Family Therapy: Inner,Outer and the Issue of Pathology

This paper sets out to examine the relationship between ‘the inner’, ‘the outer’, and ‘the issue of pathology’ in the family therapy field. It begins with the observations that ‘pathology’ has become a rarely mentioned issue in family therapy, and ‘what is wrong’ is increasingly located in ‘the outer’: the family ‘game’, ‘linguistic activity’ or ‘the cultural discourse’. At the same time, family therapy often hosts forums in which presenters are ‘attacked’ for not seeming to hold the ‘correct view’. The paper considers these phenomena in tandem, looks at the matter of ‘method’, and applies James Hillman's critique of psychoanalysis to family therapy. The suggestion is that family therapy has been blinded by its own metaphor of ‘seeing’, symbolised and literalised in the one way screen. Alternative metaphors privileging intuition, feeling and aesthetics are put forward, before discussion points are raised, and before this paper on therapy concludes poetically, or this paper concludes that therapy may be poetry.     

County child poverty rates in the US: a spatial regression approach

We apply methods of exploratory spatial data analysis (ESDA) and spatial regression analysis to examine intercounty variation in child poverty rates in the US. Such spatial analyses are important because regression models that exclude explicit specification of spatial effects, when they exist, can lead to inaccurate inferences about predictor variables. Using county-level data for 1990, we re-examine earlier published results [Friedman and Lichter (Popul Res Policy Rev 17:91–109, 1998)]. We find that formal tests for spatial autocorrelation among county child poverty rates confirm and quantify what is obvious from simple maps of such rates: the risk of a child living in poverty is not (spatially) a randomly distributed risk at the county level. Explicit acknowledgment of spatial effects in an explanatory regression model improves considerably the earlier published regression results, which did not take account of spatial autocorrelation. These improvements include: (1) the shifting of “wrong sign” parameters in the direction originally hypothesized by the authors, (2) a reduction of residual squared error, and (3) the elimination of any substantive residual spatial autocorrelation. While not without its own problems and some remaining ambiguities, this reanalysis is a convincing demonstration of the need for demographers and other social scientists to examine spatial autocorrelation in their data and to explicitly correct for spatial externalities, if indicated, when performing multiple regression analyses on variables that are spatially referenced. Substantively, the analysis improves the estimates of the joint effects of place-influences and family-influences on child poverty.

Time Insensitivity for Protective Investments

Investments in protective measures involve an initial immediate cost in exchange for a stream of potential benefits accruing over time in the form of reduced expected losses. This paper describes two studies in which individuals were asked both to make choices and indicate the maximum amount they were willing to pay (WTP) for such protective measures. By varying the number of years that the measures provided protection, we observed four different decision strategies that individuals use to determine their maximum WTP. The findings from these experiments strongly suggest that most individuals do not take into account the added benefits of having a protective measure in place over a longer period of time when determining the likelihood of purchasing protection or the maximum price they are willing to pay. The behavior of a relatively small proportion of the subjects was consistent with a discounted utility model. Most subjects were either myopic in their behavior or did not change their maximum WTP as the time horizon changed. Despite the fact that most subjects were insensitive to time changes, they were generally willing to purchase the protective measures. Implications of these results for investment in risk mitigation measures are briefly explored.     

A Bayesian-loss function-based method in assessing loss caused by ship-source oil spills in the arctic area

It is difficult to assess the risk of ship-source oil spills in Arctic waters for insurance purposes due to many unknowns and the lack of reliable data. However, maritime activities in the Arctic area continue to grow, indicating the urgent needs for the development of innovative methods to estimate loss from potential ship-source oil spills in the Arctic area. To fill this gap, we develop a hybrid Bayesian-loss function-based method to assess ship-source oil spill-related loss and implement an illustrative test on Baffin Island, Nunavut in Canada. The results confirm that our method can accurately assess loss and, subsequently, develop reliable insurance premiums for shipping activities in the Arctic area. This enables governmental and nongovernmental organizations alike to use the method as a reliable loss estimation mechanism for ship-source oil spills. Also, it is a valuable tool in designing measures for safer and more resilient Arctic shipping.     

Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators

In an effort to improve the small sample properties of generalized method of moments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilting estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find that GEL has no asymptotic bias due to correlation of the moment functions with their Jacobian, eliminating an important source of bias for GMM in models with endogeneity. We also find that EL has no asymptotic bias from estimating the optimal weight matrix, eliminating a further important source of bias for GMM in panel data models. We give bias corrected GMM and GEL estimators. We also show that bias corrected EL inherits the higher order property of maximum likelihood, that it is higher order asymptotically efficient relative to the other bias corrected estimators.     

Efficient Semiparametric Estimation via Moment Restrictions

Conditional moment restrictions can be combined through GMM estimation to construct more efficient semiparametric estimators. This paper is about attainable efficiency for such estimators. We define and use a moment tangent set, the directions of departure from the truth allowed by the moments, to characterize when the semiparametric efficiency bound can be attained. The efficiency condition is that the moment tangent set equals the model tangent set. We apply these results to transformed, censored, and truncated regression models, e.g., finding that the conditional moment restrictions from Powell's (1986) censored regression quantile estimators can be combined to approximate efficiency when the disturbance is independent of regressors.     

Implementing the right project structure to achieve coopetitive innovation projects

This research focuses on the project structure used by coopetitors to achieve common innovation projects. Scholars have recently identified an original but complex project structure that they call the Coopetitive Project Team (CPT). However, other project structures can also be implemented by coopetitors to achieve innovation. Therefore, we address the following question: for which types of innovation projects is CPT appropriate? We argue that coopetitors need to use CPT for high-risk and high-cost projects when the aim is to develop radical innovation. CPT allows coopetitors not only to develop innovation capabilities through close resource and knowledge sharing but also to manage the risk of opportunism. Conversely, coopetitors should use another project structure, Separated Project Teams (SPTs), for low-cost and low-risk projects when the aim is to develop incremental innovation. The SPT design allows coopetitors both to achieve the goal of the project and to minimize the risk of opportunism. To confirm our assumptions, we studied the project portfolios of Airbus and Thales, two firms in the space satellite industry. Our findings confirm that coopetitors should implement CPTs to handle innovation projects that are costly, risky and highly innovative. CPTs permit the sharing of knowledge and the management of high opportunism risk, both of which are necessary to achieve radical innovation. Conversely, coopetitors rely on SPTs for low-cost projects that require a low degree of knowledge sharing, thus avoiding the risk of opportunism in achieving their incremental innovation objectives.     

Exploring drivers of demand for child protection services in an English local authority

This paper reports on an empirical study of child protection services in a local authority where rates of investigations and interventions rose to unprecedented levels during the course of a single year. The aim of the research was to explore explanations for this rise in demand among the providers of children's social care in the area. Using an interpretative qualitative design, a series of focus groups and interviews were carried out with practitioners and managers (n = 25) from statutory services and Early Help. The findings identified a combination of long‐term and short‐term drivers of demand. Long‐term factors emphasized the impact of rising levels of deprivation combined with cuts to community‐based services for children and young people. Short‐term factors ranged from a more proactive approach to child neglect to more effective multi‐agency partnerships and joint decision making. The interaction between these factors was found to be accentuating an underlying shift to “late intervention” across the sector. The findings are contextualized in relation to contemporary debates about the crisis of demand for children's social care and the complex relationship between prevention and protection.