This study assesses household vulnerability to poverty in rural Gambia using the Vulnerability as Expected Poverty (VEP) approach, based on cross-sectional data. This approach provides a forward-looking measure of welfare, moving beyond static poverty headcounts to identify households at risk of future poverty. We interchanged income, total consumption, and food consumption to estimate vulnerability, thereby employing multiple welfare metrics to ensure robust, dimension-specific findings. A three-step Feasible Generalised Least Squares (FGLS) method was applied: first, estimating the ex-ante mean using OLS; second, modelling variance from squared residuals; and third, correcting for heteroskedasticity to predict vulnerability. Findings show that household size has a positive and significant effect on expected log income, while its squared term is negative and significant, indicating diminishing returns. The age of the household head has a slightly positive but statistically insignificant effect on income, with the squared term weakening this effect. Employment status is positively associated with income; a one-unit increase leads to a 2.9% rise in expected log income and reduced vulnerability. Educational attainment also shows a positive, though insignificant, effect. Non-land production assets significantly reduce vulnerability, with a one-unit increase lowering it by 18.8%. The share of irrigated land contributes to a 4.4% reduction in vulnerability. To reduce vulnerability in rural Gambia, government efforts should focus on expanding access to irrigation and productive assets, especially for smallholder farmers. Employment programs targeting rural youth and women can enhance income stability. Strengthening vocational education and improving access to agricultural extension services will also help households build resilience and reduce future vulnerability and poverty risks.
Ceesay et al. (Mon,) studied this question.