Children's involvement in their parents' divorce: implications for practice

The paper reports findings from a research study that explored children's experience of divorce. It shows that children experience parental divorce as a crisis in their lives but that they are able to mobilise internal and external resources to regain a new point of balance. In doing so, children demonstrate the degree to which they are active and competent participants in the process of family dissolution. The implications of the data are then considered in relation to engaging with children involved in divorce and in relation to some of the cultural presumptions that might militate against hearing what they have to say about their experiences. Copyright © 2002 John Wiley & Sons, Ltd.     

The crisis of 'identity' in high modernity

The concept of 'identity' is central to much contemporary sociology, reflecting a crisis that manifests itself in two ways. Firstly, there is a view that identity is both vital and problematic in this period of high modernity. Secondly, while this awareness is reflected in sociology, its accounts of identity are inconsistent, under-theorized and incapable of bearing the analytical load required. As a result, there is an inherent contradiction between a valuing of identity as so fundamental as to be crucial to personal well-being, and a theorization of 'identity' that sees it as something constructed, fluid, multiple, impermanent and fragmentary. The contemporary crisis of identity thus expresses itself as both a crisis of society, and a crisis of theory. This paper explores the diverse ways in which 'identity' is deployed before turning to case-studies of its use by Anthony Giddens and Manuel Castells. This strategy demonstrates the widespread and diverse concern with identity before exploring how problematic it has become, even in the work of two of the world's leading sociologists.     

Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval

This paper investigates nonparametric estimation of density on [0, 1]. The kernel estimator of density on [0, 1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study, the Bayesian bandwidth estimator performed better than others, and kernel estimators were sensitive to the choice of the kernel and the shapes of the population densities on [0, 1]. The simulation and empirical results demonstrate that the methods proposed in this paper can improve the way the probability densities on [0, 1] are presently estimated.     

Asymptotic tests and monte carlo studies associated with the multiplicative interaction model

Several authors have proposed approximations to percentage points required for testing certain hypotheses associated with the multiplicative interaction model. Alternative approximations based on the asymptotic joint distribution of the characteristic roots of a noncentral Wishart matrix are proposed in this paper. The type I error rates of the resulting tests and the existing procedures are then compared using Monte Carlo methods.     

SEMIPARAMETRIC ESTIMATION OF THE ERROR DISTRIBUTION IN MULTIVARIATE REGRESSION USING COPULAS

A semiparametric method is developed to estimate the dependence parameter and the joint distribution of the error term in the multivariate linear regression model. The nonparametric part of the method treats the marginal distributions of the error term as unknown, and estimates them using suitable empirical distribution functions. Then the dependence parameter is estimated by either maximizing a pseudolikelihood or solving an estimating equation. It is shown that this estimator is asymptotically normal, and a consistent estimator of its large sample variance is given. A simulation study shows that the proposed semiparametric method is better than the parametric ones available when the error distribution is unknown, which is almost always the case in practice. It turns out that there is no loss of asymptotic efficiency as a result of the estimation of regression parameters. An empirical example on portfolio management is used to illustrate the method.     

On the symmetry of m-estimators computed by the huber-dutter algorithm

An M-estimator of the Linear regression parameter computed by the Huber and Dutter (1974) algorithm is summetrically distributed about the true value, under reasonably mild conditions.     

Government-NGO collaboration and sustainability of orphans and vulnerable children projects in southern Africa

Given current donor attention to orphans and children made vulnerable by HIV/AIDS, and the need for a new framework that recognizes the complementary roles of nations and non-governmental organizations (NGOs), this analysis reviews NGO-operated community-based orphans and vulnerable children (OVC) projects in Botswana, Lesotho, Namibia, South Africa, and Swaziland. There has been a lack of attention within the field of evaluation to inter-organizational relationships, specifically those with government agencies, as a factor in sustainability. We analyzed evaluations of nine OVC projects funded by the Bristol-Myers Squibb Foundation for the influence of government-NGO collaboration on project sustainability. For eight of the nine projects, evaluations provided evidence of the importance of the government partnership for sustainability. Government collaboration was important in projects designed to help families access government grants, initiate community-based solutions, and advocate for OVC rights through legislation. Government partnerships were also critical to the sustainability of two projects involved in placing children in foster care, but these showed signs of tension with government partners. In addition to the more common factors associated with sustainability, such as organizational characteristics, donors and NGOs should concentrate on developing strong partnerships with local and national government agencies for the sustainability of their projects.     

Costly and discrete communication: an experimental investigation

Language is an imperfect and coarse means of communicating information about a complex and nuanced world. We report on an experiment designed to capture this feature of communication. The messages available to the sender imperfectly describe the state of the world; however, the sender can improve communication, at a cost, by increasing the complexity or elaborateness of the message. Here the sender learns the state of the world, then sends a message to the receiver. The receiver observes the message and provides a best guess about the state. The incentives of the players are aligned in the sense that both sender and receiver are paid an amount which is increasing in the accuracy of the receiver’s guess. We find that the size of the language endogenously emerges as a function of the costs of communication. Specifically, we find that higher communication costs are associated with a smaller language. Although the equilibrium predictions do not perform well, this divergence occurs in a manner which is consistent with the experimental communication literature: overcommunication. We find that the sender’s payoffs, relative to equilibrium payoffs, are decreasing in the cost of communication. We also find that the receiver’s payoffs, relative to equilibrium payoffs, are increasing in the cost of communication. Finally, we find imperfections in coordination on the basis of the experimental labels.     

A note on some conditions for optimality of certain ridge estimators

Consider the linear regression model, y = Xβ + ε in the usual notation with X'X being in the correlation form. Galpin(1980) claimed that the ridge estimators of Hoerl, Kennard and Baldwin(1975) and Lawless and Wang(1976) give guaranteed lower mean squared error than the least squares estimator when X'X has at least two very small eigen values. We show that the arguments of Galpin(1980) leading to the above claim are incorrect, and hence the claim itself is unsubstantited. A Monte Carlo study shows that Galpin's claim is not correct in general.     

Direct methods for generating extreme characteristic roots of certain random matrices

Computer generation of extreme characteristic roots of random matrices is considered. The usual approach in Monte-Carlo applications is to randomly generate the matrix and then compute desired characteristic roots. There are, however, theoretical results about the distribution of individual characteristic roots which might be used as a basis for computing algorithms. This alternative approach is considered for the Wishart and Beta matrices.