Calendrier du 23 septembre 2024
Roy Seminar (ADRES)
Du 23/09/2024 de 16:00 à 17:15
R1-09
SALMI Julia (Copenhagen)
Dynamic Evidence Disclosure: Delay the Good to Accelerate the Bad
écrit avec Jan Knoepfle
We analyze the dynamic tradeoff between the generation and the disclosure of evidence. Agents are tempted to delay investing in a new technology in order to learn from information generated by the experiences of others. This informational free-riding is collectively harmful as it slows down innovation adoption. A welfare-maximizing designer can delay the disclosure of previously generated information in order to speed up adoption. The optimal policy transparently discloses bad news and delays good news. This finding resonates with regulation demanding that fatal breakdowns be reported promptly. Remarkably, the designer's intervention makes all agents better off.
Paris Migration Economics Seminar
Du 23/09/2024 de 12:30 à 13:30
R1-15
DESMET Klaus (Southern Methodist University)
On the Geographic Implications of Carbon Taxes
écrit avec Bruno Conte ( Universita di Bologna) and Esteban Rossi-Hansberg (SMU)
Using a multisector dynamic spatial integrated assessment model (S-IAM), we argue that a carbon tax introduced by the European Union (EU) and rebated locally
can, if not too large, increase the size of Europe’s economy by concentrating economic activity in its high-productivity non-agricultural core and by incentivizing
immigration to the EU. The resulting change in the spatial distribution of economic activity improves global efficiency and welfare. A carbon tax introduced
by the US generates similar effects. This stands in sharp contrast with standard
models that ignore trade and migration in a world shaped by economic geography
forces.
Régulation et Environnement
Du 23/09/2024 de 11:00 à 12:15
r1-09
RUBIN Edward (Oregon State University)
Power plants, air pollution, and regulatory rebound
: Interactions between overlapping air quality regulations can have unintended impacts on polluting activities. We document one such potentially important interaction. Local regulators in areas constrained by one type of regulation—e.g., threshold-based local air quality standards—are incentivized to permit more local pollution in response to a decline in emissions induced by another kind of regulation—e.g., rules targeting power plant emissions. We combine a state-of-the-art particle trajectory model, machine learning, and an econometric model of local air pollution exposure to quantify the relationship between sustained reductions in upwind power-plant emissions of pollution (PM2.5) precursors and downwind pollution levels. We use this integrated air quality modeling framework to test whether pollution levels in constrained counties appear to rebound when emissions from upwind pollution sources decline. We document evidence that is consistent with a local emissions rebound.