Integrating Poverty and Environmental Concerns into Value‐Chain Analysis: A Strategic Framework and Practical Guide

This article aims to guide the design and implementation of action‐research projects in value‐chain analysis by presenting a strategic framework focused on small producers and trading and processing firms in developing countries. Its stepwise approach – building on the conceptual framework set out in a companion article – covers in detail what to do, questions to be asked and issues to be considered, and integrates poverty, gender, labour and environmental concerns.‘Upgrading’ strategies potentially available for improving value‐chain participation for small producers are identified, with the ultimate purpose of increasing the rewards and/or reducing the risks.     

A Bayesian non-parametric modeling to estimate student response to ICT investment†

This paper estimates the causal impact of investment in information and communication technologies (ICT) on student performances in mathematics as measured in the Program for International Student Assessment (PISA) 2012 for Spain. To do this we apply a new methodology in this context known as Bayesian Additive Regression Trees that has important advantages over more standard parametric specifications. Results indicate that ICT has a moderate positive effect on math scores. In addition, we analyze how this effect interacts with variables related to school features and student socioeconomic status, finding that ICT investment is especially beneficial for students from a low socioeconomic background.     

Evaluating positive leadership: pilot study on the psychometric properties of a reduced version of the Positive Leadership Assessment Scale / Evaluando el liderazgo positivo: estudio piloto de las propiedades psicométricas de una versión reducida del Positive Leadership Assessment Scale

Positive leadership is considered a fundamental factor which contributes significantly to the development of healthy organizations. Positive leadership has been address via other leadership models, primarily transformational and authentic leadership, with which some affinities have been established. Although there is a large body of literature on positive leadership, especially related to its practical aspects, the construct is not properly delimited and there are only a few relevant contributions on how to measure it. The purpose of this paper is to conduct a pilot study to examine the psychometric properties of a reduced version of the PLAS (Positive Leadership Assessment Scale). Results from a confirmatory factorial analysis show that a five-correlated factors model achieves a good fit with the empirical data (on a sample of Spanish students). Likewise, this study also offers a range of evidence of validity, showing a relationship with the constructs of both transformational and authentic leadership and engagement.     

Some new results on univariate and multivariate permutation tests for ordinal categorical variables under restricted alternatives

In several sciences, especially when dealing with performance evaluation, complex testing problems may arise due in particular to the presence of multidimensional categorical data. In such cases the application of nonparametric methods can represent a reasonable approach. In this paper, we consider the problem of testing whether a “treatment” is stochastically larger than a “control” when univariate and multivariate ordinal categorical data are present. We propose a solution based on the nonparametric combination of dependent permutation tests (Pesarin in Multivariate permutation test with application to biostatistics. Wiley, Chichester, 2001), on variable transformation, and on tests on moments. The solution requires the transformation of categorical response variables into numeric variables and the breaking up of the original problem’s hypotheses into partial sub-hypotheses regarding the moments of the transformed variables. This type of problem is considered to be almost impossible to analyze within likelihood ratio tests, especially in the multivariate case (Wang in J Am Stat Assoc 91:1676–1683, 1996). A comparative simulation study is also presented along with an application example.     

Reliability and Validity of the Pathological Gambling Adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS)

The Yale Brown Obsessive Compulsive Scale adapted for Pathological Gambling (PG-YBOCS) was developed to measure the severity and change in severity of pathological gambling symptoms. The PG-YBOCS is a 10-item clinician-administered questionnaire that measures the severity of PG over a recent time interval (usually within the past one/two week(s)). In order to assess and validate the scale, it was administered to 337 subjects: 188 pathological gamblers and 149 healthy controls. Internal consistency and correlations between individual items and total score were assessed for various permutations of the sample. Other scales were administered to assess convergent, discriminant and content validity. Sensitivity to change was evaluated in treatment studies with fluovoxamine, lithium, and valproate. Each item was frequently endorsed across a range of severity. Good inter-rater reliability and internal consistency were obtained. The PG-YBOCS showed high validity and reliability for total score, item-total correlations, and for each subscale (Thoughts/Urges and Behavior). PG-YBOCS scores correlated with global severity and South Oaks Gambling Screen (SOGS) scores. The scale was also sensitive to change in pathological gambling severity. PG-YBOCS thus appears to be a reliable and valid measure of pathological gambling severity, and can be regarded as an important tool for clinicians and researchers treating pathological gamblers.     

Presenting Results from Model Based Studies to Decision-Makers: Can Sensitivity Analysis be a Defogging Agent?

The motivation of the present work is to provide an auxiliary tool for the decision-maker (DM) faced with predictive model uncertainty. The tool is especially suited for the allocation of R&Dresources. When taking decisions under uncertainties, making use of the output from mathematical or computational models, the DM might be helped if the uncertainty in model predictions be decomposed in a quantitative-rather than qualitativefashion, apportioning uncertainty according to source. This would allow optimal use of resources to reduce the imprecision in the prediction. For complex models, such a decomposition of the uncertainty into constituent elements could be impractical as such, due to the large number of parameters involved. If instead parameters could be grouped into logical subsets, then the analysis could be more useful, also because the decision maker might likely have different perceptions (and degrees of acceptance) for different kinds of uncertainty. For instance, the decomposition in groups could involve one subset of factors for each constituent module of the model; or one set for the weights, and one for the factors in a multicriteria analysis; or phenomenological parameters of the model vs. factors driving the model configuratiodstructure aggregation level, etc.); finally, one might imagine that a partition of the uncertainty could be sought between stochastic (or aleatory) and subjective (or epistemic) uncertainty. The present note shows how to compute rigorous decomposition of the output's variance with grouped parameters, and how this approach may be beneficial for the efficiency and transparency of the analysis.     

Global imbalances, exchange rates adjustment and the crisis: Implications from network analysis

The persistence of global imbalances remains a potential source of instability for the international economic system, which ought to be tackled in order to exit from the current crisis in a better position. This paper shows that the complexity of the global network of trade imbalances has increased over time in terms of the number of countries involved and of the heterogeneity of their conditions. These findings imply that orchestrating a global exchange rate adjustment plan, as done in the 1980s to tackle a similar problem, is certainly more difficult than it was 20 years ago. We also show, however, that the uncoordinated movements in bilateral exchange rates occurred since the early 2000s did not go in the direction of reducing bilateral imbalances. Rebalancing the world economy, thus, seems to require a rich set of coordinated policy actions and economic changes, involving adjustments in both exchange rates and real variables, which are heterogeneous at the country level. We argue that, provided some conditions are satisfied, the variegated effects of the ongoing financial crisis, and the policy responses this has induced, may help the global and bilateral rebalancing process.     

Probabilistic spatial power indexes

In this study, we present a generalization of spatial power indexes able to overcome their main limitations, namely (i) the excessive concentration of power measures; (ii) the too high sensitivity to players’ location in the ideological space. Voters’ propensity to support an issue is modeled via a random utility function with two additive terms: the deterministic term accounts for voters’ preference-driven/predictable behavior; the random one is a catch-all term that accounts for all the idiosyncratic/unpredictable factors. The relative strength of the two terms gives rise to a continuum of cases ranging from the Shapley value, where all aggregation patterns are equally probable, to a standard spatial value, like the Owen–Shapley index, where instead the conditional order is fully deterministic. As an illustrative application, we analyze the distribution of power in the Council of Ministers under three different scenarios: (i) EU15 Pre-Nice; (ii) EU27 Nice Treaty; (iii) EU27 Lisbon Treaty.     

The Economic Perspective of Food Poverty and (In)security: An Analytical Approach to Measuring and Estimation in Italy

Social Indicators Research - The UN Sustainable Development Goals have set clear targets on global poverty, hunger and malnutrition to be achieved by 2030, which have prompted academics and...