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If individuals become aware of their stereotypes, do they change their behavior? We study this question in the context of teachers’ bias in grading immigrants and native children in middle schools. Teachers give lower grades to immigrant students compared to natives who have the same performance on standardized, blindly-graded tests. We then relate differences in grading to teachers’ stereotypes, elicited through an Implicit Association Test (IAT). We find that math teachers with stronger stereotypes give lower grades to immigrants compared to natives with the same performance. Literature teachers do not differentially grade immigrants based on their own stereotypes. Finally, we share teachers’ own IAT score with them, randomizing the timing of disclosure around the date on which they assign term grades. All teachers informed of their stereotypes before term grading increase grades assigned to immigrants. Revealing stereotypes may be a powerful intervention to decrease discrimination, but it may also induce a reaction from individuals who were not acting in a biased way.

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.

This paper relates social mobility and social stratification to higher education policy. We show that higher‐education policy which leads to differences in quality and per‐student expenditure as well as in admission procedures between standard and elite universities, is a key factor in generating permanent social stratification and social immobility. We develop an intergenerational model which shows that a two‐tier higher education characterised by a division between elite and standard universities can be a key factor in generating permanent social stratification, social immobility and self‐reproduction of the ‘elite’. In our approach, low mobility is essentially explained by the differences in quality and in selection between elite and standard universities. A key result is that the wider the quality gap and the difference in per‐student expenditures between elite and standard universities, the less social mobility. This is because a larger quality gap reinforces the weight of family backgrounds at the expense of personal ability. Our simulations show that this impact can be large. These findings provide theoretical bases for the impact of higher education policy on social mobility.

A fundamental switch in the fertilitydevelopment relationship has occurred so that among highly developed countries, further socioeconomic development may reverse the declining fertility trend. Here we shed light on the mechanisms underlying this reversal by analyzing the links between development and age and cohort patterns of fertility, as well as the role of gender equality. Using data from 1975 to 2008 for over 100 countries, we show that the reversal exists both in a period and a cohort perspective and is mainly driven by increasing older reproductive-age fertility. We also show that the positive impact of development on fertility in high-development countries is conditional on gender equality: countries ranking high in development as measured by health, income, and education but low in gender equality continue to experience declining fertility. Our findings suggest that gender equality is crucial for countries wishing to reap the fertility dividend of high development.

This article analyzes social norms regulating selection of godparents in Italy and France and how they will be affected by demographic change. On the grounds of Vatican statistics and of the World Values Survey, it demonstrates that baptisms still occur for the vast majority of children in Catholic Europe and that birth rituals are considered important even by non-believers. Relying on historical data, it shows that the custom of selecting godparents from among kinsmen, currently dominant, is a recent development. A new survey about selection of godparents in Italy and France is used which shows that they are not chosen for religious, but for social-relational reasons. Selection of kinsmen is the norm, with uncles and aunts being the majority choice. For Italy, choice determinants are explored by means of multinomial regressions. The results are contrasted with demographic change to show that in lowest-low fertility countries current godparenthood models are bound to disappear.

We develop a statistical discrimination model where groups of workers (males-females) differ in the observability of their productivity signals by the evaluation committee. We assume that the informativeness of the productivity signals depends on the match between the potential worker and the interviewer: when both parties have similar backgrounds, the signal is likely to be more informative. Under this “homo-accuracy” bias, the group that is most represented in the evaluation committee generates more accurate signals, and, consequently, has a greater incentive to invest in human capital. This generates a discrimination trap. If, for some exogenous reason, one group is initially poorly evaluated (less represented into the evaluation committee), this translates into lower investment in human capital of individuals of such group, which leads to lower representation in the evaluation committee in the future, generating a persistent discrimination process. We explore this dynamic process and show that quotas may be effective to deal with this discrimination trap. In particular, we show that introducing a “temporary” quota allows to reach a steady state equilibrium with a higher welfare than the one obtained in the decentralized equilibrium in which talented workers of the discriminated group decide not to invest in human capital. Finally, if the discriminated group is underrepresented in the worker population (race), restoring efficiency requires to implement a “permanent” system of quotas.