| dc.contributor.author | Charles, Geofrey M. | |
| dc.contributor.author | Otieno, Sixtus M. | |
| dc.contributor.author | Kimaro, Magreth A. | |
| dc.contributor.author | Heriel, Elisante | |
| dc.contributor.author | Mwakasisi, Tuntufye G. | |
| dc.contributor.author | Mganga, John G | |
| dc.date.accessioned | 2023-07-18T12:18:08Z | |
| dc.date.available | 2023-07-18T12:18:08Z | |
| dc.date.issued | 2023-06 | |
| dc.identifier.citation | Charles, G.M., Otieno, S.M., Kimaro, M.A., Heriel, E., Mwakasisi, T.G., Mganga, J.G., (2023). Determinants of Multidimensional Poverty in Rural Tanzania., Rural planning Journal, 25(1), 81-96 | en_US |
| dc.identifier.issn | 0856-3460 | |
| dc.identifier.uri | https://repository.irdp.ac.tz/handle/123456789/412 | |
| dc.description.abstract | This study examines the determinants of multidimensional poverty in rural Tanzania.
Poverty is still a challenge in Tanzania, particularly in rural areas, since its incidence rate of
decrease is slower than in urban areas. The study used binary logistic regression to identify
the key determinants of multidimensional poverty in rural Tanzania. Both the Alkire-Foster
(2011) counting and binary logistic regression methods were applied to estimate the
Multidimensional Poverty Index and determinants of multidimensional poverty respectively.
The research utilized data that were already collected by the Tanzania Demographic and
Health Survey in 2017. The Alkire and Foster estimates, showed that, the majority of the
households living in rural Tanzania (74.43 percent) were poor. Additionally, the findings
showed that, the dimension of living standard (56.6%) contributes more to the total MPI,
followed by health (23.2) and education (20.2%). Binary logit regression model estimates
showed that, the factors being studied were proven to be statistically significant
determinants that have an impact on multidimensional poverty in rural Tanzania.
Moreover, female-headed households were 1.22 times more likely to be multi-dimensionally
poor compared to male-headed households at the 5% level of significance. The findings
reveal that age, education levels and married decrease the probability of being poor.
Similarly, the model revealed that, people who use family planning are less likely to be poor
(odd ratio, 0.79). This study has important policy implications for reducing
multidimensional poverty in rural Tanzania. The government should prioritize improving
access to basic amenities, housing, and infrastructure, and promote education and family
planning services. Gender-sensitive policies and programs are also needed to address gender
inequalities in rural Tanzania. For example, the government should invest in rural
infrastructure development programs, such as the Rural Water Supply and Sanitation
Programme, which aims to provide safe water and sanitation facilities to rural communities. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IRDP | en_US |
| dc.subject | Multidimensional Poverty Index, Multidimensional approach | en_US |
| dc.title | Determinants of Multidimensional Poverty in Rural Tanzania | en_US |
| dc.type | Article | en_US |
