Trend and determinants of multidimensional poverty in rural Nigeria

Adeoti, Adetola I.

doi:10.5897/jdae2013.0535

Cited by 36 publications

(36 citation statements)

References 7 publications

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“…Increase in female headed households is seen to increase the chance of being poor by about 62%; this might be in conformity with the assertion that female access less productive capital as compare to their male counterpart. The result is in line with the findings of Adeoti (2014). Also, more years of education is known to reduce poverty in the study area by 12.9% and an increase in the share of the dependents on the household head will raise poverty of the respondents.…”

Section: Determinants Of Poverty In Rural Nigeria In the Study Areasupporting

confidence: 89%

An analysis of multidimensional poverty and its determinants in rural Nigeria

Amao¹,

Ayantoye²,

Fanifosi³

2017

J. Dev. Agric. Econ.

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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.

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Section: Determinants Of Poverty In Rural Nigeria In the Study Areasupporting

confidence: 89%

An analysis of multidimensional poverty and its determinants in rural Nigeria

Amao¹,

Ayantoye²,

Fanifosi³

2017

J. Dev. Agric. Econ.

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“…This finding implies that the probability of being poor increases with age. The above is in consonance with the submissions of Adeoti (2014) and Amao et al (2017) who reported that age is a significant determinant of poverty across Nigeria. In the study area, the likelihood of being poor increases with being a female (rather than male).…”

Section: Factors Influencing Multidimensional Povertysupporting

confidence: 89%

“…Traditionally, poverty was considered a monetary issue, and hence, income was used as proxy for measuring it (Łuczka-Bakuła and Kalinowski, 2006;Adeoti, 2014). In recent past, the concepts of poverty have been broadened to include many other human development variables that are not necessarily economic in nature (Battiston et al, 2009;Le, 2015).…”

Section: Introductionmentioning

confidence: 99%

Analysis of multidimensional poverty in rural Adamawa State, Nigeria

Michael

Tashikalma

Maurice

et al. 2019

J. Agribus. Rural Dev.

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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.

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“…Accordingly, a number of studies such as Takane (2009), Berhanu (2011), Adeoti (2014) confirmed that there is a positive association between female household headship and the prevalence of poverty. However, there are still remaining unsettled issues among previous studies on the implications of female household headship on poverty.…”

Section: Introductionmentioning

confidence: 97%

Feminization of multidimensional urban poverty in sub‐Saharan Africa: Evidence from selected countries

Ede'o¹,

Ketebo

Chala

2020

African Development Review

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The main purpose of this study was to examine feminization of poverty in urban areas of sub-Saharan Africa (SSA). The paper used the Alkire-Foster multidimensional poverty approach and compared the wellbeing of femaleheaded households with their male-headed counterparts. The study utilized data compiled from demographic and health surveys of selected SSA countries, namely, Ethiopia, Malawi, Rwanda, and Tanzania. It applied a multilevel mixed effect logistic regression model to analyze the effects of household-and country-level variables on the incidence of multidimensional poverty on the two household structures separately. The study confirmed that female-headed households were poorer than male-headed households. Among householdlevel variables, having access to finance, a higher level of education completed by the household head, the age of the household head, having a smaller-sized family, and being employed have a positive and significant effect on multidimensional wellbeing of households. Moreover, expenditures on primary school and health significantly reduce the incidence of multidimensional poverty. The effects of these micro and macro variables are found to be different for the two household structures. Therefore, antipoverty policies and programs should be implemented in such a way that they mitigate these differences in household characteristics in favor of female-headed households.

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Trend and determinants of multidimensional poverty in rural Nigeria

Cited by 36 publications

References 7 publications

An analysis of multidimensional poverty and its determinants in rural Nigeria

An analysis of multidimensional poverty and its determinants in rural Nigeria

Analysis of multidimensional poverty in rural Adamawa State, Nigeria

Feminization of multidimensional urban poverty in sub‐Saharan Africa: Evidence from selected countries

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