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Information is not Implementation: Early evidence from using machine learning for climate policies when state capacity is low
Climate change adaptation policies are increasingly using machine learning to make use of more information and provide more accurate predictions of extreme weather events. Equally, Payment for Ecosystem Services to monitor and affect land use are increasingly relying on remote sensing data. This talk will draw upon a set of recent (ongoing) field experiments to highlight the importance of designing ML-based climate policies that account for last mile implementation constraints and low citizen trust in the state.
Date:
2 June 2025, 14:15
Venue:
Manor Road Building, Manor Road OX1 3UQ
Venue Details:
Seminar Room C
Speaker:
Rohini Pande (Yale University)
Organising department:
Department of Economics
Part of:
Environment and Resource Economics Seminar
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Edward Valenzano
