Récession,austérité et genre: étude comparative sur huit marchés du travail européens

Si l'effondrement du PIB consécutif à la crise économique mondiale de 2008 a nui avant tout à l'emploi des hommes, les politiques d'austérité auraient davantage affecté celui des femmes. L'auteure cherche à vérifier ce scénario dans huit pays européens, en décomposant la variation trimestrielle du taux d'activité et du taux d'emploi des femmes et des hommes à l'échelon sectoriel. Elle montre que l'association entre he‐cession et she‐austerity ne se confirme pas toujours, mais que les politiques d'austérité peuvent nuire à l'égalité des sexes et aux droits de la femme par d'autres mécanismes d'action, qu'elle répertorie et commente.     

The multicriteria selection of products in technological diversification strategies: an application to the Spanish automotive industry based on AHP

The economic recession, the dynamism and complexity of the markets and the generalised globalisation of the world economy have forced many companies to rethink and reorganise their industrial strategies. Through identifying and taking advantage of the key technologies of a company, this work presents a new and original methodology for dealing with a general technological diversification process. The methodology, which includes an innovative cognitive perspective and its corresponding decisional tool (decision support system) has been used to select the best product in a process of technological diversification that, along with the key technologies, identifies the sub-levels consonant to the sub-technologies and applications to sectors and products. The multicriteria selection tool employed in the proposed methodology, based on the analytic hierarchy process, allows the integration of multiple scenarios, actors and criteria, both tangible and intangible. The methodology has been applied to a case study in the Spanish automotive auxiliary sector.     

Dyadic Cross-Sectional Associations Between Depressive Mood,Relationship Satisfaction,and Common Dyadic Coping

The aim of this cross-sectional study was to investigate the mediational role of common dyadic coping in the links between depressive mood and relationship satisfaction. We estimated two competing Actor–Partner Mediator Models, in which the dyad is the highest unit of analysis. The first model specified dyadic coping as a mediator in the association between relationship satisfaction and depression, whereas the second model specified dyadic coping as a mediator between depression and relationship satisfaction. Analyzing data from 198 couples, our findings provided a plausible approximation of the second model, representing the interactional model of depression. They showed that common dyadic coping mediates the link between depression and relationship satisfaction for men only.     

Accuracy of approximate progressively censored reliability sampling plans for exponential models

Reliability sampling plans provide an efficient method to determine the acceptability of a product based upon the lifelengths of some test units. Usually, they depend on the producer and consumer’s quality requirements and do not admit closed form solutions. Acceptance sampling plans for one- and two-parameter exponential lifetime models, derived by approximating the operating characteristic curve, are presented in this paper. The accuracy of these approximate plans, which are explicitly expressible and valid for failure and progressive censoring, is assessed. The approximation proposed in the one-parameter case is found to be practically exact. Explicit lower and upper bounds on the smallest sample size are given in the two-parameter case. Some additional advantages are also pointed out.     

Homicide Rates in a Cross‐Section of Countries: Evidence and Interpretations

This study uses a regression analysis to explore the cross‐country variation in homicide rates for a large sample of countries. It starts by identifying seven significant regional variables, to which traditional socioeconomic, cultural, and institutional variables are added and tested. The importance of institutions, culture, and other factors affecting homicide rates is discussed. One unexpected finding is a curious relationship between the level of education and homicide rates: while an increase in male education tends to reduce homicide rates, an increase in female education tends to increase homicides. Several possible interpretations for this phenomenon are proposed. The study points to relatively unexplored areas of research in order to better understand homicide variation around the world.     

Influence measure for the L1 regression

Because outliers and leverage observations unduly affect the least squares regression, the identification of influential observations is considered an important and integrai part of the analysis. However, very few techniques have been developed for the residual analysis and diagnostics for the minimum sum of absolute errors, L₁ regression. Although the L₁ regression is more resistant to the outliers than the least squares regression, it appears that outliers (leverage) in the predictor variables may affect it. In this paper, our objective is to develop an influence measure for the L₁ regression based on the likelihood displacement function. We illustrate the proposed influence measure with examples.     

Mean estimation with data missing at random for functional covariables

In a missing-data setting, we want to estimate the mean of a scalar outcome, based on a sample in which an explanatory variable is observed for every subject while responses are missing by happenstance for some of them. We consider two kinds of estimates of the mean response when the explanatory variable is functional. One is based on the average of the predicted values and the second one is a functional adaptation of the Horvitz–Thompson estimator. We show that the infinite dimensionality of the problem does not affect the rates of convergence by stating that the estimates are root-n consistent, under missing at random (MAR) assumption. These asymptotic features are completed by simulated experiments illustrating the easiness of implementation and the good behaviour on finite sample sizes of the method. This is the first paper emphasizing that the insensitiveness of averaged estimates, well known in multivariate non-parametric statistics, remains true for an infinite-dimensional covariable. In this sense, this work opens the way for various other results of this kind in functional data analysis.     

A study of Bayesian local robustness with applications in actuarial statistics

Local or infinitesimal Bayesian robustness is a powerful tool to study the sensitivity of posterior magnitudes, which cannot be expressed in a simple manner. For these expressions, the global Bayesian robustness methodology does not seem adequate since the practitioner cannot avoid using inappropriate classes of prior distributions in order to make the model mathematically tractable. This situation occurs, for example, when we compute some types of premiums in actuarial statistics in order to fix the premium to be charged to an insurance policy. In this paper, analytical and simple expressions that allow us to study the sensitivity of premiums, which are usually used in automobile insurance are provided by using the local Bayesian robustness methodology. Some examples are examined by using real automobile claim insurance data.     

The Impact of Patronymic Attractiveness on Employability

We link patronymics (first and last names presented together) to success in the job market by investigating the influence of name attractiveness on employability. Using data from a recruitment agency, we tested (binomial regression) for effects associated with age, gender, and name attractiveness on job interview outcomes. We found that candidates with more attractive patronymics were more likely to be retained by employers.