News & Events

ABSTRACT It is well established that the departure from the parental home of young Italian adults occurs at a particularly late age, especially when compared to northern European countries. Moreover, in Italy a large gap exists between young people’s aspirations and their subsequent realization. This study aims to explore the factors favouring or hampering the successful achievement of residential independence from the family of origin. Using data from the longitudinal surveys “Family and Social Subjects”, carried out by the Italian National Institute of Statistics (Istat) in 2003 and 2007, we analyze leaving home as a mid-term decision-making process. Our results provide empirical evidence that the inability to find a stable job reduces young adults’ autonomy. Net of employment status, attitudes and social norms also have an important effect on the intention to leave the family home. The socio-cultural status of the family of origin specifically favours the successful realization of the behaviour. Notably, this effect is gender-specific, with women more influenced by the mother and men by the father.

We empirically assess the effect of historical slavery on the African American family structure. Our hypothesis is that female single headship among blacks is more likely to emerge in association not with slavery per se, but with slavery in sugar plantations, since the extreme demographic and social conditions prevailing in the latter have persistently affected family formation patterns. By exploiting the exogenous variation in sugar suitability, we establish the following. In 1850, sugar suitability is indeed associated with extreme demographic outcomes within the slave population. Over the period 1880-1940, higher sugar suitability determines a higher likelihood of single female headship. The effect is driven by blacks and starts fading in 1920 in connection with the Great Migration. OLS estimates are complemented with a matching estimator and a fuzzy RDD. Over a linked sample between 1880 and 1930, we identify an even stronger intergenerational legacy of sugar planting for migrants. By 1990, the effect of sugar is replaced by that of slavery and the black share, consistent with the spread of its influence through migration and intermarriage, and black incarceration emerges as a powerful mediator. By matching slaves’ ethnic origins with ethnographic data we rule out any influence of African cultural traditions.

There is a growing concern that the widespread use of computers, mobile phones and other digital devices before bedtime disrupts our sleep with detrimental effects on our health and cognitive performance. High-speed Internet promotes the use of electronic devices, video games and Internet addiction (e.g., online games and cyberloafing). Exposure to artificial light from tablets and PCs can alterate individuals’ sleep patterns. However, there is little empirical evidence on the causal relationship between technology use near bedtime and sleep. This paper studies the causal effects of access to high-speed Internet on sleep. We first show that playing video games, using PC or smartphones, watching TV or movies are correlated with shorter sleep duration. Second, we exploit historical differences in pre-existing telephone infrastructure that affected the deployment of high-speed Internet across Germany (see Falck et al., 2014) to identify a source of plausibly exogenous variation in access to Broadband. Using this instrumental variable strategy, we find that DSL access reduces sleep duration and sleep satisfaction.

Discussion on the disproportionate impact of COVID-19 on African Americans has been at center stage since the outbreak of the epidemic in the United States. To present day, however, lack of race-disaggregated individual data has prevented a rigorous assessment of the extent of this phenomenon and the reasons why blacks may be particularly vulnerable to the disease. Using individual and georeferenced death data collected daily by the Cook County Medical Examiner, we provide first evidence that race does affect COVID-19 outcomes. The data confirm that in Cook County blacks are overrepresented in terms of COVID-19 related deaths since—as of June 16, 2020—they constitute 35 percent of the dead, so that they are dying at a rate 1.3 times higher than their population share. Furthermore, by combining the spatial distribution of mortality with the 1930s redlining maps for the Chicago area, we obtain a block group level panel dataset of weekly deaths over the period January 1, 2020-June 16, 2020, over which we establish that, after the outbreak of the epidemic, historically lower-graded neighborhoods display a sharper increase in mortality, driven by blacks, while no pretreatment differences are detected. Thus, we uncover a persistence influence of the racial segregation induced by the discriminatory lending practices of the 1930s, by way of a diminished resilience of the black population to the shock represented by the COVID-19 outbreak. A heterogeneity analysis reveals that the main channels of transmission are socioeconomic status and household composition, whose influence is magnified in combination with a higher black share.

In this article we compare two techniques that are widely used in the analysis of life course trajectories, latent class analysis (LCA) and sequence analysis (SA). In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of the classification obtained via the two techniques using an actual dataset on the life course trajectories of young adults. Then, we adopt a simulation approach to measure the ability of these two methods to correctly classify groups of life course trajectories when specific forms of "random" variability are introduced within pre-specified classes in an artificial dataset. In order to do so, we introduce simulation operators that have a life course and/or observational meaning. Our results contribute on the one hand to outline the usefulness and robustness of findings based on the classification of life course trajectories through LCA and SA, on the other hand to illuminate the potential pitfalls of actual applications of these techniques.