Abstract:
The objective of this study was assessing the level of rural poverty and exploring associated factors causing poverty in rural areas of Meta Woreda. A multi-stage stratified sampling technique was employed to select the representative samples. Firstly, rural kebeles (of the woreda) were stratified by agro-ecology. Secondly, from each agro-ecological zone, one rural kebele was randomly selected. Finally, random samples of 143 rural households were drawn from the kebeles based on probability proportionate to size technique. The collected data through household survey was entered, manipulated and analysed using SPSS software. The study used both descriptive and inferential statistics. Descriptive statistics such as frequency distribution tables, mean and standard deviation were used to analyze the socioeconomic characteristics of the respondents. To analyze the poverty status of the sampled households, a poverty line was calculated using cost of basic needs procedures and the absolute poverty line is used. Thereafter, the FGT poverty indices were computed and the resulting poverty estimates for the study area showed that absolute head count, the poverty gap and the severity of poverty (the squared poverty gap) indices were 46.8%, 26.6% and 16.7%, respectively. The Binary Logistic model was used to identify the determinants of poverty in the area. Thirteen explanatory variables were included in the binary logit model to identify determinants of rural household poverty. The result of logistic regression model revealed that out of 13 variables 7 are found to be significant. Accordingly, family size, dependency ratio and age of the household head were found to be significant and positively related to poverty. However, farm income, off-farm income, education of the household head, and cultivated land size were found to be significant and negatively associated with poverty status. The findings imply that emphasis should be given to the following issues with a view to reduce poverty prevalence in the study area. Accordingly, building basic livelihood assets, improving institutional services (education), implementation of family planning programs, improving the labor market and productivity at the farm level could provide entry points for policy making and intervention
