100 key research questions for the post‐2015 development agenda

The Sustainable Development Goals (SDGs) herald a new phase for international development. This article presents the results of a consultative exercise to collaboratively identify 100 research questions of critical importance for the post‐2015 international development agenda. The final shortlist is grouped into nine thematic areas and was selected by 21 representatives of international and non‐governmental organisations and consultancies, and 14 academics with diverse disciplinary expertise from an initial pool of 704 questions submitted by 110 organisations based in 34 countries. The shortlist includes questions addressing long‐standing problems, new challenges and broader issues related to development policies, practices and institutions. Collectively, these questions are relevant for future development‐related research priorities of governmental and non‐governmental organisations worldwide and could act as focal points for transdisciplinary research collaborations.     

Parametric Modeling for Survival with Competing Risks and Masked Failure Causes

We consider a life testing situation in which systems are subject to failure from independent competing risks. Following a failure, immediate (stage-1) procedures are used in an attempt to reach a definitive diagnosis. If these procedures fail to result in a diagnosis, this phenomenon is called masking. Stage-2 procedures, such as failure analysis or autopsy, provide definitive diagnosis for a sample of the masked cases. We show how stage-1 and stage-2 information can be combined to provide statistical inference about (a) survival functions of the individual risks, (b) the proportions of failures associated with individual risks and (c) probability, for a specified masked case, that each of the masked competing risks is responsible for the failure. Our development is based on parametric distributional assumptions and the special case for which the failure times for the competing risks have a Weibull distribution is discussed in detail.     

The Effect of Drop-Out on the Efficiency of Longitudinal Experiments

It is shown that drop-out often reduces the efficiency of longitudinal experiments considerably. In the framework of linear mixed models, a general, computationally simple method is provided, for designing longitudinal studies when drop-out is to be expected, such that there is little risk of large losses of efficiency due to the missing data. All the results are extensively illustrated using data from a randomized experiment with rats.     

Easy to Declare,Difficult to Implement: The Disconnect Between the Aspirations of the Paris Declaration and Donor Practice in Nigeria

The arguments in academia over the effectiveness of foreign aid fall into two broad categories: those grounded in political economy and those focused on donor conduct and aid effectiveness. There have been policy attempts within the donor community to reconcile them, including the 2005 Paris Declaration on Aid Effectiveness. This article examines the key features of foreign aid to Nigeria between 1999 and 2007. Using the Declaration as a framework, it looks for ways of making foreign aid in Nigeria more effective.     

Using repeated-prevalence data in multi-state modeling of renal replacement therapy

Multi-state models help predict future numbers of patients requiring specific treatments but these models require exhaustive incidence data. Deriving reliable predictions from repeated-prevalence data would be helpful. A new method to model the number of patients that switch between therapeutic modalities using repeated-prevalence data is presented and illustrated. The parameters and goodness of fit obtained with the new method and repeated-prevalence data were compared to those obtained with the classical method and incidence data. The multi-state model parameters’ confidence intervals obtained with annually collected repeated-prevalence data were wider than those obtained with incidence data and six out of nine pairs of confidence intervals did not overlap. However, most parameters were of the same order of magnitude and the predicted patient distributions among various renal replacement therapies were similar regardless of the type of data used. In the absence of incidence data, a multi-state model can still be successfully built with annually collected repeated-prevalence data to predict the numbers of patients requiring specific treatments. This modeling technique can be extended to other chronic diseases.     

Position in formal structure, personal characteristics and choices of advisors in a law firm: A logistic regression model for dyadic network data

This paper presents a statistical model for the analysis of binary sociometric choice data, the p₂ model, which provides a flexible way for using explanatory variables to model network structure. It is applied to examine the influence of the formal structure of an organization on interactions among its members. It is shown to provide a general and precise method for addressing this substantive issue. We identify the respective effects of position in the formal structure (status, seniority, division of work and office membership) and selected personal characteristics of members of a corporate law firm on their choices of advisors. Flows of advice are shown to be consistently shaped by status games and the pecking order in the firm. Other dimensions help members in mitigating the effect of this strong rule. This approach ultimately provides more understanding of how members of such firms try to balance cooperation and competition in terms of access to and management of key resources.     

More Efficient Tests Robust to Heteroskedasticity of Unknown Form

In the presence of heteroskedasticity of unknown form, the Ordinary Least Squares parameter estimator becomes inefficient, and its covariance matrix estimator inconsistent. Eicker (1963) and White (1980) were the first to propose a robust consistent covariance matrix estimator, that permits asymptotically correct inference. This estimator is widely used in practice. Cragg (1983) proposed a more efficient estimator, but concluded that tests basd on it are unreliable. Thus, this last estimator has not been used in practice. This article is concerned with finite sample properties of tests robust to heteroskedasticity of unknown form. Our results suggest that reliable and more efficient tests can be obtained with the Cragg estimators in small samples.     

Financing retirement pensions: Pay-as-you-go and funded systems in the European Union

The techniques used to finance retirement pensions in the European Union are extremely varied, as are schemes'institutional frameworks. The standard distinction between pay-as-you-go and funded systems obscures the fact that there are four main types of schemes, each with very distinct methods of regulation and conditions of long-term viability. An analysis of the current procedures reveals the extent to which the schemes'ways of operating differ, and points to considerable variations in the way the social actors participate in the process of regulation. The adaptation of pension systems to new realities is dependent on factors which go far beyond a simple choice between two basic methods of financing.