Apr 11, 2011 - number of countries undertake emission reduction. Firms facing higher costs through policies such as a ca
CPB
Trade and Climate Change Johannes Bollen, Paul Koutstaal and Paul Veenendaal
11 April 2011
CPB Netherlands Bureau for Economic Policy Analysis Van Stolkweg 14 P.O. Box 80510 2508 GM The Hague, the Netherlands
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Executive Summary A major concern related to the interaction of climate change and trade is the adverse impact that climate policies might have on the competitiveness of countries which implement more ambitious climate policies compared to other countries. Differences in climate change policies will not only have an impact on trade, they can also lead to increased emissions in regions with no or less ambitious climate change policies, the so-called carbon leakage. This report discusses the impacts of the EU ETS and climate policies in other countries on competitiveness and on leakage in 2020.
The macroeconomic consequences of various climate policy scenarios have been quantified using WorldScan, a global applied general equilibrium model. The AMBITIOUS PLEDGES scenario is based on pledges in which countries set relatively stringent caps on GHG-emissions and allow free permit trade amongst each other. The other scenarios implement the more modest pledges made by countries up to the Copenhagen Climate Change Conference in December 2009. In these scenarios, there is no permit trade between Annex I countries with the exception of emission trading within the EU ETS and non-ETS.
The impacts of the policy scenarios have been assessed on the basis of the 2009 World Energy Outlook baseline. The only difference between the baseline used in this report and the WEO 2009 baseline is that the ETS has been removed from the baseline in order to establish a level playing field for our assessments of the mitigation pledges in an international context, resulting in a modest increase of GHG emissions in the EU and modest decreases Japan and the US. In the baseline, global population continues to expand. Combined with worldwide economic growth of 2.7% per year global demand for energy will be almost 30% higher in 2020 than in 2004. This expansion predominantly takes place in non-Annex I, thus partially reducing the gap in energy consumption per capita with the industrialized countries.
In terms of both environmental effects and economic costs, the scenario with ambitious pledges appears to perform best, lowering global emissions by 5% at costs similar to the costs in the other policy cases. Although emission reductions are more ambitious compared to the other scenarios, trading emission permits limits total costs. In the scenario with the Copenhagen pledges (without CDM), for example, global emissions are reduced with 3%, while costs are similar to those in ambitious pledges.
Increased carbon costs in countries which introduce climate change policies can affect not only trade, but can also lead to increases in emissions in countries without climate policies. This carbon leakage occurs because of two different mechanisms. First, due to loss of competiteveness energy intensive production and therefore emissions can increases in countries 3
without binding emission limits. Second, climate policies will reduce demand for fossil fuels and therefore prices for fossil fuels will decline. This will increase demand and therefore raise emissions in regions without climate policies (the fossil fuel price channel).
An important result from our modelling exercise is the finding that carbon leakage due to direct loss of competitiveness via the trade channel is very small. Global competition distortions caused by the absence of a carbon price in countries with no binding pledges result in direct leakage effects of 1% or less. In other words, for every 100 ton CO 2eq emission reduction in the EU, emissions go up with 1 ton only in countries with no binding pledge. However, indirect leakage through the energy price channel is considerably more important. Measures taken by countries with binding pledges to reduce emissions reduce global demand for energy and thus reduce global energy prices. This actually increases energy consumption in countries that have no binding target and take no measures. It triggers high carbon leakage effects, ranging up to 36%, depending on the scenario.
Indirect carbon leakage through the energy price channel has increased significantly in this study, compared to the earlier studies. The carbon leakage rate in our study is 36 percent in the PLEDGES scenario, which is considerably higher than the 3-11 percent leakage rates reported in earlier studies. This is due to the increased importance of fossil energy use and trade in energyintensive products by non-Annex I countries, as captured by the 2004 data (GTAP-7) used to calibrate this model (compared to 2001 data used in earlier models). Other modelling teams which use the same data also report comparably higher leakage rates.
Production leakage for energy intensive industries in developed countries is rather limited. Reductions in production levels for energy intensive industries compared to baseline are 1.4% or less, depending on the scenario. This is a very low impact, considering that in the simulations run with the WorldScan model, pledges for developing countries, such as for instance the carbon intensity target in China, under the Copenhagen Accord are non-binding. If those would be binding carbon leakage would be further lowered.
Carbon leakage can be reduced through the use of CDM, which reduces the costs of emission reductions and lowers the effect on fossil fuel prices. Another option is the use of border measures (BM) which introduce a carbon levy on imports and refunds on exports. Of the policy cases assessed CDM is the most effective option to reduce the leakage rate. CDM lowers the ETS carbon price from €31 to €9 per ton CO2-equivalent. Hence, the effect on fossil fuel prices is relatively small and therefore also leakage through the fossil fuel price channel. BM are considerably less effective in reducing leakage. The effect of BM on leakage is also far more limited in our simulations compared with earlier studies. In these earlier studies, BM would reduce leakage with 30-60 percent, while in our simulations BM reduces carbon leakage by 1 4
percentage point only
from 36 to 35 percent. BM are much less effective in reducing carbon
leakage because the fossil fuel price channel rather than the trade channel is the dominant cause of leakage. BM do not address thais fossil fuel price channel.
Within the EU, the main climate instrument which has an effect on energy intensive business is the EU ETS. Free allocation or auction of the allowances do not differ in their effect on competitiveness as long as the allocation is lump sum and companies are assumed to incorporate the opportunity cost of free allowances into their price setting. However, updating and entrance and closure rules, which makes free allowances available to entrants and ends the free allocation to firms that stop producing, can mitigate the cost increase caused by the CO 2 price to some extent. The effect of these options is comparable to output-based allocation, in which firms receive allowances on the basis of their actual emissions. The effect of free allowances on production costs have been simulated on the assumption that the cost reduction for the energy intensive sectors is equal to the entrant reserve in the ETS of 5% of total allowances available in the period 2013-2020. The resulting cost reduction is limited and therefore the effects of this form of limited free allocation hardly differ from the case without free allocation. Another variant has been simulated for the EU in which the cost reduction for the energy intensive sectors is raised to the total free allocation to these sectors. In this case the EU energy intensive sector shifts the burden of higher carbon costs to the other sectors in the economy. Emission prices in other Annex I countries will drop slightly because of smaller energy intensive production and because of a smaller fossil fuel price decrease.
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Contents Executive Summary
3
Contents
6
Preface
8
1
Introduction
9
2
Climate change policy instruments and trade
11
2.1
Competitiveness and leakage
11
2.1.1
Competitiveness
11
2.1.2
Leakage
14
2.2
2.3
Emission trading and taxes
15
2.2.1
Free allocation, auction and taxes
15
2.2.2
Output-based allocation
17
2.2.3
Updating
19
2.2.4
Entrance and closure rules
19
2.2.5
Conclusion: effects of allowance allocation methods and taxes
20
CDM
20
2.3.1
CDM and the carbon price
21
2.3.2
Distributional effects of CDM
21
2.3.3
CDM and competitiveness
24
2.3.4
CDM and carbon leakage
24
2.3.5
Further improving the effect of CDM on competitiveness and leakage
25
3
Border measures
27
3.1
Theory and design of border measures (BM)
27
3.2
Border measures and WTO
30
3.3
Economic and trade effects of BM
31
4
WorldScan scenarios
36
4.1
Policy cases
37
4.2
Baseline
38
4.3
Simulation outcomes
39
4.4
Conclusion
51
5
Trade and climate change
53
6
5.1
Trade in environmental goods and services
53
5.2
Transport, trade and climate change
57
5.3
The carbon market
58
6
Conclusions
63
References
71
7
Preface Climate change, and especially climate change policies, will impact trade in different ways. Instruments such as the EU emission trading scheme will raise the costs for energy-intensive industries, while the costs of competitors from countries with no or less ambitious emission reduction targets do not increase as much. Climate change policies will also create demand for environmental friendly goods such as renewable energy technologies.
This study provides an overview of trade and climate interactions. Quantification of the effects of climate change policy on trade and carbon leakage have been made using a version of the CGE-model WorldScan which has been developed together with Corjan Brink from the Netherlands Environmental Assessment Agency (PBL). His input in the development of this WorldScan version has been, and is, invaluable.
This study was carried out at the request of the Directorate General for Trade of the European Commission. However, the views and opinions expressed in this report do not necessarily reflect those of the European Commission.
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1
Introduction Climate change and trade interact in various different ways. At present, the main interaction is between climate change policy and trade, the effect of climate change itself on trade to date is limited. A major concern is the adverse impact which climate policies might have on the competitiveness of countries which implement more ambitious climate policies compared to other countries. Differences in climate change policies will not only have an impact on trade, it can also increase emissions in regions with no or less ambitious climate change policies, the socalled carbon leakage. In this report, we study the impact of different climate change policy instruments such as emission trading and CO2 taxes on trade and leakage, based on an overview of existing literature. Design details concerning the allocation of emission allowances and additional policy instruments such as border measures and CDM are also taken into account.
We assess the competitive effects and leakage for different policy scenarios including border measures and CDM with WorldScan, a multi-sector, multi-region, global general equilibrium model. We build upon earlier work (Wobst et al., 2007; Manders and Veenendaal, 2008; Hayden, Veenendaal and Zarnić, 2010; Boeters and Koornneef, 2010). The version of WorldScan used for this study, which is being developed together with the Netherlands Environmental Assessment Agency PBL, includes other greenhouse gases next to CO2 and renewable energy in more detail than previous versions. Furthermore, the most recent GTAPdata (Badri et al. 2008) have been used to calibrate the model. We find that the growth of energy intensive production and trade in non-Annex I has significantly raised the assessments by modelling teams of the rates of production and carbon leakage that go with unilateral climate change policies in Annex I. Yet, our assessments for various policy cases indicate that EU production leakage in 2020 for the energy intensive sector will remain relatively modest in absolute terms. We find that border measures are rather ineffective in reducing leakage rates. The fossil fuel price channel appears to be the dominant channel that causes leakage and border measures do not address this channel.
Climate change policy can not only affect sectors negatively, it will also stimulate the use of and trade in environmental goods and services. Moreover, it has given rise to new markets for carbon emission reductions such as trade in ETS allowances and CDM credits. We provide an overview of these developments and outline possible future developments on these markets.
Chapter 2 discusses competitiveness and leakage, focussing on partial studies which look at the cost increase of climate change policies such as the EU ETS and the extent to which different sectors can pass these costs on to their customers, given the level of international competition which they face. Furthermore, the impact of different policy instruments on firms‟ costs is 9
described. Chapter 3 considers the theory and design of border measures which might be implemented to protect firms from competition from countries with no or less stringent climate policies. We look at the compatibility of border measures with WTO agreements and give an overview of studies which have estimated the effects of border measures on trade and leakage. We present simulations with the WorldScan model of policy scenarios including border measures and CDM in chapter 4. In chapter 5, we provide a brief overview of climate change policies and trade in environmental goods and services and of the development of carbon markets. Finally, in chapter 6 our main findings are discussed.
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2
Climate change policy instruments and trade
2.1
Competitiveness and leakage Climate change policy will not be effective in reducing global emissions if only a limited number of countries undertake emission reduction. Firms facing higher costs through policies such as a cap-of-trade system, taxes or regulation can see their profitability reduced and might lose market share to firms in countries which no or less stringent climate change policies. Investment patterns can be influenced as well, with investment in energy intensive industries moving towards countries with no or low carbon costs. Such „carbon leakage‟ across countries (and sectors) will undo part of the realised emission reduction. EU climate policy and the EU ETS are a case in point. In Europe, firms within the ETS face a higher emission price than firms in countries which do not have to reduce their emissions. In this chapter we will describe the effect of different policy instruments on competitiveness and carbon leakage, taking into account specific instrument design and the interaction between instruments in different countries. First, we will describe the ways in which climate change policy in general can influence competitiveness and trade and discuss the various leakage channels. Subsequently, the competitiveness and leakage impact of the main climate change policy instruments (emission trading, taxes and CDM) are discussed. We will provide an estimate of the size of these effects, based on existing modelling studies.
2.1.1
Competitiveness
The effects of climate policy on trade are frequently discussed in the context of their effect on competitiveness. Competitiveness is a broad and rather vague term, which is not meaningful at the macroeconomic level (Krugman 1994). At the sector or firm level, the concept of competitiveness can encompass different elements such as changes in trade flows (imports and exports), terms of trade effects and domestic economic indicators such as employment or production (Fischer and Fox 2009). Following Reinaud (2008), we define competitiveness as the ability to maintain profits and market share. Climate change policy affects competitiveness through its effect on firms costs. Generally, climate change policies will increase a firm‟s cost. Policy instruments such as an emission cap increase a firm‟s cost directly. Direct costs consist of the abatement costs a firm has to make in order to reduce its emissions and possibly the costs of paying a tax or of acquiring allowances in the ETS. There can also be an indirect cost effect, when the price of inputs rises due to climate policies. This is, for example, the case when the aluminium industry uses electricity which is subject to an emission cap in the ETS. A firm can be subject to both cost increases, for example when it falls under the ETS cap and uses electricity from power plants which also fall under the ETS. In the next section, we will discuss in more detail the effect of different policy instruments on firms costs. 11
The extent to which increasing costs affect a firm‟s earning capacity and market share is determined by its ability to reduce costs and to pass on its cost increase to its customers. The ability to pass on costs depends on the degree of international competition, market structure, the business cycle .
For some sectors, the openness to trade and therefore competition from abroad is limited. Consequently, carbon costs can to a large extent be passed on without risk of losing market share. But even when firms compete in a worldwide, competitive market, there will always be cost differentials, because of different labour costs, taxes, capital costs, transport costs etc. The ability to pass-through climate policy costs depends on these cost differentials. In the domestic market, the price differential with competing foreign products consists of a premium for local goods and trade costs (Neuhoff 2008). This premium for local goods includes elements such as customer trust, tailored product attributes and responsiveness to new specifications. Trade costs consist of transport and storage costs, risks such as tariff risks, interruption risks and exchange rate risks. The premium for local goods and trade costs provide domestic firms with a margin within which they can pass on cost increases without losing profitability and market share. Competition from abroad can also be limited by trade barriers, either in the form of tariffs or non-tariff barriers to trade such as quota or administrative procedures. In a competitive market where all firms are price-takers, competition from abroad severely limits a firms ability to pass on carbon costs. In contrast, with imperfect competition a firm has more room to accommodate cost increases, either by accepting a lower profit margin or through a higher price and lower market share. The margin firms can make also depends on the business cycle. With high demand and limited spare capacity, firms will be more able to pass on carbon costs. In contrast, with low demand and overcapacity on a market, firms will just be able to cover their variable costs. Recouping increased costs due to climate policy will then be difficult. Firms have several options to limit the cost impact of climate change policy. One option is to reduce their emissions. This will be attractive if the abatement costs are less than the alternative of paying a tax or using ETS allowances. Another option is to replace energy intensive parts of the production chain with substitutes which are less carbon intensive. Alternatively, energyintensive inputs or intermediates can be replaced by substitutes from countries without climate policy (Neuhoff 2008). This will reduce the cost increase and therefore diminish the effect on aggregate competitiveness. In contrast, energy intensive parts of the product chain can suffer higher competitiveness impacts compared to the average for the whole product chain.
Estimating competitiveness impact Various approaches and indicators have been used to assess the competitiveness impact of climate policy. A considerable literature has developed which analyses the cost increase sectors within the EU face under the EU ETS relative to total costs (for an overview of these studies, 12
see Reinaud 2008 and Dröge et al. 2009). These studies include both sector and national or EUlevel studies (Reinaud 2005a and 2005b, Smale et al. 2006; McKinsey and Ecofys 2006, Hourcade 2007, de Bruyn et al. 2008). In most studies, a distinction is made between full auctioning of allowances and free allocation. For the moment, we will focus on the cost effect of auctioned allowances, in section 2.2 we will further explore the impact of different allocation mechanisms. The ETS increases both direct emission costs and indirect costs because of the increase in electricity prices. Assuming an allowance price of € 20/ton CO2 and full pass-through of the allowance price in the electricity price, the percentage cost increase for a number of EU sectors has been calculated by Reinaud (2005a, 2005b) and McKinsey and Ecofys (2006). In these studies, the cement industry faces the largest cost increase (38% in the Reinaud study / 36.5% in the McKinsey study), followed by refinery (24% / 20.5%), Blast Oxigen Furnace (BOF)1 steel production (15.4% / 17.3%) and primary aluminium production (8% / 11.4%). At a more aggregated level, de Bruyn et al. (2008) have calculated the cost price increase of a €20/ton allowance price for Dutch sectors. In this study, high cost increases are found in cement (8,4%), the fertilizer industry (8,1%), iron and steel, which is mainly BOF in the Netherlands (6,2%) and aluminium (6%). Another approach is to relate the cost increase to the gross value added of a sector. In a study for the UK (Grubb et al. 2007) the value at stake is calculated based on a price of €20/ton CO2 which is defined as the ratio between the carbon cost increase and the value-added of a sector. Cement has the highest value at stake (15%), the iron and steel sector and refining and fuels both have a value at stake of 6%. Overall, the (sub)sectors which show the largest cost increase as a result of carbon pricing are cement, basic iron and steel, fertilizer, refining and fuels, aluminium, and paper. Differences within a sector can be considerable, depending on the aggregation level (Hourcade 2008). For example, the paper sector includes both energy-intensive paper (pulp) producers and publishing companies whose energy costs are much smaller compared to total costs. In the iron and steel sector, the production of iron an steel from ore with the BOF process is the most carbon-intensive, production from scrap iron is considerably less so. Consequently, analysis at sufficiently disaggregated level is necessary to identify which firms are most at risk of losing competitiveness because of climate policies.
Assessment of the cost increase caused by climate policy is a first step in assessing the impact on competitiveness and trade. In addition, it has to be considered to what extent a market is open to international competition. One approach is to consider the openness of a sector to trade, as has been done in the study by Grubb et al. (2007) which considered the openness of UK sectors in terms of trade intensity. Trade intensity is defined as the ratio of trade volume and market size. Trade volume is the sum of exports and imports; market size is the sum of domestic production plus demand plus exports. For the sectors with relative high carbon costs 1
BOF steel production is the production of steel from iron ore. 13
identified above, the aluminium sector shows the highest trade intensity of more than 35%. Iron and steel has a trade intensity of almost 20%, refining and fuels of more than 10%. While trade intensity provides an indicator of the openness to trade of a specific sector, it is only a first step in analysing the possibility to pass-on the carbon costs. International trade exposure will change in time, due to factors such as changing industry structure, exchange rate changes and cost changes such as changes in carbon costs (Neuhoff 2008). Trade intensity is also used by the European Commission to determine whether a sector is exposed to a significant risk of carbon leakage. This is assumed to be the case if: -
both direct and indirect costs of carbon exceed 5% of gross value added and the intensity of trade is above 10%2
-
if the cost increase is more than 30% of gross value added
-
if trade intensity is above 30%
Based on these criteria and a carbon price of €30 per ton CO2 (the average carbon price of the Commission‟s impact assessment), the Commission has established the sectors which are exposed to a significant risk of carbon leakage (Decision EC 2009e). With 151 of the 258 European industrial sectors in the 4-digit NACE classification, almost all energy intensive sectors are marked as being exposed to a significant risk of carbon leakage.
In addition to the ex-ante studies on the effects of climate change policy, there is a large empirical literature on the effects of environmental policy on competitiveness and trade. We will not discuss these studies in detail. The conclusions from this literature are ambiguous (see Lankowski 2010), there is no definite conclusion on the impact of environmental policy on competitiveness. One of the reasons for this lack of clear empirical results on the relation between environmental policy and competitiveness is the limited stringency of environmental policy. Therefore, this literature is not very relevant for the analysis of more stringent climate change policies which can potentially have a larger impact on costs than environmental policies have had so far.
2.1.2
Leakage
Reduced competitiveness for firms from countries with more stringent climate policies can lead to an increase in emissions in countries with no or less stringent climate policies. This carbon leakage reduces the environmental effectiveness of the climate policy measures. There are two main channels for carbon leakage. First, asymmetric carbon prices change relative prices between domestic and foreign production. In the short run, domestic firms can lose market share at the expense of foreign firms, who will increase their production and therefore emissions. The carbon emission reduction is therefore partly undone.
2
Calculated as the ratio between the total value of exports plus imports from outside the EU and the total market size within
the EU (turnover plus imports). 14
In addition to this short run operational leakage, in the longer run carbon price differentials will also influence investment patterns (investment leakage). New investment in energy intensive industries becomes more attractive in countries without stringent climate change policies, therefore in the longer run emissions in these countries will increase further. Decisions on where to invest are influenced by many factors, one of which are the costs of environmental policy. Capital intensive industries have sunk costs, which can make relocation costly, especially if reinvestment is incremental to existing plants. Other factors are the availability of skilled labour and access to inputs. Moreover, over the lifetime of an investment, a new host country might implement climate policies as well, reducing the advantage of relocation. Another risk is the possibility that export markets with stringent climate policies might impose border measures such as tariffs on carbon-intensive products. The second main channel of carbon leakage occurs because asymmetric carbon prices affect the relative prices of manufactured goods, but also because they drive down fossil fuel prices globally. The increased costs of emitting greenhouse gases will reduce demand and therefore the price for fossil fuels. As a result of lower fossil fuel prices, the use of fossil fuels and therefore emissions will increase in non-abating countries.
2.2
Emission trading and taxes The effects of climate change cost on competitiveness and leakage not only depends on the stringency of the target, but also on the type of policy instruments used and on the specific design of these instruments. The reason for this is that different instruments and different design options imply different magnitudes of the cost increase which firms have to face. The main instrument affecting the energy intensive sectors within the EU is emission trading. In other countries, policy proposals mainly concentrate on emission trading as well. We will therefore focus on the instrument of emission trading.
2.2.1
Free allocation, auction and taxes
In the text book emission trading scheme, an absolute cap is set on the emissions. Emission sources which fall under the scheme have either to buy their emission allowances or they receive allowances for free. In such a cap-and-trade emission trading scheme, the marginal cost increase for firms equals the price of allowances. This cost increase is the same for all firms, and as a result total costs are minimized.3 A tax on emissions would lead to an identical outcome. There has been considerable discussion in the literature on the competitiveness impact of free lump sum allocation (grandfathering) versus auctioning of allowances. While grandfathering
3
It is well established in the economic literature that an emission trading system can lead to a cost-effective outcome in
which polluters have incentives to reduce their emissions up to a point where their marginal abatement costs (including the price of the permit to pollute) are equal. The same holds for a tax (Pezzey, 1992) 15
reduces the out-of-pocket costs compared to auctioning or a tax, it does not alter a firm‟s decision at the margin. Due to the opportunity costs of using grandfathered allowances, marginal costs increase, both when allowances are allocated for free or auctioned. Firms which maximise profits will still pass-through much of the opportunity costs, realising profits at the expense of some loss of market share (Smale et al. 2006). Grandfathering therefore is of limited use in protecting firms from foreign competition, because marginal cost still increase (Grubb et al. 2007). Free lump sum allocation is not only of limited value in reducing operational leakage, it also does not reduce investment leakage. Firms which decide to move new investments to countries without stringent climate policies can sell the allowances they receive free of charge. The major difference between grandfathering and an auction or tax is the effect on the profit of firms. With grandfathering, firms receive a lump sum wealth transfer, while with auction or taxes these profits are taken away by the auction or tax. Bovenberg and Goulder (2001) show how grandfathering can be used to compensate firms for earlier investment in capital goods that loses some of its value because of the introduction of emission trading.
Free allocation of allowances is usually based on historic emissions, adjusted in order to meet the overall emission cap. This has been the approach generally taken by the member states in the ETS so far. For the third phase of the ETS, Article 10 of the directive stipulates that emissions will be allocated “through harmonised Community-wide rules” (Directive 2009/29/EC). The amended Directive gives some indications on how to determine the benchmarks on which these harmonised rules will be based. Article 10a(2) reads: "In defining the principles for setting ex-ante benchmarks in individual sectors or sub-sectors, the starting point shall be the average performance of the 10% most efficient installations in a sector or sub-sector in the Community in the years 2007-2008. The Commission shall consult the relevant stakeholders, including the sectors concerned." The number of allowances a firm will receive for free then depends on historic capacity use or production levels and the emission rate per unit of product given by the benchmark. The advantage of using benchmarks is that firms which have already reduced their emissions in an earlier period (“early action”) and emit less than the benchmark are rewarded with more allowances than they need instead of punished as is the case with grandfathering on the basis of historic emissions without benchmarks. Benchmarks however do increase the administrative burden compared to grandfathering because the benchmarks have to be established. In addition, for installations which produce more than one product, it has to be determined which emissions belong to which products (in terms of the benchmark approach under consideration at the moment by the Commission, the installation has to be divided into sub-installations (Umweltbundesamt 2010)). The main administrative burden occurs with the initial data collection and drafting of the benchmarks. Once they have been formulated, keeping benchmarks up-to-date requires little additional effort, as has been shown by the experience with the Dutch Benchmarking Covenant (see Monjon and Quirion 2010). 16
Another issue related to benchmarks is the level of disaggregation related to the fuel mix used in the production. Should there be a separate benchmark for the same products which are produced with different types of fuel mix and therefore different levels of CO2 emissions? From an incentive point of view, the effect is small. Regardless of the number of allowances grandfathered, with lump sum allocation it remains attractive to reduce emissions. It can however have considerable distributional effects. With a fuel-independent benchmark, firms which use more carbon intensive fuels will receive less allowances than needed while firms with relative clean fuels benefit by receiving more allowances than they need. The use of benchmarks for the allocation of free allowances does not have an effect on the consequences of grandfathering for on competitiveness and leakage. The main effect compared with grandfathering on the basis of historic emissions is in the distribution of the allowances. The 10 percent of the firms with lowest emissions within a benchmark will receive excess allowances per unit of output produced, while the other 90 percent will be short on allowances per unit of product given their emission rates.
Grandfathering of allowances, either on the basis of historic emissions or with the aid of a benchmark, does not alleviate competitiveness. However, there are other options for free allocation which do have an effect on competitiveness, such as output-based allocation and entrance and closure rules for the allocation to firms that either close or enter a market. In the ETS these options have been applied to some degree.
2.2.2
Output-based allocation
In the standard cap-and-trade emission trading scheme, allowances are either auctioned or grandfathered to established firms in a lump-sum way. An alternative is to relate the allowance allocation to the activity of a firm such as its actual emissions or output. In such an output-based allocation, a performance standard is set which determines the number of allowances a firm receives per unit of output (Fischer 2001, Koutstaal 2001, Gielen et al. 2002). This is comparable to the benchmark approach which is currently being investigated by the European Commission, where the number of allowances allocated to firms is based on a benchmark which is also expressed as a number of allowances per unit of output. An important difference however with benchmarking is that with output-based allocation the number of allowances a firm receives is determined ex-post on the basis of actual output. In the benchmarking approach, a benchmark is used to determine the number of allowances based on output in an earlier period. With output-based allocation, the cap on emissions will not be absolute but depends on total output of firms in the emission trading scheme. An increase in output therefore will lead to a higher level of emissions, the cap on emissions is relative. An option is to use an adjustment factor in the allocation of allowances in order to limit the total allowances allocated ex post to
17
an absolute cap. With a higher level of output, the adjustment factor will be higher and firms will receive less allowances per unit of output. With output-based allocation, firms have an incentive to increase their output in order to receive more free allowances. This is in contrast to emission trading with auctioning or free lump-sum allocation, where there is no relation between current activity and the quantity of allowances a firm will receive. Output-based allocation is equivalent to a subsidy which is equal to the number of allowances allocated per unit of output times the price of the allowances. The total effect is that emission trading with output-based allocation acts as a combination of a carbon price combined with a subsidy. Firms are both stimulated to reduce their emissions because of the carbon price and to increase their output because of the subsidy of the output-based allocation. Consequently, under output-based allocation marginal costs and therefore product prices will be lower compared with standard cap-and-trade emission trading and industry output will therefore be higher. The competitiveness impact of emission trading with output-based allocation will therefore be less than with pure grandfathering or auctioning of allowances.
Fischer and Fox (2004) have investigated output-based allocation with a CGE-model (GTAPEG). They assume that only the US implements climate change policy, with an emission reduction target of 14% in 2016 compared to the emissions in 1997. In the study, output basedallocation is compared with other allocation options such as auctioning and grandfathering on their effects on indicators such as welfare, production, allowance price, output and leakage for the US. The total emission cap is absolute, therefore the rate at which firms receive free allowances is adjusted in order to limit the number of allowances allocated to the sector-level allocation. This sector-level allocation is based either on historic emissions, which favours energy-intensive industries, or on sector value-added. The model also includes a distortionary tax on labour. Using the revenues from an auction of allowances to lower this distortionary labour tax will therefore be welfare improving compared to grandfathered allowances. Given our focus on the results for trade and leakage of the allocation method, we will focus on the difference in effects of the allocation methods. The simulations show that output-based allocation has a less negative effect on welfare, -0.05 percent change compared to the baseline, than grandfathering of the allowances, -0.07 percent compared to the baseline. This is also reflected in the change in production, -0.44 percent for grandfathering versus -0.29 percent in the case of out-based allocation. With output-based allocation, the output in energy-intensive sectors falls considerably less because of the implicit subsidy of the allocation method. The allowance price is therefore higher with output-based allocation than with grandfathering (about $40 in the former versus about $30 in the latter case), because (more expensive) emission reductions will have to be found elsewhere in the economy. The difference in the effect on trade for the energy-intensive sectors is large. With output-based allocation, the reduction in net exports in the iron and steel industry is only 6% of the reduction in net exports in the case of grandfathering. In the chemical industry, this ratio is 24%, in 18
nonferrous metals 13%. The nonferrous metals sector does not profit from output-based allocation itself, instead it profits from the lower electricity price which results from the outputbased allocation to the electricity sector. The extent to which competitiveness loss is mitigated depends strongly on the choice of sector allocation. Allocation of the sector cap on the basis of historic emissions provides the largest subsidy to the energy intensive industry. It also yields the largest benefit in terms of reduction of carbon leakage. The increase in emissions outside the US, expressed as a percentage of the emission reductions within the US (carbon leakage), is 13% in the case of grandfathering while it is 8.6% with output-based allocation.
2.2.3
Updating
So far, the allocation of free allowances in the EU ETS is based on an earlier reference period. In the first phase, 2005-2008, countries were allowed to base the allocation within the National Allocation Plans on one or more years before 2005. The same held for the second phase, 20082012. For the third phase, the way in which allowances are allocated for free to firms from carbon-intensive, exposed sectors (see above) has not yet been specified precisely. However, the amendment to directive () stipulates that the amount of allowances allocated to installations may not exceed the percentage of the corresponding emissions in the period 2005 to 2007 that those installations emitted. The reference period will therefore be updated, from before 2005 to the period 2005-2007. When firms anticipate such an update, they will have an incentive to reduce their emissions less, which is comparable to the effects of output-based allocation described above. The effect however will be less because of the longer time it takes before the increased emissions or output results in increased allocation of free allowances. The cost reduction will therefore also be less.
2.2.4
Entrance and closure rules
In the EU ETS, there are special rules for new firms that are subject to the ETS and for firms that stop producing. Under the entrant provision, new firms will receive allowances for free, based on their expected emissions. Ellerman (2006) analysed the effect of these entry and closure provisions for both the short and the long run. With an entrant provision, firms which enter the market receive a subsidy in the form of a free allocation of emission allowances. This distorts the decision on whether to entry or not, with more firms entering a market than is efficient (see also Baumol and Oates, 1988, chapter 4, on the entry inducing effect of subsidies). The same holds for exit from the market. In emission trading with a closure provision, firms which leave the market do not receive free allowances any more in a subsequent phase. Consequently, their decision whether or not to leave the industry will be distorted, with firms continuing to produce longer than is efficient. The subsidy of free allowances will reduce future marginal costs and therefore reduce the effect of emission trading on the competitiveness of firms. The effect of entry and closure rules will predominantly affect investment leakage, because it directly influences a firm‟s decision when and where to close plants and to invest in 19
new plants. The prospect of receiving free allowances when investing in a new plant will reduce the advantage of moving outside the region with carbon restrictions.
2.2.5
Conclusion: effects of allowance allocation methods and taxes
Free lump sum allocation of allowances has little effect on the competitiveness impact of climate change policies on firms because it does not influence their decision at the margin. Firms which maximise profits will still pass-through much of the opportunity costs, realising profits at the expense of some loss of market share. Investment decisions will also not be influenced by a free lump sum allowance allocation; it remains as attractive as with a tax or auction to invest in countries without climate policies and sell the grandfathered allowances. The main difference between free lump sum allocation and an auction or a tax is the effect on firm profits. Grandfathering corresponds to a wealth transfer, which increases profits compared to an auction or tax. In contrast to grandfathering, output-based allocation, updating and entry and closure rules do mitigate the competitiveness and leakage effect of emission pricing. To a larger or lesser extent these allocation methods will all reduce the cost impact of emission trading because they also include a subsidy element. Output-based allocation has the largest cost-reducing impact, this is considerably less with updating. The ETS includes some updating, output-based allocation is not used. Overall the effect on competitiveness and leakage is probably limited. The entry and closure rules in the ETS will have more of an impact on competitiveness, especially with regard to investment and closure decisions. When new firms receive a free allocation, carbon costs will be less of an issue in location choice for investments. The same holds for plant closure and relocation of production. If free allocation is stopped when firms cease operating, the cost advantage of moving production outside the EU is lessened because firms will forego future free allocation of allowances. When carbon emissions are taxed instead of capped with emission trading, there are less options to reduce the competitiveness impact of climate policy4. In most countries which have used carbon and energy taxes, energy-intensive industry has been exempted from the tax or a low tariff has been applied. The cost increase for these firms therefore has been nil or negligible, while there also have been no or insignificant emission reductions either.
2.3
CDM An important reason for the inclusion of CDM in the Kyoto Protocol is the possibility to reduce the costs of realising emission reductions. CDM has an effect on the costs of emission reduction both on firms which use CDM-credits such as the EU ETS firms and on firms in the host countries for CDM projects, the competitors of EU ETS firms. In order to explore the effect of 4
In theory, emisison trading and taxes are identical, see Pezzey () on the comparison of taxes and emission trading. In
practice however it will be difficult to achieve the same results with a tax as with allocation rules in emission trading. 20
CDM on the competitiveness of both these firms and on leakage, we will first discuss the effect CDM has on the costs of firms in CDM host countries which sell credits to firms under the ETS. Subsequently, we will describe how the use of CDM in the EU ETS influences the distributions effect of CDM for both firms in host countries and firms in the EU ETS. Last, we will discuss the effect CDM has on carbon leakage.
2.3.1
CDM and the carbon price
In the case of CDM, the cap on emissions is not absolute but relative to the business-as-usual baseline. Firms in CDM host countries can get credits if the level of emissions after the CDM project has been implemented falls below the baseline. In other words, for all emission reductions below the baseline they get some form of „subsidy‟. An individual firm will have the same incentives to reduce its emission levels under a cap-and-trade system and CDM. In both cases, a firm‟s marginal abatement costs will increase and the firm will reduce its level of emission until the marginal abatement costs equals the marginal price of emissions. In both situations, marginal costs are increased up to the point where the costs of reducing emission equals the permit price. Consequently, in the short run CDM is equivalent to emission trading with an absolute ceiling and firms reduce their output and thereby their emission level. However, the long run equilibrium implications of CDM and emission trading with an absolute ceiling are different. The subsidy granted by CDM leads to a decrease in a firm‟s average costs. Output prices will be lower and industry output of sectors in CDM host countries which sell CDM credits will expand. This long run equilibrium effect is comparable to output basedallocation or the entrance and closure provisions in the ETS discussed above. The baseline can be seen as a free gift, just as the emission allowances granted to new firms under emission trading with an entrant provision. The same holds for exit from the market. In emission trading with a closure provision, firms which leave the market do not receive free allowances any more. With CDM, a firm which leaves a market will lose the ability to sell CDM credits, it cannot sell its baseline. Therefore firms will remain in the market, even though this would not be profitable without the possibility to sell credits.
2.3.2
Distributional effects of CDM
CDM is not only attractive for firms in host countries which can sell credits, it also offers the opportunity to firms under the ETS to use emission reductions from countries which do not have an emission reduction target in the form of a cap such as the Annex-B countries of the Kyoto-protocol. This is attractive because those options are in general less costly than the measures which would be needed when emissions could only be reduced in the Annex-B countries. Allowing for the use of low-cost CDM projects in an emission trading scheme such as the EU ETS therefore creates an intramarginal rent. When CDM credits and emission allowances can be freely exchanged, the sellers of CDM credits will acquire an intramarginal rent on their credits. The total intramarginal rent for sellers of CDM is equal to the difference 21
between the revenue from selling credits and the costs incurred in producing these credits, see Figure 2.1. The x-axis shows the allocation of the emission reduction needed to meet a given target between CDM and emission trading in the ETS. The optimal distribution is at Q*, where the marginal costs of CDM and emission reductions in the ETS are equal and the price of ETS allowances and CERs is P. The intramarginal rent for producers of CDM equals the light grey triangle, the area above the marginal cost curve for CDM. Figure 2.1
CDM rent
Introducing a limit on the use of CDM credits, as is the case in the ETS where the use of CERs is restricted, limits the volume of low-cost CDM credits available for the ETS. These will have to be replaced by more expensive emission reduction options, which drive up the price of CO2 in the ETS. It will also create an additional rent on CDM credits on top of the intramarginal rent. This is illustrated in Figure 2.1. Line QL* represents the limit set on CDM. This reduces marginal costs for CDM to PLCDM, while it drives up the price in the ETS to PLETS. The additional equals the dark grey rectangle. This rent will either fall to the buyers or the sellers of CDM credits. This depends on the degree of competition between both sellers and buyers. On the buyers side, the number of (potential) participants on the CDM market is large, with both ETS firms and governments from within and outside the EU interested in using CERs to meet their GHG-targets. On the sellers side, the situation is less clear. There is in principle a large number of prospective CER producers, given that firms from all non-Annex I countries can generate CERs. In practice, however, competition might be more limited. China has a dominant position on the CDM market, supplying 72% of the CERs brought onto the market in 2009 (World Bank 2009) and the Chinese government‟s policy of demanding minimum prices for
22
CERs, depending on the project type5, which has acted as an unofficial price floor. Moreover, the time needed to develop projects and finally produce CERs is considerable. For example, in 2009 it took on average 607 days from the date of registration of a project in the UN database to the first issuance of CERs (World Bank 2010). This limits the supply of CERs for the period 2008-2012 and also reduces competition. Currently, the price of CERs is about 10 percent lower than the price for EU ETS allowances.6 This can reflect some form of market power on the side of CER producers such as China. Another explanation would be that the costs of CDM at the margin approach the costs of the EU ETS allowances. Low-cost options such as industrial gases are becoming exhausted, instead more expensive options such as renewable energy are entering the market (World Bank 2010). In both cases, the rent for the producers of CERs increases, which will increase the subsidy effect of CDM discussed in section 2.3.1, leading to less exit and more entry in the long-run equilibrium and lower product prices for firms which produce CDM credits.
So far, it was assumed that there is one market for both emission allowances and CDM credits. This reflects current and future use of CDM in the EU ETS, which allows firms to use CDM credits and therefore creates one market on which CDM credits and emission allowances can be freely exchanged within the limits set for the use of CDM credits. However, emission trading can also be designed in such a way that two distinct markets for credits and allowances are created. Instead of allowing firms and member states of the EU to trade directly with CDM credit producers, trade in CDM credits might be reserved for the EU as a single trading partner. In this case, the EU will have monopsony power on the CDM market. Reducing the amount of CDM credits bought will reduce the price of the credits and therefore the costs of acquiring credits. This might offset the increased costs of having to use more expensive options for emission reduction at home. Several studies have found that limiting the use of CDM credits can indeed reduce total costs (see e.g. Ellerman and Wing 2000, Bollen et al. 1999), although the importance of the monopsony effect has often been missed. In the context of emission trading at the level of countries, Eyckmans and Hagem (2008) describe how the EU and large sellers of tradable emission permits such as, for example, China can benefit from concluding an agreement on the amount of emissions which is allowed on the market. In a simulation for the EU and China, such an agreement lowers emission prices and abatement costs, which are a third lower for the EU compared with a scenario without such an agreement. The extent to which the EU might influence the CDM price will depend on whether there are other buyers from Annex-B countries outside the EU active on the CDM market. The smaller the share of the EU in the CDM market, the lower will be the effect of limits on the use of CDM 5
The Chinese National Development and reform Commission is reported to have used different floor prices for different
projects, such as, for example, €10 for wind projects and €8 for large hydro (Worldbank 2009) 6
Note that CDM credits and ETS allowances are not complete substitutes. CDM credits are traded at a discount of ca. 10%
on the ETS allowance price. This reflects the higher transaction costs and the risk that a CDM project might not be able to deliver the CDM credits promised. 23
credits in the EU on the CDM price. Consequently, the decrease in costs of buying CDM credits will be more limited and total abatement costs will be higher.
2.3.3
CDM and competitiveness
We have seen that CDM will have several, contrasting effects on the competitiveness of EU ETS firms. It will lower the price in the EU ETS because it makes low cost emission reduction options available for the firms within the ETS. This lowers the price differential between ETS firms and others. The limit on the use of CDM however reduces this effect. The limit also introduces an additional rent, which falls either to the buyers or the sellers of CDM, depending on the level of competition on the demand and supply sides of the market. This rent further increases the negative effect CDM has on output prices of firms which sell credits if it should fall to CDM suppliers. In that case, the positive effect on competitiveness of lower prices in the ETS will partly be undone by lower producer prices in CDM host countries.
2.3.4
CDM and carbon leakage
The option to use relatively low cost emission reduction options in non-abating countries through the use of the CDM has likewise several contradicting effects on carbon leakage. On one hand, linking CDM to a cap-and-trade system can reduce emissions leakage because it can lead to a reduction in the cap-and-trade system allowance prices. Given low cost abatement options available in CDM host countries, the price of CO2 in cap-and-trade systems will fall. As a result, the lower price differential mitigates emission leakage. Kallbekken (2007) shows that CDM is likely to reduce carbon leakage even at relatively low levels of CDM participation. Compared to a situation without CDM, Manders and Veenendaal (2008) find that CDM lowers the emission prices considerably and thereby mitigation costs leading to a reduction of carbon leakage of about 3 percentage points. In contrast, the inefficiencies in CDM and their effects on prices can lead to an increase in leakage. As has been shown above, CDM creates a subsidy which might attract new entrants into the system. This would increase output and therefore emissions. Another reason why CDM projects might increase emissions is through its effect on fossil fuel markets. For instance, CDM investment in energy-efficiency improvement may decrease the demand for fossil fuels. This may lead to lower prices for fossil fuels and increase in the fossil fuels demand and emissions in sectors not supplying CDM. The effect of CDM projects on fossil fuel markets depends on whether fossil fuel markets affected are global or local. Rosendahl and Strand (2009) distinguish between a fossil fuel that is traded only in local markets (either in CDM host countries or in Annex-I countries) and a fossil fuel that is traded at the global level and therefore has one price both in CDM host countries and in Annex-I countries. The effect on leakage through the fossil fuel market of a CDM project will depend on which fossil fuel use is reduced. If CDM reduces energy use of the globally traded fossil fuel, the price on the global market will fall. This is partly offset by the increased consumption of 24
this fuel in the Annex-I country, where the use of CDM credits to meet their emission targets will lead to an increase in energy use. If the use of fossil fuel in the local market in the host country is reduced by the CDM project, the effect on leakage will probably be smaller. As before, within the host country the reduced demand for the local fossil fuel reduces the price, consequently energy use and emissions will increase, partly offsetting the reductions realised by the CDM project. In the Annex-I country energy use will also increase because of the use of CDM credits. Assuming both the local market and the global fossil fuel market in Annex-I are affected, this will lead to an increase in the price of both the globally traded fossil fuel and the local traded fossil fuel in the Annex-I country. The higher price of globally traded fossil fuels reduces energy use in the host country, which reduces leakage.
2.3.5
Further improving the effect of CDM on competitiveness and leakage
The net impact of CDM on competitiveness and leakage can be further improved through changes to the CDM mechanism which result in modifying the baseline. An example of such a policy is the requirement that host countries first have to realize emission reductions at own costs, for example through the introduction of a carbon tax, before they are allowed to sell CDM credits. Another option is to use a sector approach which limits emissions in a specific sector. Additional emission reductions can subsequently be traded (see Bradley et al. 2007). The effect of such changes to CDM is to shift the supply curve upward. CDM credits will become more expensive, because the least-cost options for emission reduction will be used because of policies such as the tax or the sector limit introduced in the CDM host country. Consequently, CDM will be used less by firms from countries with emission trading schemes such as the ETS. The price in the ETS will fall less than in the case without policy measures in CDM host countries. However, the price differential with CDM credits supplying firms will decline. This effect occurs because these countries also introduce climate policies, which raises costs for their own firms and reduces the differential. Furthermore, the rent on CDM declines as well, both because the volume of CDM will decline and because the cost differential will between CDM-projects and the costs within the ETS will also decline. Modifying the baseline for CDM through domestic policies in CDM host countries will reduce demand for fossil fuels, which lowers the price of fossil fuels. This might offset part of the emission reductions realised with these policies, depending on the types of policies used. When these policies include an absolute target, emissions will not rise because of lower fossil fuel prices. If policies do not include absolute emission caps, such as a carbon tax, part of the emission reduction will be undone. In non-CDM sectors and other countries, emissions will also increase due to the fall in fossil fuel prices. The same holds for the effect of CDM on fossil fuel prices, which can also lead to some increases in emissions elsewhere. Hayden et al. (2010) have investigated options to modify the CDM with the CGE-model WorldScan in a scenario in which Annex-I countries reduce their emissions in 2020 with 14% 25
relative to 2005 in the EU (which equals the 20% reduction target relative to 1990 emissions) and 20% in the Annex I countries. It is assumed that all Annex I countries engage in a common emission trading scheme. One of the options for modifying CDM is a carbon tax in non-Annex I countries at 50% of the level of the emission price in the Annex I countries. The study does not report leakage and changes in energy-intensive industry output directly, but as a measure for the competitiveness and leakage impact the price differential between Annex I and non-Annex I can be taken. The difference in the CO2 price between Annex I and nonAnnex I is reduced from € 10.6 /ton CO2 in case CDM is allowed without any policies in the host countries to € 7.3 per ton CO2 when a 50% carbon tax is introduced in host countries . Moreover, the export of CDM credits falls from 2.5 Gton CO2 to 1.9 Gton CO2 with the introduction of the 50% carbon tax. This considerably reduces rent on CDM, given the higher costs of producing these CDM credits.
26
3
Border measures
3.1
Theory and design of border measures (BM) We have shown that different allocation methods and instruments such as CDM can have an effect on competitiveness and leakage. These policies might mitigate the cost impact of climate policies. Another option to reduce the competitiveness impact and leakage is to introduce border measures which lessen trade distortions caused by carbon pricing. 7 There are several types of border measures. One distinction is between border measures for imports and for exports. Border measures on imports protect industries on their domestic market through an increase in the costs of importers. These cost increases can be realised by means of border taxes, mandatory allowance purchase by importers or embedded carbon standards (Wooders 2009). Taxes and mandatory allowance purchase both raise costs directly by charging importers to pay for the carbon embodied in their imports. Carbon standards raise costs indirectly by requiring that products meet specific standards, otherwise they will not be allowed on the market. On export markets, domestic industry can be supported through rebates, which recompense them for the carbon costs incurred on their exports. Full border adjustments, combining charges and border rebates, protect domestic firms on both import and export markets and, when applied to all embodied carbon content of imports and exports, eliminate loss of competitiveness and both operational and investment carbon leakage which arise as a result of carbon price differentials. However, carbon leakage caused by reduced fossil fuel prices will not be completely eliminated. One the one hand, fossil fuel prices will fall less because export rebates will increase demand for fossil energy for export production, on the other hand import tariffs will reduce demand from producers from countries without climate change policies.
Full border adjustment on all embodied carbon of both final and intermediate products will not be feasible in practice. It would necessitate the calculation of all carbon emitted in the production chain up till the point where a product is imported, for all products imported. Moreover, the specific production processes in the country of origin would have to be known as well, because there can be considerable differences in emissions depending on the process used. For example, steel made with sustainable produced charcoal has no net emissions, while steel from recycled scrap metal uses considerably less energy than primary steel production with BOF furnaces. Therefore a balance has to be struck between comprehensiveness of border measures and administrative costs. There are several options to limit the detail and coverage of border measures and at the same time reduce the competitiveness impact for the major sectors affected 7
A third option to reduce the impact of climate change policy on competitiveness is to promote environmental action in non-
regulated countries. This option will not be discussed in this paper. 27
by climate change policies. A first option is to limit BM to those sectors for whom carbon leakage and trade impacts are expected to be a severe problem. From the literature reviewed in section 2.1.1, it can be concluded that the main markets to which border measures might be applied are steel, cement, aluminium and fertilizer (see also Monjon and Quirion 2010). The way the emissions are calculated for imported or exported products on which the import tax or export rebate are based can also be simplified. Instead of using actual emissions, Godard (2007) and Ismer and Neuhoff (2004) have suggested to use the Best Available Technology (BAT), the technology which emits least to produce a specific product such as, for example, aluminium ingots. In some cases, the BAT might emit zero emissions, such as the production of aluminium with hydro power. The BAT would therefore have to be adjusted, for example through the requirement that the technology has a certain minimum market share, otherwise a BM based on the BAT would not be effective. The product-specific benchmarks which are currently being developed by the EC for the allocation of free allowances to those sectors that are deemed to be at a significant risk of carbon leakage (see section 2.1.1) might be used as the BAT on which the BM could be based. The EU benchmarks do not necessarily reflect the actual emissions of imported products. These emission might either be higher or lower than the calculated benchmark. In the first case, imported goods will have a cost advantage compared to the benchmark level of EU firms. In practice, this cost advantage will probably be limited. Demailly and Quirion (2008) show for the cement industry that the difference in carbon leakage between BM based on BAT and BM based on their actual emissions is minimal. In the latter case, foreign firms with lower emissions than the benchmark suffer a cost disadvantage because the import BM is based on a higher emission rate. An option is to allow firms to provide evidence that their emissions are below the benchmark and subsequently to use these actual emissions as a basis for applying the BM. This will moreover provide an incentive for foreign firms to reduce their emissions. However, it might be quite cumbersome from an administrative point of view and be subject to fraud because it will be difficult to verify the emission data provided by foreign firms. In the case of a rebate on exports, either the EU benchmark might be used or the actual emissions, based on emission data which have to be supplied for the ETS. This does raise the problem of assigning emissions to specific products, which might be infeasible in the case of complex production processes in which different goods are produced at the same time. This option is therefore only available when emission can straightforwardly be allocated to specific products. In that case, it is preferable to use the actual emissions if these are lower than the benchmark. Otherwise, these firms would receive more allowances than needed and export would be subsidised. While it appears to be feasible to set the direct emissions for a number of products on which BM can be based, this poses considerably more problems for embodied emissions in downstream products. The question is whether it is necessary to apply border measures also to 28
embodied emissions or not in order to limit the negative impact of climate change policy on competitiveness and to limit carbon leakage. This will depend on the effect on the costs of finished products of embodied emissions. Monjon and Quirion (2010) report that steel and aluminium related emissions in a 1 ton car is about 1.6 ton of CO 2. For a CO2 price of €30, this would amount to a production cost increase of a car of €48, which is negligible on the total costs of car production. However, this might be different for intermediate products such as steel or aluminium semi manufactured goods such as, for example, car bodies. The administrative costs of BA depend directly on the number of goods to which BM are applied and whether both imports and exports are included. Furthermore, using emission data from the exporting countries considerably increases the administrative burden compared with the use of domestic emissions. Administrative costs can be considerably limited by using the benchmarks currently being developed by the European Commission for the allocation of allowances in the third phase of the ETS (see section 2.2.1).
If BM are applied to countries which do not take on climate change policies, they should be applied by all countries which take part in a climate change agreement. Otherwise, BM can lead to strategic behaviour which reduces their effectiveness. Trade in energy-intensive goods to which BM are applied could be shifted to countries with climate policies but without BM. For example, assume that both Japan and the EU take part in a climate change agreement, with the EU introducing BM but Japan not. Steel exports from China will than be redirected from the EU to Japan (Cosbey 2008 and Houser 2008). The EU would import more steel from Japan, because BM would not apply. Consequently, BM will be less effective and emissions will be reduced less. An alternative is to apply BM to all other countries, including those who have introduced climate policies as well. However, this would impose carbon costs on imports from participating countries while they also have to pay carbon costs in their own country (unless they receive a rebate on their exports).
BM will raise costs for firms exporting from countries without climate policies. These countries can choose between accepting the BM or introducing climate policies of their own such that importing countries do not apply BM any more for their exports. Which option is more attractive will depend on the relative costs of BM versus the policies required to have the BM removed. We will come back to this in chapter 4 were the effects of BM are discussed with the CGE model WorldScan.
As we have seen in chapter 2, instrument choice and allocation rules also influence competitiveness and leakage. Therefore, these should be taken into account together with BM instead of considering them in isolation. Allocation rules such as updating and entry and closure rules reduce the cost increase due to emission trading. Therefore, BM have to be less stringent. In practice, however, it will be difficult to assess the impact of updating and entry and closure 29
rules within the ETS on the carbon cost increase. Moreover, it would also further complicate the design of border measures. Instead of adapting BM to the allocation and the entry and exit rules in the ETS, the introduction of BM can also provide the opportunity to adapt and simplify the allocation rules within the ETS (Godard 2008). When competitiveness and leakage are addressed through BM, there is no reason for free allocation, updating and for entry and closure provisions. Free allocation is not effective to counter loss of competitiveness and leakage. Moreover, with BM, firms will be able to pass-on the carbon costs without the risk of losing market share or profitability to foreign firms. Therefore, continuing free allocation in the presence of BM would lead to windfall profits, comparable to the windfall profits power generators are receiving in the current second phase of the ETS. BM not only discourage operational leakage, but also investment leakage, which eliminates the need for entry and closure rules, which both have a distortionary impact on the ETS.
Concluding, BM appear to be feasible at acceptable costs if they are applied to a limited number of products and if use is made of the EU benchmarks which are being developed for the allowance allocation in the third phase of the ETS. In order to be effective, they have to be applied by all countries which take on climate policies, otherwise exporting countries can redirect their exports to those countries without BM. Whether they are compatible with WTOrules and whether they are effective in reducing leakage is another question. This will be explored in the following sections.
3.2
Border measures and WTO BM appear to be a feasible option to limit the competitiveness impact of climate policies. However, they might be incompatible with the WTO agreements because they restrict trade. International trade law offers several possibilities which might allow for the use of border measures: border taxes can be permitted to compensate for indirect taxes on domestic goods or exemptions can be allowed under article XX which allows for measures to conserve exhaustible resources. Whether these apply will also depend on the design of the BM. The WTO agreements in principle can allow states to impose border taxes on products or on inputs physically incorporated in imported goods when they are consumed in a country (the destination principle) and when these products or their inputs are taxed in the importing country. It is not clear whether CO2 emissions would be considered as such an input, because they are not physically incorporated in the final product. Currently, there is no case law on this issue which might clarify this question (van Asselt and Brewer 2010). In case border taxes would be admissible, imported goods should be treated in the same way as domestic goods. Consequently, imported goods should not be taxed at a higher level than those produced at home. 30
Instead of a border tax, importers might also be required to submit allowances. In the WTO agreements, no mention is made of emission trading and of related border measures. However, the rationale behind emission trading is the same as behind a tax, moreover the impact is comparable as well. It seems therefore to be justifiable to consider emission trading in the same way as a carbon tax. Following the same reasoning as with a border tax, an obligation to acquire allowances for imports might be allowed as well under trade law (Ismer and Neuhoff 2004). In order to avoid overtaxing import or subsidising exports, border taxes and rebates should not exceed the cost increase incurred by domestic producers. Options such as using best available technology or the benchmark which is being developed by the EU (Godard 2007, Monjon and Quirion 2010) might serve this purpose. In addition, one might have to take into account the extent of grandfathering of allowances and reduce border taxes and rebates accordingly in order for border measures to be allowable under the WTO agreements. In the most extreme case, if firms receive all allowances for free, it might not be possible to impose taxes at the border.
Another possibility to allow for BM is article XX of the GATT. Article XX allows for environmental exceptions for measures “relating to the conservation of exhaustible natural resources if such measures are made effective in conjunction with restrictions on domestic production or consumption”. The capacity of the atmosphere to absorb GHGs without the risk of environmental damage due to climate change might be seen as such an exhaustible resource (Godard 2007). A requirement of article XX is that the country which imposes the measure has undertaken serious efforts to negotiate with exporting countries before applying unilateral border cost adjustments. One might argue that the climate negotiations would be sufficient proof of such serious efforts. Furthermore, these measures should not force other states to adopt the same approach as the state that imposes border measures (Ismer and Neuhoff 2004).
At present, a definite answer on the compatibility of BM with the WTO agreements is not possible. Either the possibility to impose border taxes to compensate for domestic taxes or the environmental window, article XX, might allow the use of BM, such as taxes or the obligation to obtain emission allowances, to address competitiveness concerns and reduce leakage. A prerequisite is that the costs imposed on imported goods are not higher than those on domestic goods. Consequently, BM would need to take into account the level of grandfathering applied in the ETS.
3.3
Economic and trade effects of BM The welfare effects of BM depends on the various effects outlined above. Using a partial equilibrium approach, Gros (2009) shows that a carbon tariff on imports will improve global welfare because it introduces carbon pricing in countries without climate policies. Due to the import tariff on carbon, worldwide emissions will be lower, which increases global welfare. 31
This increase is larger than the decrease caused by consumer and producer loss as a result of the tariff, which reduces consumption of energy intensive goods. In recent studies on the economic and trade effects of BM which use CGE-models, the focus is on the welfare effects for on the one hand countries with climate change policies which introduce BM and on the other hand countries without climate policies. The welfare effect of lower worldwide emissions is not included in these studies. Burniaux et al. (2010) have studied the effects of BM with the use of the ENV-Linkages model for two scenarios. In the first scenario, the EU alone cuts its emissions with 20% in 2020 and 50% in 2050, compared to 2005 emissions. In the second scenario, all Annex-I countries reduce their emissions with the same amounts. As is to be expected, carbon leakage is larger in the EU scenario, 6.5 percent of EU emission reductions in 2020, than in the Annex-I scenario, 4.5 percent of the emission reduction in Annex-I countries. Burniaux et al. (2010) model various variants for border measures. BM apply either to imports or to both imports and exports. They are based on the carbon content of the imported products (the actual emissions realised by the production) or on domestic product carbon content, which is closer to the benchmark approach for determining the carbon content on which the BM is based. BM are based on only the direct carbon content of products, leaving out the carbon content of the inputs used to produce these goods. Alternatively, the carbon in the electricity inputs used to produce the imported goods is counted as well. The main result for all types of BM is that they can be effective in addressing carbon leakage in the EU scenario but are less effective in the Annex-I scenario. In the EU scenario, leakage occurs more through competitiveness loss, while in the Annex-I scenario the fossil fuel price channel is more important. As has been discussed above, BM do not address this last leakage channel, therefore the effect on leakage in the Annex-I scenario is limited. Using domestic emissions instead of the emissions from exporting firms to determine BM leads leaves leakage at a higher rate for the EU scenario, about 25% higher relative to the case with BM on the basis of foreign emissions. The reason for this is the lower carbon content of European goods and therefore lower border tax levels for imports. Another difference is between using only direct emissions or including indirect emissions from electricity inputs used to produce the final goods as well. The latter case is more effective, halving leakage in the Annex-I scenario compared to BTA based on direct emissions only. The welfare effect of introducing BM (measured as the equivalent variation in income) are small (in the range of 0.1 percent higher welfare relative to the baseline compared with scenarios without BM) but positive for the implementing countries, which are offset by comparable welfare losses in the rest of the world. The net effect on global welfare is therefore limited, however this does not include the welfare increase due to the lower emissions. There is hardly any effect of BM on the output of energy intensive sectors, the effect is even negative in the longer run (2030) in both scenarios. One reason for this is that import measures increase the costs of energy-intensive inputs which are imported, such as steel or aluminium 32
ingots. This has a negative effect on the production costs and therefore on demand, which offsets the gain in market share because of reduced competition from foreign firms. Moreover, the effect of the increase in carbon price on demand for energy-intensive products is more important than the loss of competitiveness with respect to foreign firms who do not have to bear carbon costs.
Winchester et al. (2010) use the EPPA-model to study BM in a scenario where Annex-I countries (except FSU) reduce their emissions in 2025 with cap-and-trade emission trading with 18 to 35 percent relative to 2000. The BM in their study is a tariff on imported goods, based on the embodied emissions. This tariff either applies to all sectors or to manufacturing (which includes both energy-intensive and other industry sectors) and is introduced in the US alone or in all Annex-I countries minus FSU (termed the coalition). In terms of comparability with other studies, the variant with import tariffs in all coalition countries is the most relevant. BM have a small positive effect on welfare for the coalition countries, which falls 0.1 percent less relative to the baseline compared with the scenario without BM. Welfare loss in non-coalition countries is larger, 0.5 percent relative to the baseline compared with the case without BM. Global welfare decreases with the introduction of BM. Leakage is reduced by the import tariff on industrial imports with about 60% compared to scenario without BM. This is also reflected in the change in industry output with the introduction of the import tariff, which increases with about 1 percent relative to the cap-and-trade scenario in the energy-intensive sectors and with more than 0.5 percent for the other industrial sectors. In order to estimate the relative importance of carbon leakage through loss of competitiveness versus the fossil fuel price channel, Winchester et al. (2010) estimate leakage with a variant in which crude oil prices are set at the level in the baseline scenario through a global oil tax. This reduces leakage as much as the import tariff, with about 60% compared to the cap-and-trade scenario. Consequently, in their study oil price controls are as effective in tackling leakage as import tariffs.
Manders and Veenendaal (2008) consider BM in the CGE-model WorldScan against the background of a scenario in which the EU is the only region with a strong climate change policy while other Annex-I parties only have limited policies (around 2 percent reduction compared to the baseline) and non-Annex I no policies. EU emissions are reduced with 14 percent compared to 2005 levels. Economic welfare in the EU reduced by 7 percent in 2020 compared to the baseline. Output in the ETS sectors in the EU declines with 4.5 percent relative to the baseline and carbon leakage is 3.3 percent. Two forms of BM are modeled, a levy on imports and a refund on exports, both for the ETS sectors. The levy is based on the embodied carbon content of domestic production, the refund on exports gives a full refund of the carbon price. The import levy has a small positive effect on welfare, which improves by 0.03 percent relative to the case without BM. The refund reduces welfare slightly (with 0.05 percent), caused 33
by the revenue which is spent on the refund. The import levy reduces leakage with 1.4 percent relative to the baseline, the refund with 1.3 percent. Together, these BM limit leakage to 0.5 percent. Manders and Veenendaal (2010) also consider a policy scenario in which CDM is available to the ETS sectors, up to a limit of one third of the yearly reduction effort needed to meet the target. CDM considerably reduces the permit price, from 52 €/ton CO2 in the scenario without CDM to 27 €/ton CO2 if CDM is allowed. The effect on welfare is small, from -0.72 without CDM to -0.70 with CDM. Carbon leakage is reduced with 3 percent relative to the baseline, from 3.3 to 0.3 percent when CDM is allowed. CDM also reduces competitiveness loss considerably; compared with the scenario without CDM, employment in the ETS-sectors falls with 2 percent (relative to the baseline) from -3.2 till -1.2 percent. CDM considerably reduces the impact of stand-alone climate change policy within the EU, which reduces the need for BM to combat competitiveness loss and carbon leakage.
The study by Fischer and Fox (2009) is the only study which compares the effects on competitiveness and leakage of BM with different allocation methods. They use a partial equilibrium model which is parameterized with the outcomes of a simulation with the CGE GTAP-EG model in which only the US introduces a $50/ton emission price on CO2. Leakage rates range from 11 percent for the paper, pulp and printing sector to 64 percent for the refined petroleum products. With the exception of oil products, leakage in the energy-intensive sectors is more due to oil price changes worldwide (the oil price channel of carbon leakage) than because of changes in product prices, which result in leakage rates ranging from 2 till 14 percent for different energy-intensive sectors, or about 20-40 percent of total leakage per sector. Fischer and Fox (2009) compare import taxes, export rebates and output-based allocation. The latter is the most effective in reducing production losses, which are reduced with 40-60 percent for energy-intensive sectors with the exception of oil products compared with the scenario without compensating measures. Both import taxes and export rebates reduce production losses for these sectors roughly with 10-20 percent. The effectiveness of all measures in reducing carbon leakage for these sectors is limited; they achieve a net additional emission reduction of at most 5 percent compared to the scenario without any measures.
The modelling studies discussed yield several insights on competitiveness, leakage and measures to mitigate averse effects of partial climate change policies. Obviously, the degree of loss of competitiveness and leakage depends on the stringency of policies and the size of the coalition. For the range of policies assumed in the CGE-modelling studies (see also the study of Fischer and Fox (2004) discussed in section 2.2.2), carbon leakage is between 3 and 11 percent. Leakage declines when the size of the coalition which introduces climate change policies increases.
34
Import BM will reduce leakage with 30-60 percent. The effect is larger if indirect embodied emissions are included and when the actual carbon content is used instead of a calculated content based on domestic embodied emissions. However, in practice this will be difficult to implement. The effect of import BM on the competitiveness of energy-intensive industry is less clear, with some studies showing a small or no effect at all. This is also reflected in the effect of import tariffs on welfare in the implementing countries, which is also limited. Introducing export rebates can further reduce leakage, the effect on energy-intensive output and welfare is also small. In the CGE-modelling study (Fischer and Fox 2004), output-based allocation is both successful in reducing leakage and competitiveness loss, moreover welfare is also increased compared with grandfathering allowances. However, in the partial equilibrium study of Fischer and Fox (2009), output-based allocation is considerably more effective in minimising the loss of competitiveness of energy-intensive sectors, while it is not effective in reducing leakage. Another option is to allow firms to use CDM credits to meet their obligation. This can significantly reduce the impact of stand-alone climate policies on leakage and competitiveness and thereby reduce the need for complementary BM. Some form of domestic climate policy in CDM host countries which requires firms or sectors to reduce emissions to some extent before the can sell CDM credits can further improve the effect of CDM on leakage and competitiveness.
In the next chapter, we present estimates made with WorldScan of the macroeconomic consequences and impact of climate policies, BM and CDM on trade and leakage.
35
4
WorldScan scenarios WorldScan
The macroeconomic consequences of specific climate policy scenarios are assessed using the global applied general equilibrium model WorldScan (see Bollen, Manders and Mulder, 2004; Lejour et al., 2006; Wobst et al., 2007; Manders and Veenendaal, 2008; Hayden, Veenendaal and Zarnić, 2010; Boeters and Koornneef, 2010). WorldScan data for the base year 2004 are to a large extent taken from the GTAP-7 database (Narayana and Walmsley, 2008) that provides integrated data on bilateral trade flows and input-output accounts for 57 sectors and 113 countries and regions. The WorldScan version used in this study includes the detailed electricity technology specification developed by Boeters and Koornneef (2010) and the conventional Table 4.1 Regions
Overview of regions, sectors and technologies and production inputs in WorldScan
a)
Germany France United Kingdom Italy Spain Netherlands Other EU15 Poland Rest of EU-27 Norway Switzerland Russia Ukraine USA Canada Japan Australia New Zealand Brazil Middle East and North Africa China (incl. Hong Kong) India Rest of the World
Sectorsb)
Inputs
Cereals (Wheat and Cereal Grains NEC) Oilseeds Sugar Crops (Sugar Cane, Sugar Beet) Other Agriculture Minerals NEC Oil Coal Petroleum Coal Products Natural Gas (incl. gas distribution) Electricity Energy Intensive Manufacturing Vegetable Oils and Fats Consumer Food Products Other Consumer Goods Capital Goods and Durables Road and Rail Transport Other Transport (water and air) Other Services
Factors Low-skilled labour High-skilled labour Capital Land Natural resources
Electricity Technologies Conventional fossil (without CCS) Fossil with CCS Nuclear Wind Biomass Hydropower Conventional biofuel technologies Ethanol from sugar beet from sugar cane
Non-electricity energy carriers Coal Petroleum, coal products Natural gas Modern biomass Biodiesel Ethanol Other intermediates Cereals (Wheat & Cereal Grains) Oilseeds Sugar Crops (Sugar Cane&Beet) Other Agriculture Minerals NEC Oil Electricity Energy Intensive Manufacturing Vegetable Oils and Fats Consumer Food Products Other Consumer Goods Capital Goods and Durables Road and Rail Transport Other Transport (water and air) Other Services
from wheat from corn Biodiesel a)
Non-Annex I regions are denoted in italics
b)
ETS-sectors are denoted in bold
biofuel technologies developed by Wobst et al. (2007). The model distinguishes 18 sectors. The ETS consists of two sectors (electricity and energy intensive manufacturing) while the other 36
sectors and household activities belong to non-ETS. Factor markets for high- and low-skilled labour, capital, land and natural resources are distinguished in each of the selected 23 countries and regions (Table 4.1). Six non-electricity energy carries are distinguished: coal, petroleum and coal products, natural gas, modern biomass, biodiesel and ethanol. Combustion of the first three of these contributes to the CO2-emissions simulated by the model. The model also covers emissions of methane and nitrous oxide, from the combustion of energy, industrial processes and agricultural activities (such as rice cultivation, livestock production and fertilizer use). The model can also deploy end-of-pipe methods to reduce GHG-emissions.8
4.1
Policy cases Using WorldScan we assess the impacts of five policy variants up to the year 2020, in particular on economic welfare and carbon leakage. We first show the impacts of AMBITIOUS PLEDGES which is a scenario in which Annex I countries ambitiously adopt relatively low caps on GHG-emissions and allow free permit trade amongst each other. In this scenario China and India impose relative targets for CO2 emissionintensities of 45% and 25% below 2005 intensities. The EU imposes a targeted 20% share of renewable energy in final energy use. In a second case, PLEDGES, we implement the more modest pledges that were made by the countries up to the Copenhagen Climate Change Conference in December 2009. PLEDGES describes a climate policy in which Annex I countries impose modest emission ceilings without permit trade and without the use of CDM. In this scenario China and India impose relative targets for CO2 emission-intensities of 40% and 20% below 2005 intensities. Only in the EU permit trade occurs, separately within the ETS and the non-ETS. Again, the EU imposes a targeted 20% share of renewable energy in final energy use. In the third variant, PLEDGES WITH CDM, the assumptions are the same as in PLEDGES, but in addition the Annex I countries are allowed to use CDM up to 1/3 of the reduction effort. 9 CDM supplies may originate from all production sectors of non-Annex I countries. In the fourth scenario, PLEDGES WITH BM, the assumptions are the same as in PLEDGES, but now the industrialized countries apply border measures for the ETS-sectors. They simultaneously adopt carbon levies on imports and carbon refunds on exports. The level of
8
Emission profiles consistent with the World Energy Outlook (2009) and the costs of end-of-pipe adjustments and
abatement potentials are taken from the GAINS model (http://gains.iiasa.ac.at). With ‘end-of-pipe’ methods already formed contaminants are removed from a stream of air. They are called 'end-of-pipe' as they are normally implemented as a last stage of a process before the stream is disposed of or delivered. Examples are the adoption of farm technologies that prevent inefficient fertilizer use and a higher frequency of leakage controls in gas distribution networks. 9
This assumption is derived from the ’20 20 in 2020’ proposal of the European Commission in which the use that can be
made of carbon credits from CDM is limited. We have adopted these constraints for the EU and assumed that for ETSsectors at most one third of the yearly reduction efforts (baseline minus target) may be covered by CDM-credits, while the yearly CDM-ceiling for non-ETS is 3% of 2005 emissions. For other Annex I countries the constraint for the ETS-sectors is applied (one third of the total reduction effort). 37
these border measures is based upon the average prevailing direct and indirect carbon costs in domestic production of the ETS-sectors. In the fifth case, PLEDGES WITH FA, we follow the assumptions of PLEDGES, but in stead of assuming that all permits are auctioned, we take into account free permit allocation to energyintensive manufacturing in the EU. The main subsidy effect of free allocation results from the free allocation to entrants (see section 2.2.4). Hence, in this policy case we lower production costs by providing a subsidy to EU energy-intensive manufacturing that equals the value of the allowances that are available to new firms. The entrant reserve is 5% of total allowances available in the period 2013-2020.
4.2
Baseline The effects of climate policy depend strongly on the underlying baseline. Our policy scenarios are based on the baseline of the 2009 World Energy Outlook (WEO, IEA, 2009). With our baseline we deviate from the WEO-baseline in one respect however. We remove the ETS-caps from the WEO in order to establish a level playing field for our assessments of the mitigation pledges in an international context. According to our baseline, global population will continue to expand. Combined with worldwide economic growth of 2.7% per year global demand for energy will be almost 30% higher in 2020 than in 2004. This expansion predominantly takes place in non-Annex I, thus partially reducing the gap in energy consumption per capita with the industrialized countries. Table 4.1 gives some key characteristics of the baseline for the 2004-2020 period. The table indicates that in the baseline energy- and GHG-intensities are declining worldwide and especially in non-Annex I. In principle our baseline follows the fossil fuel price projections of the 2009 World Energy Outlook. Thus the oil price will reach 100 US$ per barrel in 2020. In Europe the gas price is expected to lag behind the oil price. Regional coal prices are expected to remain constant at their 2009 level. Basically, the main difference between the WEO-baseline and our baseline is increased energy consumption in the EU (due to the lifting of ETS-caps) and reduced energy consumption elsewhere (due to somewhat higher fossil fuel prices) resulting in slightly increasing emissions in the EU over the period 2004-2020 and slightly decreasing emissions in Japan and the USA. Table A.1 in the Annex provides the differences in characteristics of both baselines.
38
Table 4.2
Characteristics of baseline scenario, average annual growth (%), 2004-2020 Population GDP volume
Energy consumption a)
GHG emissions
Energy intensity
GHG intensity b)
Annex I
0.3
1.8
0.0
0.1
-1.8
-0.0
EU-27
0.3
1.5
0.6
0.5
-1.0
-0.1
-0.1
1.1
0.0
0.2
-1.1
0.0
France
0.5
1.3
0.5
0.3
-0.8
-0.2
United Kingdom
0.5
1.6
0.0
0.1
-1.6
0.0
Italy
0.3
0.9
1.7
1.3
0.8
-0.3
Spain
1.1
2.4
1.1
0.9
-1.3
-0.1
Netherlands
0.2
1.3
-0.4
-0.3
-1.8
0.1
Other EU15
0.4
1.8
0.8
0.8
-0.9
-0.1
Poland
-0.1
3.2
0.7
0.7
-2.5
-0.3
Rest of EU-27
-0.3
3.3
0.7
0.6
-2.7
-0.2
Norway
0.5
1.3
-1.0
-0.7
-2.3
0.2
Switzerland
0.2
1.2
-0.8
-0.8
-2.1
0.1
Russia
-0.5
4.4
0.6
0.9
-3.7
0.2
Ukraine
-0.5
4.3
-0.6
-0.2
-4.9
0.3
0.9
2.1
-0.5
-0.4
-2.6
0.0 -0.2
Germany
USA Canada
0.9
2.0
0.4
0.2
-1.7
-0.2
1.1
-1.2
-1.0
-2.3
0.1
Australia
1.0
2.1
1.1
0.8
-0.9
-0.4
New Zealand
1.1
2.0
0.6
0.2
-1.4
-0.5
Japan
Non-Annex I
1.3
5.4
3.2
3.0
-2.2
-2.9
Brazil
1.0
3.3
2.5
2.5
-0.8
0.0
Middle East and North Africa
1.8
3.7
1.1
1.3
-2.6
0.1
China (incl. Hong Kong)
0.7
8.2
4.4
3.3
-3.7
-1.1
India
1.3
7.1
4.6
3.2
-2.5
-1.4
Rest of the World
1.5
4.5
2.5
2.6
-1.9
0.1
1.1
2.7
1.6
-1.6
-1.1
-1.7
World
a) Total of coal, refinery products, natural gas, biofuels, commercial biomass and renewable energy b) GHG-intensity represents the ratio of GHG-emissions and energy consumption Source: WorldScan
4.3
Simulation outcomes Against the background of our baseline the outcomes of the AMBITIOUS PLEDGES policy scenario indicate modest costs and modest benefits at the global level. At the expense of 0.2% of global economic welfare a decrease in global emissions of 4% is reached in 2020 against the baseline (Table 4.3). On average economic welfare decreases by 0.3% in Annex I and by 0.1% in non-Annex I. Permit trade within Annex I occurs against a permit price of 9 euro/tCO 2-eq. and due to permit trade emissions in individual countries of Annex I may differ from the emission targets in 2020. The table shows that permits are bought from Eastern Europe, Russia and Ukraine. The carbon leakage rate in this scenario amounts to 16%. This leakage rate is defined as the increase of GHG-emissions in non-Annex I countries as a percentage of the 39
Table 4.3
AMBITIOUS PLEDGES, 2020 Emission price
Economic welfare a)
Percentage GHG reduction Target (or 2020
Target
Emissions 2020
emissions)
compared to
compared to
compared to
baseline
baseline
2005
emissions 2020
emissions 2020
(%)
(%)
(%)
€ / tCO2
(%)
Annex I
-13
-14
-14
9
-0.3
EU-27
-19
-29
-15
9
-0.5
Germany
-28
-35
-12
9
-0.4
France
-26
-32
-10
9
-0.2
United Kingdom
-30
-34
-18
9
-0.5
Italy
-26
-44
-11
9
-0.3
Spain
-23
-39
-12
9
-0.3
Netherlands
-30
-30
-18
9
-0.9
Other EU-15
-24
-35
-25
9
-0.7
emissions
Poland
20
3
-14
9
-0.6
Rest of EU-27
13
-3
-18
9
-0.8
Norway
-44
-37
-4
9
-1.2
Switzerland
-31
-22
-3
9
-0.1
18
3
-16
9
-1.1
Russia Ukraine
77
83
-11
9
3.9
USA
-17
-12
-12
9
-0.2
Canada
-17
-19
-15
9
-0.5
Japan
-30
-18
-13
9
-0.2
Australia
-29
-37
-17
9
-0.8
New Zealand
-36
-38
-11
9
-0.5 -0.1
Non-Annex I
59
-
2
-
Brazil
50
-
3
-
0.0
Middle East and North Africa
24
-
2
-
-0.6
China (incl. Hong Kong)
70
-
1
-
0.0
India
64
-
2
-
0.2
Rest of the World
53
-
3
-
-0.1
22
-
-5
-
-0.2
World
a) Equivalent variation as % of national income of the baseline Source: WorldScan
40
Table 4.4
PLEDGES, 2020 Emission pricea)
Economic welfare b)
Percentage GHG reduction Target (or 2020 emissions) compared to 2005 emissions
Target compared to baseline emissions 2020
Emissions 2020 compared to baseline emissions 2020
(%)
(%)
(%)
€ / tCO2
(%)
Annex I
-7
-7
-13
-
-0.3
EU-27
-9
-21
-21
31
-0.5
Germany
-15
-22
-16
11
-0.3
France
-15
-22
-19
11
-0.4
United Kingdom
-17
-21
-21
11
-0.4
Italy
-14
-34
-18
11
-0.4
Spain
-10
-29
-20
11
-0.4
Netherlands
-17
-17
-17
11
-0.7
Other EU-15
-14
-27
-29
11
-0.7
15
-1
-22
11
-0.6
Poland
10
-5
-25
11
-0.6
Norway
Rest of EU-27
-35
-27
-27
115
-1.4
Switzerland
-21
-10
-10
39
-0.2
Russia
33
17
4
-
-1.3
Ukraine
77
83
5
-
0.3
USA
-17
-12
-12
12
-0.1
Canada
-17
-19
-19
14
-0.5
Japan
-30
-18
-18
14
-0.2
Australia
-10
-20
-20
13
-0.7
New Zealand
-28
-30
-30
51
-0.5 0.0
Non-Annex I
62
-
3
-
Brazil
53
-
6
-
0.1
Middle East and North Africa
26
-
4
-
-0.5
China (incl. Hong Kong)
72
-
2
-
0.1
India
66
-
4
-
0.3
Rest of the World
57
-
6
-
0.0
26
-
-3
-
-0.2
World
a) For EU-27 ETS-price, for member states non-ETS-price, for other Annex-I countries national carbon tax b) Equivalent variation as % of national income of the baseline Source: WorldScan
emissions reduction in Annex I countries. This means that 16% of the emission reduction in Annex I is compensated by increasing GHG-emissions in non-Annex I. Overall, Annex I reduces emissions with 13% compared to the baseline at limited economic costs. The relative
41
targets on CO2-emission intensities in China and India (45% and 25% respectively below 2005 intensities) appear not to be binding in this scenario. 10 The outcomes of the PLEDGES policy scenario indicate costs and benefits at the global level that are very similar to those of AMBITIOUS PLEDGES. At a cost of 0.2% of global economic welfare global emissions arrive at a level that is 3% below the baseline in 2020. On average economic welfare decreases by 0.3% in Annex I while in non-Annex I economic welfare remains almost unchanged with respect to the baseline. Due to permit trade in ETS and non-ETS 2020 emissions of individual EU member states may differ from their emission targets. The table shows that permits are mainly bought by the largest member states of EU-15 from the new member states and from the smaller countries of EU-15. The carbon leakage rate in PLEDGES amounts to 36% (see also Table 4.8). This leakage rate is considerably higher than the leakage rates that were found in previous analyses with applied general equilibrium models that were calibrated to the GTAP-6 database with base year 2001. As an example, Manders and Veenendaal (2008) report a carbon leakage rate of 3.3% for a similar scenario and a production leakage rate of 38% for ETS-sectors.11 Reasons for the higher leakage rates may be that the 2004 GTAP-7 data show for non-Annex I both a higher share in global fossil energy use and a higher share in global trade in energyintensive products. Thus, both the price channel for carbon leakage and the trade channel may have become more important. On the one hand fossil energy use in non-Annex I is calibrated at a higher base year level. Expansion of energy consumption in non-Annex I due to lower fossil fuel prices thus tends to become more important. On the other hand trade in energy-intensive manufacturing with non-Annex I is also calibrated at a higher base year level which fosters leakage via trade. If the model used in the analysis of Manders and Veenendaal (2008) would have been calibrated to the 2004 base year data, they would have reported a carbon leakage rate of 14% and a production leakage rate of 50%. The carbon leakage rate for PLEDGES is of the same order of magnitude as the rates reported in Böhringer et al. (2010) for similar simulations in 2020 with a static CGE-model calibrated to the 2004 GTAP database. Conversely, in a similar policy setting OECD (2009) reports a much lower carbon leakage rate of 0.7% in 2020 using a CGE-model calibrated to the 2001 GTAP dataset. In PLEDGES we have assumed that the EU 20% renewables target has been met. If we would have dropped this assumption and let the model endogenously determine the optimal level of renewables in the EU the ETS emission prices would rise from 31 to 45 euro per ton CO2-eq. while non-ETS-prices would be unaffected (Table A.2 in the Annex). The reason is that renewables are mainly replacing emissions from fossil power generation and thus the reduction effort within ETS has to increase if the share of renewables declines. Abandoning the 20% renewables target yields a gain of 0.05% in economic welfare at the EU-level. This 2020 gain is 10
Table 4.10 below gives an overview for 2020 of the CO2-intensities of China and India for selected policy cases.
11
Their scenario IMPASSE assumes 20% emissions reduction in 2020 with respect to 1990 in the EU and imposes also (quite
generous) emission caps on the other countries of Annex I. The production leakage rate is defined as the increase in ETSproduction outside the EU as a percentage of the decrease of ETS-production in the EU. 42
relatively small because in the baseline the share of renewables is already quite high (15% in 2020).
Table 4.5
PLEDGES WITH CDM, 2020
Percentage GHG reduction Target (or 2020 emissions) compared to 2005 emissions
Target compared to baseline emissions 2020
Emissions 2020 compared to baseline emissions 2020d)
(%)
(%)
(%)
Emission
Economic
pricea) ,b)
welfare c)
€ / tCO2
(%)
Annex I
-7
-7
-5
-
-0.2
EU-27
-9
-21
-13
9
-0.4
Germany
-15
-22
-10
6
-0.3
France
-15
-22
-9
6
-0.2
United Kingdom
-17
-21
-16
6
-0.4
Italy
-14
-34
-9
6
-0.2
Spain
-10
-29
-9
6
-0.2
Netherlands
-17
-17
-17
6
-0.8
Other EU-15
-14
-27
-23
6
-0.6
15
-1
-9
6
-0.4
Poland
10
-5
-17
6
-0.8
Norway
Rest of EU-27
-35
-27
-18
58
-0.8
Switzerland
-21
-10
-6
20
-0.1
Russia
33
17
3
-
-0.9
Ukraine
77
83
4
-
0.2
USA
-17
-12
-8
9
-0.1
Canada
-17
-19
-14
10
-0.3
Japan
-30
-18
-12
10
-0.1
Australia
-10
-20
-14
10
-0.7
New Zealand
-28
-30
-20
31
-0.3 0.0
Non-Annex I
53
-
-2
6
Brazil
46
-
0
6
0.1
Middle East and North Africa
25
-
3
6
-0.3
China (incl. Hong Kong)
63
-
-3
6
0.1
India
54
-
-4
6
0.2
Rest of the World
48
-
0
6
0.0
22
-
-5
-
-0.2
World
a) For EU-27 ETS-price, for member states non-ETS price, for other Annex-I countries national carbon tax, for non-Annex I countries CDM-price b) If emission prices in Annex I exceed the CDM-price this is due to the limit imposed on the allowable use of CDM of one third of the reduction effort. c) Equivalent variation as % of national income of the baseline Source: WorldScan d) The emissions reported here are actual emissions, therefore CDM emission reductions are taken into account in the nonAnnex I countries where these emission reductions are realised. 43
44
If we allow CDM to be used in Annex I
up to one third of targeted emissions reductions
policy costs diminish and policy benefits increase to some extent at the global level compared to PLEDGES. In PLEDGES WITH CDM a decrease in global emissions of 4% is reached in 2020 at the expense of 0.2% of global economic welfare (Table 4.5). On average economic welfare decreases by 0.2% in Annex I while in non-Annex I countries economic welfare remains at the baseline level. The carbon leakage rate falls from 36% to 13% when CDM is used (see also Table 4.8).12 Would Annex I countries benefit from border measures? Our simulation outcomes show relatively small impacts of the adoption of import levies and export refunds for the energy intensive sector in the countries of Annex I (Table 4.6). Compared to PLEDGES the impacts on economic welfare are negligible for both Annex I and non-Annex I. Hence, chances are low that the adoption of BM will induce countries in non-Annex I to embark on GHG-mitigation programmes. Moreover, carbon leakage is hardly reduced. The leakage rate drops from 36% to 35%. Finally, in our last scenario we indicate the impacts of free allowances for EU energy-intensive manufacturing. It turns out that the simulation outcomes do not noticeably differ from PLEDGES (Table 4.7). In PLEDGES WITH FA we lower production costs by providing a subsidy to EU energy-intensive manufacturing that equals the value of the allowances that are available to new firms (5% of the ETS-ceiling). Though there is some increase in the ETS-price the change is so small that it does not show up as a difference in the table. Apparently, in our assessment the impacts of free rather than auctioned allowances to energy-intensive manufacturing are negligible. It may be argued that in certain cases incumbents too would channel some of the value of the free allowances to customers in order to maintain competitiveness. To assess what would be the maximum impact of such behaviour we have simulated an additional „what if‟ scenario in which the energy intensive sector in the EU passes on 100% of the permit value as a subsidy on the product price. The results are given in table A.3 in the Annex. They show that within the EU the ETS-price will rise (from 31 € / tCO2 in PLEDGES to 36 € / tCO2) as will the non-ETS price (from 11 to 12 € / tCO2). With a 100% output subsidy the energy intensive sector shifts the burden of higher carbon costs to the other sectors in the economy. Emission prices in other Annex I countries will drop slightly because of smaller energy intensive production and because the fossil fuel price decrease is less than in PLEDGES. The leakage rate falls to 35% and the impact on production levels for energy intensive industries in the EU compared to the baseline reverses from a reduction of 3.3% or less towards an increase of 0.1%.
12
Note that we modify the leakage rate in the case of CDM according to equation (4.2). 45
Table 4.6
PLEDGES WITH BM, 2020 Emission price a)
Target (or 2020 emissions) compared to 2005 emissions (%)
Economic welfare b)
Percentage GHG reduction
Target Emissions 2020 compared to compared to baseline baseline emissions 2020 emissions 2020 (%)
(%)
€ / tCO2
(%)
Annex I
-7
-7
-13
-
-0.3
EU-27
-9
-21
-21
32
-0.5
Germany
-15
-22
-16
11
-0.3
France
-15
-22
-19
11
-0.4
United Kingdom
-17
-21
-21
11
-0.4
Italy
-14
-34
-18
11
-0.4
Spain
-10
-29
-20
11
-0.4
Netherlands
-17
-17
-16
11
-0.6
Other EU-15
-14
-27
-29
11
-0.7
15
-1
-23
11
-0.6
Poland
10
-5
-25
11
-0.6
Norway
Rest of EU-27
-35
-27
-27
117
-1.4
Switzerland
-21
-10
-10
39
-0.2
Russia
33
17
4
-
-1.3
Ukraine
77
83
5
-
0.3
USA
-17
-12
-12
12
-0.1
Canada
-17
-19
-19
14
-0.5
Japan
-30
-18
-18
14
-0.2
Australia
-10
-20
-20
13
-0.7
New Zealand
-28
-30
-30
52
-0.5 0.0
Non-Annex I
61
-
3
-
Brazil
53
-
5
-
0.1
Middle East and North Africa
26
-
4
-
-0.5
China (incl. Hong Kong)
72
-
2
-
0.1
India
66
-
3
-
0.3
Rest of the World
56
-
6
-
0.0
26
-
-4
-
-0.2
World
a) For EU-27 ETS-price, for member states non-ETS-price, for other Annex-I countries national carbon tax b) Equivalent variation as % of national income of the baseline Source: WorldScan
46
Table 4.7
PLEDGES WITH FA, 2020 Emission pricea)
Target (or 2020 emissions) compared to 2005 emissions (%)
Economic welfare b)
Percentage GHG reduction
Target Emissions 2020 compared to compared to baseline baseline emissions 2020 emissions 2020 (%)
(%)
€ / tCO2
(%)
Annex I
-7
-7
-13
-
-0.3
EU-27
-9
-21
-21
31
-0.5
Germany
-15
-22
-16
11
-0.3
France
-15
-22
-19
11
-0.4
United Kingdom
-17
-21
-21
11
-0.4
Italy
-14
-34
-18
11
-0.4
Spain
-10
-29
-20
11
-0.4
Netherlands
-17
-17
-16
11
-0.6
Other EU-15
-14
-27
-30
11
-0.7
15
-1
-22
11
-0.6
Poland
10
-5
-25
11
-0.6
Norway
Rest of EU-27
-35
-27
-27
115
-1.4
Switzerland
-21
-10
-10
39
-0.2
Russia
33
17
4
-
-1.3
Ukraine
77
83
5
-
0.3
USA
-17
-12
-12
12
-0.1
Canada
-17
-19
-19
14
-0.5
Japan
-30
-18
-18
14
-0.2
Australia
-10
-20
-20
13
-0.7
New Zealand
-28
-30
-30
51
-0.5 0.0
Non-Annex I
62
-
3
-
Brazil
53
-
6
-
0.1
Middle East and North Africa
26
-
4
-
-0.5
China (incl. Hong Kong)
72
-
2
-
0.1
India
66
-
4
-
0.3
Rest of the World
57
-
6
-
0.0
26
-
-3
-
-0.2
World
a) For EU-27 ETS-price, for member states non-ETS-price, for other Annex-I countries national carbon tax b) Equivalent variation as % of national income of the baseline Source: WorldScan
47
An overview of the outcomes for the five scenarios is given in Table 4.8. One may recall that we defined the leakage rate as the increase of GHG-emissions in non-Annex I countries as a percentage of the emissions reduction in Annex I countries. If we define the set of countries belonging to Annex I as
IA
(and
I # A as
its complement, indexing the countries of non-Annex I)
the leakage rate can be expressed as
e j bj lr
j I# A
bi ei
*100
(4.1)
i IA
where
ei denotes emissions in the policy scenario and bi emissions in the baseline for country i.
With CDM, calculating the leakage rate is less straightforward because the emission reduction realised through CDM projects can either be attributed to the countries which produce these emission reductions or to those countries that buy the emission reductions. Using the latter approach has the advantage that the resulting leakage rate reflects the net effect of policies in Annex I countries on emissions in non-Annex I countries. Hence we modify the leakage rate for the case of CDM by adding CDM-demands to the denominator (keeping the targeted reduction unchanged Annex I) and adding CDM-supplies to the nominator (or subtracting them from the baseline as a reflection of the expectation that emissions will be reduced in CDM host countries with the CDM-credits that they supply).
e j b j cdm sj lrcdm
j I# A
bi ei cdmid
*100
(4.2)
i IA
Economic welfare is least affected in PLEDGES WITH CDM and most in AMBITIOUS PLEDGES (Table 4.8). Global emissions are most reduced in AMBITIOUS PLEDGES and PLEDGES WITH CDM while the reduction is smallest in PLEDGES and PLEDGES WITH FA. The leakage rates are relatively high in PLEDGES and PLEDGES WITH BM. In PLEDGES WITH CDM the leakage rate falls to 13%, which reflects carbon leakage within CDM-supplying countries (see also section 2.3.4). If the leakage definition from equation 4.1 would have been used, leakage in PLEDGES WITH CDM would
have been negative, -32%, because emission reductions from CDM reduce
non-Annex I emissions below their baseline. We assessed the importance of the price channel for the leakage rates in additional policy variants where we forced fossil fuel prices to remain at baseline levels. 13 The results show a predominant importance of the price channel rather than the trade channel. In PLEDGES, for
13
As instruments we used reductions of the natural resource stocks of fossil fuels. The stocks were reduced until fossil fuel
prices returned to baseline levels. 48
example, the leakage rate of 36% drops to 2% if the price channel is eliminated in this way. These results are quite similar to those obtained by Böhringer et al. (2010). They report that for different climate policy scenarios, including various border measure variants, leakage is never reduced by more than 15%. Thus, as in their study, also in our simulations the main channel for carbon leakage appears to be the fossil fuel price channel, not carbon leakage through the trade channel. Due to the emissions ceilings imposed in Annex I fossil fuel prices decline and thus the use of fossil fuels is fostered in non-Annex I. In fact, also within some Annex I countries with non-binding emission ceilings such as Russia and Ukraine fossil fuel use increases in response to lower energy prices in four out of five scenarios. 14 Table 4.8
Economic welfare, GHG- and production leakage, fossil energy prices and global emisions, 2020 AMBITIOUS
PLEDGES
PLEDGES Economic welfare (%)
PLEDGES WITH
PLEDGES WITH
PLEDGES WITH
CDM
BM
FA
a)
Annex I
-0.32
-0.32
-0.24
-0.32
-0.32
EU-27
-0.46
-0.47
-0.37
-0.46
-0.47
USA
-0.16
-0.12
-0.09
-0.11
-0.12
Other
-0.32
-0.34
-0.24
-0.34
-0.34
Non-Annex I
-0.08
0.01
0.01
0.01
0.01
China
0.02
0.07
0.06
0.07
0.07
India
0.15
0.31
0.19
0.30
0.31
Other
-0.17
-0.06
-0.04
-0.06
-0.06
-0.25
-0.22
-0.17
-0.22
-0.22
-2.09
-1.48
-2.04
-1.51
-1.48
16
36
13
35
36
0
2
-3
0
2
54
64
64
53
65
0.7
1.4
0.7
0.9
1.3
-1.8
-3.2
-2.8
-3.3
-3.2
World Global GHG-emissions (in Gton CO2-eq. deviation from baseline) GHG leakage rate b) GHG leakage rate trade channel c) Energy intensive production leakage rate d) Energy intensive production leakage as % of baseline levele) Global fossil energy price (% dev. baseline)
a) Economic welfare is measured in equivalent variation as a % of baseline national income b) The GHG leakage rate is defined the leakage rate as the increase of GHG-emissions in non-Annex I countries as a percentage of the emissions reduction in Annex I countries; in the case of CDM the leakage rate is modified according to equation (4.2) c) The GHG leakage rate as defined in b) when fossil fuel prices are kept at baseline levels d) Production leakage rate is defined as the increase in energy intensive production in non-Annex I countries as a percentage of the decrease of energy intensive production in Annex I e) Production leakage is defined as the increase in energy intensive production in non-Annex I countries as a percentage of baseline energy intensive production in Annex I Source: WorldScan
14
The exception being AMBITIOUS PLEDGES which effectively puts
by allowing full permit trade
a joint emissions ceiling on
Annex I. 49
The production leakage rate for energy-intensive manufacturing is rather high in all policy cases, ranging from 54% in AMBITIOUS PLEDGES to 65% in PLEDGES WITH FA. However, when we look at the actual volume displacements of energy-intensive production (by multiplying the production leakage rate with the relative deviation of production from the baseline for the countries of Annex I) the picture becomes more varied. The range of production leakage outcomes in terms of % deviation from baseline production then is as follows: PLEDGES 1.4%, PLEDGES WITH FA 1.3% , PLEDGES WITH BM 0.9%, PLEDGES WITH CDM and AMBITIOUS PLEDGES BOTH 0.7%. The global fossil fuel price falls with 3.3% in PLEDGES WITH BM, exceeding the price fall in PLEDGES with 0.1%. Thus, border measures do not seem to address the fuel price channel and may in fact depress energy prices even further (see section 3.1). The fossil fuel price declines least in AMBITIOUS PLEDGES (1.8%).
Table 4.9
EU production, by sector, 2020, in % deviation from baseline AMBITIOUS
PLEDGES
PLEDGES
PLEDGES
PLEDGES
PLEDGES
WITH CDM
WITH BM
WITH FA
Cereals (wheat and cereal grains nec)
-1.5
-1.8
-1.0
-1.9
-1.8
Oilseeds
-1.7
-1.9
-1.1
-2.1
-1.9
Sugar crops (sugar cane, sugar beet)
-1.1
-1.3
-0.7
-1.3
-1.3
Other agriculture
-1.5
-1.6
-0.9
-1.7
-1.6
Minerals NEC
-0.5
-1.4
-0.3
-1.4
-1.4
Oil
-1.9
-1.6
-1.0
-1.7
-1.6
-19.0
-15.6
-9.5
-15.8
-15.6
Petroleum, coal products
-3.8
-5.3
-3.2
-5.2
-5.3
Natural gas (inc. gas distribution)
-9.7
-5.1
-3.3
-5.1
-5.1
Electricity
-1.7
-9.6
-1.2
-9.7
-9.7
Energy intensive manufacturing
-1.0
-3.3
-1.1
-2.8
-3.2
Vegetable oils and fats
-0.9
-1.0
-0.6
-1.2
-1.1
Capital goods and durables
-0.7
-0.9
-0.6
-1.2
-0.9
Consumer food goods
-0.6
-0.5
-0.4
-0.6
-0.5
Other consumer goods
-1.0
-1.2
-0.7
-1.4
-1.3
Road and rail transport
-0.8
-1.0
-0.5
-1.0
-1.0
Other Transport (water and air)
-1.0
-0.8
-0.5
-0.9
-0.9
Other services
-0.4
-0.3
-0.3
-0.3
-0.3
Coal
Source: WorldScan
The decline in EU energy-intensive production is reduced by 15% if border measures are adopted (PLEDGES WITH BM 2.8% compared to PLEDGES 3.3%, Table 4.9). EU electricity production is slightly negatively affected by adopting border measures because residential electricity demand is decreasing as well as demand from the non-ETS production sectors. Border measures are more effective in curbing the decline of energy-intensive production in the EU than free permit allowances: in PLEDGES WITH FA the decline amounts to 3.2% (rather than 50
2.8% in PLEDGES WITH BM). However, in the „what if‟ scenario where EU incumbents subsidize the price of energy intensive production by the full value of their permits energy intensive production rises slightly above baseline (+0.1%) at the expense of larger declines in production in the other production sectors of the EU.
In none of our policy cases the relative targets of China and India for CO 2-intensity have become binding (Table 4.10). In 2020 in all cases, the CO2-intensity remained well below the most Table 4.10
Average annual growth rates of GDP and emissions (2005-2020) and CO2 intensity reductions in 2020 with respect to 2005, China and India, selected policy cases GDP
CO2
GHG
CO2 intensity 2020 % reduction below
Average % annual growth 2005-2020
2005
China BASELINE
8.2
4.0
3.5
47.3
AMBITIOUS PLEDGES
8.2
4.2
3.6
45.2
PLEDGES
8.2
4.2
3.7
45.9
PLEDGES WITH BM
8.2
4.1
3.7
45.9
BASELINE
7.1
4.3
3.2
35.1
AMBITIOUS PLEDGES
7.1
4.9
3.3
28.9
PLEDGES
7.1
4.6
3.4
31.3
PLEDGES WITH BM
7.1
4.6
3.4
31.4
India
Source: WorldScan
ambitious pledges of China and India (45% and 25% reduction below 2005 intensity). In terms of GHG-intensity the reduction performance of these countries is even better than for CO 2. In terms of environmental effectiveness AMBITIOUS PLEDGES appears marginally outperforms the other four scenarios, lowering the global emissions by 2.1 Gton CO2-eq. at costs that are similar to the costs in the other policy cases. Second comes PLEDGES WITH CDM, decreasing the global emissions by 2.0 Gton CO2-eq.. Moreover, in this policy variant OECD production leakage of the energy intensive sector is lowest in absolute terms.
4.4
Conclusion The growth of fossil energy use and of trade in energy-intensive products by non-Annex I has significantly raised the assessments by modelling teams of the rate of carbon leakage that goes with unilateral climate change policies in Annex I. There is no doubt that high leakage rates will lead to vigorous pleas that border measures are necessary to curb the leakages. Our simulation outcomes indicate that production leakage for the energy intensive sector will be relatively modest in absolute terms for Annex I, ranging from 1.4% (PLEDGES) to 0.7% (PLEDGES WITH 51
CDM and AMBITIOUS PLEDGES) of baseline production. Our simulations also suggest that border measures are rather ineffective in reducing leakage
the leakage rate for energy-
intensive production being reduced by a modest 17% and for carbon by only 4%. Moreover, the border measures in our analysis hardly affect economic welfare in Annex I. Finally, our simulations show that the fossil fuel price channel is by far the most important cause of carbon leakage. The border measures investigated in this report hardly affect leakage as they do not address this channel.15
15
These outcomes may depend on model parameterizations and specifications. Table A.4 in the Annex gives the Armington
elasticities adopted in our study. 52
5
Trade and climate change Climate change policies will not only affect trade negatively (through cost differences and possible border measures). Climate change policies also foster trade in environmental goods and services which contribute to emission reductions. Moreover, it also leads to direct trade in emission reductions such as the EU ETS allowances and emission reductions from CDM. In this chapter, we will describe the markets for both environmental goods and services and for emission reductions. Furthermore, we will investigate the barriers for trade in environmental goods and services.
5.1
Trade in environmental goods and services Establishing trade and trade patterns of environmental goods and services is hampered by the fact that data are difficult to obtain. In the Harmonized Commodity Description and Coding System (HS), environmental goods and services are not readily recognisable at the 6-digit level. At this level, they are lumped together with other products which do not necessarily contribute to reducing environmental pressure. For example, solar photo-voltaics panels are in the same category as LEDs. At a more detailed level (e.g. 8 or 10 digits), this problem does not arise. However, only a limited number of countries report trade at this level of disaggregation, moreover the use of the classification system at these levels is not uniform (Veena Jha 2009). Another problem is that products frequently are dual-use, either as part of an environmental friendly technology or of a conventional technology. For example, ball bearings can be used in both wind-turbines and in conventional power plants. In World Bank 2008, the trade volume has been calculated for 40 goods that are categorized as climate friendly, based on a list of 153 environmental goods which has been produced by a group of countries for discussion in the WTO16. This reduces the problem of overestimating the volume of trade in environmental goods.
Table 5.1
Trade in climate-friendly technologies High-Income WTO members Low- and Middle-Income WTO members ($ billion)
($ billion)
Year
Imports
Exports
Imports
Exports
2002
24
26
14
9
2003
27
29
17
10
2004
35
40
23
14
2005 Source: World Bank 2010
42
46
27
18
16
This is the so-called Friends of Environmental Goods and Services (EGS) country group, 53
Trade has increased considerably in the period 2002-2005, both in high-income and low- and middle-income WTO members. The latter remain net importers of climate friendly goods, even though their exports doubled in this period. The study by Veena Jha (2009) has considered trade in renewable energy goods such as wind turbines and photo-voltaic panels, both end-use products and intermediates. She has also used the HS-codes, which also raises the problem of including dual-use goods and therefore overestimating actual trade in renewable energy goods. Therefore, she makes a distinction between multi-use and goods which have only an environmental friendly application. Using this latter subgroup eliminates this problem (although it underestimates real trade volumes in renewable energy related goods). Table 5.2
Trade between WTO members in single-use renewable energy technologies, 2007 Imports
Exports
$ billion
$ billion
Developing countries
22
18
Developed countries
45
47
Total Source: Veena Jha 2009
67
65
The five largest exporters in 2007 of renewable energy technologies where Germany, Japan, United States, China and the Netherlands. Germany, United States and China were also in the top-five of importing countries, together with Spain and Korea. As in the data from the World Bank study (2008) cited above, lower-income countries are net importers, although the difference is considerably less for the goods and countries considered here. This might also reflect the growth in production of these goods in countries such as China and India in recent years.
An important driver for trade in renewable energy technologies (both imports and exports) is the deployment of renewable energy in a country. The more countries invest in renewable energy themselves, the more likely are they to be important importers and exporters of renewable energy goods. Deployment is largest in countries which stimulate renewable energy through, for example, subsidies or a renewable energy obligation. Tariffs on renewable energy goods differ. For solar technologies and components, they were generally below 15 percent in 2007, for wind they are generally below 10 percent (Veena Jha 2009). Tariffs on these goods are in general higher in developing countries than in developed countries (Veena Jha 2009). In the EU and the US, applied tariffs on both wind and solar energy technologies and components are below 5 percent, in India and Brazil they are above 10 percent. World Bank (2008) also shows that average applied tariffs in low- and middle-income member countries of WTO are higher than those in high-income WTO members. Part of the explanation for this difference is that developing countries use tariffs in order to develop their 54
own industries in these fields. Furthermore, the tariffs are on broader categories of goods which include also other than environmental friendly goods and also dual-use goods. An important function of these tariffs in these countries is also to raise revenues. In addition to tariffs, trade in environmental goods can also be hampered by non-tariff measures such as, for example, administrative procedures, investment restrictions, import quota, divergent technical standards or violations of intellectual property rights. Steenblik and Kim (2009) and Steenblik and have investigated trade barriers for a number of climate change technologies such as renewable energy, combined heat and power, district heating and cooling, solar heating and cooling and energy-efficient motors. Their findings concerning tariffs on these goods confirm that on average tariffs in developing countries are higher than in developed countries. Given the lack of data on non-tariff measures, Steenblik and Kim (2009) and Steenblik et al. (2010) have used information acquired from major companies who trade in the selected technologies. The major non-tariff measures identified in these studies were: -
Technical standards which differed from international standards. This requires additional testing and therefore raises costs for importers
-
Lack of protection of intellectual property. Importers often had to compete with local made copies of their products, against which authorities no action was taken by the authorities. This problem occurred especially in China.
Veena Jha (2009) mentions localization measures, which require that part of the equipment used in a project is provided by domestic producers. For example, localization requirements of 70% have been reported for renewable energy projects in China.
Reducing trade barriers (both tariffs and non-tariff barriers) will increase the volume of trade in environmental goods17. The number of studies which try to quantify the effect of liberalisation on trade volume however is limited. A World Bank study (2008) considered the effects on trade in 12 goods in four technologies (clean coal plants, wind power, solar PV and energy-efficient lighting). They used a partial equilibrium approach based on import demand elasticity‟s derived from the World Bank‟s Global Monitoring Report to estimate trade effects between 18 developing countries with high GHG emissions. Two scenarios were considered: (i) tariff removal and (ii) elimination of both tariff and non-tariff barriers for the 12 goods taken into account. Trade volumes increase on average with 7.2 percent for all four categories of technologies with the abolition of tariffs. Eliminating NTBs as well increases trade volume with 13.5 percent on average. Trade volume for the goods from the efficient lighting technology increase the most, with 64 percent. A study by the Peterson Institute (Adler et. Al. 2009) looked at trade in environmental goods between 22 countries (both developed and developing countries). They have used a more extensive list of environmental goods which have been identified by the World Bank (2007). 17
More trade will increase the efficiency of realising emission cuts and deploying renewable energy. 55
For these countries, imports in 2007 amounted to $136 billion, about 1.6 percent of all merchandise imports in these countries. Reducing applied tariffs leads to an increase in trade in environmental goods of 5.7 percent compared to current trade volume.. These studies suggest that substantial trade volume increases can be attained with tariff cuts and elimination of NTBs. However, it should be realised that demand for environmental goods is to a large extent driven by government policy, especially in the field of renewable energy. Lowering trade barriers in itself it will not necessarily increase the use of these goods and technologies, because of the higher costs of renewable technologies compared with fossil fuels. Increased trade will result in a shift in production between trading partners, not necessarily a substantial increase in production and use of renewable technologies. Other policies, such as climate change policies and policies for the stimulation of renewables are necessary to increase demand for these technologies. Moreover, transport costs for some goods are relatively high, such as windmills. Opening production facilities, either directly or through joint-ventures and take-overs, in countries with a significant demand is a more appropriate strategy fore these types of goods.
In addition to trade in goods that are beneficial for GHG emission reduction, there is also trade in services which contribute to GHG reductions. Examples of these are financing of renewable energy projects, training of personnel and R&D services for emission reduction projects such as CMD projects and engineering services. Data on the volume of trade in services related to climate change is difficult to acquire, because data on trade in services related to climate change are no collected separately from trade in the same kind of services which are used for other purposes. In a study of the OECD (2010), a number of examples and case studies are examined, based on information from interviews with firms that provide climate related services. One of the findings is that these services are important for the deployment of climate change mitigation technologies. They are often supplied together with environmental friendly goods as an integrated package (World Bank 2008). Important services are business services, construction, environmental and energy services. Financial services related to carbon finance such as CDM are also an important part of the services provided. Many of these services involve high-skilled personnel which is not available in many countries, given the specific type knowledge needed. In terms of the modes of trade in services as defined by the GATT (1. cross-border trade, 2. consumption abroad, 3. commercial presence and 4. movement of natural persons), services related to climate change are predominantly of type 3 and 4. Because many of the services have to do with construction and operation of production facilities such as, for example, renewable energy installations, a commercial present in the host country is needed. This is supplemented by the temporary movement of personnel, both from firms which have established a commercial presence and from other independent firms.
56
In the current DOHA-round of trade negotiations, there are specific discussions on the liberalisation of environmental goods (environmental friendly services are not included in these particular discussions). At present, progress is limited. A major issue is which approach should be used for liberalising trade in environmental goods. In the list approach, which is favoured by developed countries, environmental goods are identified and subsequently elimination of barriers and non-tariff barriers are negotiated on a most-favoured nation basis. Instead, some developing countries have proposed a project approach, in which temporarily imports of goods and services are liberalised which are necessary for a specific environmental project. One of the reasons for suggesting this approach is the fear that the list approach would also lead to liberalisation for a large numbers of goods, such as goods which have other uses than only an environmental (the dual-use goods) and other goods within 6-digit HS categories (see above on the problems of identifying environmental friendly goods). In contrast, the project approach would not provide access to foreign markets on a predictable and permanent basis, which would reduce the effect of liberalisation (World Bank 2008).
Concluding, trade in environmental friendly goods and more specific goods which contribute to mitigating climate change emissions has grown considerably over the last years. The main reason for this growth has been policies promoting the use of these goods, such as climate change policies and stimulation of renewable energy use. Tariffs on the import of these goods are low in most developing countries, while developed countries tend to have tariffs which are considerably higher. Moreover, non-tariff barriers and measures also reduce trade in environmental goods services. Reducing tariffs and non-tariff measures will foster trade. It will also reduce the costs of meeting climate change and renewable energy policy goals worldwide, although so far the extent of the efficiency gain which can be realised is difficult to predict. Trade liberalisation in itself will not necessarily increase demand for environmental friendly goods and services, because demand is to a large extent driven by other policies such as climate change and renewable energy measures.
5.2
Transport, trade and climate change International trade depends on transport, on the movement of goods and services. Climate change can either have a direct effect on transport or indirectly through climate change policies. As regards the latter, current and foreseen climate change policies will only have a limited effect on transport because GHG-emissions from international sea and air transport are not limited by the Kyoto-protocol. An exception is international air transport, which will be brought under the EU ETS in 2012 as far as aviation within and to and from the EU is concerned. Moreover, seaborne transport is energy extensive. Even if CO2 emissions from cargo ships would be priced, the impact would be limited because seaborne trade is one of the least energyintensive modes of transport. In terms of total volume, GHG-emissions from cargo ships 57
account for about 5 percent of global greenhouse gases (Curtis 2009). A moderate increase in seaborne transport costs would probably have limited effect. This does not necessarily hold for larger cost increases which might result from more ambitious climate policies. For example, the high oil prices in 2008 raised the costs of shipping a standard 40-foot container from Shanghai to the eastern seaboard of the US to $8000, compared with $3000 in 2000 (Rubin and Tal 2008). Climate change itself may affect transport more directly over time. Increased chances of extreme weather events such as hurricanes could increase the frequency of disruptions of transport routes and infrastructure such as roads, railways, ports and airports. Inland waterways might be affected by periods of drought, which could interrupt water transport. More frequent transport disruptions would not only raise transport costs, it would also interfere with global supply chains which depend on just-in-time production and distribution and could therefore have a significant impact on global trade (Curtis 2009). However, given the current knowledge about the impact of climate change, it is difficult to provide a detailed analysis of the impacts of climate change on transport. Moreover, these effects will probably develop over a considerable period of time. The impact of climate policies might be felt more immediately once international agreement would be reached on limiting emissions from transport within the context of international climate change policy.
5.3
The carbon market Climate change policy does not only increase trade in environmental goods and services, it has also led to the development of an international carbon market. The international carbon market consists of markets for several different products, which are linked in varying degrees. The different markets and products are: the EU ETS CDM and JI other emission trading schemes voluntary market The World Bank provides an annual overview of these carbon markets (World Bank 2009 and 2010). Table 5.3 presents the relative size and value of these markets in 2009.
58
Table 5.3
Global carbon market 2009 Volume
Value
(1000 Mton CO2 -eq)
(€ million)
EU ETS
6.3
85.3
CDM and JI
1.3
14.8
Other trading schemes
1.0
3.1
Voluntary market
0.0
0.2
Total
8.6
103.4
EU ETS and CDM The trade in EU ETS allowances is both in volume and in financial terms the largest market. In 2009, the trading volume was 6.3 billion tCO2-eq for spot, futures and options contracts together, more than a doubling compared with the volumes traded in 2008. The value of these trades rose considerably less, from €68 billion in 2008 to €85 billion in 2009. The reason for this is the fall in allowance prices, from an average of €22.1 in 2008 to €14.0 in 2009, due to the financial crisis. Linked to the EU ETS is the market for project-based emission reductions such as CDM and JI. CDM is the most important of these markets. It consist of a primary market and, starting from 2005 when the Linking Directive entered into force, also on a secondary market. On the primary market, the future CERs generated by a project are sold by the project developer to buyers such as firms or countries. The contracts for primary CERs can take various forms such as payment now for future credits, option contracts and payment at the time of delivery for a fixed (or indexed) price, called ERPA (Emission Reduction Purchase Agreement). This last form is the most common contract used on the primary market. On the secondary market, CERs are bought and sold on which have already been delivered or which have been contracted on the primary market. The risks associated with secondary CERs are therefore less than those of primary CERs and their price is higher. As CERs are to a large extent exchangeable with the ETS allowances, their price has been linked to the price of ETS allowances. Given the higher risks of CERS compared with ETS allowances, secondary CERs are trading at a discount with respect to the ETS allowance price (the average price in 2009 was € 11.9 per ton CO2-eq). This price discount is roughly 10-15%% (see also Green 2008) This discount reflects the higher risks associated with buying CERs as compared with trading ETS allowances, risks which consist, among others, of the possibility that in the future stricter limits might apply to the use of CERs in the ETS, which makes them less fungible. The secondary market has increased considerably over time, with an increase in both value and volume of 350% in 2008, compared to 2007, reaching a volume of 1072 Mton CO 2-eq. In 2009, growth stalled , with the total traded volume on both spot and futures market at just above 1 billion ton CO2-eq. Volumes on the primary market have declined considerably, from a volume of 552 Mton CO2eq in 2007 to 404 Mton CO2-eq in 2008 and 211 Mton in 2009 (World Bank 2010). The 59
financial crisis has significantly reduced the availability of capital for CDM-projects. Moreover, uncertainty about the future of international climate change policy after the inconclusive Copenhagen summit, the lack of progress on emission trading in countries such as the US and Australia and the eligibility of CERs in the third phase of the EU ETS has reduced interest in primary CERs. Prices on the primary market for CERs have reflected the waning interest. After a high average price in 2008 of €11.46 (World Bank 2009), the average price in 2009 has declined to €9.1 per ton. CERs which will be delivered after 2012 are sold at a discount, at prices in the range of €68, because of the enduring uncertainty regarding the post-Kyoto period. Bottom prices for primary CERs have partly been determined by the Chinese government‟s policy of demanding minimum prices for primary CERs, depending on the project type 18, which has acted as an unofficial price floor, given the dominant position of China on the primary CER market. In 2008, China supplied 84% of the primary CDM market, a market share which declined to 72% in 2009. In earlier years, projects which reduced the emissions of HFC greenhouse gases were responsible for a large share of the volume. Since 2006, however, the relative share of these HFC projects has diminished. In 2008 and 2009, the main types of projects were in the fields of renewable energy (especially wind and hydropower) and energy efficiency improvement and fuel switch (World Bank 2009 and 2010). European buyers dominate the market for project-based emission reductions (CDM and a limited amount of JI), with a market share of 80% in 2007 and 2008. Private sector companies contracted the major share of this, 90% (World Bank 2009). Up till the 1st of august 2010, 423 million CERs have been issued for the emission reductions generated by the products that have been contracted on the primary market so far (http://cdmpipeline.org/overview.htm)19. Installations which fall under the EU ETS have surrendered 160 million CERs in 2008 and 2009 in order to comply with the ETS. In terms of total verified emissions within the ETS in 2008 and 2009 of 3993 Mton CO2, this represents 4.0 percent (based on http://ec.europa.eu/environment/climat/emission/pdf/AL_VE_2009_public_format.xls). ETS companies further hold CERs in order to comply with future obligations, both in the second phase of the ETS and in the 2012-2020 phase20.
Other trading In addition to the ETS and the related trade in primary and secondary CERs, there are other allowance trading schemes and markets and there is a limited voluntary demand 21. In terms of 18
The Chinese National Development and reform Commission is reported to have used different floor prices for different
projects, such as, for example, €10 for wind projects and €8 for large hydro (Worldbank 2009) 19
Primary CER transactions do not directly result in the issueance of CERs, these will only be issued once a project yields
emission reductions which are subsequently verified and approved by the CDM executive board. 20
One European utility purportedly holds more than 15% of the CERs issued so far (World Bank 2010).
21
These markets consist of an allowance scheme in New-South Wales in Australia, the Regional Greenhouse Gas Initiative
in 10 eastern US states, trade in assigned amount units and a voluntary market for offsets such as CERs. 60
trade volume, these markets add-up to 12% of total trade on allowance markets including the ETS, in value it only represents 3% (based on World Bank 2010). The largest single market in 2009 next to ETS and CDM is the Regional Greenhouse Gas Initiative, with a volume of 805 Mton CO2-eq. Activity in this market was partly driven by the passage of the Waxman-Markey Bill on emission trading in the US house of representatives, which raised expectations about the introduction of CO2 emission trading in the US at the national level. However, when the prospects of passage in the US senate diminished, market activity declined considerably.
Future market development The development of carbon markets after 2012 remains to a large extent uncertain. The EU ETS is the only market with relative clear prospects up to 2020, even though there is still some uncertainty about the size of the cap, which depends on the extent of climate change policies in other countries. The market for CERs is uncertain because the rules governing the use of CERs in the third phase of the EU ETS also partly depend on whether there will be an international agreement on climate change policy or not. The financial crisis and the following economic downturn has affected the willingness of countries to engage in climate change policies, as is illustrated by the absence of an international agreement in December 2009 in Copenhagen. Plans for allowance trading in a number of countries such as Australia and the US have also been delayed, which further diminishes the prospect for future carbon markets.
Based on the analysis with the WorldScan model in chapter 4, we can provide some idea about the size of future carbon markets in terms of international trade in emission reductions and CERs. Table 5.4 presents CDM trade volumes and the value of this trade for different countries and regions in 2020 in the PLEDGES WITH CDM scenario. Total volume of CDM is almost 800 Mton CO2-eq. Given the price paid for CERs of €6 per ton CO2-eq, total value of this trade amounts to € 4.6 billion. The assumption is that the rent created by the limit on the use of CDM falls to the buyers, see section 2.3.2. The CDM price and therefore the value of trade in CERs would be higher if the buyers would be able to appropriate this rent. China is the largest exporter with a market share of 66%. Note that these figures represent the flow of primary CERs; the trade volumes reported in Table 5.3 are considerably larger because an allowance or secondary CER can be traded more than once within a year. The trade volumes in Table 5.4 can better be compared with data on the primary market. According to the World Bank (2010), the volume on the primary CER market was 406 Mton CO2-eq in 2008 and 211 Mton CO2-eq. Given the current pledges made by countries in the climate negotiations, the supply of primary CERs might be expected to double, compared to the average of 2008 – 2009.
61
Table 5.4
CDM trade in 2020 in PLEDGES WITH CDM scenario Volume
Value
(Mton CO2-eq)
(€ billion)
EU27
-419
-2,4
USA
-219
-1,3
Rest of OECD
-161
-0,9
China
527
3,1
India
149
0,9
Rest of non-Annex I
123
0,7
Source: WorldScan
The analysis presented above did not include credits which might come available from reducing deforestation such as REDD („Reducing Emissions from Deforestation and Degradation‟). Within the context of the Kyoto-protocol, the use of CDM credits from forest sinks is limited because CERs from land use and land use change and forestry (LULUCF) expire either within the commitment period (so-called tCERs, temporary CERs) or at the end of the crediting period of the project (long-term CERs, LCERS). When these CERs, expire, they have to be replaced, for example, by AAUs or CERs from other types of CDM-projects. In the period after the Kyoto-protocol, the use of CERs from forestry might be less restricted, depending on the negotiations about a future climate policy regime. Anger et al. (2009) have investigated the impact which the availability of emission credits from REDD might have on carbon markets. They have used a partial equilibrium model of world carbon markets which includes supply curves for credits from REDD which are derived from the global forestry model GCOMAP. Abatement costs for Annex I countries and CDM supply are derived from the POLES energy-system model. Anger et al. (2009) have simulated scenarios with varying restrictions on the use of REDD credits. They have taken the announcements about intended emission reductions of Annex I parties up to October 2008 as targets for the Annex I countries. In a scenario without CDM and REDD credits, the emission price in 2020 is €38 per ton CO2. Allowing for CDM reduces the price to €16. Including unlimited REDD credits on the carbon market reduces the CO2 price further to about €8 per ton. Africa is the largest supplier of REDD credits, around 1000 Mton in 2020, while South America supplies 300 Mton. The use of CDM credits is reduced by half with the inclusion of REDD credits. Restricting the use of REDD credits produces intermediate results, depending on the level of restriction applied. With a restriction of REDD credit use to 20% of the reduction requirement of Annex I countries in 2020, the emission price falls to €12 per ton CO2. Total REDD CER exports are reduced from almost 1500 Mton in 2020 in the scenario without limits to the use of REDD CERs to about 600 Mton.
62
6
Conclusions Climate change policies which do not have a global coverage will be less effective than a worldwide agreement because emission reduction policies will only apply to part of the global emissions of greenhouse gasses. Moreover, increased carbon costs in those countries which introduce climate change policies will reduce the competitiveness of firms in these countries, which will affect trade. These effects are most pronounced in sectors which are both energyintensive, and therefore suffer the most from increased carbon costs, and which are open to foreign competition, both in their home market and in export markets. The main sectors for which this applies at an aggregated level are the iron and steel sector, cement, aluminium and fertilizer production. At a more disaggregate level, there can be firms in other sectors which also run a higher risk, moreover there will be considerable differences between firms in the sectors mentioned. Loss of competitiveness will reduce exports and increase imports. Foreign firms will increase their market share and increase their production. Consequently, emissions will increase as well, which will partly undo the realised emission reductions. This carbon leakage, which is defined as the increase in emissions in non-Annex I countries compared to the baseline divided by the reduction in emissions in Annex I compared to the baseline, can occur either because of a shift in current production (operational leakage) or because firms decide to build new plants in carbon-intensive sectors in countries without climate policies (investment leakage). Moreover, climate policies will reduce demand for fossil fuels and therefore prices for fossil fuels will decline. This will increase demand and therefore emissions in regions without climate policies. The impact of climate policies on competitiveness and leakage will not only depend on the stringency of the emission reduction target, but also on the policy instruments used to realise these reductions. The main instrument used within the EU is the EU ETS. The cost increase due to the pricing of CO2 is mitigated to some extent by the expectation that the base for free allocation of permits will be updated and by the entrance and closure rules, which makes free allowances available to entrants and ends the free allocation to firms that stop producing. The effect of these options is comparable to output-based allocation, in which firms receive allowances on the basis of their actual emissions. The possibility to use CDM will reduce the costs of emission reductions, thereby reducing the competitiveness impact of emission trading. It can also have a contrary (but smaller) effect on competitiveness because it acts as a subsidy for foreign firms who supply CDM credits. The effect of CDM on competitiveness and leakage can be further improved by modifying the baseline through domestic climate policies in CDM host countries. Another option to address concerns on competitiveness and leakage is to use border measures. Border measures can introduce carbon costs on imports, for example through a tax or the obligation to acquire allowances, give a rebate on exports or combine the two. Imposing border measures can produce a considerable administrative burden. This burden can be reduced by 63
limiting BM to those sectors which are most at risk of leakage mentioned above. Moreover, using the benchmarks which are being developed for the allocation of allowances in the third phase of the EU ETS as a basis for border measures reduces the costs of determining the emissions of imported products. BM will be less effective if they are not applied in all countries which take part in a climate agreement, because it would give exporters from other countries the option to strategically direct their exports at those countries which have not introduced BM. At present, a definite answer on the compatibility of BM with the WTO agreements is not possible. Either the possibility to impose border taxes to compensate for domestic taxes or the environmental window, article XX, might allow the use of BM, such as taxes or the obligation to obtain emission allowances. A prerequisite is that the costs imposed on imported goods are not higher than those on domestic goods. Consequently, BM would need to take into account the level of grandfathering applied in the ETS.
The main result from our modelling exercise is the finding that carbon emission leakage due to direct loss of competitiveness via the trade channel is very small. Global competition distortions caused by the absence of a carbon price in countries with no binding pledges result in direct leakage effects of 2% or less. In other words, for every 100 ton CO2eq emission reduction in the EU, emissions go up with 1 ton only in countries with no binding pledge. However, indirect leakage through the energy price channel is considerably more important. Measures taken by countries with binding pledges to reduce emissions reduce global demand for energy and thus reduce global energy prices. This actually increases energy consumption in countries that have no binding target and take no measures. It triggers high carbon leakage effects, ranging between 13% and 36%, depending on the scenario. Indirect carbon leakage through the energy price channel has increased significantly in this study, compared to the earlier studies. The carbon leakage rate in our study is 36 percent in the Pledges scenario, which is considerably higher than the 3-11 percent leakage rates reported in earlier studies. This is due to the increased importance of fossil energy use and trade in energyintensive products by non-Annex I countries, as captured by the 2004 data (GTAP-7) used to calibrate this model (compared to 2001 data used in earlier models). It also confirms responsiveness of fossil fuel prices to climate policies, reducing prices due to binding climate targets but leading to increased consumption and upward price effects in countries without binding targets. Other modelling teams which use the same data also report comparably higher leakage rates. Production leakage for energy intensive industries in developed countries is also very limited. Reductions in production levels for energy intensive industries compared to baseline are 1.4% or less, depending on the scenario. This is a very low impact, considering that the WORLDSCAN model assumes that pledges for developing countries under the Copenhagen Accord are non-binding.
64
Another major difference with earlier studies is the limited effect that border measures (BM) have on leakage in our simulations. In these earlier studies, BM would reduce leakage with 3060 percent, while in our simulations BM reduces carbon leakage by 1 percentage point only from 36 to 35 percent. BM are less effective in reducing carbon leakage because the fossil fuel price channel rather than the trade channel is the dominant cause of leakage. BM do not address that channel. Allocating allowances for free to energy intensive industry might to some extent reduce the competitiveness impact of climate change policy. The effect of free allowances on production costs have been simulated on the assumption that the cost reduction for the energy intensive sectors is equal to the entrant reserve in the ETS of 5% of total allowances available in the period 2013-2020. The resulting cost reduction is limited and therefore the effects of free allocation hardly differ from the case without free allocation. Another variant has been simulated for the EU in which the cost reduction for the energy intensive sectors is raised to the total free allocation to these sectors. In this case the EU energy intensive sector shifts the burden of higher carbon costs to the other sectors in the economy. This actually reverses production losses in these sectors within the EU. Emission prices in other Annex I countries will drop slightly because of smaller energy intensive production and because of a smaller fossil fuel price decrease.
In terms of environmental effectiveness the "Ambitious Pledges" scenario and "Pledges with CDM" appear to outperform the other scenarios, lowering global emissions by 5%. Of the policy cases that we assessed CDM is the most effective option to reduce the leakage rate. CDM lowers the ETS carbon price from €31 to €9 per ton CO2-equivalent. Hence, the effect on fossil fuel prices is relatively small and therefore also leakage through the fossil fuel price channel. Moreover, CDM redcues welfare costs to 0.2 percent comparedf to the baseline in 2020.
Climate change policy can not only affect sectors negatively, it will also stimulate trade in and the use of environmental goods and services. Moreover, it has given rise to new markets for carbon emission reductions such as trade in ETS allowances and CDM credits. Trade in environmental friendly goods and more specific trade in goods which contribute to mitigating climate change emissions has grown considerably over the last years. The main reason for this growth has been policies promoting the use of these goods, such as climate change policies and stimulation of renewable energy use. Tariffs on the import of these goods are low in most developing countries, while developed countries tend to have tariffs which are considerably higher. Non-tariff barriers and measures also reduce trade in environmental goods services. Trade liberalisation will increase trade in environmental friendly goods and services, however it will not necessarily increase demand for these goods and services. Demand is to a large extent driven by other policies such as climate change and renewable energy measures. 65
Carbon markets have also developed over the last years, although the financial crises and uncertainty about future climate policies have reduced market activity in 2009, especially regarding the development of new CDM projects. In 2020, trade in primary CERs can increase considerably compared to current levels. In the PLEDGES WITH CDM scenario which has been simulated with WorldScan, total volume on the CDM market for primary CERs is 800 Mton, compared to a supply of primary CERs of 211 Mton in 2009. If emission reduction credits from reduced deforestation (REDD) would be included, the use of CDM would be considerably less. Partial equilibrium analysis using marginal cost curves for emission reductions and deforestation show that the inclusion of REDD credits halves the sum of CDM CERs.
66
Annex Tables in addition to section 4 Table A.1
Differences between WEO-scenario and baseline of average annual growth rates, 2004-2020 Population GDP volume
Energy consumption a)
GHG emissions
Energy intensity
GHG intensity b)
Annex I
0.0
0.0
-0,6
-0,3
-0,6
0,4
EU-27
0.0
0.0
-2,9
-1,0
-2,9
1,9
Germany
0.0
0.0
-2,5
-1,1
-2,4
1,4
France
0.0
0.0
-4,4
-0,8
-4,4
3,6
United Kingdom
0.0
0.0
-2,7
-0,8
-2,7
1,9
Italy
0.0
0.0
-3,5
-0,9
-3,5
2,6
Spain
0.0
0.0
-3,5
-1,0
-3,4
2,5
Netherlands
0.0
0.0
-1,9
-0,5
-1,9
1,4
Other EU15
0.0
0.0
-4,2
-1,3
-4,1
2,8
Poland
0.0
-0.1
-2,1
-1,2
-2,0
0,9
Rest of EU-27
0.0
-0.1
-3,1
-1,1
-3,0
1,9
Norway
0.0
0.0
3,3
0,5
3,3
-2,9
Switzerland
0.0
0.0
0,1
0,2
0,1
0,1
Russia
0.0
0.0
0,3
0,1
0,4
-0,3
Ukraine
0.0
0.0
0,2
0,1
0,2
-0,1
USA
0.0
0.0
0,1
0,0
0,1
0,0
Canada
0.0
0.0
0,3
0,1
0,3
-0,2
Japan
0.0
0.0
0,1
0,1
0,1
-0,1
Australia
0.0
0.0
0,2
0,1
0,2
-0,1
New Zealand
0.0
0.0
0,0
0,0
0,0
0,0
Non-Annex I
0.0
0.0
0,1
0,0
0,1
0,0
Brazil
0.0
0.0
0,1
0,0
0,1
-0,1
Middle East and North Africa
0.0
0.0
0,2
0,1
0,2
-0,1
China (incl. Hong Kong)
0.0
0.0
0,0
0,0
0,0
0,0
India
0.0
0.0
0,0
0,0
0,0
0,0
Rest of the World
0.0
0.0
0,2
0,1
0,2
-0,1
0.0
0.0
-0,1
-0,1
-0,1
0,1
World
a) Total of coal, refinery products, natural gas, biofuels, commercial biomass and renewable energy b) GHG-intensity represents the ratio of GHG-emissions and energy consumption Source: WorldScan
67
Table A.2
PLEDGES WITHOUT THE EU RENEWABLES TARGET, 2020 Emission price a)
Target (or 2020 emissions) compared to 2005 emissions (%)
Economic welfare b)
Percentage GHG reduction
Target Emissions 2020 compared to compared to baseline baseline emissions 2020 emissions 2020 (%)
(%)
€ / tCO2
(%)
Annex I
-7
-7
-13
-
-0.3
EU-27
-9
-21
-21
45
-0.4
Germany
-15
-22
-17
11
-0.3
France
-15
-22
-20
11
-0.4
United Kingdom
-17
-21
-19
11
-0.3
Italy
-14
-34
-20
11
-0.5
Spain
-10
-29
-22
11
-0.5
Netherlands
-17
-17
-13
11
-0.4
Other EU-15
-14
-27
-26
11
-0.6
15
-1
-25
11
-0.4
Poland
10
-5
-25
11
-0.2
Norway
Rest of EU-27
-35
-27
-27
115
-1.4
Switzerland
-21
-10
-10
39
-0.2
Russia
33
17
4
0
-1.2
Ukraine
77
83
6
0
0.4
USA
-17
-12
-12
12
-0.1
Canada
-17
-19
-19
14
-0.5
Japan
-30
-18
-18
14
-0.2
Australia
-10
-20
-20
13
-0.7
New Zealand
-28
-30
-30
52
-0.5 0.0
Non-Annex I
61
-
3
0
Brazil
53
-
6
0
0.1
Middle East and North Africa
26
-
4
0
-0.5
China (incl. Hong Kong)
72
-
2
0
0.1
India
66
-
4
0
0.3
Rest of the World
57
-
6
0
0.0
26
-
-3
World
a) For EU-27 ETS-price, for member states non-ETS-price, for other Annex-I countries national carbon tax b) Equivalent variation as % of national income of the baseline Source: WorldScan
68
-0.2
Table A.3
PLEDGES WHAT IF FA 100% SUBSIDY, 2020 Emission price a)
Target (or 2020 emissions) compared to 2005 emissions (%)
Economic welfare b)
Percentage GHG reduction
Target Emissions 2020 compared to compared to baseline baseline emissions 2020 emissions 2020 (%)
(%)
€ / tCO2
(%)
Annex I
-7
-7
-13
-
-0.3
EU-27
-9
-21
-21
36
-0.4
Germany
-15
-22
-16
12
-0.3
France
-15
-22
-20
12
-0.4
United Kingdom
-17
-21
-21
12
-0.4
Italy
-14
-34
-17
12
-0.4
Spain
-10
-29
-20
12
-0.4
Netherlands
-17
-17
-16
12
-0.5
Other EU-15
-14
-27
-31
12
-0.7
Poland
15
-1
-21
12
-0.4
Rest of EU-27
10
-5
-25
12
-0.4
Norway
-35
-27
-27
112
-1.3
Switzerland
-21
-10
-10
38
-0.2
Russia
33
17
4
-
-1.3
Ukraine
77
83
5
-
0.4
USA
-17
-12
-12
12
-0.1
Canada
-17
-19
-19
14
-0.5
Japan
-30
-18
-18
14
-0.2
Australia
-10
-20
-20
13
-0.7
New Zealand
-28
-30
-30
51
-0.5 0.0
Non-Annex I
61
-
3
-
Brazil
53
-
5
-
0.1
Middle East and North Africa
26
-
4
-
-0.5
China (incl. Hong Kong)
72
-
2
-
0.1
India
66
-
3
-
0.3
Rest of the World
57
-
6
-
0.0
26
-
-4
-
-0.2
World
a) For EU-27 ETS-price, for member states non-ETS-price, for other Annex-I countries national carbon tax b) Equivalent variation as % of national income of the baseline Source: WorldScan
69
Table A.4
Armington trade elasticities, by sector
Cereals (wheat and cereal grains nec)
5.4
Electricity
5.6
Oilseeds
4.9
Energy intensive sectors
6.5
Sugar crops (sugar cane, sugar beet)
5.4
Vegetable oils and fats
6.6
Other agriculture
4.7
Capital goods and durables
7.6
Minerals NEC
1.8
Consumer food goods
4.8
10.4
Other consumer goods
6.7
Coal
6.1
Road and rail transport
3.8
Petroleum, coal products
4.2
Other Transport (water and air)
3.8
Other services
3.8
Oil
Natural gas (incl. gas distribution) Source: GTAP-7 database
70
20.5
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