Trying to stay ahead of the curve in Chile's economic development: exploring a way out of the middle‐income trap through pragmatic export development

Underneath impressive growth levels, the Chilean economy displays signs of being caught in a middle‐income trap. It has been unable to improve its productivity, increase the added value of its exports or upgrade its value chain. Its economy cannot compete either with low‐wage countries or highly productive, innovative countries. Its export strategy based on export promotion seems to have outlived its usefulness. It achieved remarkable quantitative success, but must now attend qualitative attributes. Instead of regarding market‐driven export promotion and state‐led export development as substitutes, this article proposes to view them as alternatives in different stages of development. To choose the appropriate time, more attention should be given to non‐traditional, structural indicators, like export sophistication and political‐institutional capabilities.     

Myths and realities about input subsidies in sub‐Saharan Africa

Using a recent public expenditure dataset, this article proposes a ‘reality check’ of the level and composition of input subsidies in nine African countries between 2006 and 2013. Results show that input subsidies (1) received close to 35% of agricultural‐specific expenditure on average and (2) cover a variety of interventions, including investments in capital, such as on‐farm irrigation, and in on‐farm services, such as inspection or training. Further, the figures show that input subsidies tended to become entrenched in agricultural budgets over time, leading to sub‐optimal execution rates, and were primarily funded by the national taxpayer, while donors invested more in public goods. Findings confirm that input subsidies crowded out other spending categories likely to be more supportive of long‐term agricultural development objectives. The article concludes that the political economy of input subsidies should be directed to making more concrete efforts to attain a better balance of public expenditure on agriculture. Furthermore, policy‐makers should aim to increase the efficiency and policy coherence of input subsidies, since merely abolishing them is likely to be unfeasible in the short term.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Self-validated Computations for the Probabilities of the Central Bivariate Chi-square Distribution and a Bivariate F Distribution. This work partially supported by National Science Foundation grant DMS-9500831

Self-validated computations using interval analysis produce results with a guaranteed error bound. This article presents methods for self-validated computation of probabilities and percentile points of the bivariate chi-square distribution and a bivariate F distribution. For the computation of critical points (c ₁,c ₂) in the equation P(Y ₁ @ c ₁, Y ₂ ≤ c ₂) = 1 ? α, the case c ₁ = c ₂ is considered. A combination of interval secant and bisection algorithms is developed for finding enclosures of the percentile points of the distribution. Results are compared to previously published tables.     

Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data

In this paper, a competing risks model is considered under adaptive type-I progressive hybrid censoring scheme (AT-I PHCS). The lifetimes of the latent failure times have Weibull distributions with the same shape parameter. We investigate the maximum likelihood estimation of the parameters. Bayes estimates of the parameters are obtained based on squared error and LINEX loss functions under the assumption of independent gamma priors. We propose to apply Markov Chain Monte Carlo (MCMC) techniques to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, a simulation study is carried out.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

The struggle for Via Bologna street market: crisis,racial denial and speaking back to power in Naples Italy

This paper is based on ethnographic research conducted with migrant and Italian street vendors in Naples, southern Italy, in 2012. It tells the story of Via Bologna market which was nearly closed down by the City Hall at the time. Naples is a city where issues of poverty and unemployment pre‐date and have been exacerbated by manifold narratives of crisis now unfolding across Europe regarding the economy, political legitimacy, security and migration. Street markets have always been an important and visible economic survival strategy for both Neapolitans and migrants there. This article shows how the Via Bologna street vendors appropriated and adapted discourses about crisis to form their own cosmopolitan social movement that halted the closure of the market. It argues that, in the age of globalized migration, the multilingual nature of such collective action is central to understanding social struggles that must be organized between marginalized groups of people divided by race, religion, politics and legal status. This, frequently ambiguous, transcultural solidarity speaks back against a mainstream post‐racial discourse – often articulated by the Neapolitan street vendors at the market – that would reduce the complexity of such collective action to questions of poverty and class struggle.     

Graduating Out of Poverty Across Generations: Unpacking Children’s Well‐being Trajectories in Burundi

Graduation model interventions represent a new wave of anti‐poverty programming that seeks to offer a sustainable pathway out of poverty. An expanding evidence base points towards positive economic outcomes at household level but little is known about impacts on child well‐being. This paper investigates children’s well‐being in Burundi during and after participation in a graduation model programme using a longitudinal mixed‐methods approach. The programme is found to improve child well‐being, particularly in relation to housing, food security and education. Covariate shocks undermine sustainability of effects but greater knowledge, experience and prioritisation of children’s needs contribute to harnessing improved outcomes.     

The competing risks analysis for parallel and series systems using Type-II progressive censoring

Abstract

Recently, the study of the lifetime of systems in reliability and survival analysis in the presence of several causes of failure (competing risks) has attracted attention in the literature. In this paper, series and parallel systems with exponential lifetime for each item of the system are considered. Several causes of failure independently affect lifetime distributions and observations of failure times of the systems are considered under progressive Type-II censored scheme. For series systems, the maximum likelihood estimates of parameters are computed and confidence intervals for parameters of the model are obtained using Fisher information matrix. For parallel systems, the generalized EM algorithm which uses the Newton-Raphson algorithm inside the EM algorithm is used to compute the maximum likelihood estimates of parameters. Also, the standard errors of the maximum likelihood estimates are computed by using the supplemented EM algorithm. The simulation study confirms the good performance of the introduced approach.     

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

We used an agent‐based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision‐making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers’ behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system‐level responses are predicted using a bottom‐up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food‐safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.