Parental unemployment and children's educational attainment: How big is the role of aspirations?

Children exposed to parental unemployment have been found to lag behind in school, but research has struggled to pin down the underlying explanation. One hypothesis is that parental unemployment may dampen children's aspirations to do well and go far in school. Yet, few studies on parental unemployment have relied on actual measures of children's aspirations or devised a formal analysis of this mechanism. Using the UK Household Longitudinal Study (Waves 1–12, N = 1067), I investigate the role of educational aspirations in children's General Certificate of Secondary Education (GCSE) attainment. I compare adolescents exposed to parental unemployment before or only after the typical age at which GCSE exams are taken. In adjusted models, children exposed to parental unemployment before their GCSEs are around 6 percentage points less likely to attain any GCSE qualification by age 17. On average, children have high educational aspirations, although intentions to enrol in college or university are relatively lower among children exposed to an early spell of parental unemployment. Nevertheless, a hypothetical intervention setting these aspirations to the same level for all children only accounts for a modest portion of the educational penalty tied to an early spell of parental unemployment. Several sensitivity and robustness tests support this conclusion. This note seeks to stimulate more research on the mechanisms underpinning the intergenerational effects of unemployment. Findings cast doubts on the idea that children's aspirations, the target of broader policy discourse and interventions, are a crucial part of the equation.     

Stigma toward internalizing and externalizing disorders: How do adolescents perceive their peers? A network analysis approach

This study's first aim was to explore whether stigma's facets differ between internalizing and externalizing disorders in adolescence. The second aim was to compare the relationships among stigma's facets toward these disorders. Two vignettes depicting a peer with Major Depressive Disorder (MDD) or Attention-Deficit Hyperactivity Disorder (ADHD) were used with 616 adolescents in Italy. A Repeated measure MANOVA showed biogenetic causes, social distancing, and discomfort were more attributed to depression, while dangerousness to ADHD. Furthermore, a Psychometric Network Analysis showed no differences between these disorders in the relations among stigma's components. However, dangerousness seemed to be among the nodes with the highest levels of “strength,” confirming previous literature that shows that dangerousness plays a major role in stigma.     

Effects of air pollution and weather on the initial COVID-19 outbreaks in United States,Italy, Spain,and China: A comparative study

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO₂). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.     

Development and International Migration: The Effect of Income on Regular and Irregular Migration Intentions to Europe

In recent years, the development-migration debate has re-gained popularity in policy circles, especially after the so-called “migration crisis” in Europe and the following approval of the European Agenda on Migration. Much of the empirical literature supports the idea that the relationship between international migration and incomes at origin follows hump-shaped patterns. A growing number of studies find that increasing economic development and financial resources in developing countries would allow a greater number of individuals to afford the costs of emigrating. However, this evidence heavily relies on measures of regular migration only. Using nationally representative data from 12 Middle East and North Africa countries, this study adopts a multinomial logit model to frame migration intentions, distinguishing between regular and irregular routes. The main finding is that the level of household income is associated negatively with the demand for irregular migration to Europe. Predictive margins clearly show that higher household incomes increase the probability of planning only regular migration, while decreasing that of considering also irregular migration. The policy implications are not negligible: improving economic conditions in countries of origin may be effective at deflecting migrants from irregular to regular routes.     

The evolution of employee engagement: Towards a social and contextual construct for balancing individual performance and wellbeing dynamically

Research demonstrates that high Employee Engagement (EE) sustains job satisfaction and performance among staff. This literature review analyses the evolution of EE, highlighting the theoretical frameworks used to explain the concept, the measurement scales adopted by researchers and the principal antecedents and outcomes relating to EE that have been progressively considered along the way. Three main findings emerge from the analysis. First, we highlight the social and relational nature of EE, providing a more sociological interpretation of this phenomenon. Second, we underscore the fact that EE is dynamic, and when combined with modern digital technologies, it can be studied through innovative approaches. Third, we discuss how EE could be a fundamental ingredient in shifting towards a human centred approach through which balancing individuals’ wellbeing and performance. We discuss the implications of these findings, highlighting the necessity to rethink EE in relation to the new normal ushered in by Covid-19, and the increasing role of hybrid working.     

Transnational social protection infrastructures: African migrants in Mexico

In the past years, increasingly restrictive migration policies have pushed many migrants to seek new and more risky migration routes. Many studies have investigated aspects of social protection for migrants from the Global South in industrialized countries of the Global North, with powerful welfare states. Yet, such focus has failed to understand the complexities during the migration process, where people often spend uncertain periods of time in transit countries and the state is frequently absent. In these contexts, social protection is predominantly provided by the third sector (TS) and informal networks both nationally and transnationally. Based on ethnographic fieldwork conducted with African migrants and TS organizations in Mexico, this paper explores the different and often semi-formal relationships between the TS, the state, and the migrants that result in complex transnational social protection infrastructures to cover the migrants' basic social protection needs.     

On the Failure of the Bootstrap for Matching Estimators

Matching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap is, in general, not valid for matching estimators, even in the simple case with a single continuous covariate where the estimator is root‐N consistent and asymptotically normally distributed with zero asymptotic bias. Valid inferential methods in this setting are the analytic asymptotic variance estimator of Abadie and Imbens (2006a) as well as certain modifications of the standard bootstrap, like the subsampling methods in Politis and Romano (1994).