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In this paper, we examine the aid-growth-poverty relation by using quantile regression, which enables us to estimate the impact of growth and growth enhancing policies at different quantiles in the conditional distribution of poverty. The coefficient estimates in a quantile regression capture the marginal impact of a change in the explanatory variable observed at the τth quantile of the dependent variable. We find that growth in average income and other growth enhancing policies have heterogeneous impact on poverty, specifically that the marginal effect of growth and growth enhancing policies decreases at higher levels of poverty. These results are robust to the consideration of endogeneity of aid and use of alternative measures of poverty--poverty gap and squared poverty gap. [ABSTRACT FROM AUTHOR]