Research
Working Papers
Best Doctoral Dissertation of the European Association of Environmental and Resource Economists (EAERE) 2023
SDG Impact Award, University of Zurich 2023
1st prize by the Swiss Association for Energy Economics (SAEE) 2022
IAERE Young Environmental Economist Award 2021
As climate changes and natural disasters intensify, the threat of human displacement increases. This paper explores how carbon should be taxed in the presence of international displacement caused by climate change. It first provides empirical evidence on the migration response to natural disasters from developing to developed countries. Second, it develops a climate-economy growth model with climate refugees and theoretically characterizes global and local social cost of carbon (SCC, equivalently, the optimal carbon tax) taking into account the economic and social impact of climate refugees. Third, it quantifies the SCCs in a North-South calibration. The main finding is that refugees enhance host regions' incentives to unilaterally fight climate change, leading to 26% increase in the local SCC, more so if political conflict is accounted for. This stands in contrast to the global SCC, and the origin regions SCC, which barely change in magnitude after accounting for refugees.
The effects of short-term exposure to air pollution on COVID-19 fatality
with J. Vall. R&R at Environmental and Resource Economics
Air pollution is a major concern that constitutes an important part of the climate change thread. Furthermore, since the outbreak of the pandemic, there is an increased interest in understanding the role of environmental conditions in determining the severity of infectious diseases. We contribute to this debate by quantifying the effect of short-term exposure to air pollution on COVID-19 mortality. We construct a novel county-level dataset of daily COVID-19 mortality and, in order to overcome the potential endogeneity problems caused by factors related to both the virus and mortality rates (such as county-level economic conditions), we use wind speed as an instrument for air pollution. Our results show that being exposed to one additional unit (μg/m3) of nitrogen dioxide, particulate matter and nitrogen oxides, increases COVID-19 mortality by a factor of between 1.1-1.3. By highlighting the positive effects that air pollution reduction policies can generate on population health, our results are relevant for the design of policy tools to be used during the next natural disaster events.
Directed Technical Change and the Energy Transition: The Role of Storage Technology
with I. Hovdahl
Publications
with I. Hovdahl. Journal of the Association of Environmental and Resource Economists, forthcoming.
This paper investigates how patent policy can induce the transition to clean technology. It is well established that environmental policy should not only price emissions, but also induce innovation in emission-free technology. Although the combination of a price on emissions and a government subsidy to clean research has been shown to be first-best, we argue that this policy is unattainable. First, the magnitude of the necessary carbon tax seems unfeasible, and second, there can be large efficiency losses associated with public research funding. Using an endogenous growth model with directed technical change, we show how reducing patent protection on dirty technology can improve second-best outcomes. In numerical simulations, we find that combining environmental policy with patent policy can recover a substantial amount of the welfare loss in second-best, and at a lower carbon tax and clean innovation subsidy than in first-best.
The effect of carbon taxes on emissions and carbon leakage: Evidence from the European Union (2017), in: Critical Issues in Environmental Taxation, eds. Weishaar, S.E. et al. (eds.), Edward Elgar, Vol. XIX, 30-46.
Selected Work in Progress
Growing green: how state-level banking deregulation helped to reduce industrial emissions
with M. Hoffmann
Technological change and uncertain climate change information - a Bayesian Learning approach
It is commonly understood that technological change is the ultimate tool to meet climate change targets and avoid catastrophic events. However, uncertainty about the impact of global warming challenges the design of policies. This study examines the consequences of imperfect information about climate damages on the optimal direction of innovation efforts. I assume that R&D can be directed either to improve energy efficiency or non-energy technology. I first abstract from uncertainty and show the optimal allocation paths under different targets and expected climate damages. I then incorporate uncertainty about climate damages into the analysis as well as dynamic learning in a Bayesian fashion.