobb Douglas production function were applied and statistical significance was declared at 0.05. The maximum likelihood estimates of the stochastic frontier model showed that land, labor, tomato seed, and oxen have a significant effect on tomato output; and education, extension contact, training, and access to credit have a positive and significant effect on technical efficiency, whereas household size, off-farm income, livestock ownership, distance to market, and pesticides have a worthy and significant effect on technical efficiency; and also estimated mean technical efficiency of tomato producer in a study area was 80.9%. In a line with this, the responsible body should prioritize rural infrastructure development in areas such as education, marketplace, and farmer training centers; demonstrate access to credit and extension services; use the recommended amount of pesticides per hectare, and give more intension to mixed farming rather than animal husbandry exclusively.

Household welfare is depleted by catastrophic health expenditure by forcing families to reduce the consumption of necessary goods and services, underutilization of health services, and of finally falling into the poverty trap. To mitigate such problem, the Government of Ethiopia launched CBHI schemes. Therefore, this study investigates the household welfare impact of Community based health insurance (CBHI) in the Chilga district. A multi-stage sampling technique was used to select 531 households (of which 356 were treated and 175 control groups). Probit and propensity score matching (PSM) were used to analyze the data. Probit model revealed the following: Level of education, access to credit, chronic disease, insurance premium, awareness, distance to health service, and health service waiting time are significant determinates for being insured in CBHI. The PSM method revealed that the insured households associated with visits increased by 2.6 times, reduced per-capita health expenditure by 17–14% points, increased the per-capita consumption of non-food items by 12–14% points, increased the per-capita consumption of food items by 12–13% points in a given matching algorithm compared to the counterparts. Therefore, CBHI has enhanced service utilization by reducing per-capita health expenditure and increasing consumption per-capita, in general, it improved household welfare. To this end, the results of this study suggested that the government (ministry of health) and concerned bodies (such as NGOs) should extend the coverage and accessibility of CBHI schemes, create aware to the society about CBHI, and subsidize premium costs of the poor.

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The main objective of this study was to analyze the effect of COVID-19 on social welfare in the case of Afar regional, state, Ethiopia using panel data collected from a sample of 384 in Asyaita, Dubti Samara-Logia, and Awash town. Both descriptive statistics and econometric models were used to analyze the data. The descriptive analysis results revealed that the main source of income emanated from self-employment (81.67%), from the total households 70% of them were engaged in the service sector, due to COVID-19 the income trends of 81% of households decreased, increase expenditure on food & food items (13%) and service delivering (15%). After conducting necessary pre and post-estimation tests, the econometric model found that the three basic policy variables (number of COVID-19 victims, number of days with the COVID-19 disease and transportation ban) adversely affected the welfare of the society by lessening the income of households and growing their expenditures. Finally, considering regional experience, econometric and descriptive results, this study recommends that the government and the concerned policy maker should give more attention and subsidize the service sector, support those self-employee and daily laborers, make awareness to the society about COVID-19 epidemic, place an alternative mechanism to fill potential trade gaps.