Measurement and Analysis of Poverty in Rwanda

Heshmati, Almas; Rashidghalam, Masoomeh

doi:10.1007/978-3-030-11419-0_2

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…Even though the difference between income per capita and expenditure per capita is significantly low, this difference is predominantly negative (see World Development Indicators for Rwanda). Besides, Heshmati and Rashidghalam (2018) identified the differences between consumption and income measures of poverty in Rwanda. By means of income, head count absolute poverty is above 0.80 in all districts, whereas the absolute poverty by means of consumption is 0.531 on average.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of the Determinants of Household Expenditures in Rwanda

Maniriho

Musabanganji

Nkikabahizi

et al. 2021

UKHJSS

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Economists use two different approaches, unitary and collective, to analyze household decisions. The unitary approach ignores the differences between single-person and multi-person households, whereas the collective approach states that each person in the household must be characterized by specific preferences. The household’s decisions concern mainly the allocation of their income to current consumption or for savings and future consumer expenditures. This study uses the Comprehensive Food Security and Vulnerability Analysis (CFSVA) data collected from a random sample in 2015 in Rwanda. The ordinary least squares (OLS) method was applied to a linear regression model to estimate the household demand functions (total household consumption expenditures, household food consumption expenditures and household nonfood consumption expenditures). The results show that the socioeconomic characteristics of the household, the possession of productive assets and wealth conditions as well as the household locational controls are among the primary drivers of its consumption expenditures. The findings highlight the policy efforts that improve household human capital (education, health), access to and capitalization of productive assets and financial capital, continuous urbanization of rural areas, and sustained provision of quality infrastructure, to achieve high standards of household welfare.

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Section: Introductionmentioning

confidence: 99%

An Analysis of the Determinants of Household Expenditures in Rwanda

Maniriho

Musabanganji

Nkikabahizi

et al. 2021

UKHJSS

View full text Add to dashboard Cite

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Enhancing poverty classification in developing countries through machine learning: a case study of household consumption prediction in Rwanda

Nkurunziza,

Kabanda,

McSharry

2024

Cogent Economics & Finance

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Nexus between participation in nonfarm enterprises and poverty among rural farm households: evidence from Nigeria

Adeyonu,

Akerele,

Kehinde

et al. 2024

IJSE

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PurposeDespite a reduction in poverty the global population in 2015, the incidence of poverty remains very high in Sub-Saharan African countries. Most of the countries in the region are agrarian, with most of their population residing in rural areas, and a majority of the poor in the region are found in Nigeria. This study examined the nexus between participation in nonfarm enterprises (NFEs) and poverty among rural farm households in Nigeria and across the six geopolitical zones.Design/methodology/approachThe Nigerian Living Standard Survey (NLSS) conducted in 2018–2019 by the National Bureau of Statistics was used. We made use of 13,440 farm households with useful information for the purpose of this study. The sample comprises 6,885 households that participated in NFEs and 6,555 nonparticipating households. The data were analyzed with Foster, Greer, and Thorbecke (FGT) (1984) metrics, probit, and fractional probit models at p = 0.05.FindingsThe incidence of poverty was lower among the participating households than in the nonparticipating households. Participation in NFEs had a mitigating effect on poverty. We also established that zonal differentials in poverty rates exist among households in all the analyses. Participation in NFEs was influenced by individual, household, and institutional factors and was also able to explain the depth of poverty among the respondents.Practical implicationsIt is suggested that poverty alleviation policies should be targeted at improving access to nonfarm economic activities by rural farm households residing in vulnerable geopolitical zones.Originality/valueThis study is the first attempt to profile household poverty based on the type of NFEs they are involved in. The study also provides an insight into the effect of the state of residence on zonal poverty models, which is expedient if the country must achieve Sustainable Development Goal 1 on the eradication of poverty everywhere.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0493

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Measurement and Analysis of Poverty in Rwanda

Cited by 3 publications

References 10 publications

An Analysis of the Determinants of Household Expenditures in Rwanda

An Analysis of the Determinants of Household Expenditures in Rwanda

Enhancing poverty classification in developing countries through machine learning: a case study of household consumption prediction in Rwanda

Nexus between participation in nonfarm enterprises and poverty among rural farm households: evidence from Nigeria

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