Pricing Climate Change

The concern over the negative consequences of global warming has led to a vast array of policy measures aimed at reducing the use of fossil fuels. Yet a comprehensive plan for a shift towards more climate-friendly energy is still lacking. This column argues that a major reason for this is that macroeconomists have not been sufficiently active in the policy discussion. It then lays out four lessons from macroeconomics that should be helpful.

The combustion of fossil fuels is most probably the main cause of global warming, which is likely to induce substantial costs on the global economy. There is considerable uncertainty about the strength of these effects, as well as regarding their geographic distribution. Furthermore, countries not directly hit by the negative consequences of climate change, such as perhaps the countries in northern Europe, will nonetheless be affected by various macroeconomic and political spillovers.

The concern over the negative consequences of global warming has led to a vast array of policy measures aimed at reducing the use of fossil fuels. Over the past two decades, the share of fossil fuel in energy consumption has, however, been quite stable, at around four-fifths. Renewable energy has increased, but still accounts for less than 10% of energy consumption. Wind energy has grown very fast and is now a very visible source of energy in the European landscape. Nevertheless, it only accounts for around 0.5% of total primary energy consumption in the union.

It is obvious that the transformation of our energy production and usage to make it more climate-friendly will be a very costly process, even if optimally implemented. Attempts to do it sub-optimally will likely be too costly to be politically feasible and may even not be worth their cost. Despite this, a comprehensive plan for the transformation is still lacking. This is particularly true of policies targeted at promoting so-called “green technologies”. We argue that a major reason for this is that macroeconomists have not been sufficiently active in the policy discussion. Macroeconomics can provide a number of important lessons that we believe may be very helpful.

Lesson 1

Any analysis of the effects of taxation and quantity restrictions requires an understanding of the underlying market structure. It is a well-known, but unfortunately often forgotten truth that the effects of taxing a good depend crucially on both demand and supply. Part of the fossil fuel market is characterized by prices that are high relative to extraction and transportation costs. An example of this would be Saudi Arabian oil. Such a good should be thought of as largely supplied in a fixed quantity over the foreseeable future.

Taxes, unilateral or global, have a potential confined to affecting when oil is used and who uses it, but not the overall quantity. In plain words, all cheap oil will eventually be used by someone. Other fossil fuels, such as coal, have extraction and transportation costs that are non-negligible relative to their prices. Here, taxes may affect usage, in both the short and the long run.

Lesson 2

Releasing fossil carbon is an almost perfect externality. Carbon dioxide spreads quickly throughout the atmosphere and any effect it has is independent of where it was released. The social cost of emissions is highly uncertain, depending on a number of unknown parameters. As shown in Golosov et al (2011), three separate factors are the key determinants of the social cost of emitting carbon, namely:

• How long CO2 stays in the atmosphere.
• How much damage a given CO2 concentration causes.
• How the welfare of future generations is discounted.

Given the best estimates of the first two factors and standard subjective discount rates, the social cost of emitting one ton of CO2 is on the order of €10-15. With a higher weight on future generations, the cost is higher. At a subjective discount rate of 0.1% per year, the cost is around €100 per ton of CO2 (see Figure 1).

Figure 1.

Lesson 3

The social cost of carbon is independent of who emits, where emissions take place, and when in the business cycle the emissions take place. Therefore, policies aiming at internalizing the cost of emissions into private decisions should not discriminate between different users. Currently, however, fossil fuel is taxed at very different rates depending on who uses it. Even with a wide range of uncertainty surrounding the true social cost of carbon, it is easy to find examples of existing tax schemes in the EU that are too high, as well as examples that are too low. Furthermore, the emission trading system in the EU has led to very unstable prices on emission rights. The social cost of carbon is hardly sensitive to business cycle conditions in the short run, so that the variability in the price of emission rights is likely to be inefficient. EU policy should be directed towards a harmonized and stable price for fossil fuel emissions.

Lesson 4

When emission externalities are priced correctly, arguments can be made in favour of subsidies to develop new technologies. It is well known that the full social value of developing new and better technologies is rarely fully appropriated by the developer. One can also make a logical argument in favor of subsidizing the use of particular technologies based on learning externalities. By producing and using a particular technology, knowledge is accumulated that can improve the technology and reduce its installation and operation costs. This learning is often partly an externality that can motivate a subsidy. It is key to keep in mind that this is a quantitative argument. Without a quantification of the value of the learning externality, the argument provides no policy guidance at all.

In fact, there is substantial knowledge about the learning rates of different technologies. In Table 1, we present learning rates for different “green technologies”. The learning rate is defined as the cost reduction implied by a doubling of the installed capacity. This learning rate is highest for photovoltaic solar power (17%), but is negligible for hydropower. Given these learning rates, it is possible to calculate the value of the externality and of an appropriate subsidy. In the table, we present the results from such a calculation. Many of the assumptions are such that we may interpret the results as upper bound on the subsidy. For example, it is assumed that the learning is fully external. In reality, it is reasonable to assume that a non-negligible share of the learning is appropriated by the investor. Nevertheless, the value of the externalities is in most cases fairly small. Despite this, there is an unreasonably large variation in the level of subsidies to different green technologies across the EU. The large sums spent on such subsidies, for example in the form of so-called feed-in tariffs are, in the best of cases, simply a waste. However, they may very well also be downright counterproductive (Sinn 2012).

Table 1. Cost reductions of future investments due to learning externalities in % of current investment cost

Source: IEA (2010) and own calculations.

The lessons provided above are straightforward and build on standard economic principles. If policy were to be based on them, a successful green transformation of the European economy is possible.

Editor’s note: This column is based on EEAG (2012), The EEAG Report on the European Economy, “Pricing Climate Change”, CESifo, Munich 2012, pp. 131–145. The EEAG members are Jan-Egbert Sturm (KOF Swiss Economic Institute, ETH Zurich; Chairman), Lars Calmfors (Stockholm University), Giancarlo Corsetti (Cambridge University), John Hassler (Stockholm University), Gilles Saint-Paul (University of Toulouse), Hans-Werner Sinn (Ifo Institute and LMU University of Munich), Akos Valentinyi (Cardiff Business School) and Xavier Vives (IESE Business School). They are collectively responsible for each chapter in the Report. They participate on a personal basis and do not necessarily represent the views of the organisations they are affiliated with.

References

Golosov, M., Hassler, J., Krusell, P. and A. Tsyvinski (2011), “Optimal Taxes on Fossil Fuel In General Equilibrium”, NBER Working Paper 17348.
IEA (2010), World Energy Outlook 2010, International Energy Agency, Paris, France, 2010.
Sinn, H.-W. (2012), The Green Paradox, MIT Press, Cambridge, MA, 2012

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