For very high poverty rates, reducing the Gini increases poverty. Hence, there may be a certain trade-off between decreasing the poverty rate and decreasing inequality for very poor countries. Panels b and c show that reducing inequality almost unambiguously decreases both the poverty gap and the squared poverty gap even for high initial headcount ratios. This indicates that the trade-off is rather about maximizing the reduction in the headcount ratio or the poverty gap – the latter corresponding to a stronger focus on the poorest of the poor.

# 6 Conclusion

Using a global database covering 97% of the world’s population, this paper shows that under assumptions of distribution-neutral growth, the World Bank’s goal of achieving less than 3% extreme poverty by 2030, as well as the United Nations’ Sustainable Development Goal of complete eradication of poverty, will be very difficult to reach by 2030. It also shows that these goals become more viable by reducing inequalities, for any given growth rate of the mean. Conversely, regressive distributional changes can severely limit the way in which growth contributes to poverty reduction.

Motivated by the Sustainable Development Goal 10 on inequality, we modeled inclusive growth in terms of lowering the Gini index in every country. The poverty impact of more inclusive growth defined in this way is different across countries and depends on the initial level of poverty, as well as the shape of the distribution, the precise growth incidence curve used and the growth rate. At high levels of initial poverty, reducing the Gini index could lead to a decrease in the pace of poverty reduction in the short term compared with a distribution-neutral growth scenario. In other words, for a country with a high headcount ratio, the welfare of the marginally poor may be growing slower when lowering the Gini than in a distribution-neutral scenario. This highlights a certain trade-off between focusing on the poor within every country and the poor according to an international poverty line. Nevertheless, in such cases the poorest of the poor still receive a growth premium and thus the poverty gap and severity are reduced.

While many of the findings are intuitive, one of the contributions of the paper is to quantify these effects using plausible distributional changes. A 1% annual decline in each country’s Gini index is shown to have a bigger impact on global poverty than if each country experiences 1 pp higher annual growth rates than forecast. It is important to highlight that making growth more pro-poor as simulated in this paper does not impose a large cost on the rest of the distribution. Because of the large income share of the top of the distribution, the reduction in the growth rate of the wealthiest individuals necessary to ensure that the bottom grows substantially faster than the mean is relatively small. For example, in the case of Côte d’Ivoire, a convex growth incidence such that the Gini decreases by 1% means that households at the 10<sup>th</sup> percentile grow 2.5 pp faster than the mean, yet the growth at the 90<sup>th</sup> percentile is reduced by only 0.5 pp. In other words, the distributional changes simulated in this paper are not unrealistic, and as we have shown, making growth more pro-poor will be crucial for reaching the poverty goals set by the global development community.

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