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Peace and security are basic conditions for economic and social development. Conflict, on the other hand, can reverse years of economic growth and induce long-term harm on almost all aspects of development. For the past decade, the Lake Chad region has been the setting of conflicts between government forces and armed groups, most notably the Boko Haram. Although the intensity of fighting has petered off in recent years, the conflict has spread from Northern Nigeria and now affects all four countries of the region. Due to the paramount importance of avoiding armed conflict, a large economic literature exists that seeks to find explanations for the onset and prevalence of conflict in developing countries. Blattman and Miguel [2010] list some of the most common theories of conflict including competition for resources, economic grievances, and the possibility of looting. This paper attempts to shed light on the geographical distribution of conflict and its climatic determinants in the Lake Chad region following a sub-national approach where readily available spatial data is employed at two different units of aggregation: Firstly, 90 second level administrative areas, and secondly, around 5,318 grid cells covering the same region. Exposure to conflict is here defined as the intensity (for districts) or incidence (for cells) of conflict in a given unit each year. Parts of the population may not be directly exposed by this definition, but since the units of analysis are relatively small, most will be affected in some ways, for instance by safety concerns when visiting the nearest towns to trade or by the general economic consequences.

Armed Conflict --- Climate and Meteorology --- Climate Change --- Climate Change Impacts --- Conflict and Development --- Environment --- Natural Disasters --- Precipitation --- Rainfall --- Science and Technology Development

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Although resilience has become a popular concept in studies of poverty and vulnerability, it has been difficult to obtain a credible measure of resilience. This difficulty is because the data required to measure resilience, which involves observing household outcomes over time after every exposure to a shock, are usually unavailable in many contexts. This paper proposes a new method for measuring household resilience using readily available cross section data. Intuitively, a household is considered resilient if there is very little difference between the pre- and post-shock welfare. By obtaining counterfactual welfare for households before and after a shock, households are classified as chronically poor, non-resilient, and resilient. This method is applied to four countries in the Sahel. It is found that Niger, Burkina Faso, and Northern Nigeria have high percentages of chronically poor: respectively, 48, 34, and 27 percent. In Senegal, only 4 percent of the population is chronically poor. The middle group, the non-resilient, accounts for about 70 percent of the households in Senegal, while in the other countries it ranges between 34 and 38 percent. Resilient households account for about 33 percent in all countries except Niger, where the share is around 18 percent.

Finance and Financial Sector Development --- Health, Nutrition and Population --- Macroeconomics and Economic Growth --- Poverty Reduction

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Reducing child undernutrition is a key social policy objective of the Ethiopian government. espite substantial reduction over the past decade and a half, child undernutrition is still high. With 48 percent of children stunted, underweight, or wasted, undernutrition remains an important child health challenge. The existing literature highlights that the targeting of efforts to reduce undernutrition in Ethiopia is inefficient, in part because of the lack of data and updated information. This paper remedies some of this shortfall by estimating levels of stunting and underweight in each woreda for 2014. The estimates are small area estimations based on the 2014 emographic and Health Survey and the latest population census. It is shown that small area estimations are powerful predictors of undernutrition, even controlling for household characteristics, such as wealth and education, and hence a valuable targeting metric. The results show large variations in share of children undernourished in each region, more than between regions. The results also show that the locations with larger challenges depend on the chosen undernutrition statistic, as the share, number, and concentration of undernourished children point to vastly different locations. There is limited correlation between the shares of children underweight and stunted across woredas, indicating that different locations face different challenges.

Adolescent Health. --- Child Malnutrition. --- Demographic and Health Survey. --- Early Child and Children's Health. --- Health Monitoring and Evaluation. --- Health, Nutrition and Population. --- Population and Development. --- Small Area Estimation. --- Targeting.