Nonlinear regression in a trivariate elliptical distribution via a linear combination of order statistics

In this paper, by assuming that (X, Y ₁, Y ₂)^T has a trivariate elliptical distribution, we derive the exact joint distribution of X and a linear combination of order statistics from (Y ₁, Y ₂)^T and show that it is a mixture of unified bivariate skew-elliptical distributions. We then derive the corresponding marginal and conditional distributions for the special case of t kernel. We also present these results for an exchangeable case with t kernel and illustrate the established results with an air-pollution data.     

Is the Criminalisation of Child Harm and Injury in the Interests of the Child?

The impetus to prosecute in cases of child harm and injury has increased considerably over recent years with earlier involvement of the police in child protection and incremental legal reform which aims for more child-centred practices. Research on the implementation of the Memorandum of Good Practice is presented to propose that the prosecution of child abuse is neither achieved nor achievable in the majority of cases and that the assumption on which the criminalisation of child abuse is based should be challenged.     

Research from within: blurring boundaries and developing new methods

For many social scientists the transition from academic research to research within a policy and practice setting is riddled with theoretical difficulties. Research models and the role of the researcher have to be re-examined and re-defined. In discussing the work carried out within one Health Authority particular difficulties will be addressed and the need to develop new models emphasized.     

International Migration Dynamics: The Role of Experience and Social Networks

This paper tests the dynamic implications of cumulative causation and network theory on the self‐sustaining nature of the migration process. A sequential migration model is derived and estimated with a panel of Mexican household heads for the years 1980–89. Consistently with cumulative causation and network theory, the empirical results show that, after controlling for unobserved heterogeneity, previous migration experience and migration‐related variables are the strongest predictors of current migration decisions. This persistence in migration patterns implies that immigration policies inducing small changes in expected costs and benefits of US work fail to prevent entry into, or encourage exit from, the US labor market by experienced migrants. However, large temporary disruptions such as the 1994 Mexican peso devaluation may permanently increase migratory flows by inducing new migrants to enter the US labor market.