Simulation-based model comparison methodology with application to road accident models

This article assumes the goal of proposing a simulation-based theoretical model comparison methodology with application to two time series road accident models. The model comparison exercise helps to quantify the main differences and similarities between the two models and comprises of three main stages: (1) simulation of time series through a true model with predefined properties; (2) estimation of the alternative model using the simulated data; (3) sensitivity analysis to quantify the effect of changes in the true model parameters on alternative model parameter estimates through analysis of variance, ANOVA. The proposed methodology is applied to two time series road accident models: UCM (unobserved components model) and DRAG (Demand for Road Use, Accidents and their Severity). Assuming that the real data-generating process is the UCM, new datasets approximating the road accident data are generated, and DRAG models are estimated using the simulated data. Since these two methodologies are usually assumed to be equivalent, in a sense that both models accurately capture the true effects of the regressors, we are specifically addressing the modeling of the stochastic trend, through the alternative model. Stochastic trend is the time-varying component and is one of the crucial factors in time series road accident data. Theoretically, it can be easily modeled through UCM, given its modeling properties. However, properly capturing the effect of a non-stationary component such as stochastic trend in a stationary explanatory model such as DRAG is challenging. After obtaining the parameter estimates of the alternative model (DRAG), the estimates of both true and alternative models are compared and the differences are quantified through experimental design and ANOVA techniques. It is observed that the effects of the explanatory variables used in the UCM simulation are only partially captured by the respective DRAG coefficients. This a priori, could be due to multicollinearity but the results of both simulation of UCM data and estimating of DRAG models reveal that there is no significant static correlation among regressors. Moreover, in fact, using ANOVA, it is determined that this regression coefficient estimation bias is caused by the presence of the stochastic trend present in the simulated data. Thus, the results of the methodological development suggest that the stochastic component present in the data should be treated accordingly through a preliminary, exploratory data analysis.     

The roads of immanence: infrastructural change in southern Chile

In southern Chile, the building of roads has triggered profound socio-material transformation in indigenous worlds. In this article, we attempt to comprehend and conceptualize the capacities of roads to reconstitute radically a relationally constituted world, a world that is therefore in itself contingent. We suggest that the material alteration of indigenous worlds produce uncertain results, including possibly its own destruction. The arguments raised in this article indicate that the analytical and political problem of ontological self-determination can be advanced once reshaped in infrastructural terms.     

The statistical impact of inflation on interest rates

Understanding the behavior of interest rates is of central importance in finance. This is due to the fact that interest and forward rates serve as underlyings for many fixed income products. Furthermore, interest rate-based quantities may be used as numeraires when it comes to computing present values of future payoffs. An important macroeconomic factor which is likely to trigger interest rates is inflation. In this paper we extend a well-known continuous time interest rate model by incorporating inflation. Finally, we apply a statistical test to real data to explore the goodness-of-fit of the inflation-based model.     

Hand-Hygiene Mitigation Strategies Against Global Disease Spreading through the Air Transportation Network

The risk for a global transmission of flu-type viruses is strengthened by the physical contact between humans and accelerated through individual mobility patterns. The Air Transportation System plays a critical role in such transmissions because it is responsible for fast and long-range human travel, while its building components—the airports—are crowded, confined areas with usually poor hygiene. Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) consider hand hygiene as the most efficient and cost-effective way to limit disease propagation. Results from clinical studies reveal the effect of hand washing on individual transmissibility of infectious diseases. However, its potential as a mitigation strategy against the global risk for a pandemic has not been fully explored. Here, we use epidemiological modeling and data-driven simulations to elucidate the role of individual engagement with hand hygiene inside airports in conjunction with human travel on the global spread of epidemics. We find that, by increasing travelers engagement with hand hygiene at all airports, a potential pandemic can be inhibited by 24% to 69%. In addition, we identify 10 airports at the core of a cost-optimal deployment of the hand-washing mitigation strategy. Increasing hand-washing rate at only those 10 influential locations, the risk of a pandemic could potentially drop by up to 37%. Our results provide evidence for the effectiveness of hand hygiene in airports on the global spread of infections that could shape the way public-health policy is implemented with respect to the overall objective of mitigating potential population health crises.     

Domestic Violence, Emotional Competence, and Child Adjustment

This article examined emotion competence in children exposed to domestic violence (DV). It also examined the hypothesis that children's emotional competence mediates relations between DV and children's later difficulties with peers and behavioral adjustment. DV was assessed when children were at the age of five, emotional competence was assessed at the age of 9.5, and peer quality and behavioral adjustment were obtained at the age of 11. Children from homes with greater DV were less aware of their own emotions and more emotionally dysregulated at the age of 9.5. Emotional awareness mediated the relationship between DV at the age of five and children's friendship closeness and internalizing problems at the age of 11. Emotion dysregulation mediated the relationship between DV at the age of five and children's negative peer group interactions, social problems, and internalizing and externalizing problems at the age of 11. Results are discussed in terms of the impact of DV on children's emotional development and the role that different aspects of emotional competence play in children's socio‐emotional adjustment.     

Nonparametric analysis of aggregate loss models

This paper describes a nonparametric approach to make inferences for aggregate loss models in the insurance framework. We assume that an insurance company provides a historical sample of claims given by claim occurrence times and claim sizes. Furthermore, information may be incomplete as claims may be censored and/or truncated. In this context, the main goal of this work consists of fitting a probability model for the total amount that will be paid on all claims during a fixed future time period. In order to solve this prediction problem, we propose a new methodology based on nonparametric estimators for the density functions with censored and truncated data, the use of Monte Carlo simulation methods and bootstrap resampling. The developed methodology is useful to compare alternative pricing strategies in different insurance decision problems. The proposed procedure is illustrated with a real dataset provided by the insurance department of an international commercial company.     

How Children and Young People Influence Policy‐Makers: Lessons from Nicaragua

This article describes a participatory research project, which explored four case studies of children and young people's successful political advocacy in Nicaragua. The analysis combined a human rights‐based approach and a human development approach, and included concepts of multiple settings and levels, interrelated participation spaces, children and young people's citizenship, inclusion and exclusion, democracy, advocacy and empowerment. The main problems faced by children and young people seeking to influence policy‐makers were identified as adultism, dependency and lack of accountability. The research identified pre‐conditions, participation spaces and ways of organising for effective advocacy, and facilitation methods that had proved effective. It concludes that children and young people who achieve effective advocacy are generally self‐empowered, but can count on effective adult support and facilitation. They work through coordination with the authorities and not by clashing with them, but need to ensure effective follow up if they want politicians to keep their promises.     

Evaluation and Treatment of Pathological Gambling

The aim of this article was to describe a model for evaluating and implementing cognitive-behavioral treatment for pathological gambling. The model takes into account the fact that pathological gamblers form a heterogeneous group with varied biopsychosocial characteristics.