The Cost of Hunger in Africa (CoHA): The Social and Economic Impact of Child Undernutrition in Malawi report shows that the country loses significant sums of money each year as a result of child undernutrition through increased healthcare costs, additional burdens to the education system and lower productivity by its workforce. It estimates that child undernutrition cost Malawi 10.3 percent of Gross Domestic Product in 2012 (most recent year with complete data).
The 12-country, government-led study is commissioned by the African Union and the New Partnership for Africa’s Development’s Planning and Coordinating Agency and supported by the UN Economic Commission for Africa and the UN World Food Programme. The study's model estimates the additional cases of illness, death, school repetitions, school dropouts, and reduced physical productivity directly associated with those suffering undernutrition before the age of five. Based on data from each country, the model then estimates the associated economic losses incurred by the economy in terms of health, education, and potential productivity in a single year. So far, it has been conducted in six countries in Africa including Malawi.
Some key findings to emerge from the study in Malawi reveal that:
Overall, the Cost of Hunger in Africa study serves as an important tool to show how undernutrition is not just a health issue, but an economic and social one as well that requires multi-sectoral commitment and investment. It reinforces the critical need to prioritize nutrition in the national development agenda.
This publication “School feeding and possibilities for direct purchases from family farming in Latin American countries” contributes to the articulation of the sectors involved with school feeding, in the search for alternatives for the institutionalization and strengthening of school feeding policies in the countries; equally, it is hoped that in the medium and long term SFPs can contribute to the human right to food (HRF) and to sustainable human development.
The Food Security Information Network (FSIN) supports the development and harmonization of resilience measurement methods. A technical working group composed of renowned experts was constituted to lead the identification of resilience measurement principles and the development of a common analytical framework and technical guidelines for measurement.
This paper is an initial step toward the development of resilience measurement design used by stakeholders (e.g. programme staff, monitoring and evaluation, policy makers). It outlines:
This publication is the first in a series of three papers that will be issued over the course of the next year, which will focus on an analytical framework that addresses the challenges, issues and concerns associated with resilience measurement.
That Africa has become a net importer of food and of agricultural products, despite its vast agricultural potential, is puzzling. Using data mainly for the period 1960-2007, this report seeks to explain Africa’s food-trade deficit since the mid-1970s. The core finding is that population growth, low and stagnating agricultural productivity, policy distortions, weak institutions and poor infrastructure are the main reasons. A typology of African countries based on data between 2000 and 2005 reveals that the state of food import dependency is different across the continent and varies according to countries’ levels of income. Although the few and relatively rich countries in Africa had the highest net food imports per capita (USD 185 per year in real terms), they had ample means to pay for their food import bills using revenue from non-agricultural sources. Conversely, the majority of the Africa’s low-income countries (mostly in Sub-Saharan Africa), where twothird of its population lives, had been net food importers; they imported far less food per capita (USD 17 per year) but had difficulty covering their food imports bills, as their export revenues were limited. Overall, between 1980 and 2007, Africa’s total net food imports in real term grew at 3.4 percent per year, but this growth was mostly fuelled by population growth (2.6 percent per year); the increase in per capita food import was only about 0.8 percent per year. Food consumption on per capita basis grew only at about 1 percent per year, while food production grew at an even smaller rate of less than 0.1 percent per year. The slow growth of food consumption and imports per capita is consistent with the weak economic growth and unchanged dietary pattern in the continent. Food import share, regardless of income levels, is relatively small and represents less than 5 percent of per capita income (GDP per capita). Because the share of food expense in household income is generally high in Africa, especially in Sub-Saharan Africa, that the share of food imports over GDP is small implies that domestic production has largely contributed to feeding Africa’s population. Still, domestic food production has remained relatively low and increased only by 2.7 percent per year, just barely above population growth rate. This implies that any increase in per capita consumption had to be met by an increase in imports. The weak growth in food production arises from various constraints including those linked directly to agricultural productivity. Data and evidence from literature highlight that technical, infrastructural and institutional constraints share the blame. Likewise, distortions arising from both internal and external economic and agricultural policies (especially the protection and subsidies from developed countries and taxation on food production within Africa) have affected food productivity, production and trade in Africa. However, the examples of a few successful practices in African agriculture and the fact that the domestic food production has managed to keep up with population growth inspire optimism that the future is not all dark. There is a lot of room for improvement for agricultural productivity in these low-income countries to the point at which production growth outpaces the growth of population and per capita consumption.