Author(s): Salim Msalilwa

Abstract: Despite the international development community's longstanding emphasis on poverty reduction, Tanzania continues to face persistent multidimensional poverty, hindering socioeconomic development and nutritional quality. This study analyzed determinants of multidimensional poverty using the 2017-2018 Tanzania household budget survey dataset (8767 households). The principal component analysis (PCA) was deployed to obtain the outcome indicator by combining those dimensions that contribute the most to multidimensional poverty to capture more information. FGLS method, as an extension of the OLS method, was used to solve the problem of heteroscedasticity by including the predicted weights. The study found that age of the household head, marital status of the household head, location, years of schooling of the headship, household size, income, and employment status were significantly related to multidimensional poverty index. Urban location, official employment status, not married status were better in reducing poverty situation than rural location, not employed status and married status, respectively. In addition, higher household income, years of schooling, age of headship as well as smaller household size, were found to be absolutely improving the household well-being. The findings suggest enhancements in agricultural technology, education, and access to loans for small farmers and small entrepreneurs tackle household poverty effectively.

DOI: 10.22271/maths.2024.v9.i5b.1845

Pages: 145-151 | Views: 83 | Downloads: 7

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