A Communication Perspective on Video Lottery Terminals

Video Lottery Terminals (VLT) are associated with pathological gambling and with most of the requests for help in combating gambling addiction. Embeddedness of a person in his or her social network is among the communicational factors that may help explain this phenomenon. To verify this, we compared ego networks of VLT gamblers, of gamblers of games with low request for help and of VLT gamblers in treatment (n = 90). The networks of regular VLT gamblers are small and dense and offer little social support. Gamblers in treatment also have small networks, but they are less dense, have more components and offer more social support. Networks of gamblers with low requests for assistance are approximately twice the size as those of VLT gamblers, are sparser and offer more companionship. In conclusion, the VLT gambler is not an isolated individual, but rather an individual ‘shut-in’ a small network of tightly knitted relationships.     

About an adaptively weighted Kaplan-Meier estimate

The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function. We use the Kaplan-Meier estimate to let the weights accommodate right-censored data and use them to define the weighted Kaplan-Meier estimate. The proposed estimate is smoother than the usual Kaplan-Meier estimate and converges uniformly in probability to the target distribution. Simulations show that the performances of the weighted Kaplan-Meier estimate on finite samples exceed that of the usual Kaplan-Meier estimate. A case study is also presented.     

Tax–benefit revealed social preferences

This paper inverts the usual logic of applied optimal income taxation. It starts from the observed distribution of income before and after redistribution and corresponding marginal tax rates. Under a set of simplifying assumptions, it is then possible to recover the social welfare function that would make the observed marginal tax rate schedule optimal. In this framework, the issue of the optimality of an existing tax–benefit system is transformed into the issue of the shape of the social welfare function associated with that system and whether it satisfies elementary properties. This method is applied to the French redistribution system with the interesting implication that the French redistribution authority may appear, under some plausible scenario concerning the size of the labor supply behavioral reactions, non Paretian (e.g. giving negative marginal social weights to the richest class of tax payers).     

Asymptotic properties of the MAMSE adaptive likelihood weights

The weighted likelihood is a generalization of the likelihood designed to borrow strength from similar populations while making minimal assumptions. If the weights are properly chosen, the maximum weighted likelihood estimate may perform better than the maximum likelihood estimate (MLE). In a previous article, the minimum averaged mean squared error (MAMSE) weights are proposed and simulations show that they allow to outperform the MLE in many cases. In this paper, we study the asymptotic properties of the MAMSE weights. In particular, we prove that the MAMSE-weighted mixture of empirical distribution functions converges uniformly to the target distribution and that the maximum weighted likelihood estimate is strongly consistent. A short simulation illustrates the use of bootstrap in this context.     

Using Predictive Risk for Process Control

When monitoring highly capable processes, it is often desirable to tolerate small instabilities in order to avoid tempering. One approach in this setting is to monitor the capability of the process dynamically and signal if the estimated capability reaches an unacceptably low level. We suggest that monitoring the probability of the next item not falling between the specification limits is a more natural scale to evaluate risk, and offers appreciable flexibility. We use a statistical model and a window of data to evaluate this probability and decide if the process should be halted immediately based on that estimate. The properties of this method are explored numerically and a case study is provided.     

Habitat rehabilitation in urban waterways: the ecological potential of bank protection structures for benthic invertebrates

Compensating for the adverse ecological impacts of waterway development and improving their ecological functioning to achieve good ecological potential (GEP) have become mandatory within the European Union (EU). The technical rehabilitation measures presented here aim to functionally minimize the hydraulic impacts of navigation on aquatic biota in highly urbanized waterways. Their ecological functioning and potential to enhance biodiversity locally was assessed by comparing their macro-invertebrate community composition with nearby non-restored sites. Rehabilitation led to lower hydraulic impact on the littoral zone, which in turn led to the presence of otherwise missing macrophytes and the occurrence of organic mud habitats colonized by invertebrates typically rare in urban waterways. While the control sites were dominated by few, mostly invasive taxa in vast numbers, the rehabilitated sites exhibited a highly diverse community with 22 protected mollusc and insect taxa typically found in the oxbow communities of natural rivers. This major improvement was however not detected using the core metrics of the legally required national assessment tools of the EU Water Framework Directive. Overall results proved the success of this type of rehabilitation measure with respect to improving biodiversity, but they also showed the limiting and key factors influencing the macro-invertebrate communities of highly deteriorated urban waterways. Indeed, future implementations of this type of rehabilitation measure should consider spatial extent, water exchange rates, temporal succession of vegetation and adaptive management to improve its ecological functioning.     

Effect of the board of directors and the audit committee on firm performance: a panel data analysis

This research examines the relationship between independent directors, the audit committee (AC), and firm performance, taking into account the impact of the chief executive officer’s powers and block shareholders. We use the maximum likelihood estimator, based on agency theory assumptions and cylindered panel data, to examine three models of firm performance. The results show that the independence of the board is reflected clearly by increased economic and equity performance of the firm. However, an AC that is fully independent or meets frequently is associated with lower firm performance. Unlike pension funds, institutional shareholders can be considered an effective control mechanism in the context of France. Our results development includes advanced explanations for market liquidity and shareholders’ portfolios. The study period ends before the European regulation on ACs came into effect in 2008. This allows for an appreciation of soft law in French corporate governance. It also lets us compare the data with the way firms operate their boards one decade later. The evidence provides useful guidelines on the supremacy of soft law in corporate governance and suggests that the composition and functioning of the board of directors should be moderated based on the firms’ context. The specificity of the cylindered panel data helps to better examine the impact of the board and AC’s independence and functioning in French corporate governance structure.     

Multiplier bootstrap methods for conditional distributions

The multiplier bootstrap is a fast and easy-to-implement alternative to the standard bootstrap; it has been used successfully in many statistical contexts. In this paper, resampling methods based on multipliers are proposed in a general framework where one investigates the stochastic behavior of a random vector \(\mathbf {Y}\in \mathbb {R}^d\) conditional on a covariate \(X \in \mathbb {R}\). Specifically, two versions of the multiplier bootstrap adapted to empirical conditional distributions are introduced as alternatives to the conditional bootstrap and their asymptotic validity is formally established. As the method walks hand-in-hand with the functional delta method, theory around the estimation of statistical functionals is developed accordingly; this includes the interval estimation of conditional mean and variance, conditional correlation coefficient, Kendall’s dependence measure and copula. Composite inference about univariate and joint conditional distributions is also considered. The sample behavior of the new bootstrap schemes and related estimation methods are investigated via simulations and an illustration on real data is provided.