Poverty in Kenya

Abstract

There is a lack of consensus on how to measure poverty in general, even though poverty indices and poverty profiles are increasingly being used as guides in targeting resources to reduce poverty. In order to compare changes in poverty rates for Kenya, this study tests robustness of the observed changes in the poverty using stochastic dominance analysis, a robust way of ranking distributions. This approach avoids the problem that poverty comparisons may not be robust to the subjective choice of a poverty line. It also avoids the potential that small movements across the thresholds may have large impacts on poverty indices. This is then compared with results from other studies to determine the extent to which conclusions differ and the extent to which the findings are sensitive to the choice of poverty lines. Hence this study tries to answer the following questions. Are the results from poverty studies sensitive to the choice of poverty lines especially when the choice is at the discretion of the analyst? How does this affect their robustness? Does the conclusion differ substantially when summary measures (e.g. mean, variance) and stochastic dominance analysis methods are employed? Do we have an improvement in the levels of poverty in