生态系统与生态学杂志

抽象的

Households Income Poverty and Inequalities in Tanzania: Analysis of Empirical Evidence of Methodological Challenges

Lusambo LP

The overarching objective of this study was to assess poverty situation in Tanzania using a multitude of approach so as to provide empirical evidence of conceptual and methodological challenges encountered in poverty analysis studies. Specifically, the study strove to: (1) analyse the poverty situation in the study sites, (2) assess income inequality in study sites, and (3) determine the method that could be commonly employed to measure poverty , with a view to improve consistency in poverty statistics. A sample of 568 respondent households was involved in the study. Data was collected through household questionnaire, key informant interview, focus group discussion and researcher’s direct observations. Collected data was analysed using statistical package for social sciences (SPSS) and Microsoft excel computer programmes. Different poverty lines have provided different results regarding the number of households which are poor. Relative poverty line of 40% of the median income gave the lowest value of poverty in the study area, while the ethical poverty line provided the highest rate of poverty. Accordingly, it was found that using selected poverty lines: overall, 29.3% - 98.2% of households are poor. In rural areas, 24.5% - 96.8% of households are poor. In peri-urban areas, it was found that 20% to 100% (depending on the poverty line used) were poor, while in urban areas the poverty rate was found to be between 37.1% to 99%. Using weighted geometric mean of relative and absolute poverty lines (ρ = 0.7) at relative poverty line of 50% of median income and absolute poverty line of US$ 1-a-day (2005PPP): Overall, 53.5% of households are poor, and poverty rates in rural, peri-urban and urban areas are 55%, 53% and 46% respectively. The findings revealed further that the poverty gap ratio and severity ratio are highest in urban areas (0.35 and 0.29 respectively), medium in rural area (0.33 and 0.24 respectively) and minimum in peri-urban area (0.29 and 0.20 respectively). Household income inequality in the study area is high (Gini Coefficient = 0.773), with variations in the strata as follows: rural areas (Gini Coefficient = 0.821); peri-urban areas (Gini Coefficient = 0.574); and urban areas (Gini Coefficient = 0.717). Inter-strata inequality index in the study area (depending on the method used) ranged between 0.158 – 0.172, while inter-regional inequality index ranged between 0.004 and 0.116. Some recommendations have been put forward: Firstly, in the determination of poverty rates (head counts) the appropriate yardstick to be used is weighted geometric mean of relative and absolute poverty lines (ρ = 0.7) at relative poverty line of 50% of median income and absolute poverty line of US$ 1-a-day (2005PPP). Secondly, in the determination of household income inequality, Gini Coefficient should be used. Thirdly, the Hoover coefficient (Robin Hood Index) is a more appropriate metric for regional and inter-strata inequality.