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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.

The mounting evidence on the demographics of COVID-19 fatalities points to an overrepresentation of minorities and an underrepresentation of women. Using individual-level, race-disaggregated, and georeferenced death data collected by the Cook County Medical Examiner, we jointly investigate the racial and gendered impact of COVID-19, its timing, and its determinants. Through an event study approach we establish that Blacks individuals are affected earlier and more harshly and that the effect is driven by Black women. Rather than comorbidity or aging, the Black female bias is associated with poverty and channeled by occupational segregation in the health care and transportation sectors and by commuting on public transport. Living arrangements and lack of health insurance are instead found uninfluential. The Black female bias is spatially concentrated in neighborhoods that were subject to historical redlining.

This paper shows and explains lower wealth inequality in East Asia than Western Europe over the very long-run, 1300-2000. A rich new dataset of village censuses in Japan, 1640-1870, and secondary evidence suggest Gini coefficients of wealth inequality in the East were 0.4-0.5 relative to 0.7-0.9 in the West preceding industrialization. Such regional patterns also precede the black death so any explanation must predate this. I propose the demographic institution of adoption as one such explanation. Adoption prevented the failure of male lines through which wealth was inherited. Adoption was practiced across Eurasia until the 5th century when the church began preaching against it. This increased household extinctions in Europe causing wealth concentration among surviving male lines. In contrast, the Japanese data suggest adoption prevented household extinctions and kept wealth in the family. Simulations show that this mechanism can explain much of the gap in regional wealth inequality.

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.

This article provides a picture of long-term developments in the relationship between population and resources in Northern Italy that takes fully into account climate. It analyzes both the slow underlying development of climatic conditions over the centuries  (in the theoretical framework of the Little Ice Age) and the consequences of short-term periods of heightened instability. The most severe famines are shown to be events triggered by climatic and environmental factors operating at a time when the maximum carrying capacity of the system had been reached or, at least, when the population was exerting considerable pressure on the potential for food production. This is the case of the famine of the 1590s, the greatest demographic catastrophe of a non-epidemic nature to strike Northern Italy since the Black Death and up to the end of the eighteenth century. The article also analyzes long-term paths of agrarian innovation, suggesting that most (but not all) of this was consistent with Boserup's idea of chain-reactions of innovations induced by demographic pressure. These processes, though, were too slow to compensate for a rapidly growing population. Finally, the article provides a periodization in which the period between the famine of the 1590s and the great plague pandemic of 1630 is shown to be the crucial turning point in how population dynamics, climate and agrarian innovation interacted.

We consider the case when it is of interest to study the different states experienced over time by a set of subjects, focusing on the resulting trajectories as a whole rather than on the occurrence ofspecific events. Such situation occurs commonly in a variety of settings, for example in social and biomedical studies. Model‐based approaches, such as multistate models or Hidden Markov models, are being used increasingly to analyze trajectories and to study their relationships with a set of explanatory variables. The different assumptions underlying different models typically make the comparison of their performances difficult. In this work we introduce a novel way to accomplish this task, based on microsimulation‐based predictions. We discuss some criteria to evaluate one model and/or to compare competing models with respect to their ability to generate trajectories similar to the observed ones.

Understanding the impact of the COVID-19 pandemic on education requires a solid grasp of the impact of student autonomy on learning. In this paper, we estimate the effect of an increased autonomy policy for higher-performing students on short- and longer-term school outcomes. We exploit an institutional setting with high demand for autonomy in randomly formed classrooms. Identification comes from a natural experiment that allowed higher-achieving students to miss 30 percent more classes without penalty. Using a difference-in-difference-in-differences approach, we find that allowing higher-achieving students to skip class more often improves their performance in high-stakes subjects and increases their university admission outcomes. Higher-achieving students in more academically diverse classrooms exerted more autonomy when allowed to.

ABSTRACT Evidence suggests that the significantly higher life expectancy levels witnessed over the past centuries are associated with a lower concentration of survival times, both cross-country and over time. The purpose of this work is to study the relationships that exist among models for the evolution of survival distributions, longevity measures, and concentration. We first study relationships between concentration and cohort longevity through empirical comparisons. We then propose a family of survival models that can be used to capture such trends in longevity and concentration across survival distributions.