Consumption Growth, Household Splits and Civil War

We analyse the effect of civil war on household welfare. Using Burundian panel data for the 1998-2007 period in which we re-interviewed original as well as newly formed households (split-offs), we show that headcount poverty decreased by 3.5 % points when split-off households are taken into account and 1% when splits are left out. Poverty is persistent while prosperity is not, in particular in war-affected areas. We find that 25 war-related deaths or wounded at the village level reduce consumption growth by 13%. We also find that violence afflicted on household members decreases growth whereas membership of rebel groups increases it. Apart from such war-related effects - and controlling for initial levels of consumption - we find that temporarily famine-induced migration and illness decrease growth while good harvests, more split-offs and higher initial levels of education increase it. Good harvests are found to have persistent positive effects on growth. Our results are robust for different household and province fixed effects specifications.Consumption, Growth, Split-off households, Civil war, Panel data, Africa

Health and civil war in rural Burundi

This paper combines household survey data with event data on the timing and location of armed conflicts to examine the impact of Burundi's civil war on children's health status. The identification strategy exploits exogenous variation in the war's timing across provinces and the exposure of children's birth cohorts to the fighting. After controlling for province of residence, birth cohort, individual and household characteristics, and province-specific time trends, the authors find that children exposed to the war have on average 0.515 standard deviations lower height-for-age z-scores than non-exposed children. This negative effect is robust to specifications exploiting alternative sources of exogenous variation.Youth and Governance,Rural Poverty Reduction,Population Policies,Post Conflict Reconstruction,Health Monitoring&Evaluation

The Impact of Violent Conflict on Child Health: What Are the Channels?

Child health during and after violent conflicts has been a priority for both policymakers and academics, as ill-health in early life can be impossible to make up for in later life, and has important effects on education and adult wages. In order for policy interventions to mitigate health impacts, it is essential to understand the channels through which conflict impacts on child health. This briefing uses empirical results of research in Burundi and Rwanda to identify these channels. It outlines the policy implications of these findings, arguing that policymakers should prioritise interventions to rebuild agricultural capacity and improve sanitation conditions and nutrition in displacement camps.violent conflict; child health; Burundi; Rwanda; policy

Civil war, crop failure, and child stunting in Rwanda

Economic shocks at birth have lasting effects on children's health several years after the shock. The authors calculate height for age z-scores for children under age five using data from a Rwandan nationally representative household survey conducted in 1992. They exploit district and time variation in crop failure and civil conflict to measure the impact of exogenous shocks that children experience at birth on their height several years later. They find that boys and girls born after the shock in regions experiencing civil conflict are both negatively affected with height for age z-scores 0.30 and 0.72 standard deviations lower, respectively. Conversely, only girls are negatively affected by crop failure, with these girls exhibiting 0.41 standard deviation lower height for age z-scores and the impact is worse for girls in poor households. Results are robust to using sibling difference estimators, household level production, and rainfall shocks as alternative measures of crop failure.Youth and Governance,Population Policies,Rural Poverty Reduction,Children and Youth,Adolescent Health

On the Foundations of the Theory of Evolution

Darwinism conceives evolution as a consequence of random variation and natural selection, hence it is based on a materialistic, i.e. matter-based, view of science inspired by classical physics. But matter in itself is considered a very complex notion in modern physics. More specifically, at a microscopic level, matter and energy are no longer retained within their simple form, and quantum mechanical models are proposed wherein potential form is considered in addition to actual form. In this paper we propose an alternative to standard Neodarwinian evolution theory. We suggest that the starting point of evolution theory cannot be limited to actual variation whereupon is selected, but to variation in the potential of entities according to the context. We therefore develop a formalism, referred to as Context driven Actualization of Potential (CAP), which handles potentiality and describes the evolution of entities as an actualization of potential through a reiterated interaction with the context. As in quantum mechanics, lack of knowledge of the entity, its context, or the interaction between context and entity leads to different forms of indeterminism in relation to the state of the entity. This indeterminism generates a non-Kolmogorovian distribution of probabilities that is different from the classical distribution of chance described by Darwinian evolution theory, which stems from a 'actuality focused', i.e. materialistic, view of nature. We also present a quantum evolution game that highlights the main differences arising from our new perspective and shows that it is more fundamental to consider evolution in general, and biological evolution in specific, as a process of actualization of potential induced by context, for which its material reduction is only a special case.Comment: 11 pages, no figure

Continuous Ultrasound Speckle Tracking with Gaussian Mixtures

Speckle tracking echocardiography (STE) is now widely used for measuring strain, deformations, and motion in cardiology. STE involves three successive steps: acquisition of individual frames, speckle detection, and image registration using speckles as landmarks. This work proposes to avoid explicit detection and registration by representing dynamic ultrasound images as sparse collections of moving Gaussian elements in the continuous joint space-time space. Individual speckles or local clusters of speckles are approximated by a single multivariate Gaussian kernel with associated linear trajectory over a short time span. A hierarchical tree-structured model is fitted to sampled input data such that predicted image estimates can be retrieved by regression after reconstruction, allowing a (bias-variance) trade-off between model complexity and image resolution. The inverse image reconstruction problem is solved with an online Bayesian statistical estimation algorithm. Experiments on clinical data could estimate subtle sub-pixel accurate motion that is difficult to capture with frame-to-frame elastic image registration techniques

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1