Simple Rules for Climate Policy and Integrated Assessment

Environmental and Resource Economics pp 1–32 | Cite as Simple Rules for Climate Policy and Integrated Assessment AuthorsAuthors and affiliations Frederick van der PloegArmon Rezai Open Access Article First Online: 18 August 2018 2 Shares 388 Downloads Abstract A simple integrated assessment framework that gives rules for the optimal carbon price, transition to the carbon-free era and stranded carbon assets is presented, which highlights the ethical, economic, geophysical and political drivers of optimal climate policy. For the ethics we discuss the role of intergenerational inequality aversion and the discount rate, where we show the importance of lower discount rates for appraisal of longer run benefit and of policy makers using lower discount rates than private agents. The economics depends on the costs and rates of technical progress in production of fossil fuel, its substitute renewable energies and sequestration. The geophysics depends on the permanent and transient components of atmospheric carbon and the relatively fast temperature response, and we allow for positive feedbacks. The politics stems from international free-rider problems in absence of a global climate deal. We show how results change if different assumptions are made about each of the drivers of climate policy. Our main objective is to offer an easy back-on-the-envelope analysis, which can be used for teaching and communication with policy makers. KeywordsSimple rules Climate policy Ethics Economics Geophysics Politics Discounting with declining discount rates Positive feedback Free riding  JEL ClassificationD81 H20 Q31 Q38  1 Introduction Our aim is to present a back-on-the-envelope integrated assessment framework that can be used to derive optimal climate policies in a transparent and intuitive way. Climate policy has to deal with several intertemporal, geophysical, and interregional aspects. To discuss these issues, we use a framework consisting of an economic part (to describe the use of fossil fuel use and its substitute renewable energy, carbon sequestration with trend growth and sector-specific rates of technical progress, global damages to economic production) and a climate part (to describe the dynamics of atmospheric carbon and global mean temperature). This framework allows us to derive welfare-maximising climate policies as simples rules for the optimal carbon price (equal to the social cost of carbon), the rate at which renewable energies are substituted for fossil fuel, the fraction of fossil that is abated by carbon capture and sequestration (CCS), the optimal timing of the transition to the carbon-free era, the maximum cumulative emissions (or the carbon budget for short) and the maximum warming level, and the amount of fossil fuel locked up forever in the crust of the earth. The geophysical, ethical and economic drivers of climate policy can thus clearly be identified. We highlight various features. Regarding the ethics of climate policy, we allow discount rates to decline with the horizon at which costs and benefits are evaluated. Since the costs of global warming occur many decades or even centuries into the future, this has important implications for policy. This feature is known as hyperbolic discounting and has been put forward by Laibson (1997). Following von Below (2012), Schmitt (2014), Belfiori (2017), and Barrage (2018) we also allow policy makers to have a lower ethical discount rate than the market. Both these features allow us to take a stance between the low discount rate used by Stern (2007) and the high discount rate used by Nordhaus (2008): policy makers use lower discount rates for long-run than for short-run appraisal of costs and benefits and may be more farsighted than the market. Both features generally lead to time inconsistency. Given simplifying assumptions, problems of commitment do not arise in our model.1 Regarding the geophysical drivers of climate policy, apart from our benchmark of simple linear carbon and temperature dynamics used by atmospheric physicists (e.g., Joos et al. 2013; Allen 2016; Aengenheyster et al. 2018) and economists (e.g., Hassler and Krusell 2012; Golosov et al. 2014; van den Bijgaart et al. 2016; Rezai and van der Ploeg 2016; Gerlagh and Liski 2018), we also allow for a model of carbon dynamics with the positive feedback loop that get unleashed as the capacity of the oceans to absorb carbon diminishes (Millar et al. 2017). Finally, regarding the political drivers of climate policy, we extend our simple rules to allow for non-cooperative decision making to illustrate the point of international free riding and the less ambitious climate policies that result from this (Barrett 2003). This addresses the problem of free riding and is relevant as long as there are no international climate deals with appropriate international transfers to ensure that the global carbon price indeed gets implemented throughout the world economy. Our objective is not to present any novel theoretical results, but to present a simple framework that is consistent with a large and sometimes hard to comprehend integrated assessment literature. We have used our framework for undergraduate and graduate teaching and in discussions with policy makers and interested lay persons. We have found it useful to highlight the drivers on climate policy and to illustrate various assumptions regarding the ethics, economics, geophysics and politics underlying climate policy.2 Our contribution ties in with the emerging literature on simple and robust rules for the optimal carbon price (e.g., Nordhaus 1991; Golosov et al. 2014; Rezai and van der Ploeg 2016; van den Bijgaart et al. 2016; Allen 2016; Dietz and Venmans 2018; van der Ploeg 2018; van den Bremer and van der Ploeg 2018). We also offer simple rules for the optimal transition time to the carbon-free era and the amount of locked up fossil fuel. These simple rules take advantage of the much faster convergence of Ramsey economic growth dynamics than that of the carbon cycle, thus greatly simplifying the complexity of the underlying system. The resulting rules are easy to understand, calculate, explain, and communicate. Furthermore, being simple feedback rules, they appear robust to different model specifications as they perform well in a wide variety of integrated assessment models (Rezai and van der Ploeg 2016; van den Bijgaart et al. 2016; Barrage 2014). A multitude of very large and detailed Integrated Assessment Models (IAMs) of the economy and the climate are able to generate numerical simulations of the optimal global price of carbon, the implied optimal substitution rates of renewable energies for fossil fuel, and the optimal sequestration rates. Although such IAMs give careful suggestions for climate policies, the key determinants of these are difficult to understand. Furthermore, it has been argued that in providing exact numbers they appear more precise than the underlying (...truncated)