Dissertation (MA Economics)The literatures show that, until recently, Tanzania’s poverty indices have been calculated using an income approach only. Therefore, this study aimed at covering the existing gap of measuring poverty in multidimensional way. The main objective of the study was to calculate the multidimensional poverty index of Tanzania. Specifically, the study intended to determine non-monetary deprivation levels in Tanzania; to examine the determinants of multidimensional poverty; and to determine the non-indicator measurement variables of multidimensional poverty. By using the most recent nations representative Tanzania Demographic and Health Survey (TDHS) of 2015/16, the study has empirically measured multidimensional poverty both at the national and subnational levels. In measuring the multidimensional poverty index, the study adopted the Alkire Foster methodology and focusing on three globally non-monetary poverty dimensions: standard of living, education and health. On the other hand, the Logit regression model was used to determine the nature of relationship between the status of multidimensional poverty and the non-indicator measurement variables of multidimensional poverty. The findings revealed that, the Tanzanian’s headcount ratios for the year 2015/16 was 57.86%, the average intensity of deprivation stood at 51.38% and thus Tanzania multidimensional poverty index was 29.7%. Also, the multidimensional poverty index was higher in rural areas (36.2%) than in urban areas (14.3%). On the other hand, results for logistic regression model showed that, the odds ratio of a household of being multidimensionally poor increased by 40% for a household living in rural areas. Also, the odds of a household of being multidimensionally poor increased by 10% for a household, for each additional household member. Therefore, the calculation of poverty based solely on monetary terms does not account for multiple deprivations to which people are subject and thus provides insufficient details for policy making. The study recommends that, the MPI index may be used to enhance social assistance targeting, with an emphasis on those with multiple deprivations. Also, the index may be used to build new and improved poverty maps.