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Robots have radically changed the demand for skills and the role of workers in production at an unprecedented pace, with little scope for human capital adjustments. This has affected the job stability and the economic perspectives of large parts of the population in all industrialized countries. Recent evidence on the US labor market has shown negative effects of robots on employment and wages. In this study, we examine how exposure to robots and its consequences on job stability and economic uncertainty have affected individual demographic behavior. To establish this relationship, we use data from the American Community Survey and the International Federation of Robotics and we adopt an empirical strategy that relies on regional industry specialization before the advent of robots combined with the growth of robot adoption by industry. We first document the differential effect of robots on the labor market opportunities of men and women. We find that in regions that were more exposed to robots, the gender-income and labor-force-participation gaps declined. We then show that US regions affected by intense robot penetration experienced a decrease in new marriages, and an increase in both divorce and cohabitation. While there was no change in overall fertility rate, marital fertility declined, and there was an increase in out-of-wedlock births. Our findings are consistent with the hypothesis that the changes in labor markets triggered by robot adoption increased uncertainty, reduced the relative marriage-market value of men, and the willingness to commit for the long term.

Education is a key sociological variable in the explanation of health and health disparities. Conventional wisdom emphasizes a life course-human capital perspective with expectations of causal effects that are quasi-linear, large in magnitude for high levels of educational attainment, and reasonably robust in the face of measured and unmeasured explanatory factors. In this paper, we challenge this wisdom by offering an alternative theoretical account and an empirical investigation organized around the role of measured and unmeasured cognitive and non-cognitive skills as confounders in the association between educational attainment and health. Based on longitudinal data from the National Longitudinal Survey of Youth – 1997 spanning mid adolescence through early adulthood, results indicate that a) effects of educational attainment are very vulnerable to issues of omitted variable bias; b) that measured indicators of cognitive and non-cognitive skills account for a significant proportion of the traditionally observed effect of educational attainment; c) that such skills have effects larger than that of even the highest levels of educational attainment when appropriate controls for unmeasured heterogeneity are incorporated; and d) that models that most stringently control for such time-stable abilities show little evidence of a substantive association between educational attainment and health. Implications for theory and research are discussed.

Using descriptive statistics, civil marriages and marriages preceded by premarital cohabitation are more unstable, i.e., more frequently followed by divorce. However, the literature has shown that selectivity plays an important role in the relationship between premarital cohabitation and union dissolution. We do not have evidence to date regarding the selectivity in the effect of civil marriage. The Italian case appears particularly interesting given the recent diffusion of premarital cohabitation and civil marriage. Using micro-level data from a national-level representative survey held in 2003, we develop a multiprocess model that allows unobserved heterogeneity to be correlated across the three decisions (premarital cohabitation, civil marriage, and divorce). Our results show that selectivity is the main factor that explains the higher divorce rates among those who experience premarital cohabitation and a civil marriage. Net of selectivity, the causal effect on union dissolution disappears.

Agent-based modelling and numerical simulations are means that facilitate exploring the structural and dynamic characteristics of systems which may prove intractable with analytical methods. This contribution examines the issues related to them with a particular attention to their use in the study of social economic and ecological systems. Besides a general description, the possibilities, limitations and their relationship with other more traditional investigation methods are examined. Special focus is put on the assessment of their validation and reliability. Finally an application example is provided. A simple model is built to analyse the movements of tourists and the relationship between these and the attractiveness of a tourism destination. The results are discussed along with possible future developments.

Does removing the constraints of time and place of work increase the utility of workers and firms? We design a randomized experiment on a sample of workers in a large Italian company: workers are randomly divided into a treated group that engages in flexible space and time job (which we call “smart-working”) one day per week for 9 months and a control group that continues to work traditionally. By comparing the treated and control workers, we find causal evidence that the flexibility of smart-working increases the productivity of workers and improves their well-being and work-life balance. We also observe that the effects are stronger for women and that there are no significant spillover effects within workers of a team.

We investigate the gender gap in Economics among bachelor's and master's graduates in Italy between 2010 and 2019. First we establish that being female exerts a negative impact on the choice to major in Economics: at the bachelor level, only 73 women graduate in Economics for every 100 men, with the mathematical content of high school curricula as the key driver of the effect and a persistence of the gap at the master level. Second, within a full menu of major choices, Economics displays the largest gap, followed by STEM and then Business Economics. Third, decomposition analyses expose a unique role for the math background in driving the Economics gender gap relative to other elds. Fourth, a triple difference analysis of a high school reform shows that an increase in the math content of traditionally low math curricula caused an increase in the Economics gender gap among treated students.