Bayesian networks for imputation

Summary.  Bayesian networks are particularly useful for dealing with high dimensional statistical problems. They allow a reduction in the complexity of the phenomenon under study by representing joint relationships between a set of variables through conditional relationships between subsets of these variables. Following Thibaudeau and Winkler we use Bayesian networks for imputing missing values. This method is introduced to deal with the problem of the consistency of imputed values: preservation of statistical relationships between variables ( statistical consistency ) and preservation of logical constraints in data ( logical consistency ). We perform some experiments on a subset of anonymous individual records from the 1991 UK population census.     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

Composition-consistent tournament solutions and social choice functions

This paper introduces a new axiom for choice in preference profiles and tournaments, called composition-consistency. A social choice function is composition-consistent if it is non-sensitive to the cloning of one or several outcomes. The key feature of the composition consistency property is an operation concept called multiple composition product of profiles. The paper provides a brief overview of some social choice functions studied in the literature. Concerning the tournament solutions, it is proved that the Top Cycle, the Slater and the Copeland solutions are not composition-consistent, whereas the Banks, Uncovered Set, TEQ, Minimal Covering Set are composition-consistent. Moreover, we define the composition-consistent hull of a solution as the smallest composition-consistent solution containing . The composition-consistent hulls of the Top cycle and Copeland solutions are specified, and we give some hints about the location of the hull of the Slater set. Concerning social choice functions, it is shown that Kemeny, Borda and Minimax social choice functions are not composition-consistent, whereas the Paretian one is composition-consistent. Moreover, we prove that the latter is the composition-consistent hull of the Borda and Minimax functions.     

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

The objective of this article is to discuss a needed paradigm shift in disaster risk analysis to emphasize the role of the workforce in managing the recovery of interdependent infrastructure and economic systems. Much of the work that has been done on disaster risk analysis has focused primarily on preparedness and recovery strategies for disrupted infrastructure systems. The reliability of systems such as transportation, electric power, and telecommunications is crucial in sustaining business processes, supply chains, and regional livelihoods, as well as ensuring the availability of vital services in the aftermath of disasters. There has been a growing momentum in recognizing workforce criticality in the aftermath of disasters; nevertheless, significant gaps still remain in modeling, assessing, and managing workforce disruptions and their associated ripple effects to other interdependent systems. The workforce plays a pivotal role in ensuring that a disrupted region continues to function and subsequently recover from the adverse effects of disasters. With this in mind, this article presents a review of recent studies that have underscored the criticality of workforce sectors in formulating synergistic preparedness and recovery policies for interdependent infrastructure and regional economic systems.     

Lessons from Nigeria for improved thinking and working politically in the extractives sector

Despite the wealth that comes from being the biggest oil producer in Africa, Nigeria has some of the worst development indicators in the world. From 2011 to mid‐2016, the DFID‐funded Facility for Oil Sector Transparency and Reform (FOSTER) programme's unique design aimed to reduce incentives for the capture of oil revenue by elites and international oil companies, restoring the potential of those revenues to accelerate economic and social development. This article asks what lessons FOSTER's successes and failures offer for improved “thinking and working politically” (TWP). It examines the outcomes from five “clusters” of interventions: three viewed by the FOSTER team as successes and two as failures. The article identifies factors for successful TWP‐based programming, including the need for local ownership rooted in staff with a combination of technical expertise, a deep knowledge of the local political context and excellent networking abilities. The research used a qualitative and inductive approach. Field research was undertaken with 44 semi‐structured qualitative interviews during one month of fieldwork in Abuja and Lagos. The research also included reviews of FOSTER's internal documentation and evaluation frameworks, as well as analysis of newspaper articles and grey literature on the oil sector in Nigeria. The project offers important lessons for politically informed programming about how interventions were implemented (process), what was actually done (content) and how the project responded to changes in context that created or blocked opportunities for reform (responsiveness). The article identifies factors for successful TWP‐based programming, including the need for local ownership rooted in staff with a combination of technical expertise, a deep knowledge of the local political context and excellent networking abilities. The findings have important implications for programme design. They demonstrate the value of built‐in flexibility that allows staff to choose and switch the partners they work with and the channels they work through. They also show that a key aspect of TWP‐based programming is implicit acceptance that some failure may be unavoidable, since this permits staff to balance risk against opportunities. Finally, a better understanding of FOSTER's failures reveals the challenges of a TWP‐based approach and the trade‐offs it demands.     

Income Diversity,Technology Choice and Agricultural Research Policy in Sub‐Saharan Africa

This article makes an initial analysis of the implications of income diversification for technical change and agricultural research policy in Africa, leading to two insights. First, that the dilution effect of income diversification means that, as the proportion of non‐farm income increases, so must the expected gains from adopting a new agricultural technology. Second, that diversified producers will face disproportionately large transactions costs associated with information acquisition to inform technology choice decisions. Two hypotheses about how diversified producers are likely to react are then explored. Both point to the conclusion that income diversification among the poor is likely to constrain significantly the direct poverty impacts of agricultural research. The policy implications of these findings are then considered.