Abstract
Welfare transitions are weakly understood in sub-Saharan Africa due to limited panel data to analyze trajectories of household escaping from, falling into, or remaining out of deprivation. We model data from 3500 households in coastal Kenya in three panels from 2014 to 2016 to evaluate determinants of welfare by multidimensional and subjective measures. Findings indicate that more than half of the households are deprived, with female-headed households being the most vulnerable and making the least progress. The subjective welfare measure identified three times more chronically poor households than the multidimensional metric (27% vs. 9%); in contrast, the multidimensional metric estimated twice as many ‘never poor’ households than the subjective measure (39% vs. 16%). The ‘churning poor’ were broadly consistent for both measures at roughly half the sample. Four welfare priorities converged from modelling welfare transitions. Broadening access to secondary education and energy services, improving the reliability and proximity of drinking water services, and ending open defecation improve welfare outcomes. While the policy implications do not align neatly with Kenya’s national and county government mandates, we argue that prioritising fewer but targeted sustainable development goals may improve accountability, feasibility, and responsibility in delivery if informed by local priorities and political salience.
Highlights
The nature of welfare in rural Africa is often characterized by lack of or poor access to public services such as water, education, health, energy, and transportation, among others [1,2,3,4]
We report the descriptive findings which reveals the nature of welfare transitions (Table 1)
Welfare transitions identify a substantial number of households that are churning poor and chronically poor with implications to design of policy and practice
Summary
The nature of welfare in rural Africa is often characterized by lack of or poor access to public services such as water, education, health, energy, and transportation, among others [1,2,3,4]. While the effects of these factors vary between different groups of households or individuals in both space and time, their empirical relationships to welfare are often not properly understood due to limited data availability. The existing information asymmetry in rural Africa limits objective assessments, as baseline conditions for social, economic, and environmental systems are commonly absent, unavailable, or incomplete to support empirical analysis of the relationships between welfare and its determinants. Distributional implications and impacts for local populations over time and across varying environmental conditions are poorly documented, providing a weak platform to inform policy and practice to guide sustainable development pathways.
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