Estimation of Deprivation Level Functions using a Numerical Rating Scale

Evaluating and quantifying human suffering in humanitarian operations offers an innovative and potentially powerful way to assess the performance of humanitarian logistics (HL) and help build optimization models. Previous studies have suggested deprivation cost as a metric and have estimated deprivation cost functions for water using willingness‐to‐pay. Our study proposes deprivation levels, defined as the degree of human suffering caused by lack of access to a good or service, and estimates deprivation level functions using a numerical rating scale. Analyzing data collected from respondents with and without disaster experience, we find that individuals in the latter category estimate deprivation differently from the beneficiaries of disaster relief. Our study demonstrates that deprivation levels can be expressed as logistic growth functions with a typical S‐shape, and that these can be integrated into HL optimization models to better account for human suffering.     

The Role of Media Exposure on Coordination in the Humanitarian Setting

Despite high demand and resource limitations, humanitarian organizations (HOs) typically do not share resources and/or coordinate in the field. While coordination enhances operational performance and saves costs, the general perception is that it dilutes the media attention that individual organizations might receive, and negatively influences their future donation income. In this study, we empirically unveil the impact of media exposure and operational performance on the donations obtained by HOs. Then, based on the empirical results, we develop a stylized model to characterize the structure of preferred coordination policies with respect to an organization's funding source and main mandate. Our findings shed light on the incentives and dynamics that drive behaviors in humanitarian operations and provide insights for policy makers on designing and implementing mechanisms that encourage humanitarian coordination.     

Dual class shares,board of directors’ effectiveness and firm’s market value: an empirical study

This study aims to identify whether a relationship exists between the controlling shareholders’ voting power and outside directors’ effectiveness in maximizing firms’ financial performance. We analyze a panel data with 3057 observations for the 2000–2012 period using a random effects model, logit and probit regressions, and the two-stage model of Heckman in the Brazilian stock market. Our findings show that firms whose controlling shareholders use dual class shares to leverage their voting power have less independence from the board and worse financial performance and market value. Further, the percentage of outside directors tends to be ineffective in increasing the firm’s value, and in changing the firm’s chief executive officer (CEO) when (1) the controlling shareholder’s voting power is leveraged, or (2) when the CEO assumes a position on the board of directors simultaneously. We interpreted that these results are in line with the arguments in favor of the existence of a new agency cost, which is related to the undue obedience of board members to authority, such as the largest controlling shareholder or the CEO in Brazilian listed firms.     

Fast parallel $$\alpha $$-stable distribution function evaluation and parameter estimation using OpenCL in GPGPUs

\(\alpha \)-Stable distributions are a family of probability distributions found to be suitable to model many complex processes and phenomena in several research fields, such as medicine, physics, finance and networking, among others. However, the lack of closed expressions makes their evaluation analytically intractable, and alternative approaches are computationally expensive. Existing numerical programs are not fast enough for certain applications and do not make use of the parallel power of general purpose graphic processing units. In this paper, we develop novel parallel algorithms for the probability density function and cumulative distribution function—including a parallel Gauss–Kronrod quadrature—, quantile function, random number generator and maximum likelihood estimation of \(\alpha \)-stable distributions using OpenCL, achieving significant speedups and precision in all cases. Thanks to the use of OpenCL, we also evaluate the results of our library with different GPU architectures.     

Forward irrelevance

We investigate how to combine marginal assessments about the values that random variables assume separately into a model for the values that they assume jointly, when (i) these marginal assessments are modelled by means of coherent lower previsions and (ii) we have the additional assumption that the random variables are forward epistemically irrelevant to each other. We consider and provide arguments for two possible combinations, namely the forward irrelevant natural extension and the forward irrelevant product, and we study the relationships between them. Our treatment also uncovers an interesting connection between the behavioural theory of coherent lower previsions, and Shafer and Vovk's game-theoretic approach to probability theory.     

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model. Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the r$r$th moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin et al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214–223]. The usefulness of these models is illustrated in a simulation study and in applications to three real data sets.     

Measuring Child Poverty in South Africa: Sensitivity to the Choice of Equivalence Scale and an Updated Profile

This paper offers evidence on the sensitivity of child poverty in South Africa to changes in the adult equivalence scale (AES) and updates the child poverty profile based on the Income and Expenditure Survey 2005/06. Setting the poverty line at the 40th percentile of households calculated with different AESs the scope and composition of child poverty are found to be relatively insensitive to the scale used. The rankings of children of different ages, girls versus boys, racial groupings and children living in rural versus urban areas are unaffected by choice of AES, although some provincial rankings on the poverty headcount measure are. The proportions of children and households ‘correctly’ identified as poor for the full range of scales is extremely high. These findings support the argument that it may be appropriate for profiling poverty in South Africa to use a poverty line based on a per capita welfare measure. For the construction of the child poverty profile, per capita income is used as the welfare indicator with the poverty line set at the 40th percentile of household. The profile suggests that poverty amongst children is more extensive than amongst the population or adults even after the massive injection of transfers into households with poor children through the child support grant. The child poverty headcount, depth and severity are all highest amongst children age 0–4 and lowest amongst those aged 15–17, who are not yet beneficiaries of the grants. They are also highest amongst African and Coloured children. Large variations across provinces remain. The analysis underlines the importance of prioritising children in the fight against poverty, particularly in their earliest years.     

The effects of under‐skilling on need for recovery,losing employment and retirement intentions among older office workers: A prospective cohort study

Based on a sample of older workers from the Maastricht Cohort Study, the authors investigate the prevalence and dynamics of self‐reported under‐skilling and its effects on workers' need for recovery, their risk of losing employment and their retirement intentions over a two‐year period. They find that being under‐skilled is associated both with higher levels of need for recovery over time and with the risk of losing employment, but not with early retirement intentions. To achieve sustainable employment, they argue, the course of under‐skilling should be monitored throughout workers' careers, enabling timely interventions to avoid its negative consequences.