Over the last decade, advances in artificial intelligence, machine learning, and new data systems have revolutionized nearly every sector of the economy, and have led to new and exciting research across economic policy areas.
With generous support from Schmidt Futures, the Opportunity Lab’s Labor Science Initiative is coordinating a new community of scholars utilizing cutting-edge data science tools to pose new questions about labor markets and the public sector. On October 9th, the O-Lab will assemble leading researchers in healthcare and education policy to present work that exemplifies the best of this initiative. The workshop will offer a chance for faculty, students, and other colleagues to share insights on their research and to find commonalities in the work done across these applications.
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AM Session: Healthcare (Moderator: Jon Kolstad)
10:00 - 10:35
Ziad Obermeyer (UC Berkeley)
Computational Medicine
10:40 - 11:15
Petra Persson (Stanford)
Family Spillover Effects of Misdiagnosis
11:20 - 11:55
Ben Handel (UC Berkeley)
The Social Determinants of Choice Quality: Evidence from Health Insurance in the Netherlands
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PM Session: Education (Moderator: Jesse Rothstein)
12:00 - 12:35
Seth Zimmerman (Yale)
The Distribution of and Returns to Social Success at Elite Universities
12:40 - 1:15
Claudia Allende (University of Chicago)
Identifying the Equilibrium Effects of Informed
School Choice
1:20 - 1:55
Chris Walters (UC Berkeley)
Using Centralized Assignment Data to Estimate School Value-added
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