In this working package, I studied the literature covering a broad range of issues dealing with uncertainty in climate change. In particular, I focused on the role of uncertainty and how it is modeled in the context of integrated assessment modeling of climate change and economy. The innovative findings are summarized in 5 categories. First, I identified the main source of uncertainty facing policy makers that wish to stick to the Paris agreement to be the uncertainty about the transient response to cumulative emissions. This uncertainty significantly curbs the available carbon budget to keep temperature below the target, and more so if policy makers are willing to accept less risk than the two third chance of not hitting the Paris target mentioned by the IPCC. Second, I highlighted new findings that contrary to traditional cost-benefit analysis, if the effects of temperature on output growth rate (and not level) are being considered, the carbon prices can be much higher if damages are presumably severe. Third, I reported that beside climate damages, there is a high level of heterogeneity in the GHG emissions with some countries more than others. This leads to a significant free-rider problem that makes it enormously hard to achieve any global agreement on this matter. Finally, I stressed that IAM analysis needs to take aboard climate risks and implications for finance. This means a richer set of asset menus consisting of carbon-free risky assets, carbon-intensive risky assets and safe assets and detailed study of how institutional investors can decarbonize their portfolios in an efficient manner taking full account of the wide range of economic, climatic and damage risks facing them. 

To showcase the findings and generate a momentum in the debates about climate change uncertainty, I organized an international workshop on Climate change and uncertainty. It was held in Milan on February 13, 2018 and was attended by a group of international leading experts in this field.

The outcome of the workshop was published as deliverable 1 in a working paper under the title “Recalculating the social cost of carbon”. 

Climate change presents the international community with a unique challenge that we argue is comparable in scope and breadth to challenges posed by global public health threats. In this discussion paper we examine the respective global roles of the World Health Organization (WHO) and the Intergovernmental Panel on Climate Change (IPCC). Despite important differences between these two organizations and their mandates, tackling both climate change and public health challenges depend on progress in few areas of governance and communication. In this WP I outline five areas for co-learning between climate change and global public health management: timely information dissemination; transparent communication; policy coherence; multi-stakeholder contributions; and, emergency response.

There are at least three overlapping characteristics amongst the WHO and the IPCC. First, their respective epistemic framing of the underlying problem, for example that these threats are shared by large populations of people, or all of humanity. Second, the struggle to convey a strong message to the public without compromising their scientific integrity, which has constrained the soft power of the IPCC for several decades. Third, the growing and wide range of local and global actions to address the problem, for example by encouraging local communities to take responsibility for the spread of disease or greenhouse gas emissions into the atmosphere. I show how the relative success of global public health management, in contrast to the relative failure of climate change forward policy guidance, can inform the IPCC as well as the UNFCCC negotiation process. 

The outcome of this working package was published as a working paper under the title “Earth and Health: Learning Across the Boundaries of Global Governance”. 

In this working package, I focused on how uncertainty can be presented in integrated assessment models of climate change and economy. I showcased this through an example of carbon dioxide removal (CDR). This new technology has gained interests among academicians and practitioners in recent years. Many researchers and policy makers see CDR as the only way of moving forward with the current trend of greenhouse gas emissions. In order to fulfill the goals outlined in the Paris agreement, we either need to stop all the emissions in a very short time frame or use some forms of what is known as “Geoengineering” to elaborately reduce the impacts of emissions on the climate system. The CDR technologies are however still in developing phase and there are many uncertainties around their efficiency and effectiveness. One way of modeling these uncertainties is to perform a “sensitivity analysis” over a range of plausible values of the main parameters of the model. If CDR is not an option the optimal decision for the global planner is to emit less as abatement is the only option to control and reduce climate damages. When CDR is allowed in the policy mix, but with constant outgassing effect, the optimal level of emissions increases as CDR and abatement are substitutable. Finally, when the outgassing depends on how much CDR the decision maker uses, the optimal policy depends on how effectively CDR can be deployed. Outgassing cancels some of the benefits from CDR by releasing more carbon dioxide in to the atmosphere. This mechanism forces the optimal CDR to a lower level when it is less effective. Our main finding from the numerical exercise is that ignoring CDR can result in up to about 0:3% GDP loss in the case with highly effective CDR deployment. Thus, if we take into account the outgassing effect, the benefits of using CDR decreases as the outgassing effect increases. Our results also indicate that by the end of this century, CDR can potentially offset not only all emissions but also reduce the stock of existing carbon concentration.

These results are published as deliverable 2 in a working paper titled “Optimal carbon dioxide removal in face of ocean carbon sink feedback”. 

In this working package, I focused on how uncertainty can shape climate change policies and how this process can be guarded against uncertainties. In particular, we focused on the impacts of climate change on human systems and developed new methodology to study and analyze such impacts. We build a dynamic general equilibrium model with endogenous fertility and human capital decisions. In our main quantitative results, we compare the effects of climate change on economic outcomes with and without the potential for migration. In doing so, we demonstrate the role that migration plays in mitigating the negative effects of climate change. In particular, we find that the potential of migration lowers the fertility rate and increases the number of children receiving an education, when compared to a world without climate change. The increase in skilled children almost fully offsets the increased number of skilled individuals who migrate, leaving the skill composition of remaining workers virtually unchanged. The net effect on income per capita of remaining people is also very small. Thus, the mitigating impacts of migration responses occur at the level of individuals, implying that most of the benefit of migration still accrues to those who can leave. Without endogenous migration responses, climate change greatly increases inequality, but the endogenous response significantly mitigates this effect. Even after considering this response, however, inequality increases as a result of climate change.

These results are published in a working paper titled “To go or not to go: migration alleviates climate damages even for those who stay behind”.