"The EU 2050 low-carbon strategy: which policy design?" - - PowerPoint PPT Presentation

"The EU 2050 low-carbon strategy: which policy design?"

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Anil Markandya Ikerbasque Professor, BC3, Spain Honorary Professor, Bath University, UK

Issues to Discuss

• We have an EU commitment to reduce GHGs by 80% by 2050.
• Implications of such a commitment depend on what other countries

do.

• We look at these implications for a variety of possible coalitions with

different commitment to reduce emissions.

• A key instrument in achieving the 80% reduction will be taxes on
• GHGs. One question that comes up a lot is the distributional

implications of these taxes.

• We look at the distributional implication of carbon taxes and pollution

taxes for different EU member states.

• Lastly we already have a system of implicit carbon taxes but they are

very inefficient. We look at the extent of this inefficiency to see what kind of changes we will need to make to get a unified carbon tax system in place.

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Date: meeting

Meeting the 2050 Goal – Different Scenarios

• 1. Introduction
• We consider different coalitions for reducing

GHGs and examine their impacts in terms of:

• Emissions of GHGs
• Energy
• Carbon leakage Industrial and Terrestrial (ICL/TCL)
• Land use
• Price of food
• Climate system

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Date: meeting

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2. Model:

• Global Change Assessment Model (GCAM): an Integrated Assessment

model that links the world’s energy, agriculture and land use systems with a climate model.

• GCAM was one of the four models chosen by IPCC to create one of the main

scenario (RCP 4.5) for the IPCC’s AR5 (Thomson et al. 2011).

• GCAM model can track not only fossil fuel and industrial emissions but also

terrestrial emissions associated to land use change.

• GCAM contains detailed representations of technology options for each of its

economic components with technology choice determined by market probabilistic competition (Clarke and Edmonds 1993).

• More info: http://wiki.umd.edu/gcam/

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• 3. Scenarios (1/3): different coalitions

Scenarios Scenario Participating Regions REF None FR1 EU-27 FR2 EU-27 + US FR3 All Developed FR4 All Developed + China FR5 All Developed + BASIC FR6 All, except Africa, Russia, Middle East

BASIC (Brazil, South Africa, India and China) group was formed by an agreement on 28 November 2009.

Share of the global total CO2 emissions by scenario, 2050

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• 3. Scenarios (2/3): temporal commitments
• First Time Period:
• Developed countries follow EU if inside the agreement: then they

reduce emissions by 80% in 2050.

• Developing countries follow China: peak emissions in 2030.
• Second Time Period:
• From 2030 for developing countries and from 2050 for developed

countries.

• Common but differentiated convergence approach.
• Developed and developing countries converge towards an equal per-

capita emissions levels in 2100 [0.5 tons of CO2-eq to meet the 2 C target]. (Could be linked to the ambition mechanisms of Paris).

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4.

Scenarios (3/3): emissions per capita (tCO2pc)

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5. Results: energy system

• The main channel for ICL is the change in fossil fuel prices, which decrease

with the increasing size of coalition.

Global Fossil Fuel Price Index,2050 (2010=100) Global Energy Mix, 2050 (EJ/y)

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5. Results: global land-use change

• There is an incentive to trade products from land with low carbon density

(e.g. crop land) for products from land with high carbon density (e.g. forest) as CO2 from land has now a market price.

Evolution of Global Forest Area (Mkm2)

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5. Results: regional land-use change

• As a result of the same factors there will be also an incentive for

deforestation in non-participant regions.

Africa, Russia and ME

Evolution of Regional Forest Area (Mkm2 wrt to REF)

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5. Results: side-effects on the price of food

• There is a important trade-off to pay from afforestation: an important

increase in the price of food.

• The highest increases in prices are in the price of animal products such as

beef and poultry.

Global Food Price index (Base 2010=100)

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5. Results: climate system (1/3)

• Price of CO2 increases with participation as global mitigation effort will also

increase.

• In scenarios FR4, FR5 and FR6 there will be two CO2 markets (developing and

developed ) and, therefore, there will be two prices for CO2.

CO2 prices by regions ($/tCO2 US$2010)

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5. Results: climate system

• Unilateral action from developing countries will have a small impact.
• It will be very difficult to met the 2 degree target if some countries never

join to the coalition (unless negative emission technologies or Bioenergy in combination with Carbon Capture & Storage would be available)

Global temperature change, 2010-2100 (ºC)

• 1. Carbon Leakage

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• Fragmented climate policy -> carbon leakage (Böhringer et al. 2012)
• Carbon leakage: carbon regulation/price in some countries could increase the

carbon emissions of non-participatory countries.

• Main channels: change in the price of fossil fuels (ICL, Calvin et al. 2009) and

changes in competitiveness (Rutherford et al 1995).

• However, there is another channel has received little attention: the carbon

leakage triggered by land use changes or “terrestrial carbon leakage” (TCL)

• Literature on TCL: Wise et al. (2009), Calvin et al. (2010, 2014) and Kuik (2014)
• No previous study has analyzed the “industrial” (ICL) and “terrestrial” (TCL)

channel in combination (Otto et al. 2015). We explore these two forms of leakage when emissions from both sources are taxed identically.

• Our analysis does not cover carbon leakage due to change in competiveness.

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• 5. Results: regional carbon leakage (GtCO2, wrt REF, 2010-2050)

Africa, Russia and ME Africa, Russia and ME Africa, Russia and ME Africa, Russia and ME Africa, Russia and ME Africa, Russia and ME

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5. Results: global carbon leakage (GtCO2)

• The relation between leakage (in absolute terms) and the size of the

coalition implementing the climate regime shows an inverted-U shape.

• TCL is relevant for the period 2020-2050, when land-use change take place.

However, in the longer period 2020-2100 and once the carbon storage potential of afforestation is fully exploited, the ICL effect dominates.

Global carbon leakage (GtCO2) for 2020-2050 (left) and 2020-2100 (right)

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5.

Results: carbon leakage rate (%)

• Carbon leakage rate: % of the reduction shifted to non-participants.
• ICL is below 30%, but TCL is much larger due to the

afforestation/deforestation processes.

• Total carbon leakage rate decreases with the size of the coalition from 24%

in FR1 to 5% in FR6.

Cumulative carbon leakage rate (%) for 2020-2050 (left) and 2020-2100 (right)

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6. Conclusions

• 1. A large coalition is needed to get us close to the 2°C target.
• 2. Fragmentation takes us for from that target.
• 3. Fragmentation in terms of coalitions can lead to relevant carbon leakage effects,

especially if terrestrial carbon leakage is considered.

• 4. Fragmentation can hurt vulnerable countries (even if they do not participate in the

climate coalition), because it induces deforestation in those regions and increases (remarkably) the global price of food.

• 5. The dominant type of carbon leakage up to 2050 is the terrestrial channel,

although industrial carbon leakage takes over during the second half of the century,

• nce the carbon storage potential of afforestation is fully exploited.

Distributional Implications of Carbon and Pollution Taxes

Who pays for mitigation policies?

Most studies find regressivity in GCC related taxes, but this conclusion cannot be taken as a rule because it depends on the case study. GCC tax LAP Tax

Here, we conduct a distributional analysis of an LAP tax (based on the internalization of the external costs of several pollutants) and compare it in a comprehenive way with a GCC tax (tax on CO2)

The distributional implications of a revenue- neutral tax reform are also explored.

Environmental taxes allocated to producers ∆ Consumer prices Income impacts of households INPUT-OUTPUT MODEL DEMAND MODEL (AIDS)

Methodology

Scenarios Description Tax Equivalent GCC tax Tax on CO2 emissions levied on producers. €25/t CO2 LAP Tax Tax on NH3, NOX, SO2, NMVOC, and PM10 emissions levied on producers. We use the external cost of CASES project but only internalize 47.2% of external costs Revenue-Recycling Reduction in social security contributions paid by employers 7.5% reduction in SS contributions

Scenarios

0,00 2,50 5,00 7,50 10,00 Electricity, water and gas production Food Sector Energy sector Industries Mining and quarrying Sanitary and vetinary activities; social services Real estate activities and entrepreneurial services Education Financial intermediation Homes that employ domestic staff top 5 Bottom 5 GCC tax LAP tax

Change (%) in production prices. Top and bottom sectors

0,00% 0,20% 0,40% 0,60% 0,80% 1,00% 1,20% 1,40% 1 2 3 4 5 6 7 8 9 10 LAP tax GCC tax

Cost impacts change (EV, %) by expenditure deciles

The importance of consumption pattern

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 2 3 4 5 6 7 8 9 10 Other services Restaurants and hotels Education Leisure and culture Communication Transport Health Home furnishing and home maintenance House Clothing and footwear Alcoholic beverages, tobacco and narcotic Food

Second exercise: Revenue recycling

• 1,5

0,0 1,5 3,0 4,5 6,0 7,5 9,0 Electricity, water and gas production Food Sector Energy sector Industries Mining and quarrying Sanitary and vetinary activities; social services Real estate activities and entrepreneurial services Education Financial intermediation Homes that employ domestic staff top 5 Bottom 5 GCC tax LAP tax

The impact of revenue recycling on price change

0,00% 0,10% 0,20% 0,30% 0,40% 0,50% 0,60% 0,70% 0,80% 1 2 3 4 5 6 7 8 9 10 LAP tax GCC tax

Cost impacts after recycling per expenditure group

Conclusion

• LAP taxes are more regressive than GCC taxes. LAP is more linked to

goods that are consumed by low incomes groups than GCC taxes, where its potential regressive effect is compensated by the higher consumption

• f transport and energy of the higher income groups.
• The result does not improve with the revenue-recycling effect because,

again, the beneficiaries of this policy are labour-intensive and non- polluting goods that are consumed proportionally more by high income groups.

• Although these results are of course an empirical matter, they can be

extrapolated to countries with similar production and consumption profiles.

• Although it was thought that LAP taxes might be easier to implement

because their effects (mainly on health) are felt more immediately by citizens and by low-income households than those of GCC taxes, this may not be the case if the distributional issue is factored into the policy maker’s equation

• If it is wished to correct the distributional effect of this type of tax reform

the standard approach, i.e. reducing taxes on labor, may not improve the distributional effect. However given that the overall regressivity of these taxes is low, various specific combinations of policies could be design to compensate the households or groups that are most affected.

Policy implications:

Inefficiencies in the Taxation of Carbon

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• How do we measure static efficiency?
• Ideally, the static efficiency is assessed in terms of

how successful the current policy mix is in equalising the marginal abatement cost across sectors and across emitters.

• This measure is typically approximated through the

carbon price: the policy mix is statically efficient if it succeeds in generating a uniform carbon price across sectors and emitters.

• Carbon prices can be explicit, such as the carbon

price of the EU ETS, or implicit.

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• Implicit carbon price: financial support by

technology divided by the amount of CO2 emissions avoided.

• Example: average support is 50 €/MWh and emissions account for 0.5

tCO2/MWh. This implies an implicit carbon price of 100 €/tCO2.

• Average financial support by technology is obtained

from CEER database.

• The amount of CO2 avoided:
• National mix (excluding renewables)
• EU mix (excluding renewables)
• Natural gas

RES support mechanisms in the electricity sector

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Hydro Wind Biomass Biogas PV Geo- thermal Waste

Czech Republic

83.2 21.1 59.3 166.2 790.4 :: ::

France

133.2 385.2 536.8 420.7 5381.0 :: ::

Germany

67.4 77.6 228.6 :: 733.8 294.5 ::

Italy

149.9 142.1 224.8 :: 759.5 153.8 ::

Netherlands

224.9 185.4 171.0 :: 890.2 :: 111.3

Spain

124.8 129.2 219.8 :: 1134.3 :: 84.5

United Kingdom

131.0 145.4 129.5 127.6 416.7 :: ::

RES-E support mechanisms: Implicit carbon price (€/tCO2) (2010). National Mix

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Hydro Wind Biomass Biogas PV Geo- thermal Waste

Czech Republic

97.5 24.7 69.5 194.8 926.2 :: ::

France

22.9 66.3 92.3 72.4 925.7 :: ::

Germany

66.5 76.6 225.6 :: 723.9 290.5 ::

Italy

149.9 142.0 224.7 :: 759.2 153.8 ::

Netherlands

183.7 151.5 139.7 :: 727.2 :: 90.9

Spain

82.1 85.0 144.6 :: 746.3 :: 55.6

United Kingdom

117.1 129.9 115.8 114.0 372.5 :: ::

RES-E support mechanisms: Implicit carbon price (€/tCO2) (2010). EU Mix

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Hydro Wind Biomass Biogas PV Geo- thermal Waste

Czech Republic

143.2 36.3 102.0 285.9 1359.8 :: ::

France

33.6 97.3 135.6 106.2 1359.0 :: ::

Germany

97.7 112.5 331.2 :: 1062.8 426.5 ::

Italy

220.0 208.5 329.9 :: 1114.5 225.8 ::

Netherlands

269.8 222.4 205.0 :: 1067.6 :: 133.5

Spain

120.6 124.8 212.4 :: 1095.7 :: 81.7

United Kingdom

172.0 190.8 170.0 167.4 546.9 :: ::

RES-E support mechanisms: Implicit carbon price (€/tCO2) (2010). Natural Gas

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• Implicit carbon price: excise tax per unit of energy product

divided by the CO2-eq emissions per unit.

• Example: excise tax is 0.5 €/litre and emissions account for 2 kgCO2/litre. This implies

an implicit carbon price of 250 €/tCO2.

• Taxes are obtained from the IEA and emission factors from

the IPCC. Energy taxes

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Energy taxes: Implicit carbon price (€/tCO2) (2012).

Electricity Natural gas Diesel Unleaded gasoline Light fuel oil LPG Industry Households Industry Households

Czech Republic

1.91 2.03 6.03 0.00 163.61 222.40 9.86 53.10

France

212.41 299.49 7.23 5.50 151.10 248.71 20.86 37.09

Germany

72.67 160.52 19.95 27.23 175.71 270.36 22.94 56.87

Italy

196.11 152.04 21.79 ::: 230.74 316.01 151.28 90.87

Netherlands

30.84 18.77 13.37 84.42 162.02 318.20 ::: 58.11

Poland

6.12 6.12 0.00 0.00 129.19 175.54 20.73 68.25

Spain

21.85 36.76 0.00 0.00 133.26 191.20 31.20 19.78

United Kingdom

7.55 0.00 4.40 0.00 263.54 312.09 50.62 :::

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• What happens if we include other externalities?
• We include data from the IMF on air pollution, accidents…

Excise tax (€/litre) local air pollution (€/litre) congestion (€/litre) Accidents (€/litre) road damage (€/litre) Implicit Carbon Price (€/tCO2)

Czech Republic

0.4366 0.139 0.178 0.103 0.041

• 9.670

France

0.43 0.128 0.391 0.101 0.039

• 84.400

Germany

0.47 0.154 0.302 0.077 0.026

• 33.069

Italy

0.606 0.146 0.217 0.116 0.026 37.942

Netherlands

0.44028 0.121 0.409 0.068 0.010 60.408

Poland

0.35461 0.098 0.107 0.164 0.012

• 13.215

Spain

0.361 0.164 0.343 0.085 0.030

• 94.172

United Kingdom

0.67415 0.091 0.356 0.050 0.026 72.019

DIESEL

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Excise tax (€/litre) local air pollution congestion accidents Implicit Carbon Price (€/tCO2)

Czech Republic

0.511 0.008 0.189 0.151 70.973

France

0.604 0.008 0.373 0.112 47.289

Germany

0.655 0.008 0.287 0.085 113.385

Italy

0.717 0.007 0.207 0.129 163.110

Netherlands

0.736 0.007 0.390 0.076 113.887

Poland

0.398 0.009 0.114 0.239 15.657

Spain

0.457 0.015 0.326 0.094 8.866

United Kingdom

0.715 0.004 0.339 0.056 137.781

GASOLINE

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Conclusions

• There is little harmonisation in the promotion of renewables and

energy taxes at the EU level.

• The implicit carbon price set by the different policies, vary

widely.

• In the long-term, in order to maximize the static efficiency of the

EU climate instrument mix, the implicit carbon price set by the different policies should convergence with the carbon price of the EU ETS.

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References

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