PhD graduates are overrepresented among inventors, yet little is known about whether PhD programs themselves foster innovation. This paper estimates the causal impact of doctoral programs on innovation, exploiting the centrally planned, staggered introduction of PhD programs in Italy starting in 1983. Using a newly assembled dataset linking the rollout of PhD programs to local patenting, I find that the introduction of these programs increased patenting by 21% between 1986 and 2001. To shed light on mechanisms, I use newly collected individual-level data on performance in PhD admission exams in a regression discontinuity design and find that about 30% of the overall increase is driven by PhD graduates producing more patents. The remaining effects arise mostly from spillovers to local firms, concentrated in R&D-intensive industries whose workers have stronger social links to local PhD students. These results suggest that PhD programs foster innovation both by increasing graduates’ inventiveness and by strengthening the local innovation ecosystem. Under conservative assumptions about patent value, program costs, and PhD students’ opportunity cost, the returns from PhD programs are at least 46% higher than their costs.

Skills acquired on the job, whether general or industry-specific, significantly influence workers' labor market outcomes. Workers with general skills tend to have higher re-employment prospects and greater resilience to economic shocks. Using novel data from a recent policy intervention in the Italian labor market, we develop a new measure that captures the tasks taught in firm-provided training for individual workers. This measure enables us to examine the relationship between labor market competition and firms' decision to invest in general versus industry-specific skills. Our findings indicate that, as theory predicts, workers in more competitive labor markets receive less general training.

This study examines the impact of digital technology adoption on Italian firms’ performance and workforce composition. Analyzing 2011–2020 data, we focus on six technologies categorized as “information” (e.g., Big Data, Cloud Computing) and “operation” (e.g., Robots, IoT). Employing synthetic difference-in-differences methods, we find that adoption increases sales by 5% and employment by 1% for both technologies. Workforce composition effects vary: information technologies raise the share of older graduates and younger non-graduates, while operation technologies increase young, non-graduate workers without significantly altering the overall educational mix. These findings suggest that digital technology adoption enhances firm productivity but may reinforce existing skill polarization, offering limited benefits to highly educated young workers and potentially reducing opportunities for older, less-educated employees, while operation technology adoption has more muted effects on the skill composition.