Modelling the determinants of rural household poverty: empirical evidence from Somalia

Although poverty has been decreasing globally in recent years, it remains a significant challenge in Somalia, particularly in rural areas where the poverty rate is higher than the national figure. Most livelihoods in these areas rely on rain-fed agriculture and livestock. However, there is currently no comprehensive study examining the extent of poverty and the associated risk factors in these regions. This study utilizes multivariate logit model to analyze the impact of socio-economic characteristics of rural households on poverty in Somalia, using data from the Somalia High-Frequency Survey (SHFS) wave 2. Key determinants of rural household poverty include household size, access to modern energy, remittances, agricultural land ownership, house ownership, age group, and gender of the household head. It was found that household size and the age group of the household head can negatively affect the well-being of rural households. Conversely, access to modern energy, remittances, agricultural land ownership, house ownership, and the gender of the household head can reduce rural household poverty. Therefore, the BAXNAANO program should prioritize support for rural households headed by women, older individuals, and those with larger household sizes. Additionally, the government should implement electrification programs as an integral component of its rural development policy.

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Publication Details

Journal
Cogent Food & Agriculture
Published
2024-12-26
DOI
https://doi.org/10.1080/23311932.2024.2445139
Citations
1
Primary Topic
Agricultural risk and resilience
Type
article
Field-Weighted Citation Impact
0.33
Controls
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article

Modelling the determinants of rural household poverty: empirical evidence from Somalia

Mohammad Sahabuddin, Dahir Abdi Ali, Nasra Abdulhalim Mohamed, Abdirahman Ibrahim Ismail et al.
1 citations
Cogent Food & Agriculture
Agricultural risk and resilience
0.33
article

Modelling the determinants of rural household poverty: empirical evidence from Somalia

Mohammad Sahabuddin, Dahir Abdi Ali, Nasra Abdulhalim Mohamed, Abdirahman Ibrahim Ismail, Jama Moahmed
article en
1 citations

Abstract

Although poverty has been decreasing globally in recent years, it remains a significant challenge in Somalia, particularly in rural areas where the poverty rate is higher than the national figure. Most livelihoods in these areas rely on rain-fed agriculture and livestock. However, there is currently no comprehensive study examining the extent of poverty and the associated risk factors in these regions. This study utilizes multivariate logit model to analyze the impact of socio-economic characteristics of rural households on poverty in Somalia, using data from the Somalia High-Frequency Survey (SHFS) wave 2. Key determinants of rural household poverty include household size, access to modern energy, remittances, agricultural land ownership, house ownership, age group, and gender of the household head. It was found that household size and the age group of the household head can negatively affect the well-being of rural households. Conversely, access to modern energy, remittances, agricultural land ownership, house ownership, and the gender of the household head can reduce rural household poverty. Therefore, the BAXNAANO program should prioritize support for rural households headed by women, older individuals, and those with larger household sizes. Additionally, the government should implement electrification programs as an integral component of its rural development policy.

Cogent Food & AgricultureVol. 11(1)
Chittagong University of Engineering & Technology (BD), University of Hargeisa (SO), SIMAD University (SO), University of Chittagong (BD), University of Science and Technology Chittagong (BD)
No poverty
Openalex Percentile: Top 32%
Agricultural risk and resilience
0.33
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Modelling the determinants of rural household poverty: empirical evidence from Somalia — Mohammad Sahabuddin, Dahir Abdi Ali, et al. · Cogent Food & Agriculture (2024) | TGRS Research Map | TGRS