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on Sociology of Economics |
| By: | Francesca Barigozzi; Natalia Montinari; Giovanni Righetto; Alessandro Tampieri |
| Abstract: | In most countries, women systematically outperform men in academic achievement across fields of study. Yet within a year of graduation, they earn less, face lower employment rates, and are more likely to work part-time. If human capital were the sole determinant of pay, this pattern would be difficult to reconcile. We address this puzzle by extending the statistical discrimination framework ‘a la Phelps (1972) to include not only human capital but also additional components of productivity, such as IT skills and mobility intentions -the willingness to travel or relocate for work -which might capture candidates’ technological proficiency and adaptability. Using rich microdata from the AlmaLaurea survey of master’s graduates from the University of Bologna (2015–2022), we show that while human capital alone predicts no gender wage gap in favor of men, combining it with mobility intentions reproduces the early wage disadvantage observed for women in Economics and Engineering. We further show that IT skills -an observable CV trait constructed from multiple IT-skill items- reduce the residual gender wage gap, especially in Engineering. Our findings highlight the importance of complementing human capital with field-specific preference and skill traits to explain-and potentially address-early gender wage gaps. |
| JEL: | J16 J31 J71 J24 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:bol:bodewp:wp1212 |
| By: | Erik Brynjolfsson; Anton Korinek; Ajay K. Agrawal |
| Abstract: | As we approach Transformative Artificial Intelligence (TAI), there is an urgent need to advance our understanding of how it could reshape our economic models, institutions and policies. We propose a research agenda for the economics of TAI by identifying nine Grand Challenges: economic growth, innovation, income distribution, decision-making power, geoeconomics, information flows, safety risks, human well-being, and transition dynamics. By accelerating work in these areas, researchers can develop insights and tools to help fulfill the economic potential of TAI. |
| JEL: | A11 O33 O40 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34256 |