Leader: Lorenzo Cappellari (UNICATT); Other collaborator(s): Giacomo PASINI (UNIVE)
Examine work-related risks and trigger points over the life-course which can have a permanent impact on job opportunities and wellbeing in old age, such as unemployment shocks, between jobs transitions, maternity leave. Develop through and econometric model based on longitudinal data a "career tracker" at individual level, to identifying the policy interventions necessary to make aging at work sustainable and active over the life course. Investigate forms of intergenerational family links in the ageing process. Contribute to the definition and prediction of a "job fragility Index" making use of the estimated work-related risks.
Brief description of the activities and of the intermediate results:
Econometric models to understand the lifelong career trajectories of Italians, utilizing SHARE data to highlight disparities in gender and regional career patterns. The influence of remote work adoption and labor supply dynamics by exploiting the recent pandemic shock. Modelling the impact of the green transition on the employability of older workers, to identify green jobs using occupation-level data from O*Net and linking it with micro-data on older workers from SHARE, over time and across regions
Main policy, industrial and scientific implications
First results on the impact of the digital and green transition on the employability of older workers.
Brief description of the activities and of the intermediate results:
1. A detailed map of individuals’ working career looking at fragmented working paths and the consequences on workers’ contribution to social security and for eligibility for a pension at older age.
2. Estimates of the impact of tertiary education availability on long-term labor market outcomes.
3. Estimates of the impact of the digital and green transition on the employability of older workers.
4. Estimates of organizational well-being on firm-level turnover rates and the overall financial performance of firms, as measured by per capita value added and by Return On Assets (ROA) indicators.
5. Estimates of the relevance for the organization of work and the investment in ICT skills and about the role of social partnerships and collective bargaining for counterbalancing risks of job insecurity and difficulty to make ends meet of older workers.
Brief description of the activities and of the intermediate results:
In a separate project (Albanese A., Cappellari L., Ovidi M.), we use admin (INPS) data to extend the canonical AKM model of wage determination to allow for worker ageing. Namely, we allow for age effects both in the worker component and the form component. This allows us to study life cycle mobility through the distributions of worker and firm effects finding that there is more mobility in the former. We use machine learning algorithms to characterize recurrent patterns of mobility through these distributions. Further, we exploit administrative information on the reasons of plant closure to set up event study models for the causal effects of job loss on worker and form effects and how they vary over the life cycle. Ultimately, we seek to understand if the cost of job loss is due to human capital deterioration or the loss of market rents, and how these two elements change as workers age.
(Belloni M., Lucifora C., Micera P.) This study offers an opportunity to exploit the life-course perspective to measure the occupational risk on the health status of workers exposed to harmuful working conditions during their entire working career. Levereging the Job Episode Panel from SHARE dataset and O*NET work context module we built cumulative exposure indicators in various domanis such as physical, environmental and psychosocial stress. We obtain health indices exploiting the time variation from the waves from SHARE using econometric and PCA techniques.
Main policy, industrial and scientific implications
In the ageing-AKM project we have first of all established the feasibility of allowing for a non-parametric specification of age effects in the worker and firm components. We have estimated life-cycle transition probabilities in the quantiles of worker and form distribution. We have developed machine learning algorithms that search for the best predictors of life cycle trajectories. In the job-loss part of the project, we have specified the job loss instrument and estimated the overall cost of job loss at different stages of the life cycle.
Brief description of the activities and of the intermediate results:
Implementation of job loss event studies on the worker and firm effects estimated from AKM model. Estimation of job mobility patters across regions and gender over entire working careers.
"Working conditions and health at work over the life-cycle: Evidence from Europe” (Prof. Michele Belloni, Prof. Claudio Lucifora , Paolo Micera) We continued to analyse the cumulative impact of working stressors aquired in the entire career of individuals aged 50+ across Europe, constructing indicators of these cumulative exposures for Environmental, Psychosocial and Physical domains. Built a frailty index which is a for the health conditions of workers overtime. Implement a novel dataset with working conditions from the 1966 at each ISCO-08.
Main policy, industrial and scientific implications
Dissemination Events:
Scientific outputs: