Speaker
Description
Objectives: Food insecurity and malnutrition are major concerns worldwide linked to food price volatilities, financial crises, and climate change including weather shocks. Food insecurity can increase the risk of various forms of malnutrition and can have both severe short- and long-term impacts on health and well-being. Despite rapid economic growth and poverty reduction within the last three decades, food insecurity still afflicts many people In 2020, 8.9 percent of the world’s population are undernourished – this means they have a caloric intake below minimum energy requirements; 22% of children younger than five are ‘stunted’ – they are significantly shorter than the average for their age, as a consequence of poor nutrition or repeated infection, and in 2019 close to 750 million – or nearly one in ten people in the world – were exposed to severe levels of food insecurity. Moreover, current events like the Russian-Ukraine war have further strained a global food system already weakened by global inequalities, climate change, and the COVID-19 pandemic, with devastating consequences for poor people in low- and middle-income countries (LMICs). Therefore, we are far from meeting the commitments made by the international community in the 2030 Agenda for Sustainable Development, in particular SDG 2, which aims to eradicate hunger, food insecurity, and malnutrition by 2030, by ensuring that food is universally available, adequate and accessible Therefore, eradicating food insecurity is a top priority on the development agenda in many countries.
However, estimates of food insecurity or hunger are typically presented as national averages and only minimal information on measures of hunger and food insecurity within countries exists. Only the recent availability of better data and more capable statistical methods has enabled the first attempts at doing so on a global scale. Hence, commonly used aggregate food security indices mask within-country variation in food insecurity and are not sensitive to the distribution of the index. In addition, short-term food shocks or seasonal fluctuations are not well taken into account. Furthermore, it is crucial to recognize that food insecurity cannot be adequately assessed by relying on just one specific indicator. Different indicators are designed to capture various facets of this complex issue
We aim to characterize spatio-temporal patterns of food insecurity in sub-Saharan Africa (SSA). The overall objective of this project is to enhance our understanding of within-country variations of food insecurity in SSA which allows a better targeting of policy measures to reduce food insecurity. In particular, this study aims to estimate the Global Hunger Index (GHI) and its components at disaggregated levels within countries in Sub-Sahara Africa. This enables the identification of high-risk areas of food insecurity within countries and allows more precise targeting of policy interventions. In doing so, our study directly contributes to the empirical literature by estimating spatial patterns of food insecurity within Sub-Saharan African countries.
Data and Methods: We use Bayesian distributional regressions to analyze and map the GHI within Sub-Saharan African countries. This approach allows us to analyze the complete distribution of the GHI. The GHI combines four equally weighted indicators: undernourished people, wasting, stunting, and child mortality. By pooling several Demographic and Health Surveys (DHS) and Living Standard Measurement Surveys (LSMS) with demographic, environmental, and geospatial factors we create a unique data set to analyze the impact of socioeconomic, environmental, and spatial patterns associated with food security. While the calculation of stunting, wasting, and child mortality is relatively straightforward, deriving the indicator of the share of undernourished people is more complicated because of high data requirements, particularly the conversion from quantities and types of foods to associated calorie consumption. To calculate undernourishment, we use various methods for the conversion of quantities (e.g. heap to kg) such as the USDA conversion factors, and from units to calories (e.g. kg to kcal) such as country-specific or African Food Consumption Tables. There is a huge data effort because of several thousand food items and units per survey.
The analysis has four steps: First, we generate subnational microdata at the first administrative level for each survey year. Second, we gather data on covariates related to food insecurity. Third, a geostatistical approach based on a Bayesian regression is used to provide high-resolution maps of the GHI. We model subnational rates of the GHI as a function of several covariates related to human development, nutrition, health, infrastructure, and the environment. As a starting point, the normal distribution for the GHI index is assumed. Finally, we extrapolate the GHI to all admin-1 level regions in sub-Saharan Africa.
Results: Our results show considerable variation in the GHI and hence food security within Sub-Saharan African countries. The estimates also show large heterogeneity in the GHI across and within countries by socio-economic sub-groups. In addition, the spatial distribution is analyzed which allows the creation of a unique high-resolution map helping to identify hot spots of food security.
Discussion: This paper presents the first estimates of the GHI at subnational levels for Sub-Saharan Africa. We provide a detailed within-country analysis of food security in Sub-Sahara Africa. Policy interventions to improve food security and reduce poverty depend on the effective identification of the vulnerable population as well as an understanding of the underlying determinants of both phenomena. The large share of people suffering from hunger hampers productivity and is a major obstacle to achieving sustained economic and social development. In the short term and in acute situations of food insecurity, safety nets, insurance, and social protection programs can provide immediate relief to poor households, helping them remain food secure. In the long term, improving agricultural productivity is fundamental for ensuring food security and promoting poverty reduction.
