Analyse biographique du travail féminin

Cet article montre comment l'application d'une méthode d'analyse biographique d'interaction à un domaine où l'interaction paraît évidente — activité féminine et fécondite — ouvre des perspectives nouvelles. En effet, les limites qui apparaissent lors de cette analyse conduisent les auteurs à conclure que ce n'est pas en raffinant les méthodes mais plutôt la collecte que l'on parviendra à progresser dans ce domaine. Le problème des interactions de l'activité et de la fécondité semble mal posé avant même le recours à la méthode. Cela justifie la nécessité de saisir le travail féminin comme concept unifié ne dissociant pas la sphère domestique et la sphère rémunérée. Cela conduit les auteurs à dégager quelques principes de collecte mieux adaptés aux préoccupations récentes dans ce domaine: des données biographiques sur le travail féminin. L'interaction collectée à sa source se prêterait alors à une analyse biographique plus révélatrice que celle qui confronte deux processus sans en évaluer les modalités changeantes.This article demonstrates how life event history analysis applied to the interaction between fertility and female economic activity can lead to new perspectives in the analysis of this complicated relationship. The authors identify limits to the analysis of the interaction given the anticipatory nature of behaviour. They conclude that progress in this field requires not the refinement of methods but rather a fundamental change in the approach to the data collected. If fertility and employment are considered separately, a problem is created even before the methods of analysis are applied. They recommend a conception of women's work as a whole, a conception that does not dissociate domestic and paid work. The authors go on to identify ways of improving the relevance of data collection to contemporary issues in the life history analysis of women's work. They argue that data on the interaction, collected at its source, would yield a more revealing life history than that which sees domestic work and paid work as separate spheres, and fails to take account of changes in their relationship.     

Expected sample moments of concomitants of selected order statistics

In this paper, the task of determining expected values of sample moments, where the sample members have been selected based on noisy information, is considered. This task is a recurring problem in the theory of evolution strategies. Exact expressions for expected values of sums of products of concomitants of selected order statistics are derived. Then, using Edgeworth and Cornish-Fisher approximations, explicit results that depend on coefficients that can be determined numerically are obtained. While the results are exact only for normal populations, it is shown experimentally that including skewness and kurtosis in the calculations can yield greatly improved results for other distributions.     

International and internal migration decision making: a value-expectancy based analytical framework of intentions to move from a rural Philippine province

"The study compares determinants of internal and international migration intentions, drawing upon interview data from a sample of adults in Ilocos Norte, a largely rural province in the Philippines. A regression model is applied to test the relative determinants of intentions to migrate to Manila and to Hawaii. The study is based on a value-expectancy model of migration decision making. The results document the importance of subjective expectations related to the attainment of different values and goals in Manila and Hawaii."     

A Macro-Economic Framework for Evaluation of Cyber Security Risks Related to Protection of Intellectual Property

The article is based on the premise that, from a macro-economic viewpoint, cyber attacks with long-lasting effects are the most economically significant, and as a result require more attention than attacks with short-lasting effects that have historically been more represented in literature. In particular, the article deals with evaluation of cyber security risks related to one type of attack with long-lasting effects, namely, theft of intellectual property (IP) by foreign perpetrators. An International Consequence Analysis Framework is presented to determine (1) the potential macro-economic consequences of cyber attacks that result in stolen IP from companies in the United States, and (2) the likely sources of such attacks. The framework presented focuses on IP theft that enables foreign companies to make economic gains that would have otherwise benefited the U.S. economy. Initial results are presented.     

A Joint Modeling Approach for Longitudinal Outcomes and Non-ignorable Dropout under Population Heterogeneity in Mental Health Studies

The paper proposes a joint mixture model to model non-ignorable drop-out in longitudinal cohort studies of mental health outcomes. The model combines a (non)-linear growth curve model for the time-dependent outcomes and a discrete-time survival model for the drop-out with random effects shared by the two sub-models. The mixture part of the model takes into account population heterogeneity by accounting for latent subgroups of the shared effects that may lead to different patterns for the growth and the drop-out tendency. A simulation study shows that the joint mixture model provides greater precision in estimating the average slope and covariance matrix of random effects. We illustrate its benefits with data from a longitudinal cohort study that characterizes depression symptoms over time yet is hindered by non-trivial participant drop-out.KEYWORDS: Latent growth curve, MNAR drop-out, survival analysis, finite mixture model, mental health     

Regression modelling of interval censored data based on the adaptive ridge procedure

A new method for the analysis of time to ankylosis complication on a dataset of replanted teeth is proposed. In this context of left-censored, interval-censored and right-censored data, a Cox model with piecewise constant baseline hazard is introduced. Estimation is carried out with the expectation maximisation (EM) algorithm by treating the true event times as unobserved variables. This estimation procedure is shown to produce a block diagonal Hessian matrix of the baseline parameters. Taking advantage of this interesting feature in the EM algorithm, a L0 penalised likelihood method is implemented in order to automatically determine the number and locations of the cuts of the baseline hazard. This procedure allows to detect specific areas of time where patients are at greater risks for ankylosis. The method can be directly extended to the inclusion of exact observations and to a cure fraction. Theoretical results are obtained which allow to derive statistical inference of the model parameters from asymptotic likelihood theory. Through simulation studies, the penalisation technique is shown to provide a good fit of the baseline hazard and precise estimations of the resulting regression parameters.