Analysis of multidimensional poverty in rural Adamawa State, Nigeria

Abstract

This study assessed multidimensional poverty in rural parts of Adamawa state, Nigeria. Specifically, the study objectives were to: describe the respondents’ socio-demographic characteristics, determine their multidimensional poverty status, and identify the determinants of multidimensional poverty in the sampled communities. Multi-stage cluster sampling technique was used to collect primary data from 480 household heads selected from 16 villages across the study area. Data collected were analysed using descriptive statistics, Multidimensional Poverty Analytical Tool (MPAT), and Binary Logistic regression model. The respondents’ socio-demographic characteristics described in the study showed that the mean age was 46.3 years, while the average household size was 7 persons. The study indicated that most (86.7%) of the respondents were male, who are mostly married (91.7%), and that majority (74%) are educated. The distribution of the respondents’ multidimensional poverty status revealed that majority (61.7%) of the households were poor. The study revealed that multidimensional poverty in the study area is influenced negatively by age, marital status, and household size. Similarly, gender, educational level, livelihood activities, farm size, livestock ownership, remittance, membership of group, and access to credit positively influence multidimensional poverty. Key among the recommendations of the study is the adequate provision of basic infrastructure in the area.

Rural Households’ Multidimensional Poverty and Its Determinants in Konso Woreda, SNNP Region, Ethiopia

“…A household with extensive tracts of cultivated land is more likely to generate more food and is less likely to live in poverty. This result is in agreement with the study conducted by Amao et al (2017), Adepoju (2018), Michael et al (2019), and Chen (2019) et al, who found that household head farm size helps households reduce multidimensional rural poverty.…”

“…This outcome supports the findings of Michael et al (2019), according to which the likelihood of being poor increases with being a female-headed household (rather than a male headed household). Family size is significantly and negatively correlated with multidimensional poverty status.…”

“…Therefore, households with more family members who are actively involved in family farm activities can manage their family farms easily, and the more economically active household members in a family, the less likely the family is to fall into poverty. This outcome supports the conclusions of Amao et al (2017), Heshmati & Yoon (2018, Michael et al (2019), andChen (2019) et al, who conducted a study on the determinants of multidimensional poverty and found that household size is negatively and significantly associated with multidimensional poverty. Spending per adult equivalent has a negative impact on the probability of households' multidimensional poverty status in the study area and is statistically significant at the 1% probability level.…”

“…As a result, poverty will worsen in old age for household heads. The study's findings support those of Amao et al (2017), Michael et al (2019), and Chen (2019) et al, who conducted a study on the determinants of multidimensional poverty and found that the age of the household head is positively and significantly associated with multidimensional poverty.…”

Multidimensional poverty in South‐West Nigeria: Empirical insights from a household survey in Osun State

“…Decomposing for gender based on the four‐dimension (as shown in Table 8) revealed that children from the male‐headed household are less likely to be educationally deprived, less likely to have a better living standard, less likely to have health‐related issues, and 1% more likely to have access to the internet than female‐headed household. These results correspond to those of Fonta et al (2018), White and Yamasaki (2017), and Michael et al (2019).…”