Studying the relationship between anxiety and school achievement: evidence from PISA data

Statistical Methods & Applications - Using the Programme for International Student Assessment (PISA) 2015 data for Italy, this paper offers a complete overview of the relationship between test...     

Managerial Delegation under Alternative Unionization Structures

This paper studies the effects of managerial delegation in a duopoly game under alternative unionization structures. Introducing managerial delegation in a framework with centralized unionization leads to incentives for sales, lower profits and higher consumer surplus as well as overall welfare. In contrast, delegating output decisions to managers in the presence of decentralized unionization produces opposite results unless unions are strongly employment‐oriented. Moreover, managerial delegation makes unionization structure neutral in relation to consumer surplus and overall efficiency. Finally, the timing of moves in the three‐stage game proves to be important for obtaining the above qualitative results under decentralized unionization.     

Asymptotic Properties and Variance Estimators of the M-quantile Regression Coefficients Estimators

M-quantile regression is defined as a “quantile-like” generalization of robust regression based on influence functions. This article outlines asymptotic properties for the M-quantile regression coefficients estimators in the case of i.i.d. data with stochastic regressors, paying attention to adjustments due to the first-step scale estimation. A variance estimator of the M-quantile regression coefficients based on the sandwich approach is proposed. Empirical results show that this estimator appears to perform well under different simulated scenarios. The sandwich estimator is applied in the small area estimation context for the estimation of the mean squared error of an estimator for the small area means. The results obtained improve previous findings, especially in the case of heteroskedastic data.     

Multiracial Identities and Employee Absenteeism: Testing Contact and Depletion Hypotheses

Employee absenteeism costs the U.S. economy billions of dollars each year. Recent research finds that workplace characteristics are important predictors, yet variation remains by racial identity. Less is known about the reasons multiracial workers miss work. With data from the 2014 General Social Survey, we test a contact hypothesis and a depletion hypothesis. The findings support the depletion hypothesis. Multiracial workers are likely feeling cognitively taxed from comparatively more interracial interaction in the workplace, resulting in their higher rate of employee absenteeism. Given that the number of multiracial individuals living and working in the United States is expected to grow substantially over the next decade, understanding the factors that explain their work behavior may be beneficial to all social groups.     

Women migrants in the global economy: a global overview (and regional perspectives)

ABSTRACT

Huge advances have been made in deepening and expanding our knowledge of gendered migration over the last decades in both theoretical and methodological terms. Empirically it is, however, still the case that North–South migration is at the basis of most theorisations, leaving the characteristics of South–South migration at the margins. In this paper we, therefore, shift the focus to intra- and trans-regional migration in a South–South context in exploring what this means for women migrants. While feminist scholars have highlighted care and the ways in which migration challenges social reproduction as an important issue, mainstream approaches continue to focus predominantly on the ‘productive’ lives of migrant workers. With migration theories still largely drawing on the experience of South–North migration, there continues to be relatively little understanding of South–South migration’s gender dynamics, despite the fact that many of the highly feminised, yet hyper-precarious, migration flows occur intra-regionally.     

Optimization of Cascade‐Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.