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We investigate whether classical studies in high school - that emphasize in Italy the study of ancient languages such as Latin and Greek - affect personality traits. Using Italian survey data, we compare individuals who did classical studies in high school with similar individuals who completed a more scientific academic curriculum. We find that having done classical studies does not affect conscientiousness and openness but increases neuroticism and self-reported unhappiness.

We explore the long run determinants of current differences in the degree of cooperative labor relations at local level. We do this by estimating the causal effect of the medieval communes - that were established in certain cities in Centre-Northern Italy towards the end of the 11th century - and that contributed to the emergence of a cooperative attitude in the population on various proxies for current cooperative labor relations. Conditional on a large set of firm and municipality level controls, as well as a full set of province fixed effects, we find that firms located in municipalities that had been a free medieval commune in the past, have higher current probabilities to adopt two-tier bargaining structures and to be unionized. We also report IV and propensity score estimates that confirm our main results.

It is now well accepted that human capital is a heterogeneous aggregate and that non-cognitive skills are at least as relevant as cognitive abilities. In spite of this growing interest in the labour market consequences of personality traits, the relationship between these and educational and skill mismatch is scant. In this paper, we investigate the impact of the five main personality traits (Big 5) on educational and skill mismatch in Italian graduates. To this aim, we use the 2018 wave of the INAPP-PLUS survey, which contains information on skill mismatch, on the Big 5 personality traits, and on a large number of other individual and job-specific characteristics. The empirical analysis takes into account both demand and supply variables mediating the effect of personality on skill mismatch and controls for non-random selection into employment and tertiary education. We find that some personality traits reduce the probability of overeducation, suggesting complementarity between cognitive and non-cognitive skills. In addition, we find a positive effect of conscientiousness on both overeducation and overqualification. The evidence regarding job satisfaction suggests that individuals with high scores for conscientiousness voluntarily decide to be mismatched when this entails higher satisfaction in other dimensions of the job.

This work investigates the impact that the change in the exposure to robots had on the Italian local employment dynamics over the period 2011-2018. A novel empirical strategy focusing on a match between occupations' activities and robots' applications at a high level of disaggregation makes it possible to assess the impact of robotization on the shares of workers employed as robot operators and in occupations deemed exposed to robots. In a framework consistently centered on workers' and robots' activities, rather than on their industries of employment, the analysis reveals for the first time reinstatement effects among robot operators and heterogeneous results among exposed occupations.

This paper evaluates if and to what extend the risk of becoming Not in Employment, Education or Training (NEET) has worsened during the Covid-19 pandemic in Italy. The analysis is based on a unique dataset from the merging of two sample surveys, the Italian Labor Force Survey and the Institutional Quality Index dataset. We find that the probability of being NEET significantly increased during the pandemic, but heterogeneously between age cohorts and geographical areas. The most affected categories have been young people (aged 25-34) and those living in North-West regions. Females are mostly affected compared to males, especially those experiencing motherhood and living in a Southern province. Investment in education reduces the NEET status, mainly for age-group 25-34 in the South. Participation in the civil society significantly reduces the probability to being NEET. Finally, active policies conducted at regional level are a further educational investment that protect from becoming NEET, although their effectiveness is not significant in the Southern regions. We provide novel evidence to inform policymakers and help building evidence-based policies, tailored on local needs.

The Routine-Biased Technological Change (RBTC) has been called as a relatively novel technology-based explanation of social changes like job and wage polarization. In this paper we investigate the wage inequality between routine and non-routine workers along the wage distribution in Italy. Thanks to unique survey data, we can estimate the wage differential using both actual and perceived level of routine intensity of jobs to classify workers. We adopt semi-parametric decomposition techniques to quantify the importance of characteristics of workers in explaining the gaps. We also employ non-parametric techniques to account for self-selection bias. We find evidence of a significant U-shaped pattern of the wage gap, according to both definitions, with non-routine workers earning always significantly more than routine workers. Results show that workers' characteristics fully explain the gap in the case of perceived routine, while they account for no more than 50% of the gap across the distribution in the case of actual routine. Thus, results highlight the importance of taking into account workers' perceptions when analyzing determinants of wage inequality. Overall, we confirm that, after leading to job polarization, RBTC induced a similar polarizing effects on wages in Italy.

In this paper we use two different non-parametric methods to disentangle the role of Great Recession on income polarization in Italy by population groups (gender, occupational status, education, age, residential area and state of birth). By using data from the Survey on Household Income and Wealth of the Bank of Italy, first, we decompose the Duclos, Esteban and Ray polarization index by population groups. Second, we employ the Relative Distribution Approach by groups. Our results show a general downgrading, particularly of lower incomes, where low-educated, young, southern and foreign head of household are located out of the crisis. Young people and especially foreigners have suffered the most from the crisis. The lowest (highest) homogeneity within groups and the lowest (highest) heterogeneity between groups is observed when groups are formed on the basis of the state of birth (residential area).Thus, the decomposition of the polarization indices by population groups is able to provide specific useful policy indications, tailored to groups' needs.

In this paper, we explore channels by which household background determines an individual's educational and social opportunities in Italy. Our analysis relies on a rich dataset that contains data both on individuals and their real parents, as well as information on individuals' non-cognitive skills. This paper also represents the first attempt to evaluate if and to what extent personality traits affect educational and occupational opportunities in Italy and how they interact with household background. The results highlight that the level of parental education is more relevant than the level of parental occupational skill in individuals' educational and social opportunities. The inclusion of 'Big-5' variables in the model helps control for omitted variables and reduces the unobserved heterogeneity in intergenerational social mobility among individuals with the same level of education and skills. Our results depict a dual and unequal labour market.

We analyse how the adoption of technological innovations correlates with workers' perceived levels of job insecurity, and what factors mediate such relationship, by exploiting a recent, large and dedicated survey distributed to a representative sam- ple of Italian workers. The dedicated survey allows us to look at both cognitive and affective job insecurity as well as different technological innovations actually adopted by the companies where the workers are employed. The results show that the adoption of technological innovations by companies is related to a reduction in the level of job insecurity perceived by their workers and suggest that technological innovation is perceived by active workers as a signal of firms' health and of their commitment to preserving the activity. We also find that the reassuring effect of technological innovations is differentiated across companies and workers, due to the mediating role played by a number of factors, such as specific training and signifi- cant changes in workers' usual activities.

Working from home (WFH) has become a key factor during the COVID-19 pandemic, especially in countries that have implemented severe social distancing measures. This paper investigates the potential influence of the working from home attitude of occupations on the gender wage gap (GWG) reported by Italian employees, on average and along the distribution. Based on Oaxaca-Blinder decompositions and unconditional quantile regressions, our results show that the GWG is greater among females working in an occupation with a high level of WFH attitude, thus among those more likely to be affected by a (probably) persistent spread of WFH procedures after the COVID-19 pandemic. In addition, we find evidence of both sticky floor and glass ceiling effects for employees with a high WFH attitude and only a sticky floor effect for the group with a low WFH attitude. The positive association revealed between the level of WFH attitude and the GWG appears particularly strong among older and married female employees, as well as among those working in the private sector. Finally, this study confirms that allocating adequate resources to programmes and instruments that aim to achieve genderrelated goals is strongly recommended.