Chapter 3. Carbon pricing in 2015 – Detailed analysis
This chapter provides an overview of the state of carbon pricing in 2015. It shows effective carbon rates for all 42 countries combined and separately by country, discusses change between 2012 and 2015, and puts carbon pricing in a broader economic context.
This chapter provides an overview of the state of carbon pricing in 2015. It shows effective carbon rates for all 42 countries combined and separately by country. A comparison at the level of sectors reveals that effective carbon rates do not only vary substantially across sectors (as discussed in the previous chapter), but also across countries within sectors. Comparing carbon rates in 2015 with those in 2012 shows that, while carbon rates tend to increase slowly on average, some countries have made significant progress with pricing emissions more in line with social costs and long-term emission reduction commitments.
Effective carbon rates in 2015 consist of tax rates as of 1 April 2015 (OECD, 2018[1]) and average permit prices from emission trading systems for 2015 (see Annex A for details on emissions trading systems). Emission data is for 2015 and calculated from fuel use as provided by the Extended World Energy Balances (EWEB) of the International Energy Agency (IEA, 2017[2]). The coverage of emissions trading systems is estimated based on data by the authorities governing the respective systems. Effective carbon rates for 2012 consist of tax rates as of 1 April 2012, average permit prices and ETS coverage for 2012, and emissions levels in 2012.1
Share of emissions priced and price levels across countries in 2015
Across all 42 OECD and G20 countries covered in this report, 44% of carbon emissions from energy use were subject to an effective carbon rate in 2015. Rate levels remained low, with only 12% of emissions priced above EUR 30, a conservative low-end estimate of the social costs of carbon emissions in 2015. Only 9% of emissions were priced at EUR 60 or more, a midpoint estimate of the carbon prices needed in 2020 for countries to be in line with reaching their commitments from the Paris Agreement, according to the High Level Commission on Carbon Prices (2017[3]).
Aggregate numbers on carbon pricing can hide substantial differences across countries. While on aggregate 56% of emissions were unpriced across the 42 OECD and G20 countries, the simple (unweighted) average of unpriced emissions for the 42 countries was substantially lower, at 33%. This means that large emitters tend to price fewer emissions than countries that emit a smaller amount of emissions. In addition, large emitters also tend to set lower rates for those emissions that are subject to a price. While on aggregate 12% of emissions were priced above EUR 30 per tonne CO2, the simple average of emissions priced above EUR 30 across the 42 countries was 27%.
Table 3.1 shows that 15 countries priced more than 80% of carbon emissions and five (Ireland, Israel, Korea, Luxembourg and the Netherlands) priced more than 90% of carbon emissions in 2015. Price levels were generally low, with only four countries (Luxembourg, Norway, Switzerland and the United Kingdom) pricing nearly half or more of their emissions above the low-end estimate of climate costs of EUR 30 per tonne of CO2. Generally, few emissions were subject to an effective carbon rate above EUR 60 in 2015, and most of these emissions were from road transport. Table 3.6 provides more detail on effective carbon rates in the road sector.
Between 2012 and 2015, Korea and Mexico progressed strongly in pricing emissions. Korea introduced an emissions trading system, which covered most sectors of the economy in 2015, increasing the share of priced emissions by 51 percentage points, and the share of emissions priced above EUR 5 by 65 points. Mexico introduced a carbon tax in 2014 as well as increased effective excise tax rates on transport fuels (Arlinghaus and Van Dender, 2017[4]). The share of emissions priced increased by 26 percentage points (mainly through the carbon tax) and the share of emissions priced above EUR 60 per tonne of CO2 rose by 30 percentage points (through higher effective excise taxes on transport fuels). Quebec in Canada and California in the United States introduced emissions trading systems in 2013, so increasing the share of priced emissions.
The large decrease in priced emissions in South Africa results from a zero rate for the slate levy, a tax on coal products, in 2015 (South African Treasury, 2015[5]). The decrease in effective carbon rate coverage above EUR 5 in Turkey results from a depreciation of the Turkish Lira against the Euro in the same time period.
As explained above, aggregate numbers can hide the substantial progress made by some countries, because large emitters tend to price fewer emissions than countries that emit a smaller amount of emissions. Nevertheless, the share of priced emissions increased by more than 5 percentage points between 2012 and 2015 for the 42 countries as a group. The share of emissions with an effective carbon rate above EUR 30 increased by two percentage points and the share above EUR 60 by nearly four percentage points.
Priced emissions in the electricity sector in 2015
While in 2015 two-thirds of aggregate emissions from the electricity sector in the 42 countries as a group were not priced, the simple average of the share of priced emissions across the 42 countries was 62%. This means that countries with high emissions from the electricity sector tended to price fewer emissions than countries with a smaller amount of emissions. Only 1% of aggregate emissions were priced above of EUR 30 per tonne of CO2, while the simple average across the 42 countries was 3%.
Thirteen countries priced close to 100% of emissions from the electricity sector, see Table 3.3. The effective carbon rates in the electricity sector arose mostly from emissions trading systems, but Argentina, India and Israel priced large shares of electricity emissions through taxes. Most countries with nationwide emissions trading systems covered nearly all of their electricity emissions. Coverage below 100% can occur through electricity generated from biomass, for which the rate is generally zero, and small power plants, often CHP plants, below the threshold for inclusion in the system.
Emission permits traded at values between about EUR 5 to 15 in 2015. Combined with the fact that emissions trading was the main carbon pricing instrument in the electricity sector, this means that the share of emissions priced above EUR 5 was similar to the share of priced emissions for many countries. Only a few countries priced a significant share of electricity emissions at EUR 30 and above in 2015. In the United Kingdom, 79% of electricity emissions where priced above EUR 30 per tonne CO2 in 2015.
The United Kingdom introduced a Carbon Price Support (CPS) in 2013 at GBP 9 per tonne of CO2 for emissions in the electricity sector. The carbon price support is charged on top of permit prices and increased to GBP 18 by 1 April 2015. The total effective carbon rate has been slightly over EUR 30 per tonne CO2 since then.
Emissions from the electricity sector decreased by 58% from 2012, before the CPS was introduced, to 2016, the first full year for which total effective carbon rates equalled about EUR 30 (see Table 3.2). The decrease in emissions is explained by a sharp drop in the use of coal for the generation of electricity. Coal use fell by 78% in the same period. Coal was partly replaced natural gas, which is about half as emission intensive as coal per unit of energy, and partly by zero-carbon renewables.
Overall UK emissions from energy use fell by 25% in between 2012 and 2016, of which 19 percentage points can be attributed to cleaner electricity generation. British greenhouse gas emission are now below the level of 1890 (Hausfather (2018[10]), Ward (2018[11])). The British experience show how fast emissions can decline if carbon prices are at levels high enough to encourage a switch to cleaner fuels. The Dutch coalition treaty of 2017 follows on the British example by including the introduction of a minimum price for emissions covered by the EU ETS.
California included a minimum auction price for its permits when it started its cap and trade program in 2013. The minimum price increases by 5% plus inflation each year. While prices were still fairly moderate in 2015 at about USD 13 per tonne of CO2, the mandated increase in the auction price ensures that carbon price levels reach at least about EUR 30 in 2030. Ontario and Quebec follow the same approach.
The EU will introduce a Market Stability Reserve (MSR) for its ETS in 2019 (European Union, 2018[12]). The market stability reserve will remove 24% of surplus permits from the market, if the surplus of permits exceeds 833 million. A surplus of permit occurs when aggregate verified emissions are below the emission cap. The MSR will release permits into the market if the surplus falls below 400 million permits. From 2023 onwards, allowances held in the reserve that exceed the total number of allowances auctioned during the previous year they will become invalid. Research by Enerdata (2018[13]) suggests that even with the MSR, permit prices will hardly increase up to mid-2030s.2 The authors expect that the cap becomes binding only in the 2030s. Once the surplus of permits disappears, prices may soon increase. A fast increase in carbon emission prices, projected from the mid- or end-2030s onwards, can trigger a sudden loss of value of carbon intensive assets; especially if the price rise is unexpected (see the section discussing the carbon pricing gap). A minimum auction price that increases by a fixed percentage plus inflation would allow a smooth increase of carbon pricing and prevent sudden asset price revaluations.
Korea and Mexico significantly expanded their carbon pricing base in the electricity sector from 2012 to 2015. The new Korean ETS increased the share of priced electricity emissions by 77 percentage points. Mexico’s carbon tax increased the share of priced electricity emissions by 45 percentage points. China’s ETS pilots increased the share of priced emissions in the electricity sector to 14%.
As already mentioned in the previous subsection, the large decrease in priced emissions in South Africa results from a zero rate for the slate levy in 2015 (South African Treasury, 2015[5]). The significant decrease in the share of electricity emissions priced above EUR 5 in Turkey results from a depreciation of the Turkish Lira against the Euro. Israel used less oil products in 2015 compared to 2012, which are taxed at relatively high effective carbon rates, to generate electricity.
Priced emissions in the industry sector in 2015
In the industry sector, 65% of aggregate emissions from the 42 OECD and G20 countries covered in this report were unpriced in 2015. Only 2% of emissions faced an effective carbon rates larger than EUR 30 per tonne CO2. In 2012, 72% of aggregate emissions had no price.
Countries with high emissions tended to price fewer industry emissions than countries with lower amounts of industry emissions. The (unweighted) average of priced emissions across the 42 countries was 60% for industry emissions. At the same time, over a quarter of all countries analysed priced 80% of industry emissions. Rates are often above EUR 5 but significantly below EUR 30 per tonne CO2.
Few countries price a significant share of industrial emissions above EUR 30 per tonne of CO2. In Norway, natural gas used in oil and gas extraction is covered by a carbon tax in addition to being covered by the EU ETS. In Finland and Slovenia, all firms pay carbon taxes for fossil-fuel use independently of whether they participate in the EU ETS or not (OECD, 2018, p. 20[1]), Slovenia expanded the carbon tax base to include all fossil fuels, whereas in 2012, the carbon tax applied only to natural gas.
The new Korean ETS increased the carbon price base in industry between 2012 and 2015 by 55 percentage points, to 98% (Table 3.4). The share of industry emissions priced above EUR 5 increased by 86 percentage points.
This report, including Table 3.4 shows the share of emissions priced above benchmark values of effective marginal carbon rates for the 42 countries. More than 35% of the effective marginal carbon rates in industry stem from emissions trading systems (see Table 2.2). Industrial facilities subject to an ETS often receive a significant share of emission permits for free. The effective marginal carbon rate does not account for the free allocation of permits; it only takes the marginal permit price into account.
Flues and Van Dender (2017[14]) discuss how free allocation of permits can lower the incentives of firms to invest in clean technologies. They calculate an effective average carbon rate that takes into account free permit allocation and provides information on the strength of the incentives to invest in clean technologies.
Priced emissions in the residential and commercial sector in 2015
In the residential and commercial sector, 79% of aggregate emissions in the 42 OECD and G20 countries covered in this report were unpriced in 2015. Six percent of emissions faced a price above EUR 30 per tonne CO2. In 2012, 81% of emissions from the residential and commercial sector were unpriced.
Like for other sectors, inter-country differences are large, and many countries price a significant share of emissions from the residential and commercial sector. The unweighted average of the share of priced emissions is 46% across the 42 countries, the unweighted cross-country share of prices above EUR 30 and EUR 60 per tonne CO2 is 13% and 7% respectively.
Several countries price almost all residential and commercial emissions and some price these emissions at significant rates. Eight countries price more than 90% of emissions. The Netherlands and Switzerland price more than 80% of residential and commercial emissions above EUR 30 per tonne CO2. The effective carbon rate in the residential and commercial sector generally consists of both excise and carbon taxes.
In France, the share of residential and commercial emissions priced above EUR 30 increased by 23 percentage points between 2012 and 2015. Energy taxes in France have a carbon component which increases over time (Ministère de la Transition écologique et solidaire de la République Francaise, 2018[15]). In 2017, the carbon component reached EUR 30.5 per tonne of CO2, meaning that at the time of publication of this report, the vast majority of residential and commercial emissions will be priced above EUR 30 per tonne. By 2022, the carbon component is set to reach EUR 86 per tonne of CO2.
In Japan, the share of emissions priced above EUR 30 in the residential and commercial sector increased strongly as tax rates rose. The Swiss carbon tax, which applies to fuels used in the residential and commercial sector, increased from CHF 36 (about EUR 30) to CHF 60 (about EUR 50) per tonne of CO2 in 2014, because Switzerland had not reached its CO2 emission reduction goal for 2012 (Le Conseil fédéral suisse, 2013[16]). In 2016, the carbon tax increased to CHF 84 (about EUR 70) per tonne of CO2 (Le Conseil fédéral suisse, 2015[17]), so that now the majority or commercial and residential emissions are priced above EUR 60 (not shown in Table 3.5)
A number of countries expanded carbon rate coverage at rates below EUR 30 per tonne significantly between 2015 and 2012, mainly through taxing previously untaxed fuels. Iceland increased the share of priced emissions by 74 percentage points by expanding its carbon tax base to gaseous fuels. Mexico increased the share of priced emissions by 39 percentage points, mainly through the introduction of a carbon tax (OECD, 2018[1]). Spain expanded its taxbase to include biofuels for heating purposes and removed tax exemptions for natural gas and LPG. The share of priced emissions increased by 42 percentage points between 2012 and 2015. Ireland introduced a tax on solid fossil fuels in 2013, increasing the share of priced emissions in the residential and commercial sector by 23 percentage points. Poland introduced an excise duty on gaseous fuels in 2013. Its share of priced residential and commercial emissions increased by 23 percentage points.
Priced emissions in the road sector in 2015
Nearly all emissions (97%) of the road sector were priced in 2015. Effective carbon rates were significantly higher than in other sectors. 56% of aggregate emissions of the 42 countries covered have a rate above EUR 30 per tonne of CO2, and 47% also exceed EUR 60 per tonne of CO2. Compared to 2012, the share of emissions priced above EUR 60 increased by about 17 percentage points.
Many countries price close to or even 100% of road emissions above EUR 60 per tonne of CO2. The unweighted average of the share of emissions priced above EUR 60 across the 42 countries is 81%. More than three quarter of all analysed countries price 90% of road emissions above EUR 30.
From 2012 to 2015, Mexico increased the share of emissions priced above EUR 60 by 98 percentage points through reforming its excise tax regime for road fuels (Arlinghaus and Van Dender, 2017[4]). India increased the share of emissions priced above EUR 30 by 73 percentage points in the same period by increasing tax rates on road fuels.
The shares of priced emissions are calculated on the basis of fuel sold in the respective countries, as recorded in the IEA’s (2017[2]) extended world energy balances. This implies that countries that sell more fuel than used in their territory record higher emissions than if fuels used were the emission base. The energy balances do not record the amount of fuel used in a country. Countries with a high share of transit traffic and non-residents filling up their vehicles in its territories may thus record more emissions on the fuels sold compared to the fuel used base, especially when fuels are priced at a lower rate than in neighbouring countries. Other countries correspondingly show fewer emissions from sales than would be recorded on the basis of usage. OECD (2016, pp. 48-49[18]) provides more detail on countries’ shares of emissions from road transport in their overall emissions.
Many countries price all of their emission from road transport above EUR 60 per tonne CO2. Does this mean that effective carbon rates in the road sector are high enough? Not necessarily.
Road use gives rise to a range of external costs including congestion, noise, accidents and local air pollution in addition to the damage caused by CO2 emissions. Taxes on transport fuels, which account for 99% of the effective carbon rate in road transport, are a second-best instrument to internalise road use related externalities. This implies that ideally the prevailing taxes on transport energy should be compared to the full range of external costs that they are intended to cover.
A comparison of all road use related external costs is beyond the scope of the report, but an effective carbon rate of more than EUR 30 now, and EUR 60 forward looking, is justifiable. The first reason is that EUR 30 per tonne of CO2 is a low-end estimate today’s climate costs from carbon alone, EUR 60 is a low-end estimate of the climate costs in 2030 (High-Level Commission on Carbon Prices, 2017[3]) and true climate costs can be substantially higher than the low-end estimates. The second reason is that other external costs matter, and these can be high. While detailed information on the level of these costs is not at hand for all countries, some rough indications is extracted from Van Dender (2018[19]), which itself builds on sources from the European Union, France and the United Kingdom.
Based on back-of-the-envelope calculations, Figure 3.2 shows the sum of marginal external costs associated with a litre of fuel use, for France and the United Kingdom, averaged across gasoline and diesel and distinguishing between urban and rural driving. As can be seen, in the two leftmost columns, the external costs are much larger for urban driving. This is mainly because of higher congestion costs, and to a lesser extent because of greater exposure to air pollution.
In order to compare excise taxes with external costs, to know if they are approximately aligned, the external costs of congestion need downward adjustment to account for the fact that car users respond to higher fuel taxes partly by driving less (which reduces congestion) but also by investing more in fuel economy (which does not reduce congestion). Since evidence indicates that both responses are about equally large in the long run, the adjustment factor for congestion costs is 50%, as an order of magnitude. The scaled down external costs estimates are shown in the middle two columns of Figure 3.2, label mec-ft (for marginal external costs relevant to fuel tax comparison).
The adjusted marginal external costs are compared to the prevailing excise taxes. Keeping in mind that both sets of numbers (taxes and marginal external costs) are estimates, the insight is that fuel taxes appear adequately aligned with the marginal external costs of rural driving, and well below those of urban driving.
Note: MEC = marginal external cost; urban = driving in urban environments; MEC-ft = MEC as relevant to the fuel tax, i.e.. after correction for indirect impact of fuel costs on driving-related external costs; rural = driving in rural environments (to be understood as non-urban).
Source: (OECD, 2018[1])
Are fuel taxes then on average too low? The main difference between urban and rural driving pertains to congestion costs. Since congestion costs in rural driving are very low, the answer to this question depends on one’s view on how to address congestion best. As explained in more detail in Van Dender (2018[19]), fuel taxes are not very well suited for curbing congestion, and electronic charging mechanisms allow for better internalisation of congestion costs. If, however, the view is that more sophisticated congestion pricing or other congestion management policies remain elusive, then higher fuel taxes appear to be justified based on the estimates presented in Figure 3.2.
However, to allow for better congestion management and anticipating on eventual decarbonisation of road transport, it may be better to argue for more sophisticated congestion pricing than for increasing fuel taxes to reflect average congestion. Fuel taxes then would be ‘about right’ based on Figure 3.2. At this point, however, it is worth noting that the marginal external cost estimates used for Figure 3.2 should be considered as low-end estimates, particularly for air pollution, where they assume compliance with emission standards.
In sum, since fuel taxes appear to align with low end estimates of marginal external costs, and since they are in the vicinity of marginal external costs only where congestion costs are very low, current fuel taxes in France and the United Kingdom are at the low end of appropriate levels. Moderate increases are likely to engender further social benefits. If fuel taxes are thought to have a role in curbing congestion, then they at present appear to be too low. These results are similar to those of a more comprehensive exercise for EU countries (Santos, 2017[20]).
Sources: Adapted from OECD (2018[1]), OECD (2016[18]) and Van Dender (2018[19])
Carbon pricing gap across countries in 2015
The carbon pricing gap at EUR 30 was 79.5% for the 42 countries as a group in 2015. As described in Box 2.1 in more detail, the carbon pricing gap is a summary indicator to assess the extent to which countries make use of carbon pricing.
A zero gap signals to investors that a country maximises abatement and low-carbon infrastructure for each dollar invested and that its companies are on a good track to compete and thrive in a low-carbon economy. A high gap indicates countries spend more money than needed on abatement or that their climate policy is not on track to meet their commitments to decarbonise their economies as agreed at the UN Climate Conference in Paris.
The simple unweighted cross-country average of the carbon pricing gap at EUR 30 across the 42 countries was 62% in 2015, showing that countries with fewer emissions tend to price emissions more strongly than countries with large emissions.
The carbon pricing gap at EUR 30 varied significantly across countries, ranging from 27% to 100%. This shows that some countries had significantly advanced in pricing emissions, while others had hardly started doing so.
Carbon pricing progressed compared to 2012, also in countries with high emissions. The aggregate gap declined by 3 percentage points compared to 2012, the unweighted cross-country average by 2 percentage points.
Korea, Mexico and the United Kingdom substantially reduced their carbon pricing gaps between 2012 and 2015, see Table 3.7. Korea’s carbon pricing gap shrank by 30 percentage points to 43% in 2015, mainly through the introduction of its emission trading system. Mexico reformed its excise duties on transport fuels and introduced a carbon tax, reducing its carbon pricing gap by 23 percentage points. The United Kingdom lowered its gap to 42% in 2015 from 56% in 2012 by introducing a price floor for carbon emission from the electricity sector.
France decreased its carbon pricing gap by nine percentage points each between 2015 and 2012, increasing the carbon component rates in its excise duties on fuels. The Chinese gap declined slightly, mainly through its regional pilot emission trading systems. A substantially bigger drop in the Chinese gap is expected through the introduction of its national ETS, see the section on How countries can reduce the carbon pricing gap on page 31 in Chapter 2.
Note that the carbon pricing gap can also change unintentionally over time for several reasons. First, where substitute fuels subject to different rates exist, fuel substitution can affect the carbon pricing gap. For example, dieselisation of road transport tends to increase the carbon pricing gap, given the relatively low taxes on diesel. Second, by leaving tax rates unchanged in nominal terms and not adjusting them for inflation, tax rates will decrease in real terms over time. Over time, this increases the carbon pricing gap.
The carbon pricing gap at EUR 60 was 85% on aggregate for 2015, 3 percentage points lower than in 2012. The simple unweighted average of the carbon pricing gap at EUR 60 is 69% across all countries. It decreased by three percentage points compared to 2012.
The carbon pricing gap at EUR 60 varied significantly, between 30% and 100% across countries. Few countries priced a significant share of emissions above EUR 60 outside the road sector, as Section 4.1 has shown. This means that the carbon pricing gap at EUR 60 in 2015 depended to a significant extent on how fuels in the road sector were priced and what share of total emissions of a country stem from the road sector. Still, emissions priced below EUR 60 contribute to a lower carbon pricing gap at EUR 60.
As explained in the introduction, EUR 60 per tonne of CO2 is a midpoint estimate of carbon costs in 2020, as well as a low-end estimate of carbon costs in 2030, according to the High Level Commission on Carbon Pricing (2017[3]). While at least some countries have already advanced substantially to closing their carbon pricing gap at EUR 30, much more needs to be done for closing the gap at EUR 60 in the years to come.
Carbon pricing – a bigger picture
Carbon prices vary significantly across countries and sectors. This section relates the extent to which countries price carbon emissions, as measured by the carbon pricing gap, to some general macro-economic variables to gain a better understanding of patterns in how countries price carbon emissions.
Figure 3.3 shows that less populous countries tend to have a smaller carbon pricing gap than more populous countries. To the extent that larger countries emit more carbon emissions than smaller ones, this pattern helps to explain findings in the preceding section that on aggregate the carbon pricing gap is large. While some countries price a significant share of their emissions at non-negligible rates, their impact on aggregate numbers is generally limited when their share in overall emissions is low.
The current pattern may soon change with introduction of the Chinese national ETS, see Chapter 2. Once China prices a large share of its emissions significantly, the aggregate carbon pricing gap will decline substantially (see also Chapter 2).
Some fairly populous countries have recently started to decrease their carbon pricing gap as described in the previous sections. The recent carbon pricing efforts by Mexico, France, the United Kingdom and Canada also contribute significantly to lowering the aggregate gap.
Source: Population data from OECD (2018[21]) and the World Development Indicators (World Bank, 2018[22]).
Figure 3.4 shows the carbon intensity of countries’ energy uses and the energy intensity of countries’ GDPs. Multiplying the carbon intensity of energy, , with the energy intensity of GDP, , gives the carbon intensity of GDP, . Carbon intensities decrease towards the origin, i.e., the lower left corner of the graph.
Reaching the goal of the Paris Agreement to limit global temperature increase to well below 2°C requires net zero carbon emissions in the second half of this century. Scenarios congruent with the Paris Agreement by Peters et al. (2017[23]) show net zero carbon emissions for the World economy in the 2060s.3 Net zero emissions imply that either the carbon intensity of energy is zero, the energy intensity of GDP is zero, or both, as shown by the small diamonds on the vertical and horizontal axis of Figure 3.4. While zero-carbon fuels already exist, it is hard to imagine that energy intensities of GDP decline towards zero. Hence, decarbonising economies implies that countries need to move towards the horizontal axis of the graph.
Source: GDP data from the World Development Indicators (World Bank, 2018[22]), Energy use data from the Taxing Energy Use database (OECD, 2018[1]).
Equal carbon intensities of GDP are shown by four dashed-dotted isocarbon lines in Figure 3.4. A lighter colour corresponds to a lower carbon intensity of GDP. The values for the isocarbons are based on 2°C scenarios as shown in Figure 3 of Peters et al. (2017[23]). The highest carbon intensity, 0.28 kg/USD, corresponds to the level of carbon intensity for the World economy in central scenarios in 2020. The three lighter isocarbons correspond to carbon intensity for the World economy in 2030, 2040 and 2050 respectively.4
Figure 3.4 shows that many countries have a carbon intensity below the level required in 2020 by decarbonisation pathways for reaching the 2°C goal. A considerable number of countries with a large amount of emissions are still substantially above the level of carbon intensity required in 2020 for reaching the 2°C goal. On aggregate, considerable progress needs to be made for being on track with reaching the goals of the Paris Agreement.
Countries with a low carbon pricing gap , shown by lighter colour in Figure 3.4, tend to be more carbon-efficient , i.e. they have a low carbon intensity of GDP. All countries emitting less than 0.15 kg CO2 per USD in GDP have a carbon pricing gap of less than 50%. Many of the other countries with a gap below 50% show high carbon efficiencies as well.
Carbon prices raise the price of carbon-intensive energy compared to carbon-efficient energy, encouraging users to switch to more carbon-efficient fuels. Switching to more carbon-efficient fuels implies that countries move towards the horizontal axis in the graph. As long as countries use non-zero carbon fuels, carbon prices will also increase the price of energy through increasing the price of their carbon content. This encourages energy users to use less energy, making countries move towards the vertical axis.
One can expect that countries which increase and broaden carbon prices will soon improve their carbon- and energy-efficiencies. In Figure 3.4, such countries will move closer to the origin. Some countries that still had energy and carbon-intensive economies in 2015 recently broadened and increased carbon prices, among them Canada, Estonia and Korea. With their new carbon pricing efforts, one can expect that their energy- and carbon-efficiencies will improve, which will result in a movement toward the origin of Figure 3.4.
Source: GDP data from the World Development Indicators (World Bank, 2018[22]).
Figure 3.5 shows that countries with a lower carbon pricing gap are more carbon efficient, as measured by fewer carbon emissions per unit of GDP. The relationship between comprehensive carbon pricing, i.e. a low gap, and low carbon emissions does not necessarily imply a direct causal effect in either direction. Low emissions per unit of GDP can be the result of comprehensive carbon pricing steering the economy to low-emission energy sources. Alternatively, however, countries with fewer emissions per unit of GDP may find it easier to price emissions. That said, empirical evidence clearly shows that higher carbon prices discourage emissions (Arlinghaus (2015[24]), Martin et al. (2016[25])), showing in lower emissions per unit of GDP.
A simple log-linear regression of the carbon intensity of GDP on the carbon pricing gap at EUR 30 reveals that a one percentage point increase in the carbon pricing gap is associated with a 0.016 percent increase in the carbon intensity of GDP in 2015. At EUR 60, a one percentage point increase in the carbon pricing gap is associated with a 0.019 increase in the carbon intensity of GDP. A reduction of the carbon pricing gap at a higher price level thus appears to associate with a stronger decrease in emissions per GDP than the same percentage point reduction of the carbon pricing gap at a lower level.
The log-linear association between the carbon pricing gap and the carbon intensity of GDP suggests that reducing the carbon pricing gap at EUR 30 would lead to a carbon intensity of about 0.1 kg per USD of GDP. At EUR 60, a zero carbon pricing gap associates with a carbon intensity of about 0.07 kg per unit of GDP. For reaching a net zero-carbon intensity of GDP price levels will need to be higher. Over time, technological progress can also reduce the carbon intensity of GDP.
This Annex provides tables on how excluding emissions from biomass affects the shares of emissions priced at different levels of effective carbon rates. It starts with a discussion of how evidence on life cycle emissions from biomass supports the choice for including these emissions as the default for this report and related reports.
In line with previous editions of Taxing Energy Use (OECD (2013[26]), OECD (2015[27]) and OECD (2018[1])) as well as of Effective Carbon Rates (OECD, 2016[18]), this report includes emissions from the combustion of biomass in the emissions base. This means that CO2 emissions from the combustion of biomass are treated in the same way as CO2 emissions from the combustion of fossil fuels.
An alternative approach would be to assume that the net effect of production and consumption of biomass for fuels is carbon neutral as plants bind carbon from the atmosphere as they grow. Emissions from combustion of biomass would then be excluded from the emission base. The assumption of carbon neutrality from a lifecycle perspective has increasingly been challenged in the scientific literature (see, e.g., Fargione et al. (2008[28]), Searchinger et al, (2008[29]) and Liska et al. (2014[30])). The fifth IPCC assessment report states that the “neutrality perception [of biofuel emissions] is linked to a misunderstanding of the guidelines for GHG inventories” (Smith et al (2014, p. 879[31]), see also the penultimate paragraph of this Annex).
Searchinger et al. (2008[29]) note that the lifecycle approach ought to account for indirect emissions from land-use change triggered by the cultivation of biofuel crops. One potential impact is that, when biomass is planted on fields traditionally used for food production, food prices will increase. This will increase the return on agricultural land and encourages farmers to grow food on previously native land. Native land generally binds more carbon than agricultural land, and the net effect is that emissions increase. A second possible impact is that biomass for fuel production is grown on previously native land. Plants for biomass production have a shorter lifetime than native plants, meaning CO2 is bound for a shorter period, so that emissions increase.
The upshot is that taking emissions from land-use change into account is complex and quantitative modelling shows a wide range of estimates depending on the pathways, local conditions and technologies considered.
A recent study (Ecofys, IIASA and E4tech, 2015[32]) calculates the effects of land-use change for a wide range of biofuels consumed in European countries (see also Smith et al. (2014, p. 878[31]), Figure 11.24 for an earlier review of quantitative estimates) The study finds, among other things, that lifecycle emissions of biodiesel produced from food and feedstock on average exceed those of fossil fuels by about 80% (Transport & Environment, 2016[33]). This average conceals large variation. For example, there are large differences across crops: biodiesel produced from palm oil emits about three times as much carbon dioxide as fossil diesel, while biodiesel produced from sunflowers emits about the same amount as fossil diesel. Bioethanol from food and feedstock (e.g. maize, wheat, barley etc.) emits on average about two thirds of the carbon emissions from fossil diesel. Only advanced non-food based biofuels (e.g. from short-rotation coppice) are found to be potentially carbon neutral. In line with these findings, the ongoing (at the time of writing) revision of the European Directive on renewable energy (European Parliament and the Council, 2009[34]) which will update the Directive for the 2030 EU climate and energy goals, may no longer contain any target for biofuels. Instead a cap on biofuels produced from food and feedstock at 7% is being considered.
The present report calculates its emission base from the Extended World Energy Balances (EWEB) produced by the International Energy Agency (IEA, 2017[2]) as described in in Annex A of OECD (2016[18]). EWEB does not specify the source or the origins of biofuels, i.e. whether rape, soy, maize or some other input has been used to produce biofuels and where the inputs have been grown. This lack of evidence makes estimates of the lifecycle impact of biofuels more uncertain.
One indication can be extracted from one of the main scenarios of the joint ECOFYS, IASSA and E4tech (2015[32]) study, which assumes a 7% cap on biofuels produced from food and feedstock. In this scenario, overall biofuel consumption in 2020 consists of 60% biodiesel (which on average emits 80% more CO2 than fossil diesel) and 20% bioethanol (which emits two-thirds of the emissions from fossil diesel). Given this mix, overall biofuel lifecycle emissions would be close to those of fossil diesel, and would be more likely to exceed than fall below emissions from fossil diesel. Against this background, the “combustion approach” to emissions taken in Taxing Energy Use (OECD (2013[26]) and Effective Carbon Rates (OECD, 2016[18]) may also be regarded as informative about lifecycle emissions. Of course, conditions may differ across countries and across time, but in-depth analysis of the life cycle emissions from biofuels at the country level is well beyond the scope of this report.
Taxing Energy Use (OECD (2013[26]), OECD (2015[27]) and OECD (2018[1])) and Effective Carbon Rates (OECD, 2016[18]) calculate emissions from energy use directly from the IEA’s (2017[2]) EWEB as this database provides timely and consistent yearly data by fuel and user for all 42 OECD and G20 economies included in the study. By comparison, UNFCCC Greenhouse Gas inventories also cover emission sources beyond energy use (industrial process emissions as well as emissions from agriculture, forestry and other land use) and non-CO2 greenhouse gas emissions. UNFCCC greenhouse gas inventories are more difficult to compare across countries than the IEA’s EWEB as countries have significant leeway on how to report emissions. As a result, emission bases from Taxing Energy Use (OECD (2013[26]) and Effective Carbon Rates (OECD, 2016[18]) are not directly comparable with those from UNFCCC inventories.
In addition to the abovementioned differences, UNFCCC inventories account for emissions from biomass not in the category for emission from energy use, but in a different category, namely for emissions from agriculture, forestry and other land use (IPCC, 2008[35]). The present report only considers emissions from energy use, so it cannot account for emissions induced by the use of biofuels in a separate category for agriculture, forestry and other land use. The combustion approach taken here may nevertheless be informative about lifecycle emissions of biofuels as mentioned above.
The above considerations support the adoption of the combustion approach as the default for presenting results in this report. Nevertheless, the alternative assumption (neutrality from a life cycle perspective) may be of interest to specific countries or users, as it may better reflect local conditions or improve comparability with other inventories. Therefore, this annex provides tables showing results excluding emissions from the combustion of biomass. These tables can be described as showing the share of priced emissions at different levels of effective carbon rates if all biofuels used were carbon neutral. By providing this second benchmark, readers can also draw inferences on how results change given specific information about the lifecycle emissions from biofuels.
References
[24] Arlinghaus, J. (2015), “Impacts of Carbon Prices on Indicators of Competitiveness: A Review of Empirical Findings”, OECD Environment Working Papers, No. 87, OECD Publishing, Paris, https://doi.org/10.1787/5js37p21grzq-en.
[4] Arlinghaus, J. and K. Van Dender (2017), “The environmental tax and subsidy reform in Mexico”, OECD Taxation Working Papers, No. 31, OECD Publishing, Paris, https://doi.org/10.1787/a9204f40-en.
[32] Ecofys, IIASA and E4tech (2015), The land use change impact of biofuels consumed in the EU: Quantification of area and greenhosue gas impacts, Ecofys, IIASA and E4tech.
[13] Enerdata (2018), “Aligning the climate and energy framework to meet EU long-term climate ambition”, http://www.leonardo-energy.org/resources/1362/aligning-the-climate-and-energy-framework-to-meet-eu-long-te-5a82f1469befc (accessed on 19 April 2018).
[37] European Commission (2011), A Roadmap for moving to a competitive low carbon economy in 2050, http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52011DC0112&from=EN (accessed on 20 April 2018).
[7] European Energy Exchange (2015), Emission Spot Primary Market Auction Report 2015, European Energy Exchange, Leipzig, https://www.eex.com/de/marktdaten/umweltprodukte/auktionsmarkt/european-emission-allowances-auction/european-emission-allowances-auction-download (accessed on 23 March 2018).
[34] European Parliament and the Council (2009), Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC (Text with EEA relevance), https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32009L0028 (accessed on 01 June 2018).
[12] European Union (2018), “Directive (EU) 2018/ 410 of the European Parliament and the Council - of 14 March 2018 - amending Directive 2003/ 87/ EC to enhance cost-effective emission reductions and low-carbon investments, and Decision (EU) 2015/ 1814”, Official Journal of the European Union, Vol. 1933/76, http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32018L0410&from=EN (accessed on 19 April 2018).
[28] Fargione, J. et al. (2008), “Land clearing and the biofuel carbon debt.”, Science (New York, N.Y.), Vol. 319/5867, pp. 1235-8, https://doi.org/10.1126/science.1152747.
[14] Flues, F. and K. Van Dender (2017), “Permit allocation rules and investment incentives in emissions trading systems”, OECD Taxation Working Papers, No. 33, OECD Publishing, Paris, https://doi.org/10.1787/c3acf05e-en.
[10] Hausfather, Z. (2018), Analysis: UK carbon emissions in 2017 fell to levels last seen in 1890 | Carbon Brief, Carbon Brief, https://www.carbonbrief.org/analysis-uk-carbon-emissions-in-2017-fell-to-levels-last-seen-in-1890 (accessed on 19 April 2018).
[3] High-Level Commission on Carbon Prices (2017), Report of the High-Level Commission on Carbon Prices, World Bank, Washington, D.C., https://static1.squarespace.com/static/54ff9c5ce4b0a53decccfb4c/t/59b7f2409f8dce5316811916/1505227332748/CarbonPricing_FullReport.pdf (accessed on 16 February 2018).
[6] Hirst, D. (2018), “Carbon Price Floor (CPF) and the price support mechanism”, Briefing Paper, No. 05927, House of Commons Library, London.
[2] IEA (2017), Extended World Energy Balances, http://www.iea.org/statistics/topics/energybalances.
[35] IPCC (2008), IPCC Guidelines for National Greenhouse Gas Inventories – A primer, Prepared by the National Greenhouse Gas Inventories Programme, IGES, Hayama, Japan, http://www.ipcc-nggip.iges.or.jp (accessed on 01 June 2018).
[17] Le Conseil fédéral suisse (2015), Objectif de réduction 2014 manqué: hausse de la taxe CO2 sur les combustibles en 2016, Confédération suisse, Berne, https://www.admin.ch/gov/fr/accueil/documentation/communiques.msg-id-58016.html (accessed on 12 March 2018).
[16] Le Conseil fédéral suisse (2013), Objectif de réduction 2012 non tenu: hausse de la taxe CO2 sur les combustibles dès 2014, Confédération suisse, Berne, https://www.admin.ch/gov/fr/accueil/documentation/communiques.msg-id-49576.html (accessed on 12 March 2018).
[30] Liska, A. et al. (2014), “Biofuels from crop residue can reduce soil carbon and increase CO 2 emissions”, Nature Climate Change, Vol. 4/5, pp. 398-401, https://doi.org/10.1038/nclimate2187.
[25] Martin, R., M. Muûls and U. Wagner (2016), “The Impact of the European Union Emissions Trading Scheme on Regulated Firms: What Is the Evidence after Ten Years?”, Review of Environmental Economics and Policy, Vol. 10/1, pp. 129-148, https://doi.org/10.1093/reep/rev016.
[15] Ministère de la Transition écologique et solidaire de la République Francaise (2018), Fiscalité des énergies, https://www.ecologique-solidaire.gouv.fr/fiscalite-des-energies (accessed on 12 March 2018).
[21] OECD (2018), OECD.Stat, Population, OECD, Paris, http://stats.oecd.org/ (accessed on 15 February 2018).
[1] OECD (2018), Taxing Energy Use 2018: Companion to the Taxing Energy Use Database, OECD Publishing, Paris.
[18] OECD (2016), Effective Carbon Rates: Pricing CO2 through Taxes and Emissions Trading Systems, OECD Publishing, Paris, https://doi.org/10.1787/9789264260115-en.
[27] OECD (2015), Taxing Energy Use 2015: OECD and Selected Partner Economies, OECD Publishing, Paris, https://doi.org/10.1787/9789264232334-en.
[26] OECD (2013), Taxing Energy Use: A Graphical Analysis, OECD Publishing, Paris, https://doi.org/10.1787/9789264183933-en.
[23] Peters, G. et al. (2017), “Key indicators to track current progress and future ambition of the Paris Agreement”, Nature Climate Change, Vol. 7/2, pp. 118-122, https://doi.org/10.1038/nclimate3202.
[36] Quemin, S. and R. Trotignon (2018), European carbon market: Impacts of the reform and stability reserve until 2030, Dauphine Université Paris, Paris.
[20] Santos, G. (2017), “Road fuel taxes in Europe: Do they internalize road transport externalities?”, Transport Policy, Vol. 53, pp. 120-134, https://doi.org/10.1016/J.TRANPOL.2016.09.009.
[29] Searchinger, T. et al. (2008), “Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change.”, Science (New York, N.Y.), Vol. 319/5867, pp. 1238-40, https://doi.org/10.1126/science.1151861.
[31] Smith, P. et al. (2014), “Agriculture, Forestry and Other Land Use (AFOLU)”, in Edenhofer, O. et al. (eds.), Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA..
[5] South African Treasury (2015), National assembly question for written reply. Question Number 2360 [NW2772E], http://www.treasury.gov.za/publications/other/MinAnsw/2015/Reply%20to%20PQ%202360%20%5bNW2722E%5d.pdf (accessed on 19 April 2018).
[33] Transport & Environment (2016), Globiom: the basis for biofuel policy post-2020, Transport & Environment, Brussels, Belgium, https://www.transportenvironment.org/sites/te/files/publications/2016_04_TE_Globiom_paper_FINAL_0.pdf (accessed on 01 June 2018).
[9] UK Department for Business Energy & Industrial Strategy (2018), Updated energy and emissions projection 2017, Crown, London, https://www.gov.uk/government/publications/updated-energy-and-emissions-projections-2017.
[8] UK Department for Business, E. (2017), National Statistics: Digest of UK Energy Statistics (DUKES): Fuel used in generation (DUKES 5.3), https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes (accessed on 27 February 2018).
[19] Van Dender, K. (2018), “Taxing vehicles, fuel, and road use: what mix for road transport?”, forthcoming in: OECD Taxation Working Papers, OECD Publishing, Paris.
[11] Ward, A. (2018), “Coal’s rapid decline drives carbon emissions down to 1890 levels”, Financial Times, https://www.ft.com/content/47563b2a-21f6-11e8-9a70-08f715791301.
[22] World Bank (2018), World Development Indicators (WDI), The World Bank, https://datacatalog.worldbank.org/dataset/world-development-indicators (accessed on 15 February 2018).
Notes
← 1. Tax rates and permit prices are reported in 2015 price levels.
← 2. Quemin and Trotignon (2018[92]) predict that permit prices will increase moderately to about EUR 38 per tonne CO2 in absence of any major economic shock. In case of an economic crisis permit prices are expected to trade at about EUR 10.
← 3. Net carbon emissions become negative from the 2060, meaning that the amount of emissions removed from the atmosphere need to be larger than the amount of emissions emitted.
← 4. In line with recent data (OECD, 2016[18]) it is assumed that carbon emission from energy use account for 69% of total greenhouse gas emissions in 2020. Many scenarios assume that the energy use decarbonises faster than other sectors, e.g. agriculture or industrial processes (European Commission, 2011[93]). Therefore it also assumed that the share of energy use in total greenhouse gas emissions declines by one percentage point a year from 2020 onwards.