Publications

Climate policy design must balance emissions mitigation with concerns for fairness, particularly as climate change disproportionately affects the poorest households within and across countries. Integrated Assessment Models used for global climate policy evaluation have so far typically not considered inequality effects within countries. To fill this gap, we develop a global Integrated Assessment Model representing national economies and subnational income, mitigation cost, and climate damage distribution and assess a range of climate policy schemes with varying levels of effort sharing across countries and households. The schemes are consistent with limiting temperature increases to 2 °C and account for the possibility to use carbon tax revenues to address distributional effects within and between countries. We find that carbon taxation with redistribution improves global welfare and reduces inequality, with the most substantial gains achieved under uniform taxation paired with global per capita transfers. A Loss and Damage mechanism offers significant welfare improvements in vulnerable countries while requiring only a modest share of global carbon revenues in the medium term. The poorest households within all countries may benefit from the transfer scheme, in particular when some redistribution is made at the country level. Our findings underscore the potential for climate policy to advance both environmental and social goals, provided revenue recycling mechanisms are effectively implemented. In particular, they demonstrate the feasibility of a welfare improving global climate policy involving limited international redistribution.

Climate change and inequality are critical and interrelated issues. Despite growing empirical evidence on the distributional implications of climate policies and climate risks, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. Here we fill this gap through an ensemble of eight large-scale integrated assessment models that belong to different economic paradigms and feature income heterogeneity. We quantify the distributional implications of climate impacts and of the varying compensation schemes of climate policies compatible with the goals of the Paris Agreement. By 2100, climate impacts will increase inequality by 1.4 points of the Gini index on average. Maintaining global mean temperature below 1.5 °C reduces long-term inequality increase by two-thirds but increases it slightly in the short term. However, equal per-capita redistribution can offset the short-term effect, lowering the Gini index by almost two points. We quantify model uncertainty and find robust evidence that well-designed policies can help stabilize climate and promote economic inclusion.

One of the challenges in managing the Earth’s common pool resources, such as a livable climate or the supply of safe drinking water, is to motivate successive generations to make the costly effort not to deplete them. In the context of sequential contributions, intergenerational reciprocity dynamically amplifies low past efforts by decreasing successors’ rates of contribution. Unfortunately, the behavioral literature provides few interventions to motivate intergenerational beneficence. We identify a simple intervention that motivates decision makers who receive a low endowment. In a large online experiment with 1378 subjects, we show that asking decision makers to forecast future generations’ actions considerably increases their rate of contribution (from 46% to over 60%). By shifting decision makers’ attention from the immediate past to the future, the intervention is most effective in enhancing intergenerational beneficence of subjects who did not receive a contribution from their predecessors, effectively neutralizing negative intergenerational reciprocity effects. We provide suggestive evidence that the attentional channel is the main channel at work.

A question arising from the COVID-19 crisis is whether the merits of cases for climate policies have been affected. This article focuses on carbon pricing, in the form of either carbon taxes or emissions trading. It discusses the extent to which relative costs and benefits of introducing carbon pricing may have changed in the context of COVID-19, during both the crisis and the recovery period to follow. In several ways, the case for introducing a carbon price is stronger during the COVID-19 crisis than under normal conditions. Oil costs are lower than normal, so we would expect less harm to consumers compared to normal conditions. Governments have immediate need for diversified new revenue streams in light of both decreased tax receipts and greater use of social safety nets. Finally, supply and demand shocks have led to already destabilized supply-side activities, and carbon pricing would allow this destabilization to equilibrate around greener production for the long-term. The strengthening of the case for introducing carbon pricing now is highly relevant to discussions about recovery measures, especially in the context of policy announcements from the European Union and United States House of Representatives.

Existing estimates of optimal climate policy ignore the possibility that carbon tax revenues could be used in a progressive way; model results therefore typically imply that near-term climate action comes at some cost to the poor. Using the Nested Inequalities Climate Economy (NICE) model, we show that an equal per capita refund of carbon tax revenues implies that achieving a 2 °C target can pay large and immediate dividends for improving well-being, reducing inequality and alleviating poverty. In an optimal policy calculation that weighs the benefits against the costs of mitigation, the recommended policy is characterized by aggressive near-term climate action followed by a slower climb towards full decarbonization; this pattern—which is driven by a carbon revenue Laffer curve—prevents runaway warming while also preserving tax revenues for redistribution. Accounting for these dynamics corrects a long-standing bias against strong immediate climate action in the optimal policy literature.

We find that if all countries adopt the necessary uniform global carbon tax and then return the revenues to their citizens on an equal per capita basis, it will be possible to meet a 2 °C target while also increasing wellbeing, reducing inequality and alleviating poverty. These results indicate that it is possible for a society to implement strong climate action without compromising goals for equity and development.

Reducing greenhouse gas emissions has the ‘co-benefit’ of also reducing air pollution and associated impacts on human health. Here, we incorporate health co-benefits into estimates of the optimal climate policy for three different climate policy regimes. The first fully internalizes the climate externality at the global level via a uniform carbon price (the ‘cooperative equilibrium’), thus minimizing total mitigation costs. The second connects to the concept of ‘common but differentiated responsibilities’ where nations coordinate their actions while accounting for different national capabilities considering socioeconomic conditions. The third assumes nations act only in their own self-interest. We find that air quality co-benefits motivate substantially reduced emissions under all three policy regimes, but that some form of global cooperation is required to prevent runaway temperature rise. However, co-benefits do warrant high levels of mitigation in certain regions even in the self-interested case, suggesting that air quality impacts may expand the range of possible policy outcomes whereby global temperatures do not increase unabated.

Tools are needed to benchmark carbon emissions and pledges against criteria of equity and fairness. However, standard economic approaches, which use a transparent optimization framework, ignore equity. Models that do include equity benchmarks exist, but often use opaque methodologies. Here we propose a utilitarian benchmark computed in a transparent optimization framework, which could usefully inform the equity benchmark debate. Implementing the utilitarian benchmark, which we see as ethically minimal and conceptually parsimonious, in two leading climate–economy models allows for calculation of the optimal allocation of future emissions. We compare this optimum with historical emissions and initial nationally determined contributions. Compared with cost minimization, utilitarian optimization features better outcomes for human development, equity and the climate. Peak temperature is lower under utilitarianism because it reduces the human development cost of global mitigation. Utilitarianism therefore is a promising inclusion to a set of benchmarks for future explorations of climate equity.

Background The 2018–2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces in the Democratic Republic of the Congo (DRC) is the largest ever recorded in the DRC. It has been declared a Public Health Emergency of International Concern. The outbreak emerged in a region of chronic conflict and insecurity, and directed attacks against health care workers may have interfered with disease response activities. Our study characterizes and quantifies the broader conflict dynamics over the course of the outbreak by pairing epidemiological and all available spatial conflict data.

Methods We build a set of conflict variables by mapping the spatial locations of all conflict events and their associated deaths in each of the affected health zones in North Kivu and Ituri, eastern DRC, before and during the outbreak. Using these data, we compare patterns of conflict before and during the outbreak in affected health zones and those not affected. We then test whether conflict is correlated with increased EVD transmission at the health zone level.

Findings The incidence of conflict events per capita is ~ 600 times more likely in Ituri and North Kivu than for the rest of the DRC. We identified 15 time periods of substantial uninterrupted transmission across 11 health zones and a total of 120 bi-weeks. We do not find significant short-term associations between the bi-week reproduction numbers and the number of conflicts. However, we do find that the incidence of conflict per capita was correlated with the incidence of EVD per capita at the health zone level for the entire outbreak (Pearson’s r = 0.33, 95% CI 0.05–0.57). In the two provinces, the monthly number of conflict events also increased by a factor of 2.7 in Ebola-affected health zones (p value < 0.05) compared to 2.0 where no transmission was reported and 1.3 in the rest of the DRC, in the period between February 2019 and July 2019.

Conclusion We characterized the association between variables documenting broad conflict levels and EVD transmission. Such assessment is important to understand if and how such conflict variables could be used to inform the outbreak response. We found that while these variables can help characterize long-term challenges and susceptibilities of the different regions they provide little insight on the short-term dynamics of EVD transmission.

It is often stated that optimal global climate policy requires global harmonization of marginal abatement costs – i.e., a single carbon price throughout the world. Chichilnisky and Heal (1994) have shown quite generally that this is only the case if distributional issues are ignored, or if lump-sum transfers are made between countries. Else, a policy in which different regions face different carbon prices may be superior to one with a single global carbon price from a welfare point of view. Still, most integrated assessment models (IAMs) assume away distributional issues and report a single optimal carbon price.1 We calculate utilitarian-optimal carbon prices under zero cross-regional lump-sum transfers in the multi-region IAM NICE. The result is optimal global climate policy with different regional carbon prices in which the poorest regions face initially low prices, while the richest regions face very high prices from the outset.

Deciding which climate policies to enact, and where and when to enact them, requires weighing their costs against the expected benefits. A key challenge in climate policy is how to value health impacts, which are likely to be large and varied, considering that they will accrue over long time horizons (centuries), will occur throughout the world, and will be distributed unevenly within countries depending in part on socioeconomic status. These features raise a number of important economic and ethical issues including how to value human life in different countries at different levels of development, how to value future people, and how much priority to give the poor and disadvantaged. In this article we review each of these issues, describe different approaches for addressing them in quantitative climate policy analysis, and show how their treatment can dramatically change what should be done about climate change. Finally, we use the social cost of carbon, which reflects the cost of adding carbon emissions to the atmosphere, as an example of how analysis of climate impacts is sensitive to ethical assumptions. We consider $20 a reasonable lower bound for the social cost of carbon, but we show that a much higher value is warranted given a strong concern for equity within and across generations.

Over the past few decades, we have improved our understanding of the health impacts of climate change.1 Although many public health researchers have contributed to this knowledge, relatively few are aware of how their work may relate to the social cost of carbon. The social cost of carbon is a core economic concept in climate policy and one that can—and should—benefit directly from research produced by the public health community. The concept’s importance was recently highlighted by this past year’s Nobel Prize in Economic Sciences, which was awarded to William Nordhaus in part for his pioneering work developing models to estimate the social cost of carbon. Below we describe this concept, explain how it is calculated, and provide some brief guidance on how health research can improve its estimation.

How much should the present generations sacrifice to reduce emissions today, in order to reduce the future harms of climate change? Within climate economics, debate on this question has been focused on so-called “ethical parameters” of social time preference and inequality aversion. We show that optimal climate policy similarly importantly depends on the future of the developing world. In particular, although global poverty is falling and the economic lives of the poor are improving worldwide, leading models of climate economics may be too optimistic about two central predictions: future population growth in poor countries, and future convergence in total factor productivity (TFP). We report results of small modifications to a standard model: under plausible scenarios for high future population growth (especially in sub-Saharan Africa) and for low future TFP convergence, we find that optimal near-term carbon taxes could be substantially larger.

The health co-benefits of CO2 mitigation can provide a strong incentive for climate policy through reductions in air pollutant emissions that occur when targeting shared sources. However, reducing air pollutant emissions may also have an important co-harm, as the aerosols they form produce net cooling overall. Nevertheless, aerosol impacts have not been fully incorporated into cost-benefit modeling that estimates how much the world should optimally mitigate. Here we find that when both co-benefits and co-harms are taken fully into account, optimal climate policy results in immediate net benefits globally, overturning previous findings from cost-benefit models that omit these effects. The global health benefits from climate policy could reach trillions of dollars annually, but will importantly depend on the air quality policies that nations adopt independently of climate change. Depending on how society values better health, economically optimal levels of mitigation may be consistent with a target of 2 °C or lower.

We analyze the role of ethical values in the determination of the social cost of carbon, arguing that the familiar debate about discounting is too narrow. Other ethical issues are equally important to computing the social cost of carbon, and we highlight inequality, risk, and population ethics. Although the usual approach, in the economics of cost-benefit analysis for climate policy, is confined to a utilitarian axiology, the methodology of the social cost of carbon is rather flexible and can be expanded to a broader set of social-welfare approaches.

The evaluation of climate policy has emerged as an important application of cost-benefit analysis (CBA). But the tool, as it had been most widely used previously, was not suited for this problem. Spatially, the effects of climate change transcend national boundaries and, temporally, they transcend generational time scales. CBA, in its standard form, relies on assumptions that are not fully appropriate in this context. In this essay, I discuss the shortcomings of CBA framed by its historical development and argue that its relatively recent application to climate change has contributed to growth in the literature re-evaluating its normative foundations. In relation to discounting, recent innovations emphasise aspects such as the aggregation of a multiplicity of time preferences and the distinction between inter- and intra-generational time preferences, which lead to discounting approaches that differ from the standard approach with the Ramsey equation. In relation to spatial equity, much of the recent literature argues for the use of equity weights to account for impacts on different income groups. These are significant changes relative to the orthodoxy in the field before the emergence of climate change.

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period’s discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing—rather than merely cost savings—again depends on the ethical approach to valuing population.

Integrated assessment models (IAMs) of climate and the economy provide estimates of the social cost of carbon and inform climate policy. With the Nested Inequalities Climate Economy model (NICE) (Dennig et al. PNAS 112:15,827–15,832, 2015), which is based on Nordhaus’s Regional Integrated Model of Climate and the Economy (RICE), but also includes inequalities within regions, we investigate the comparative importance of several factors—namely, time preference, inequality aversion, intraregional inequalities in the distribution of both damage and mitigation cost and the damage function. We do so by computing optimal carbon price trajectories that arise from the wide variety of combinations that are possible given the prevailing range of disagreement over each factor. This provides answers to a number of questions, including Thomas Schelling’s conjecture that properly accounting for inequalities could lead the inequality aversion parameter to have an effect opposite to what is suggested by the Ramsey equation.

Integrated assessment models of climate and the economy provide estimates of the social cost of carbon and inform climate policy. We create a variant of the Regional Integrated model of Climate and the Economy (RICE)—a regionally disaggregated version of the Dynamic Integrated model of Climate and the Economy (DICE)—in which we introduce a more fine-grained representation of economic inequalities within the model’s regions. This allows us to model the common observation that climate change impacts are not evenly distributed within regions and that poorer people are more vulnerable than the rest of the population. Our results suggest that this is important to the social cost of carbon—as significant, potentially, for the optimal carbon price as the debate between Stern and Nordhaus on discounting.