Social workers' views on community involvement in child protection work in Italy

Involvement of the community is a topic that is gaining increasing importance in the debate on child protection social work. However, the empirical findings that help to understand the factors which enable social workers to involve community actors successfully are still scarce. The article presents the results of an empirical pilot study carried out on a sample of 24 child protection social workers employed in four public agencies in Italy. The results of the research highlight the complexity of the factors that influence the ability of social workers to involve the community in schemes involving children and their families and the importance of constructing a community‐based approach that directly involves local‐level institutions and policy programmes.     

CYCLICAL TAX ENFORCEMENT

We wonder whether tax enforcement varies along the economic cycle and aim at answering that question from a positive perspective by means of survey data for the Spanish case (1994–2015). According to a fiscal capacity argument, tax enforcement might be stronger in times of crisis (counter-cyclical), but if the tax administration prioritizes taxpayers' welfare over public revenue, enforcement might be slacker (procyclical). We find tax enforcement is not immune to the state of the economy. In particular, it presents a prevailing counter-cyclical trend, but in presence of a severe economic crisis it turns out to be procyclical. (JEL D78, H12, H26, H83)     

Subjective Beliefs and ex ante Trade

We study a definition of subjective beliefs applicable to preferences that allow for the perception of ambiguity, and provide a characterization of such beliefs in terms of market behavior. Using this definition, we derive necessary and sufficient conditions for the efficiency of ex ante trade and show that these conditions follow from the fundamental welfare theorems. When aggregate uncertainty is absent, our results show that full insurance is efficient if and only if agents share some common subjective beliefs. Our results hold for a general class of convex preferences, which contains many functional forms used in applications involving ambiguity and ambiguity aversion. We show how our results can be articulated in the language of these functional forms, confirming results existing in the literature, generating new results, and providing a useful tool for applications.     

Weighted likelihood latent class linear regression

Statistical Methods & Applications - A weighted likelihood approach for robust fitting of a finite mixture of linear regression models is proposed. An EM type algorithm and its variant based on...     

Internationalisation and outsourcing of operations and product development in the fashion industry

This paper investigates the choices in terms of internationalisation and outsourcing of operations and product development activities, as well as collaboration practices used within and across organisations, in different segments of the European fashion industry. Based on multiple, in-depth case studies from Italy, Germany and the UK, the paper shows that fashion companies adopt different configurations of operations and product development, i.e. integrated, collaborative and virtual, ranging from local-integrated models to global-full outsourcing of operations and product development activities. For each configuration, different collaboration practices are in use. Product line positioning and quality, firm size, sales volumes and technical complexity of the products are the key drivers determining the configuration choices and the adoption of certain collaboration practices.     

When nature rebels: international migration, climate change, and inequality

We study climate change and international migration in a two-country overlapping generations model with endogenous climate change. Our main findings are that climate change increases migration; small impacts of climate change have significant impacts on the number of migrants; a laxer immigration policy increases long-run migration, aggravates climate change, and increases north–south inequality if climate change impacts are not too small; and a greener technology reduces emissions, long-run migration, and inequality if the migrants’ impact to overall climate change is large. The preference over the policies depends on whether the policy maker targets inequality, wealth, the environment, or the number of migrants.     

Objective Bayes Covariate‐Adjusted Sparse Graphical Model Selection

We present an objective Bayes method for covariance selection in Gaussian multivariate regression models having a sparse regression and covariance structure, the latter being Markov with respect to a directed acyclic graph (DAG). Our procedure can be easily complemented with a variable selection step, so that variable and graphical model selection can be performed jointly. In this way, we offer a solution to a problem of growing importance especially in the area of genetical genomics (eQTL analysis). The input of our method is a single default prior, essentially involving no subjective elicitation, while its output is a closed form marginal likelihood for every covariate‐adjusted DAG model, which is constant over each class of Markov equivalent DAGs; our procedure thus naturally encompasses covariate‐adjusted decomposable graphical models. In realistic experimental studies, our method is highly competitive, especially when the number of responses is large relative to the sample size.     

Weighted likelihood based inference for P(X < Y)

This contribution deals with the statistical problem of evaluating the stress–strength reliability parameter R = P(X < Y), when both stress and strength data are prone to contamination. Standard likelihood inference can be badly affected by mild data inadequacies, that often occur in the form of several outliers. Then, robust tools are recommended. Here, inference relies on the weighted likelihood methodology. This approach has the advantage to lead to robust estimators, tests, and confidence intervals that share the main asymptotic properties of their classical counterparts. The accuracy of the proposed methodology is illustrated both by numerical studies and real-data applications.