Conference Agenda
Overview and details of the sessions of this conference.
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Some information on the session logistics:
If not stated otherwise, the discussant is the following speaker, with the first speaker being the discussant of the last paper. The last speaker of each session is the session chair. (Exception: invited sessions)
Presenters should speak for no more than 20 minutes, and discussants should limit their remarks to no more than 5 minutes. The remaining time should be reserved for audience questions and the presenter’s responses. We suggest following these guidelines also in the (less common) 3-paper sessions in a 2-hour slot, to allow participants to move between sessions. Discussants are encouraged to avoid summarizing the paper. By focusing on a few questions and comments, the discussants can help start a broader discussion with the audience.
Only registered participants can attend this conference. Further information available on the congress website https://www.iseg.ulisboa.pt/en/event/iipf/ .
Venue address: ISEG - Lisbon School of Economics & Management, R. Francesinhas 21, 1200-675 Lisboa, Portugal
Please note that all times are shown in the time zone of the conference. The current conference time is: 17th Sept 2026, 11:39:16am WEST
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Daily Overview |
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C09: Parental Inputs, Teaching Styles, and Child Development Location: Room 109 (Francesinhas 1) | |
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Effects of Genetic Propensity for Education on Labor Market and Health Trajectories across the Working Life 1: Tampere University, FIT; 2: VATT Institute for Economic Research; 3: IFAU and Uppsala Center for Labor Studies; 4: IZA; 5: Rockwool Foundation; 6: Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki,; 7: University of Minnesota; 8: Broad Institute of MIT and Harvard; 9: Analytic and Translational Genetics Unit, Massachusetts General Hospital Using Finnish registry data on 51,056 graduates followed annually since graduation for up to 25 years, we report three findings. First, higher EA-PGI strongly predicts income growth, but only among higher-educated people. This effect is not mediated by overall health. Second, EA-PGI does not predict income differences at labor market entry or the quality of the first employer, but rather a higher job-to-job mobility toward better-paying firms, which drives the long-run income divergence. Third, controlling for parental EA-PGI in 12,871 parent–offspring trios reduces the discounted lifetime income gap by 71 %, and the effect of paternal (but not maternal) EA-PGI on offspring income exceeds that of the offspring’s own EA-PGI. These findings suggest that genetic factors associated with educational attainment predict income trajectories primarily through faster and more frequent changes to higher-paying employers.
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