Efficiency and Equilibrium with Dynamic Increasing Aggregate Returns due to Demand Complementarities

When do dynamic nonconvexities at the disaggregate level translate into dynamic nonconvexities at the aggregate level? We address this question in a framework where the production of differentiated intermediate inputs is subject to dynamic nonconvexities, and we show that the answer depends on the degree of Hicks-Allen complementarity (substitutability) between differentiated inputs. In our simplest model, a generalization of Judd (1985) and Grossman and Helpman (1991) among many others, there are dynamic nonconvexities at the aggregate level if and only if differentiated inputs are Hicks-Allen complements. We also compare dynamic equilibrium and optimal allocations in the presence of aggregate dynamic nonconvexities due to Hicks-Allen complementarities between differentiated inputs.     

Flexible clustering via hidden hierarchical Dirichlet priors

The Bayesian approach to inference stands out for naturally allowing borrowing information across heterogeneous populations, with different samples possibly sharing the same distribution. A popular Bayesian nonparametric model for clustering probability distributions is the nested Dirichlet process, which however has the drawback of grouping distributions in a single cluster when ties are observed across samples. With the goal of achieving a flexible and effective clustering method for both samples and observations, we investigate a nonparametric prior that arises as the composition of two different discrete random structures and derive a closed-form expression for the induced distribution of the random partition, the fundamental tool regulating the clustering behavior of the model. On the one hand, this allows to gain a deeper insight into the theoretical properties of the model and, on the other hand, it yields an MCMC algorithm for evaluating Bayesian inferences of interest. Moreover, we single out limitations of this algorithm when working with more than two populations and, consequently, devise an alternative more efficient sampling scheme, which as a by-product, allows testing homogeneity between different populations. Finally, we perform a comparison with the nested Dirichlet process and provide illustrative examples of both synthetic and real data.     

Column generation approach for the point-feature cartographic label placement problem

This paper proposes a column generation approach for the Point-Feature Cartographic Label Placement problem (PFCLP). The column generation is based on a Lagrangean relaxation with clusters proposed for problems modeled by conflict graphs. The PFCLP can be represented by a conflict graph where vertices are positions for each label and edges are potential overlaps between labels (vertices). The conflict graph is decomposed into clusters forming a block diagonal matrix with coupling constraints that is known as a restricted master problem (RMP) in a Dantzig-Wolfe decomposition context. The clusters’ sub-problems are similar to the PFCLP and are used to generate new improved columns to RMP. This approach was tested on PFCLP instances presented in the literature providing in reasonable times better solutions than all those known and determining optimal solutions for some difficult large-scale instances.     

Social work with middle‐class Spanish families: The challenge of the work–family conflict

In the current economic crisis, middle‐class families often find themselves immersed in a process of downward social mobility. These are families in which both spouses work, and where many relational conflicts begin in the sphere of work–family reconciliation and the allocation of household responsibilities. This article presents the results of a research study we conducted on middle‐class families in Spain. We focus specifically on the problems associated with work–family reconciliation and gender, and the mitigating role played by social support. Based on our results, we want to call the attention to a prevalent and ‘new’ conflict in family‐based practice social work in Spain: the work–family conflict.     

Controlling for initial endowment and experience in binary choice tasks

Learning literature typically assumes that initial attractions to choose each possible alternative are given exogenously. However, evidence shows that current behaviour depends on past experiences. In this paper, we design an experiment to control for the initial experience in decisions from experience by providing decision makers with an exogenous history (successful vs. unsuccessful) prior to initiating the decision task. Moreover, varying the initial endowment level for fixed histories we investigate the income effect. We are also interested in analysing the duration of both effects (history and income). We find significant treatment effects in the sense that more risk taking behaviour is associated with good histories and with low income levels. According to previous literature, our results confirm the transitory nature of both effects, although the duration of the income effect doubles the duration of the history effect. In the long run, risky choice behaviour converges across different treatments.     

Penalized quantile regression for dynamic panel data

This paper studies penalized quantile regression for dynamic panel data with fixed effects, where the penalty involves l₁ shrinkage of the fixed effects. Using extensive Monte Carlo simulations, we present evidence that the penalty term reduces the dynamic panel bias and increases the efficiency of the estimators. The underlying intuition is that there is no need to use instrumental variables for the lagged dependent variable in the dynamic panel data model without fixed effects. This provides an additional use for the shrinkage models, other than model selection and efficiency gains. We propose a Bayesian information criterion based estimator for the parameter that controls the degree of shrinkage. We illustrate the usefulness of the novel econometric technique by estimating a “target leverage” model that includes a speed of capital structure adjustment. Using the proposed penalized quantile regression model the estimates of the adjustment speeds lie between 3% and 44% across the quantiles, showing strong evidence that there is substantial heterogeneity in the speed of adjustment among firms.     

The Cassa Integrazione Guadagni

ABSTRACT: The purpose of this paper is to provide an analytical survey of the historical and normative evolution of the Italian Cassa Integrazione Guadagni (hereafter Earnings Integration Fund or EIF) through examination of the prevalent economic and juridical models during the 40 years of the EIF's existence. The evolution of the EIF in the periods examined is classified according to five theoretical models, so as to bring out the many different standards accumulated during the administration of the EIF, and the many measures adopted by Public Authorities in response to the various requirements which have arisen over time. The result is an overall reference framework for the EIF's present administration, which is characterised by the presence of both the need for various reforms and alterations, and an equal number of ways of carrying them out; from the development of an ever more direct link between crisis situations and specific EIF requirements, and the evident need to bring the institution within a normative framework correlated to a global labour policy. A verification of the different methods of utilising the EIF is therefore, for the authors, utilizable in defining suitable solutions for modern situations, which require effective EIF models to be worked out in conjunction with an appropriate mix of active labour policies.     

Population Changes in Europe. Demographic and Social Prospects and Problems

Abstract. Over recent years, the European Community has experienced profound demographic changes which, to a large extent, have already determined its demographic future. One of the more significant consequences of demographic and social trends is a marked fragmentation of the family with people giving absolute priority to the individual dimension in their lives and in terms of society as a whole. Legal regulations and administrative practice have not totally–and not everywhere – adapted to the far-reaching changes in the family so as to adequately protect the family and its weaker members in particular: children, the elderly, the disabled, people with mental and social illnesses, the poor. In this field, some measures will be proposed in this paper. The imbalances in demographic-occupational growth in the Euro-Mediterranean area–the area with which the EC is most directly in contact–are and will be of an exceptional amplitude, as has already been shown, to an extent never before experienced in the history of mankind. We must ask ourselves if this very strong differential pressure, which is also of a political and socio-economic nature, will lead to steady and long-lasting migratory flows. Some considerations regarding the future action and intervention of the EC close the paper.     

The Insidious Effects of Sexual Stereotypes in Clinical Practice

The present study investigated the influence of sexual stereotyping on the diagnostic impressions and treatment expectations of gay and straight male patients. Italian male, straight, licensed psychotherapists (N = 152) were presented with clinical vignettes that described a gay (versus straight) male patient reporting either a straight-stereotypical disorder (i.e., rage dyscontrol) or a gay-stereotypical disorder (i.e., sexual compulsivity). Results revealed that treatment efficacy expectations were influenced by the patient’s sexual orientation and the stereotypicality of the disorder. Specifically, psychotherapists anticipated fewer benefits from psychotherapy when gay patients reported a sexual disorder rather than a rage disorder. Furthermore, explicit and implicit levels of sexual prejudice did not play any role in driving such results. Taken together, these findings reveal that sexual stereotyping might exert its subtle effects among clinicians by influencing their clinical evaluations.     

Bayesian non-parametric inference for species variety with a two-parameter Poisson–Dirichlet process prior

Summary.  A Bayesian non-parametric methodology has been recently proposed to deal with the issue of prediction within species sampling problems. Such problems concern the evaluation, conditional on a sample of size n , of the species variety featured by an additional sample of size m . Genomic applications pose the additional challenge of having to deal with large values of both n and m . In such a case the computation of the Bayesian non-parametric estimators is cumbersome and prevents their implementation. We focus on the two-parameter Poisson–Dirichlet model and provide completely explicit expressions for the corresponding estimators, which can be easily evaluated for any sizes of n and m . We also study the asymptotic behaviour of the number of new species conditionally on the observed sample: such an asymptotic result, combined with a suitable simulation scheme, allows us to derive asymptotic highest posterior density intervals for the estimates of interest. Finally, we illustrate the implementation of the proposed methodology by the analysis of five expressed sequence tags data sets.