The Dynamics of Nutrition and Child Health Stocks

Height-for-age (HA) and weight-for-age (WA) of children are standard measures to study the determinants of stunting and short-term underweight. Rather than studying these indicators separately, this paper looks at their interaction and therefore at the dynamics of height and weight. Considering HA a child's health stock and WA nutritional investment, we develop an overlapping generations model. The main features of the model are self-productivity of health stocks and the dynamic complementarity between past health stocks and contemporaneous nutrition. We test the model's predictions on a Senegalese panel of 305 children between 0 and 5 years over three periods. To control for endogeneity and serial correlation we employ different GMM methods. We find evidence of self-productive health stocks and that child health produced at one stage raises the productivity of nutritional inputs at subsequent stages. Our results indicate that child health is quickly depleted and needs constant updating. Simulations based on our estimates show that a positive nutritional shock during the first six months of life is essentially depleted at the age of 2. Consequently, sustainable development and nutrition programs have to be long-term and yield higher returns if they reach babies in the early months of infancy.Child health, Health production, Height-for-Age, Weight-for-Age, Dynamic Panel Regression, GMM

Aid, peasants and social exclusion

Using unique village census data collected in 2003 and 2008 in Senegal, we assess the impact of a major World Bank-funded Community Driven Development (CDD) program on membership and assortative matching in community-based organizations (CBOs). We implement both standard discrete choice and dyadic regression techniques. We find that channeling development aid through CBOs makes these organizations more inclusive in the sense that a number of tradition-bound assortative matching patterns are partly broken. Ceteris paribus, this leads to more heterogeneous CBOs. On the other hand, the likelihood of CBO membership is reduced in treated villages, with significant differences between men and women. Our results suggest that grassroots level development projects which target CBOs must be carefully designed and executed if they are not to result, paradoxically, in a greater degree of social exclusion, with differentiation by gender playing a crucial role.Community Based Organizations, Dyadic Regression, Gender Differences, Social Exclusion

`Natural' Disaster, Conflict and Aid Allocation

This paper looks into aid allocation in the response to multiple crises, focusing more specifically on the cases of concomitance between so-called `natural' hazard/disaster and conflict situations. Over 150 natural disasters have occurred alongside complex political crises in the past seven years alone. Yet, the fields of conflict and disaster research remain largely isolated from one another, and in fact, no aid related research has addressed the issue of the concomitance of conflict and disaster. We exploit a large panel dataset that includes official development aid, and information about the victims from natural disasters and conflicts for 112 developing countries over a period of 35 years. For eight different donor countries and groups of donor countries we find that while conflict does not affect their aid allocation patterns, the occurrence of natural disasters does. The econometric analysis demonstrates that aid allocation needs to be analyzed in a disaggregated fashion -for each donor individually- as donors clearly have different agendas. Applying GMM techniques we account for the endogenous nature of the control variables such as per capita GDP. In addition we use the relative size of the youth cohort as exogenous instrument for conflict.Disaster, Conflict, Aid Allocation, Longitudinal Panel Methods, GMM

Long-term impacts of an early childhood shock on human capital:Evidence from the 1999 economic crisis in Ecuador

This paper provides evidence on the lasting effects of the 1999 economic crisis in Ecuador on human capital formation. We show for children born during the crisis that the negative repercussions are still observable more than 10 years after macroeconomic recovery. Taking advantage of micro-level data collected in 2012 and 2014, we assess long-term impacts on health and education. After controlling for age-in-months and survey effects as well as a linear birth year-cohort trend that varies by region, we find that after 12–16 years, the cohorts born during the recession report height-for-age Z-scores that are 0.003 standard deviations (SDs) lower for each month of exposure and have 0.002 fewer years of schooling per month exposed compared to the cohorts born outside the recession years. Children exposed to the entire crisis are 0.063 SDs smaller and have 0.042 years less of schooling. Girls have lower health outcomes than boys. Concomitantly, we show that selective childbearing or excess infant mortality are unlikely to drive our results. The persistence of the negative effects points to the existence of a poverty trap suggesting that policy interventions in response to (economic) crizes should be extended beyond macroeconomic recovery to counteract long-term, micro-level consequences.</p

How manufacturing firms respond to energy subsidy reforms?:An impact assessment of the Iranian Energy Subsidy Reform

Energy prices increased several folds due to the 2010 Iranian Energy Subsidy Reform. This study assesses the impact of the reform on the performance of the manufacturing sector using a detailed micro-panel dataset at the 4-digit ISIC level for the period 2009 to 2013. Since the reform universally affected all firms, the analysis relies on a quasi-experimental framework implementing first an explorative before-after design with structural fixed-effects and second a difference-in-difference analysis exploiting the energy-sensitivity of the studied firm-groups. The subsidy reform reduced output and value-added by 3 and 7%, respectively. Profits decreased by nearly 9%. Heterogeneity analyses show that the manufacturing sector has been affected through three channels: increasing costs of direct energy inputs, pass-through costs for inputs from upstream firms and an energy-price-induced demand contraction. We conclude that for successfully implementing an energy subsidy reform while maintaining growth in the manufacturing sector, direct and indirect costs have to be considered. Importantly, the results can inform expected energy reforms to mitigate climate change

Extracting Agricultural Fields from Remote Sensing Imagery Using Graph-Based Growing Contours

Knowledge of the location and extent of agricultural fields is required for many applications, including agricultural statistics, environmental monitoring, and administrative policies. Furthermore, many mapping applications, such as object-based classification, crop type distinction, or large-scale yield prediction benefit significantly from the accurate delineation of fields. Still, most existing field maps and observation systems rely on historic administrative maps or labor-intensive field campaigns. These are often expensive to maintain and quickly become outdated, especially in regions of frequently changing agricultural patterns. However, exploiting openly available remote sensing imagery (e.g., from the European Union’s Copernicus programme) may allow for frequent and efficient field mapping with minimal human interaction. We present a new approach to extracting agricultural fields at the sub-pixel level. It consists of boundary detection and a field polygon extraction step based on a newly developed, modified version of the growing snakes active contours model we refer to as graph-based growing contours. This technique is capable of extracting complex networks of boundaries present in agricultural landscapes, and is largely automatic with little supervision required. The whole detection and extraction process is designed to work independently of sensor type, resolution, or wavelength. As a test case, we applied the method to two regions of interest in a study area in the northern Germany using multi-temporal Sentinel-2 imagery. Extracted fields were compared visually and quantitatively to ground reference data. The technique proved reliable in producing polygons closely matching reference data, both in terms of boundary location and statistical proxies such as median field size and total acreage