Conference Agenda

This study explores how learning affects optimal economic policy-making, focusing on climate policy. Dynamic economic models with uncertainty depend on how agents anticipate and adapt to new information. We show that seemingly similar approaches to modeling learning can lead to very different risk premiums in policy decisions. Our analysis focuses on the uncertain climate sensitivity, the temperature response to greenhouse gas accumulation. We distinguish two uncertainty components: natural temperature variability and subjective uncertainty about nature's true climate sensitivity.

We provide an analytic formula for optimal carbon pricing under anticipated Bayesian learning. Whereas a decreasing variance over time reduces the risk premium, we show that learning's impact on the prior mean (``updating shocks'') has an opposing effect. We explore these two different channels and different model variations in a stochastic dynamic programming version of Nordhaus' DICE model, exploring the trade-off between a ``wait-and-see'' argument and a more cautious approach.

This paper examines how household preferences for green consumption influence firm investment in green research. I develop a semi-endogenous growth model featuring two consumption goods—green and brown. The model incorporates directed technological change, allowing for innovation efforts on green or brown production sectors. The transition dynamics reveal that an increase of 5 percentage points in green preferences immediately affect resource allocation, leading to a 20 % increase in green technology level and a 10 % reduction in brown production. Policy evaluations indicate that production-side interventions lead to greater utility losses compared to consumer-side interventions.

We develop a growth model to estimate the social cost of waste. We integrate material flows into a Brock-Mirman economic growth framework and derive a formula for the social cost of waste. Our calibration for plastic use suggests that the social cost of plastic waste is significantly higher than its market price, indicating a pressing need for policy intervention. The model shows an increasing historical and future plastic dependency in the economy and substantial GDP losses due to plastic waste if not addressed.