Making climate change policies fit their own domain

A new framework acts as a sound guide for policy formation.

There is a widely held narrative for climate policy that runs something like this.  The costs of damage due to greenhouse gas emissions are not reflected in economic decisions.  This needs to be corrected by imposing a price on carbon, using the power of markets to incentivise efficient emissions reduction across diverse sources.  Carbon pricing needs to be complemented by measures to address other market failures, such as under-provision of R&D and lack of information.  Correcting such market failures can help carbon markets function more efficiently over time.  However further interventions, especially attempts by governments to pick winners or impose regulations mandating specific solutions, are likely to waste money.  This narrative, even if I have caricatured it a little, grants markets a central role with other policies in a supporting role.  Its application is evident, for example, amongst those in Europe who stress and exclusive or central role for the EUETS.

While this narrative rightly recognises the important role that markets can play in efficient abatement, it is incomplete to the point that it is likely to be misleading as a guide to policy.  A better approach has recently been characterised in a new book by Professor Michael Grubb and co-authors.  He divides policy into three pillars which conform to three different domains of economic behaviour.  Action to address all three domains is essential if efforts to reduce emissions to the extent necessary to avoid dangerous climate change are to succeed.  These domains and the corresponding policy pillars are illustrated in the chart below.

Three domains of economic behaviour correspond to three policy pillars …

In the first domain people seek to satisfy their needs, but once this is done they don’t necessarily go further to achieve an optimum.  Although such behaviour is often characterised by economists as potentially optimal subject to implicit transaction costs this is not a very useful framework.  Much better is to design policy drawing on disciplines such as psychology, the study of social interactions, and behavioural economics.  This domain of behaviour relates particularly to individuals’ energy use, and the corresponding policy pillar includes instruments such as energy efficiency standards and information campaigns.

The second domain looks optimising behaviour, where companies and individuals will devote significant effort to seeking the best financial outcome.  This is the domain where market instruments such as emissions trading have the most power.  Policy making here can draw strongly on neoclassical economics.

The third domain is system transformation, and requires a more active role from governments and other agencies to drive non-incremental change.  The policy pillar addressing this domain of behaviour includes instruments for technology development, the provision of networks, energy market design, and design and enforcement of rules to monitor and govern land use changes such as deforestation.  Markets may have a part to play but the role of governments and other bodies is central here.  The diversity of policies addressing this domain means that it draws on a wide range of disciplines, including the study of governance, technology and industrial policy, institutional economics and evolutionary economics.

As one moves from the first to the third domain there is increasing typical scale of action, from individuals through companies to whole societies, and time horizons typically lengthen.

This framework has a number of strengths.  It is both simple in outline and immensely rich is its potential detail.  Each domain has sound theoretical underpinnings from relevant academic disciplines.  It acknowledges the power of markets without giving them an exclusive or predominant role – they become one of three policy pillars.  It implies that the vocabulary of market failures becomes unhelpful, as I’ve previously argued.  Instead policy is framed as a wide ranging endeavour where the use of markets fits together with a range of other approaches.  While this may seem obvious to many, the advocacy of markets as a solution to policy problems has become so pervasive, especially in Anglo-Saxon economies, that this broader approach stands as a very useful corrective to an excessively market-centric approach.

The framework is high level, and specific policy guidance needs to draw on more detailed analysis.  The authors have managed to write 500 pages of not the largest print without exhausting the subject.  However, the essential framework is admirable in its simplicity, compelling in its logic, and helpful even at a high level.  For example it suggest that EU policy is right to include energy efficiency, emissions trading and renewables – broadly first, second and third domain policies respectively – as well as to be active in third domain measures such as improving interconnection, rather than relying exclusively on emissions trading (although as the EUETS covers larger emitters, so first domain effects are less relevant for the covered sector).

The framework in itself does not tell you what needs to be done.  In particular the challenges of the third domain are formidable.  But it provides a perspective which deserves to become a standard structure for high level guidance on policy development.

Adam Whitmore – 31^st October 2014

Costing damages from climate change offers only a partial guide to choice of policy

Estimates of the cost of damages from greenhouse gas emissions are more use for ruling in policy measures than ruling them out.

Estimates of the cost of the damages caused by greenhouse gas emissions (often referred to as the social cost of carbon) are widely used to assess the cost effectiveness of policies to reduce emissions.  Broadly speaking, emissions reductions that are cheaper than the cost of damages are judged cost-effective, while emissions reductions more expensive than the cost of damages risk being deemed not cost effective.  For example, the US EPA uses an estimate for the social cost of carbon of $39/tonne of CO₂ (in 2015 at a 3% discount rate) as its benchmark, with policy measures leading to emissions reductions at a cost lower than this being considered cost effective.  Such estimates also act as a benchmark for carbon prices, on the grounds that an economically efficient carbon price should equal the expected cost of damages [1].

Detailed modelling is used to estimate the additional costs of damage per tonne of additional emissions (see notes at the end of this post for a short summary of this process).  The modelling is often thorough and elaborate, and attempts to be comprehensive.  However there are several factors which tend to lead to estimates of the cost of damages being below what it is really worth paying to avoid emissions.

Omitted costs

Many of the costs of climate change are omitted from models, essentially assuming that they are zero.  For example, knock-on effects, such as conflict from migration, are often not modelled, but may be among the largest costs of climate change.  Other costs are dealt with only partially, because they are difficult to estimate reliably [3], or difficult to measure as a financial loss.  For example, it is difficult, and in many ways impossible, to develop adequate costings for the loss of major ecosystems.

Difficulties in estimating the effects of large temperature changes

Models designed to estimate the cost of damages for a temperature change of one or two degrees may be become highly misleading if used to estimates the costs of larger temperature changes.  Damages may increase only quite slowly with small temperature changes, but are likely to increase quite rapidly thereafter, and perhaps catastrophically when certain thresholds are reached [4].  This is often not represented adequately in models.  For example, the widely used DICE model shows GDP only approximately halving with a temperature rise of 19 degrees centigrade.  This is unlikely to be realistic, and indeed the model’s author has cautioned against its use for temperature changes above around 3 degrees.  But temperature changes above 3 degrees would be very likely under a business as usual emissions scenario, and the effects of such large temperature changes are a major cause for concern.

Treating GDP growth as exogenous

Most models assume that the drivers of GDP growth are largely unaffected by even very severe climate change.  Over a century, even slow growth (anything above 0.7% p.a.) more than doubles GDP, and so more than offsets the costs of warming even if GDP is assumed to halve from the level it would otherwise reach.  Even with a temperature rise of 19 degrees over a century people appear, on average, better off than today, because the benefits of growth (more than doubling GDP) outweigh the costs of climate change (halving GDP).  Calling this result counterintuitive is something of an understatement.

Role of risks

Analysis often excludes some risks which are difficult to model, for example some types of climate feedbacks.  This effectively assumes that they won’t happen and so won’t cause any damage, ignoring the risks.  Indeed, even attempting to set a single average cost of damages fails to address the question of willingness to tolerate the chance of a cost much larger than the estimated average (due to low probability high impact events).  The EPA does estimate of the cost in the upper tail of the damage distribution, and some other modelling explicitly includes a range of sensitivities.  However these approaches, at best, go only part way towards addressing the problem of the risk of catastrophe outcomes, especially in view of the other limitations I’ve outlined.

Finally, the process of assessing policy measures needs to take account of all costs and benefits.  Measures to reduce emissions often have valuable co-benefits for health which need to be factored in to decision making.  And analysis needs to take account of future benefits for emissions reduction, for example in promoting early stage technologies.

Estimates of the cost of damage from greenhouse gas emissions remain useful inputs into decision making.  They can be useful in ruling policy measures in – if a policy measure has a cost per tonne below even a cautious estimate of the cost of damages then it is very likely cost-effective.  But they are much less useful for ruling measures out.  It is probably worth paying a good deal more to reduce the risks of large changes to the climate than the conventional estimates of damage costs suggest.  And in any case judging which risks are acceptable will always be a matter of political and ethical debate, rather than a simple matter of costings.

Adam Whitmore – 13^th October 2014

Notes

[1] This principle that pricing of pollutants should reflect the cost of damages is commonly discussed in terms of Pigovian taxes or the Polluter Pays Principle.  

[2] The cost of damages, commonly referred to as the social cost of carbon (SCC), is usually estimated by modelling the cost of damages from additional emissions.  A base case emissions track is specified.  The changes to the climate and the resulting impacts associated with this base case emissions track are modelled.  The financial costs of the damages resulting from the impacts, for example due to rising sea levels, are estimated.  This process is repeated, adding an additional (say) billion tonnes of extra emissions, and calculating the costs of the additional damages that result.  The (discounted) additional cost of damages per tonne of additional emissions is derived from this.  These calculations are usually done using elaborate models known as Integrated Assessment Models (IAMs).  Estimates of the Social Cost of Carbon such as those used by the US EPA can refer to estimates from several different IAMs.  The uncertainties involved in the modelling lead to a wide range of estimates for the SCC. 

[3] A good survey of omissions from calculations of the SCC is given by a recent report co-sponsored by the US NGOs the Environmental Defense Fund and National Resources Defence Council:  http://costofcarbon.org/blog/entry/missing-pieces

[4] A good review of the limits of modelling can be found in Nicholas Stern, The Structure of Economic Modelling of the Potential Impacts of Climate Change, Journal of Economic Literature 2013.  This includes the reference to damages at very large temperature changes, quoting work by Ackerman, Stanton and Bueno: Fat tail, Exponents, Extreme Uncertainty: Simulating Catastrophe in DICE, Ecological Economics 69, 2010