Optimal CO2 mitigation under damage risk valuation

Abstract

The current generation has to set mitigation policy under uncertainty about the economic consequences of climate change. This uncertainty governs both the level of damages for a given level of warming, and the steepness of the increase in damage per warming degree. Our model of climate and the economy is a stochastic version of a model employed in assessing the US Social Cost of Carbon (DICE). We compute the optimal carbon taxes and CO 2 abatement levels that maximize welfare from economic consumption over time under di erent risk states. In accordance with recent developments in finance, we separate preferences about time and risk to improve the model's calibration of welfare to observed market interest. We show that introducing the modern asset pricing framework doubles optimal abatement and carbon taxation. Uncertainty over the level of damages at a given temperature increase can result in a slight increase of optimal emissions as compared to using expected damages. In contrast, uncertainty governing the steepness of the damage increase in temperature results in a substantially higher level of optimal mitigation. T he DICE integrated assessment model 1,2 couples a growing global economy to a simple climate model. The economy produces emissions that accumulate in the atmosphere, change the radiative forcing, and warm the planet's surface. This warming feeds back into economic production and consumption (goods and services humans care about). The climate-economy interactions are nonlinear and delayed. Integrated assessment models such as DICE inform us about the long-term economic loss resulting from current carbon emissions and help us evaluate climate policy. Many of the interactions within and between climate and the economy are uncertain and an increasing number of studies simulate the consequences of given policies under uncertainty 2-10 . We follow Kelly and Kolstad 11 , Keller et al. 12 and Leach 13 in building a stochastic integrated assessment model that evaluates the optimal policy response to uncertainty. Optimality means that resources within and across periods are distributed to maximize the expected stream of global welfare. Our contribution is twofold. First, our optimal trade-off among consumption, emissions, and capital investment treats the damage parameters governing the relation between climate change and economic impact as stochastic. Second, we use a more sophisticated approach to evaluate the uncertain impact of climate change on economic and human welfare. Uncertainty evaluationNordhaus 2 estimates the DICE damages as a function of the global average temperature increase T t above the level prevailing in 1900. In these estimates, the fraction of global economic production lost to climate change isDICE's damage function and similar variations are widespread in the integrated assessments of climate change. The damage coefficient b 1 captures the level of damages at a 1 • C warming (damage level). The damage exponent b 2 captures the steepness of the damage increase as temperature rises (dam...

Optimal Carbon Abatement in a Stochastic Equilibrium Model with Climate Change

“…On the other hand, if climate damages are moderate as in Nordhaus and Sztorc (2013), median results over the next 100 years are similar for a level and growth rate impact. We also complement the results in Crost and Traeger (2014), Jensen and Traeger (2014), and Ackerman et al (2013), among others, who find that risk aversion has only a second-order effect in their models. By contrast, we show that risk aversion significantly matters if climate damages are severe and the temperature dynamics involve the above-described feedback loops.…”

Environmental tipping points significantly affect the cost−benefit assessment of climate policies

“…environmental tipping points has been shown to produce a precautionary optimal management response in many cases (20)(21)(22). Stochastic uncertainty surrounding climate change damages has been shown to generally increase the optimal level of mitigation (23,24). Furthermore, the combination of stochastic uncertainty and abrupt, irreversible patterns of climate change has been shown to increase optimal levels of mitigation (25,26).…”

The simple arithmetic of carbon pricing and stranded assets

“…In recent estimates of the non-climaterelated health benefits of abandoning fossil fuels (e.g. Parry et al 2014;Thompson et al 2014;West et al 2013;Ščasný et al 2015), the effects of uncertainty about the steepness of climate damages (Crost and Traeger 2014) and the potential of multiple abrupt disruptions in the climate system (Cai et al 2016;Lemoine and Traeger 2016) provide ample reasons for raising the carbon price.…”