The inaugural Annual Bank Conference on Africa examined strategies for converting economic growth into poverty reduction. Taking an economic historian’s perspective, the prospects are complicated by long-term shifts in fundamental patterns, specifically from land abundance to land scarcity and, relatedly, from labor repression to landlessness as the principal source of poverty.
“I am always hungry, as oftentimes my family and I skip meals. I want to go to school like my friends, but my parents always say it is too expensive. If I go to school, then I can’t work to help them buy food, and then I am hungry again. I am helpless when it comes to changing my situation, I have no voice and there are few people that see things the way I do.”
Despite hundreds of millions spent on more and better household surveys across Africa in recent decades, we only have a very rough idea about the levels and trends in income poverty and inequality in sub-Saharan Africa. Many reasons contribute to this unfortunate state of affairs.
Women are less productive farmers than men in Sub-Saharan Africa. A new evidence-based policy report from the World Bank and the ONE Campaign, Leveling the Field: Improving Opportunities for Women Farmers in Africa, shows just how large these gender gaps are. In Ethiopia, for example, women produce 23% less per hectare than men. While this finding might not be a “big” counter-intuitive idea (or a particularly new one), it’s a costly reality that has big implications for women and their children, households, and national economies.
The policy prescription for Africa’s gender gap has seemed straightforward: help women access the same amounts of productive resources (including farm inputs) as men and they will achieve similar farm yields. Numerous flagship reports and academic papers have made this very argument.
Photo Credit: @Gates Foundation. A girl plays with a bicycle tire in the slum of Korogocho, one of the largest slum neighborhoods of Nairobi, Kenya
This is an impressive decrease from 58% in 1999, but at the same time there is a general sense that progress has been too slow. Africa is rising, with GDP growth rates upwards of 6% between 2003 and 2013 (if one excludes richer and less dynamic South Africa) but the poor’s living standards are not rising as fast as GDP.
Une petite fille joue avec un pneu de bicyclette dans le bidonville de Korogocho,à Nairobi au Kenya @Fondation Gates
Bien que l’Afrique subsaharienne connaisse une croissance économique soutenue depuis près de deux décennies, l’extrême pauvreté continue d’y sévir : environ un Africain sur deux (49 % selon nos estimations les plus fiables) vivait avec moins de 1,25 dollar par jour en 2010 (aux prix de 2005). Certes, c’est neuf points de moins qu’en 1999 mais, en dépit de ce recul exceptionnel, le sentiment général est celui de progrès bien trop lents. Si l’essor de l’Afrique est réel, avec des taux de croissance du PIB de plus de 6 % entre 2003 et 2013 (en exceptant l’Afrique du Sud, plus riche et moins dynamique que les autres pays de la région), le niveau de vie des populations les plus démunies ne croît pas aussi vite que le PIB…
The expansion of household surveys in Africa can now show us the number of poor people in most countries in the region. This data is a powerful tool for understanding the challenges of poverty reduction. Due to the costs and complexity of these surveys, the data usually does not show us estimates of poverty at “local” levels. That is, they provide limited sub-national poverty estimates.
For example, maybe we can measure district or regional poverty in Malawi and Tanzania from the surveys, but what is more challenging is estimating poverty across areas within the districts or regions (known as “traditional authorities” in Malawi and “wards” in Tanzania).
To address this shortfall, several years ago a research team from the World Bank developed a technique for combining household surveys with population census data, and poverty maps were born. Poverty maps can be used to help governments and development partners not only monitor progress, but also plan how resources are allocated. These maps depend on having access to census data that is somewhat close in time to the household survey data. But what if there is no recent census (they are usually done every 10 years) or the census data cannot be obtained? (I will resist naming and shaming any specific country): we are left with no map. Can we fill in the knowledge gaps in our maps?
Countries coming out of crises undergo rapid structural changes, including migration and big economic shifts. This can complicate the measurement of their progress, sometimes in unexpected ways, as we found out recently in Sierra Leone.