An analysis of multidimensional poverty and its determinants in rural Nigeria

Abstract

Human beings live to get happiness, livelihood, peace, security, safety, dignity and respect among others. Deprivation of any of these could be frustrating. Thus, attempts were made to determine multidimensional poverty index (MPI) of rural households and its decomposition by geo-political zones in Nigeria using the Alkire-Foster MPI approach. The result showed that the headcount poverty ratio H was 78.1% when K = 30 as compared to 58.8% for K = 40 and 23.6% for K = 60. The adjusted headcount ratio also suggested that 41% of the households were poor at K=30, whereas 34.2 and 16.7% of the households were considered poor for K=40 and K=60, respectively. The intensity of poverty from the result showed that the share of dimensions in which the poor were deprived increased with K, while the MPI of the households was decreasing with K. The result further revealed that living conditions contributed the largest value (59.9%) to the multidimensional poor, followed by education (14.3%), health (13.4%) and assets (12.4%). Therefore, the living condition and education of households should be prioritized in targeting poverty as it contributes largely to MPI across all the geopolitical zones in the country.

Effects of Ill-Health Cost on Multidimensional Poverty: Evidence From Rural Households in Nigeria

“…The multidimensional poverty index was 0.28, this implies that the rural households are deprived in 28% of the total deprivations they could experience overall. These findings differ from that of OPHI (2017) and Amao et al, (2017) that found out that the multidimensional poverty status of Ogun state and south-western Nigeria are 11.2% and 31.8% respectively.…”

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

“…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.…”

Nonmonetary poverty in Ethiopia: Multidimensional approach

“…Alkire and Santos (2010), Alkire and Foster (2011), Alkire et al (2018), World Bank (2018), and Alkire et al (2014) represented education by school attendance and years of schooling; health by nutrition and child mortality; and living standards by cooking fuel, electricity, housing, improved water, improved sanitation, and asset ownership. Nonetheless, in other studies, particularly in those at the national level, including Woldehanna (2011), Mekonnen (2015), Tilman and Kebede (2013), and Joshua et al (2017), the dimensions and indicators differ across countries and scholars. This shows that the selection of dimensions and respective indicators for the estimation of poverty in a multidimensional approach depends on the socioeconomic characteristics and contexts.…”

“…These studies were mainly based on three dimensions—education, health, and living standards—with 10 indicators for more than 104 countries. In contrast, there are studies undertaken at the national level, such as in South Africa by Rogan (2016), Brazil by Justino et al (2004), India by Alkire et al (2014), Nigeria by Joshua et al (2017), and in Uganda by Arinaitwe et al (2017). They consider country‐specific characteristics in their identification of dimensions and indicators.…”