We develop a generic and transparent calibration strategy for simple climate models used in economics. The goal is to choose the free model parameters such as to best match the output of large-scale Earth System Models from the Coupled Model Intercomparison Project, run on pre-defined emissions scenarios. We propose to jointly use four different test cases that are considered pivotal in the climate science literature: two highly idealized tests to separately examine the carbon cycle and the temperature response, and two tests closer to real scenarios, incorporating gradual changes in CO2 emissions and exogenous forcings. To illustrate the applicability of our method, we re-calibrate the free parameters of the climate part of the seminal DICE-2016 model for three different CMIP5 model responses: the multi-model mean as well as two CMIP5 models that exhibit extreme but still permissible equilibrium climate sensitivities. As an additional novelty, our calibrations of DICE-2016 allow for an arbitrary time step in the model explicitly. By applying our comprehensive suite of tests, we i) confirm that both the temperature equations and the carbon cycle in DICE-2016 are miscalibrated and ii) we show that by re-calibrating coefficients all CMIP5 targets considered can be well matched. Finally, we apply the economic model from DICE-2016 in combination with the newly calibrated climate model to compute the social cost of carbon and optimal warming. We find the social cost of carbon to be similar to DICE-2016, while the optimal long-run temperature is almost one degree lower. The social cost of carbon turns out to be much less sensitive to the discount rate than in DICE-2016. We explain how the model's climate part relates to these differences. As the temperature in DICE-2016 under optimal mitigation falls outside the range of CMIP5 projections, we caution that one might want to be skeptical about policy advice based on DICE-2016.

What are the effects of supply-side climate policies in the oil market? We use global company-level data to estimate the impact of 84 reforms of production taxes between 2000 and 2019 on oil production, exploration, and discoveries. We find that higher taxes primarily reduce companies’ exploration expenditures and oil discoveries, and also reduce short-term production of unconventional oil. We then quantify the implications for the oil market using a short- and medium-term dynamic model extending until the end of the century. Imposing a global climate royalty surcharge of 20 percentage points on oil producers reduces average annual emissions from oil by 5–7% in the first 5 years, and 9–20% in the medium term. If only OECD countries adopt this policy, 47–73% of the total emission reductions would be offset by increased production in non-OECD countries in the medium term.

We consider the effects of climate change on seasonally migrant populations that herd livestock—i.e. transhumant pastoralists—in Africa. Traditionally, transhumant pastoralists benefit from a cooperative relationship with sedentary agriculturalists whereby arable land is used for crop farming in the wet season and animal grazing in the dry season. Rainfall scarcity can disrupt this arrangement by inducing pastoral groups to migrate to agricultural lands before the harvest, causing conflict to emerge. We examine this hypothesis by combining ethnographic information on the traditional locations of transhumant pastoralists and sedentary agriculturalists with high-resolution data on the location and timing of rainfall and violent conflict events in Africa from 1989 to 2018. We find that reduced rainfall in the territory of transhumant pastoralists leads to conflict in neighbouring areas. Consistent with the proposed mechanism, the conflicts are concentrated in agricultural areas; they occur during the wet season and not the dry season; and they are due to rainfall’s impact on plant biomass growth. Since pastoralists tend to be Muslim and agriculturalists Christian, this mechanism accounts for a sizable proportion of the rapid rise in religious conflict observed in recent decades. Regarding policy responses, we find that development aid projects tend not to mitigate the effects that we document. By contrast, the effects are reduced when transhumant pastoralists have greater power in national government, suggesting that more equal political representation is conducive to peace.

The latitude gradient in comparative development is a striking fact: as one moves away from the equator, economic activity rises. While this regularity is well known, it is not well understood. In the present paper we take a step towards unpacking this gradient. Perhaps the strongest correlate with (absolute) latitude is the intensity of ultraviolet radiation (UV-R), which epidemiological research has shown to be a cause of a wide range of diseases. We establish that UV-R is strongly and negatively correlated with economic activity, both across and within countries. We propose, and test, a mechanism that links UV-R to current income differences via the impact of disease ecology on the timing of the take-off to sustained growth.

Can we reduce the damage from climate change by investing in seawalls, stilts, or other forms of adaptation? Focusing on the case of severe storms in the US, I develop a macro heterogeneous-agent model to quantify the interactions between adaptation, federal disaster policy, and climate change. The model departs from the standard climate damage function and incorporates the damage from storms as the realization of idiosyncratic shocks. Using the calibrated model, I infer that adaptation capital comprises approximately 1% of the US capital stock. I find that while the moral hazard effects from disaster aid reduce adaptation in the US economy, federal subsidies for investment in adaptation more than correct for the moral hazard. I introduce climate change into the model as a permanent increase in either or both the severity or probability of storms. Adaptation reduces the damage from this climate change by approximately one-third. Finally, I show that modelling the idiosyncratic risk component of climate damage has quantitatively important implications for adaptation and for the welfare cost of climate change.

We study the Markov perfect equilibrium in a dynamic game where agents have non-constant time preference, decentralized households determine aggregate savings, and a planner chooses climate policy. The article is the first to solve this problem with general discounting and general functional forms. With time-inconsistent preferences, a commitment device that allows a planner to choose climate policy for multiple periods is potentially very valuable. Nevertheless, our quantitative results show that while a permanent commitment device would be very valuable, the ability to commit policy for “only” 100 years adds less than 2% to the value of climate policy without commitment. We solve a log-linear version of the model analytically, generating a formula for the optimal carbon tax that includes the formula in Golosov et al. (2014, Econometrica, 82, 41–88) as a special case. More importantly, we develop new algorithms to solve the general game numerically. Convex damages lead to strategic interactions across generations of planners that lower the optimal carbon tax by 45% relative to the scenario without strategic interactions.

The paper presents a dynamic game where players contribute to a public bad, invest in technologies, and write incomplete contracts. Despite the n + 1 stocks in the model, the analysis is tractable and the symmetric Markov perfect equilibrium unique. If only the contribution levels are contractible, then investments are suboptimally small if the contract is short term or close to its expiration date. To encourage investments, the optimal contract is more ambitious if it is short term, and it is tougher to satisfy close to its expiration date and for players with small investment costs. If renegotiation is possible, such an incomplete contract implements the first-best. The framework helps to analyse emissions, investments, and international environmental agreements, and the results have important lessons for how to design a climate treaty.

I develop a directed technical change model of economic growth and energy efficiency in order to study the impact of climate change mitigation policies on energy use. I show that the standard Cobb–Douglas production function used in the environmental macroeconomics literature overstates the reduction in cumulative energy use that can be achieved with a given path of energy taxes. I also show that, in the model, the government combines energy taxes with research and development (R&D) policy that favors output-increasing technology—rather than energy efficiency technology—to maximize welfare subject to a constraint on cumulative energy use. In addition, I study energy use dynamics following sudden improvements in energy efficiency. Exogenous shocks that increase energy efficiency also decrease the incentive for subsequent energy efficiency R&D and increase long-run energy use relative to a world without the original shock. Subsidies for energy efficiency R&D, however, permanently alter R&D incentives and decrease long-run energy use.

We analyse discontinuous Markovian strategies for differential games. The best response correspondence uniquely maps almost all profiles of opponents’ strategies back to the strategy space. We thus make Markov-perfect equilibria in a wide class of differential games well-behaved, resolving a long-standing open problem. We provide a readily applicable necessary and sufficient condition for best responses and Markov-perfect Nash equilibria. We demonstrate our methods in a canonical model of non-cooperative mitigation of climate change. Our approach provides novel, economically important results: we obtain the entire set of symmetric Markov-perfect equilibria and demonstrate that the best equilibria can yield a major welfare improvement over the equilibrium which previous literature has focused on. International climate negotiations can be seen as being about coordination on good equilibria, rather than about bargaining over the limited surplus available in a dynamic prisoner’s dilemma.

Economists have widely endorsed pricing CO2 emissions to internalize climate change-related externalities. Doing so would significantly affect coal, the most carbon-intensive energy source. However, U.S. coal markets exhibit an additional distortion: the railroads that transport coal to power plants can exert market power. This article estimates how coal-by-rail markups respond to changes in coal demand. I identify markups in a major intermediate goods market using both reduced-form and structural methods. I find that rail carriers reduce coal markups when downstream power plant demand changes due to a drop in the price of natural gas (a competing fuel). My results imply that decreases in coal markups have increased recent U.S. climate damages by $11.9 billion, compared to a counterfactual where markups did not change. Incomplete pass-through would likely erode the environmental benefits of an incremental carbon tax, shifting the tax burden towards upstream railroads. Still, a non-trivial tax would likely increase welfare.