Climate change poses large aggregate risks that will likely have very different effects on different households. Unfortunately, these risks cannot be shared in existing financial markets. In this paper, author gives some quantitative examples to show that the inability to share these risks leads to much higher abatement and lower emissions at a constrained optimum.
Author considers a simple heterogeneous agents model of a production economy with uncertain climate change and examine constrained efficient carbon taxation. If there are frictionless, complete financial markets, the simple model predicts a unique Pareto-optimal level of carbon taxes and abatement. In the presence of financial frictions, however, the optimal level of abatement cannot be defined without taking a stand on how abatement costs are distributed among individuals. Author proposes a simple linear cost-sharing scheme that has several desirable normative properties. Author uses calibrated examples of economies with incomplete financial markets and/or limited market participation to demonstrate that different schemes to share abatement costs can have large effects on optimal abatement levels and that the presence of financial frictions can increase optimal abatement by a factor of three relative to the case of frictionless financial market.
In the calibrated examples, author focus on uncertainty about future temperature and aggregate damages. Of course, there might be many other risks caused by anthropogenic climate change which cannot be shared in markets and have significant effects on agents’ well beings. Risks associated with tipping points have played a prominent role in the literature (e.g., Lemoine and Traeger , Cai et al. ), but it might be as important to model the effects of climate change on idiosyncratic income risk. It is subject to further research to understand how these uncertainties interact and how large the quantitative impact on welfare and optimal taxes are.
Prof. Dr. Felix Kübler
Professor of Financial Economics
Member of Steering Committee MSc in Quantitative Finance UZH ETH
Department for Banking and Finance, University of Zürich; Swiss Finance Institute (SFI)
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