The effects of cohort size on European earnings

I use the cross-country and time variation in the demographic structure of 11 European countries to study how changes in cohort size affect real earnings in Europe. I find that cohort size has a negative and statistically significant effect on earnings, and that this effect is larger for the older age group—aged between 35 and 54—than for the younger group—aged 20 to 34. I also find that earnings are more sensible to changes in cohort size in Southern Europe, which points to a lower degree of substitutability between individuals with the same education but different age. I argue that the uncovered lower substitutability in the Olive Belt of Europe is in line with the higher employment protection that its workers enjoy, at least compared to the workers located in Northern Europe.     

Regulatory intervention and the effect of changes in corporate governance on firm decisions and market reactions

This paper investigates whether Italian companies that cross-list in the United States between 1993 and 2005 show (1) a change in their internal policies as anticipated by the bonding hypothesis, (2) an increase in market value, or (3) an increase in the access to capital funds. We use the unique environment created by the 1998 Draghi reform which significantly improved the protection of Italian listed companies’ minority shareholders and we further examine the impact of legislated changes in corporate governance in Italy on the decision of Italian companies to cross-list in the United States. Our results indicate that following the Draghi reform (1) firms that cross-list in the United States modify their dividend and cash policies as anticipated by the bonding hypothesis. Contrary to prior research, (2) we do not find evidence that cross-listing serves to enhance shareholder value or (3) is used as a vehicle to more easily access capital funds either before or after the domestic corporate governance is improved. The results of this study provide evidence that country level legislative innovations intended to enhance a weak corporate governance system can be a valid and effective substitute to the bonding mechanism by providing an alternative signal of a firm’s quality.     

On beta type-1 distributed random points in an n-ball

This article considers the problem of finding the exact density of the r-content of the simplicial convex hull of r+1 independent points in Rⁿ ” Consider r+1 independent and identically distributed points in a unit n–ball such that p of them are in the interior and r+l?p of them are on the surface of the unit n-ball., Consider the case when each point is type-1 beta distributed,, These points determine almost surely via their convex hull a unique r-simplex in Rⁿ Ihe problem of getting the exact density of the r-content of this random r-simplex is transformed into a problem in multivariate statistical analysis connected with the distribution theory of test statistics., Thus various representations for the exact density are given in this article.     

Enhancing parent-child interaction during foster care visits: experimental assessment of an intervention

Mothers of young children recently placed in foster care participated in an intervention to enhance parent-child interaction during visits. The mothers all reported substantial loss and trauma histories. Immediately prior to the visits, the mothers were coached on strategies for separating from their children at the visit's end. The mothers displayed more behavioral strategies for supporting their children when the visit was over, but were less engaged with their children during the leave-taking sequence and displayed fewer ways of maintaining the child's involvement in mother-child interaction during leave-taking than those in a comparison group. This article discusses consideration of parents' trauma history in designing interventions to enhance parent-child interaction.     

KNOWING THE RIGHT PERSON IN THE RIGHT PLACE: POLITICAL CONNECTIONS AND RESISTANCE TO CHANGE

We use a political economy model of Schumpeterian growth with entry to investigate how an incumbent politician can strategically use the level of red tape to acquire incumbency advantage. By setting sufficiently high red tape, the politician induces the incumbent firm in the intermediate sector to invest in political connections, which are valued also by voters, who recognize that bureaucratic costs can be reduced by connected firms. Within this framework, we study the Markov perfect equilibria of an infinitely repeated game among politicians, firms, and voters, and show that all equilibria are characterized by investments in political connections and the re‐election of the incumbent politician. Political connections may prevent entry of advanced competitors and cause the economy to lag behind the technological frontier. Our model provides a possible explanation for the persistence of inefficient democracies and political barriers to technology development, where these reflect shared rather than conflicting interests.     

Multilevel dimensionality-reduction methods

When data sets are multilevel (group nesting or repeated measures), different sources of variations must be identified. In the framework of unsupervised analyses, multilevel simultaneous component analysis (MSCA) has recently been proposed as the most satisfactory option for analyzing multilevel data. MSCA estimates submodels for the different levels in data and thereby separates the “within”-subject and “between”-subject variations in the variables. Following the principles of MSCA and the strategy of decomposing the available data matrix into orthogonal blocks, and taking into account the between- and the within data structures, we generalize, in a multilevel perspective, multivariate models in which a matrix of response variables can be used to guide the projections (formed by responses predicted by explanatory variables or by a limited number of their combinations/composites) into choices of meaningful directions. To this end, the current paper proposes the multilevel version of the multivariate regression model and dimensionality-reduction methods (used to predict responses with fewer linear composites of explanatory variables). The principle findings of the study are that the minimization of the loss functions related to multivariate regression, principal-component regression, reduced-rank regression, and canonical-correlation regression are equivalent to the separate minimization of the sum of two separate loss functions corresponding to the between and within structures, under some constraints. The paper closes with a case study of an application focusing on the relationships between mental health severity and the intensity of care in the Lombardy region mental health system.     

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and matrix completion with a LASSO-like nuclear norm penalty, to predict missing entries of a partially unknown I/O matrix. Through analyses based on both real-world and synthetic I/O matrices, we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input–Output Database (WIOD) tables—which are an example of industry-by-industry I/O tables—is provided. Strong similarities in structure between WIOD and other I/O tables are also found, which make the proposed approach easily generalizable to them.

     

Exact algorithms for scheduling programs with shared tasks

We study a scheduling problem where the jobs we have to perform are composed of one or more tasks. If two jobs sharing a non-empty subset of tasks are scheduled on the same machine, then these shared tasks have to be performed only once. This kind of problem is known in the literature under the names of VM-PACKING or PAGINATION. Our objective is to schedule a set of these objects on two parallel identical machines, with the aim of minimizing the makespan. This problem is NP-complete as an extension of the PARTITION problem. In this paper we present three exact algorithms with worst-case time-complexity guarantees, by exploring different branching techniques. Our first algorithm focuses on the relation between jobs sharing one or more symbols in common, whereas the two other algorithms branches on the shared symbols.