Poverty dynamics, income inequality and vulnerability to shocks in rural Kenya

Persistent poverty remains a huge challenge in Sub-Saharan Africa. In Kenya, official statistics indicate that the incidence of rural poverty was 49% in 2005/2006. This study uses different approaches and data sources to explore temporal and spatial dimensions of rural welfare in Kenya. The objective is to identify and understand the linkages between welfare, livelihood assets, livelihood strategies, local-level institutions, and exposure to shocks. First, we compared participatory and income approaches to studying poverty and poverty dynamics. We found a significant positive correlation between the results obtained using the two approaches, with both approaches showing evidence of geographical clusters of poverty. Nevertheless, discrepancies in poverty rates and dynamics were found as well. Second, we used asset-based approaches to explore the nature of rural poverty dynamics over multiple periods. We found that majority of households that were poor in two consecutive survey years were structurally poor. Of the households escaping poverty, a large proportion was characterized by stochastic transitions. Few households successfully escaped poverty through asset accumulation, while a large proportion of households declining into poverty experienced structural movements. A combination of livelihood strategies, shocks, and other factors interact to influence household structural transition. Third, we characterized shocks facing rural households. Health expenses, ill-health, funeral expenses, livestock losses, land sub-division, and death of major income earner were the most frequently reported shocks. We also found limited evidence that welfare level affects exposure to specific shocks, but a significant geographical effect. Finally, we revisited the geography versus institutions debate at the micro-level suing local data to explain within-country income differences. We found that certain geographical variables appear more important drivers of per capita income levels than local institutions. Our community-level measures of institutions did not explain within-Kenya income differences. Altogether, the findings underscore the importance of geographical targeting of poverty reduction interventions. Moreover, the coexistence of high rural poverty rates and limited asset accumulation, and strong macroeconomic growth highlight the fact that causes of poverty are complex. Macroeconomic growth policies need to be complimented with policies that enhance escapes from poverty (“cargo net” policies) and those that prevent descents into poverty (“cargo net” policies).