Browsing by Author "Kimambo, Glory V."

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    A comparative analysis of the determinants of income and non-income poverty approaches in Tanzania.
    (2023) Kimambo, Glory V.
    This study examines poverty in Tanzania through both income-based and non-income-based approaches. The aim is to provide a comprehensive analysis that can inform poverty alleviation strategies and policy-making in Tanzania. Specifically, the study focused on the estimate and compares income and non-income poverty in Tanzania, decomposing and compares income and non-income household deprivation level across social group in Tanzania and to estimate the determinant of income and non-income poverty in Tanzania. The study employed a longitudinal research design where by quantitative research approach adopted. The study used secondary data obtained from Tanzania National Bureau of Statistics (NBS) that are Household and Budget Survey (HBS) data of 2017/18 to calculate multidimensional poverty index of Tanzania that include non-income variable and headcount ratio on income variable. The collected data analyzed using descriptive statistics method and binary logistic regressions. The descriptive statistics involved Foster-Greer-Thornback (FGT) method in measuring income poverty and Alkire-Foster method that included three global dimensions in measuring non income poverty. Binary logistic regressions used to estimate of determinants of income and non-income poverty at household level in Tanzania. The findings revealed that Tanzania headcount ratios for 2017/18 was 26.4%, poverty intensity of stood 2.1% and overall Tanzania MPI estimated at 34.04% and intensity deprivation was 43.75% mean while majority of Tanzania are deprived on nutrition and cooking fuel by 77.45% and 76.12% respective which means they used wood and dung as main source of cooking fuel. Moreover, the study found that, in multidimensional poverty, household head size, the household head's educational level, the marital status of the household head, t, gender of household head, and household asset were statistically significant influences on deprivation level, while in income poverty, household size, household head education, and location of household head were only statistically significant influences on deprivation level. Therefore, study recommends that government should use both methods to measure poverty status and on reducing poverty since both measures can be complement to each other simply MPI gives more details of poverty based on dimension and indicators.