Finance and Poverty in Ethiopia: A Household-Level Analysis

Alemayehu, Getachew; Shimeles, Abebe; Zerfu, Daniel

doi:10.1057/9780230594029_4

Cited by 34 publications

(37 citation statements)

References 27 publications

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“…Fouareg and Layte (2003), in their research exhibited that education level and the numbers of household members were effective on poverty. Geda et al (2001), in their study about absolute poverty in Kenya, found that the residence, gender, the sector of employment of the head of household, education level and household size affected poverty. Most of the studies about poverty in Albania rely on the expenditure and consumption data and thus use the poverty line computed from the Albania Living Standards Surveys data using the cost of basic needs method.…”

Section: Literature Reviewmentioning

confidence: 99%

Determinants of Poverty in Albania

Spaho¹

2014

JESR

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Section: Literature Reviewmentioning

confidence: 99%

Determinants of Poverty in Albania

Spaho¹

2014

JESR

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“…Matita and Chirwa [24] analyzed the extent of urban-rural welfare inequalities in Malawi with the help of a representative sample at the national level as well as the factors which contribute to such inequalities, using the decomposition techniques of both Oaxaca-Blinder [25,26] and Machado and Mata [27] The decomposition results of this study notably show that a large share of the welfare gap may be explained by the differences in the characteristics «physical assets and education» rather than by discrimination.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This objective has been achieved in two stages: firstly by identifying the determinants of welfare in the urban and rural areas using OLS regressions and quantile regressions and secondly, by decomposing welfare inequality into the relative contributions of endowments and discrimination using the Oaxaca-Blinder [25,26]; decomposition method.…”

Section: Conclusion and Policy Implicationsmentioning

confidence: 99%

The Determinants of Inequality and Income Gap between Urban and Rural Areas in Cameroon: Evidence from the ECAM3 Household Survey

Fambon¹

2017

aeb

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This paper analyzes the determinants of income and the urban-rural income gap to highlight the urban-rural inequality problem in Cameroon. It concurrently uses the OLS regression, the conditional quantile regression as well as the Blinder-Oaxaca decomposition techniques to achieve this objective. The findings of OLS estimations show that human resources and social as well as physical capital play a major role in the improvement of welfare. Household size reduces the consumption expenditures both in rural and urban areas. The regions where the households reside also affect consumption expenditures. Household heads who work in the services sector and trade are better-off than those working in the other sectors of the economy. However, quantile regressions results show that households headed by the old people enjoy a higher level of welfare in the upper quintiles of the distribution of consumption. Household heads who work in the industrial sector have a negative relationship with consumption at the 10 th quintile of the distribution of household expenditures in the urban area. In the rural area, household heads working in the services sector have a positive relationship with consumption only at the 50 th and 90 th percentiles of the distribution of expenditures, whereas those belonging to the 10 th quintile have a negative relationship with consumption. In the rural area, the average time span spent to reach an asphalted road has a stronger positive impact on the consumption of households belonging to the 90 th percentile of the distribution of expenditures. Being a member of an association has a significant positive effect only on the consumption of households belonging to the 10 th quintile of the expenditures distribution. The study results derived with the help of the Oaxaca-Blinder decomposition method show that 59 percent of the welfare gap between urban and rural areas may be explained by differences in the characteristics, and most particularly in physical assets and education. The remaining 41 percent of the welfare gap is explained by discrimination.JEL Classification: O15, O18, D31, D63, O55

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“…To capture gender earning differences in rural Mozambique, we hypothesizing that female-headed households are disadvantaged in both income and food security, and therefore, female-headed households are more likely to be poor and food insecure than male-headed households as found elsewhere by [30,2].…”

Section: Hypothesized Drivers Of Household Food Insecuritymentioning

confidence: 99%

Food Security Dynamics and its Drivers in Rural Mozambique

Pitoro¹,

Chagomoka²

2017

ijSciences

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This paper uses regionally representative panel household survey data of 1,186 households in the high agriculture potential zone located in the Central and Northern regions to assess household food security trends and its drivers, specifically to determine the extent landholdings have influenced food security dynamics in rural Northern-Central Mozambique. The main finding of this study is that although food security level has been stable over the study period, the agricultural production, rural non-farm activities, establishment of food reserves, food availability, assets, and access to non-farm income opportunities and transportation have influenced food security level of the rural families. This suggests that investing in infrastructures such as public transportation and roads, minimizing agricultural production risks, promoting in education and livestock production aremore likely to have a larger effect on the extremely poor households than on the less poor when wage employment opportunities and proper training are available.

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Finance and Poverty in Ethiopia: A Household-Level Analysis

Cited by 34 publications

References 27 publications

Determinants of Poverty in Albania

Determinants of Poverty in Albania

The Determinants of Inequality and Income Gap between Urban and Rural Areas in Cameroon: Evidence from the ECAM3 Household Survey

Food Security Dynamics and its Drivers in Rural Mozambique

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