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This study aimed to analyze the impact of women's micro and small enterprises' (MSEs) participation on poverty in Hadiya zone, Southern Ethiopia. The research was grounded on cross-sectional survey data from 385 women who were 215 MSEs participants and 170 non-participants that were designated through multistage sampling techniques. Both primary and secondary data have utilized to address the goal of the examination. The descriptive statistics, in combination with econometric method were used for analyzing primary quantitative data. A propensity score matching was utilized to analyze the impact of women MSEs participation small on poverty. The consequences of the propensity score matching investigation indicated that women participation in MSEs have expanded household expenditure by 7891.464Birr for participant and non-participant households. The sensitivity analysis result showed that the impact results estimated were unstable to unobserved selection bias. It was presumed that women' participation in MSEs had positive and significant impact on households food, non-food and total expenditure per adult per year. Inline exertions of government and other partners should support women to shift from non-informal economic sector to the formal sector to attain their basic needs as a result to reduce poverty.

Poverty is one of the central issues and the most far-reaching social matters on the planet. It has no geological limit. Along these lines, this examination has done to distinguish the determinants of the rural household poverty in Sodo Zuria Woreda of Wolaita Zone, Ethiopia. To accomplish this goal, 152 rural family units were chosen using a systematic random sampling technique following the corresponding method’s likelihood. The primary and secondary data optional information just as quantitative and qualitative subjective details have been used. In this investigation, the Cost of Basic Needs approach has applied to determine the extent of the poverty line and Foster-Greer and Thorbecke Poverty Index has used to decide the degree of rural poverty. The aftereffect of the basic needs approach’s cost shows that the investigation zone’s poverty line was about 5348.073 Birr every year per adult equivalent consumption. Utilizing this poverty line as a benchmark, the investigation demonstrated that 39.47 per cent of the family units were poor. The headcount index, poverty gap and squared poverty gap indexes among poor people families are 0.3947, 0.1035 and 0.0427. The Binary Logit Regression model’s discoveries show eight significant variables at under 1%, 5% and 10% likelihood level among 15 factors. As needs are, the family size was a positive relationship with the rural family’s poverty and measurably significant. In the interim, sex, age, educational level, land size, total livestock unit, use of technology and participation of saving have a tangible negative relationship with the rural household poverty and factually huge up to under 10% likelihood level. There is a need to reinforce the link between rural development and poverty reduction programs that consider old aged and female-headed families in mediations, limit populace size through integrated family planning and education obligations introduce appropriate livestock packages, and create awareness of the farmers for using new agricultural technologies.

The study was conducted to identify determinants of rural farm household food security status in Boloso Sore district of Wolaita Zone, Ethiopia. A three-stage sampling technique was utilized to obtain a sample size of 90 rural farm households. Cross sectional data were collected through structured questionnaire, focus group discussion and personal observation. Data were analyzed using head count index, food insecurity gap index, food surplus gap index and binary logit model. The result showed that only 34.5% of rural farm households were found food secure while 65.5% were food insecure. The food insecurity gap and food surplus index showed that food secured households exceeded the food security line by 34.6% while 27.8% of food insecure households fall below the poverty line. The severity of the food insecurity gap among the food insecure households was found to be 11.7%. The binary logit model result revealed that the major factors determining Original Research Article Tekle and Berhanu; AJAEES, 5(2): 57-68, 2015; Article no.AJAEES.2015.039 58 food security of rural farm households were family size in adult equivalent, total cultivated land size, annual income of household, oxen ownership of households, access to extension and credit and age of the household head. Age of household head, family size and access to extension services had a negative effect on household food security status while household income, credit access, oxen ownership and cultivable land size had a positive effect on household food security. Limiting the increasing population pressure, promoting income-generating activities, enhancing microfinancing efficiency, creating employment opportunities, information dissemination, among others can contribute to food security status of households in the study areas.