assessment of green taxes in the eu- the case of fuel ... · 3)an overview of fuel taxation in the...
TRANSCRIPT
Assessment of green taxes in the EU- the
case of fuel taxation in transports
C. Henriques
I. Clímaco
M. Castelo Gouveia
5th European Environmental Evaluators Network Forum
Structure of presentation
1)Rationale for fuel taxation
2)How Europe has been taxing fuels
3)An overview of fuel taxation in the EU
4)Our research question
5)Methodological framework
6)Illustrative results
7)Conclusions/policy implications
8)Future Work
Rationale for fuel taxation
Why taxing fuel?
• Many countries tax road fuels primarily → to raise revenue.
• Demand for these fuels tend to be relatively inelastic (price elasticity near 0) → fuel taxes tend to
be a stable revenue source.
• From an economic perspective taxes on road fuels may also be used to internalise
environmental externalities or other social costs (congestion, traffic accidents, etc.) associated
with their use.
• Road fuel taxation could be seen as Pigouvian tax → imposing a tax on an activity with negative
social costs in order to internalise these costs, ensuring that fuel users incorporate the full use
costs into their decisions.
• Optimal taxation postulates (Ramsey taxation) that higher taxation should be imposed on
goods with relatively inelastic demand in order to minimize the reductions in welfare.
• Distributional concerns.
How Europe has been taxing fuels
• Road fuels are taxed more heavily than non-road fuels → tax preference for diesel relative to gasoline.
• Fuel taxation accounts for around half of the pump price of fuel in every EU member state, and in many cases, much more.
• Almost all countries charge significantly less for diesel than gasoline → exception has been UK
• Low levels of diesel tax encourage higher proportions of diesel car sales and more vehicle use.
• Fuel should be taxed on the basis of its energy content with similar rates of excise duty applied to gasoline and diesel fuels to avoid market distortions leading to dieselisation.
An overview of fuel taxation in the EU: road transport
Final energy consumption, EU-28, 2014 (% of total, based on tonnes of oil equivalent)
• Road transport is the single biggest non-included sector in the ETS.
Greenhouse gas emissions, analysis by source sector, EU-28, 2014 (percentage of total)
An overview of fuel taxation in the EU : road transport
Share of transport energy demand by mode in 2014 (%)
Source: Eurostat
Share of transport energy demand by energy carrier in 2014, by mode (%)
An overview of fuel taxation in the EU: price advantage of diesel
• There has been a tax policy throughout Europe that favors diesel over gasoline.
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
PT UK DK DE IT GR SE FI
Price advantage of diesel
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Source: Based on Weekly oil Bulletin
An overview of fuel taxation in the EU: gasoline vs diesel
https://www.fuelseurope.eu
An overview of fuel taxation in the EU: contribution to climate change
• Preventing climate change is a strategic priority for the EU.
• The EU has legislated to achieve a 20% reduction of GHG emissions by 2020 below
1990 levels.
• In January 2014, the European Commission issued a communication proposing a
next step for 2030: the EU should reduce its greenhouse gas emissions by 40%
compared with 1990 levels.
• Different sectors will contribute differently towards achieving decarbonisation of the
EU’s economy.
• The White Paper on Transport established that a reduction of at least 60% of GHGs by 2050with respect to 1990 is required to achieve the overall target.
• It also established an interim target of 20% GHG reductions compared to 2008 by 2030.
An overview of fuel taxation in the EU: evolution of transport emissions
without additional measures
Source: Eurostat- European Commission, 2013
• The figure clearly suggests that without significant transport emission cuts the EU’s 2030 and certainly 2050 goals are
not achievable.
An overview of fuel taxation in the EU: the 2003 Energy Taxation Directive
• In October 2003 the Energy Taxation Directive (ETD - DIRECTIVE 2003/96/EC) became law.
• The Directive had some key shortcomings → no binding review clauses or automatic inflation adjustments were included
→ minimum taxation levels have not been updated
• In 2011 the EC proposed a revision of the ETD (same taxes for both diesel and gasoline, a CO2 element into energy
taxation, etc.)
• On April 2012 the proposal was rejected (double burden for sectors already affected by the ETS, economic crisis).
• The proposal was withdrawn by the Commission in 2015.
An overview of fuel taxation in the EU: Gasoline vs. Diesel
taxation
Source: European Commission
466
737
422
470
617
338
599
493
618
794
612655
728
681
603624
-50.00
50.00
150.00
250.00
350.00
450.00
550.00
650.00
750.00
850.00
PT UK DK DE IT GR SE FI
Excise Duty (Euro/1000 lt) – Situation as at 1 February 2016
Diesel Gasoline Minimum Diesel (330 Euro/ lt) Minimum Gasoline (359 Euro/ lt)
Excise duties on diesel closer to the
minimum
Our research question
• Assessment gasoline taxation and diesel taxation based on several criteria:
Criteria
i. Tax Burden of fuel taxation (gasoline vs diesel) → Static efficiency
ii. Raising revenue (generate revenues) → Economic Efficiency
iii. Internalize negative externalities (GHG emissions) → Effectiveness
iv. Sustainable economic growth (long term technological change) → Dynamic efficiency
v. Distributive effects (fiscal equity) → Distributive justice
vi. Tax implementation and compliance → Feasibility
• There exists a trade off between “Economic efficiency” and Effectiveness → optimal taxation
says that policymakers must tax price inelastic demand goods (ii)→ but internalizing negative
externalities (shaping consumer behavior) demands that goods (fuel) have more price elastic
demand (iii).
• We use two models to handle this apparent trade-off (Economic efficiency/ Effectiveness) to
assess the gasoline taxation and diesel taxation
Methodological framework: the choice of criteria – (1) Model Economic Efficiency
• Tax instruments are often evaluated based on the following criteria:
Min Min Min Min Max Max
Designation Tax burden Share of tax on energy
prices
(Absolute) Price Elasticity of Energy
Demand
Price advantage of diesel
Income elasticity of energy demand
Maturity
Description
Fuel tax revenue in per cent of
total revenues from taxes and social
contributions (%)
Excise tax in per cent of
pre-tax energy
prices plus the excise
tax (%)
Relationship between the changes in prices of a certain good and
demand.
Price differential (including taxes)
between diesel and super unleaded
gasoline divided by the latter.
Relationship between changes in income and demand of a
certain good.
Years from entering into force until 2016
Methodological framework: the choice of criteria – (2)Model
Effectiveness
• Tax instruments are often evaluated based on the following criteria:
Min Min Max Min Max Max
Designation Tax burden Share of tax on energy
prices
(Absolute) Price Elasticity of Energy
Demand
Price advantage of diesel
Income elasticity of energy demand
Maturity
Description
Fuel tax revenue in per cent of
total revenues from taxes and social
contributions (%)
Excise tax in per cent of
pre-tax energy
prices plus the excise
tax (%)
Relationship between the changes in prices of a certain good and
demand.
Price differential (including taxes)
between diesel and super unleaded
gasoline divided by the latter.
Relationship between changes in income and demand of a
certain good.
Years from entering into force until 2016
Methodological framework: Performance Evaluation using Value-Based DEA
• Data Envelopment Analysis (DEA) is a nonparametric approach for evaluating the relative efficiency
of Decision-Making Units (DMUs). Each DMU uses multiple inputs to produce multiple outputs.
• Different models for DEA seek to determine the DMUs that form the efficient frontier. DEA identifies
benchmarks against which the inefficient units can be compared.
• The Value-Based DEA method builds on multi-attribute utility theory (MAUT) since the input and
output factors are converted into utility functions according to the preference information provided by
decision-makers.
• The DMU being evaluated is allowed to choose the inputs and outputs weights that minimizes the
score d∗, which corresponds to the distance defined by the utility difference to the best of all DMUs,
excluding itself from the reference set.
• If d∗< 0, the DMU is efficient, otherwise the DMU is inefficient and an efficient target is determined.
Methodological framework: Performance Evaluation using Value-Based DEA
y=-0,48ln(x)- 1,5438R²=1
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
0,5% 1,0% 1,5% 2,0% 2,5% 3,0% 3,5% 4,0%
Utility
TaxBurden
y=-0,972ln(x)- 0,3466R²=1
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
25% 30% 35% 40% 45% 50% 55% 60% 65% 70%
Utility
Shareoftaxonenergyprices
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,90
1,00
0 0,2 0,4 0,6 0,8 1
Util
ity
Abs Value of Median Price Elasticicy of Energy Demand
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,90
1,00
-10% -5% 0% 5% 10% 15% 20% 25%
Utility
Price Advantage of Diesel
Methodological framework: Electre
Tri
• A methodological framework based on MCDA has also been used.
• The assignment of each action to a category is done by
comparing its value in each criterion to the performances of the
reference alternatives.
IRIS – Example of application
Devoted to the sorting problem, i.e., a given a course of action is classified into pre-defined ordered categories of merit according to its absolute
performances.
Each reference profile represents simultaneously the upper limit of a
category andthe lower limit of the next category, as
shown in Fig.
Actions are assigned to 5 categories of merit: (C 1 ) Very bad; (C 2 ) Bad, (C 3 ) Fair; (C 4 ) Good and (C 5 )
Very Good, according to the multiple evaluation criteria.
The cutting level, which determines the exigency of the classification, was constrained to the interval [0.51, 0.67], corresponding to a simple majority and a two-thirds
majority requirement, respectively.
Illustrative results: Electre Tri - Model Economic efficiency
Classification
Very Bad Bad Fair Good Very Good
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
PT Gasoline
PT Diesel
UK Gasoline
UK Diesel
DK Gasoline
DK Diesel
DE Gasoline
DE Diesel
IT Gasoline
IT Diesel
GR Gasoline
GR Diesel
SE Gasoline
SE Diesel
FI Gasoline
FI Diesel
No countries classified with a very good performance. UK is the only country that
can attain this position consistently!
DK consistently classified with a good performance for diesel.
FI with a fair performance both for diesel and
gasoline.
DE and GR with a bad/very bad performance for gasoline and IT with a
bad performance for diesel.
PT and SE improved their performance both for diesel
and gasoline.
Illustrative results: Electre Tri + DEA - Model Economic Efficiency
Classification
Very Bad Bad Fair Good Very Good
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3FI_D -0,3
DK_D -0,2588DK_D -0,2588DK_D -0,2357DK_D -0,2701DK_D -0,2408DK_D -0,2357DK_D -0,2357DK_D -0,2357DK_D -0,2357DK_D -0,238DK_D -0,2681
DK_G -0,2101DK_G -0,2081DK_G -0,1522DK_G -0,2262DK_G -0,1696PT_D -0,183GR_D -0,1355FI_G -0,0965PT_D -0,2057PT_D -0,1959DK_G -0,209
GR_D -0,166GR_D -0,1481GR_D -0,1459GR_D -0,1504GR_D -0,1336DK_G -0,0963UK_G -0,0868PT_D -0,0952UK_G -0,0967DK_G -0,1588UK_G -0,092
UK_G -0,0454GR_G -0,0515PT_D -0,0826PT_D -0,084PT_D -0,0932UK_G -0,0729DK_G -0,0825UK_G -0,0921DK_G -0,0828UK_G -0,0917PT_D -0,0768
UK_D -0,0413UK_G -0,0451UK_G -0,0449UK_G -0,0491UK_G -0,0553IT_G -0,0438PT_D -0,0686SE_D -0,0786FI_G -0,0646UK_D -0,0411SE_D -0,0235
SE_D -0,0166UK_D -0,0403UK_D -0,0427UK_D -0,0487UK_D -0,0406UK_D -0,0391UK_D -0,0399DK_G -0,0636UK_D -0,0392SE_D -0,0392FI_G -0,0085
GR_G -0,0163SE_D 0,009IT_G -0,0139SE_D -0,0118IT_G -0,0204PT_G -0,0328DE_G -0,0295UK_D -0,0391PT_G -0,0218FI_G -0,017SE_G -0,0006
IT_D 0,0086DE_G 0,0127GR_G -0,012IT_G -0,0001SE_D -0,0147GR_D -0,0111 IT_G -0,0291SE_G -0,0137SE_D 0,0008PT_G -0,009UK_D 0
PT_D 0,0319IT_D 0,0226SE_D 0,001GR_G 0,0051IT_D -0,0034SE_D 0,0065PT_G -0,0129PT_G -0,0119SE_G 0,0166SE_G -0,0014GR_D 0,0077
DE_G 0,0431IT_G 0,0387PT_G 0,0083IT_D 0,011PT_G 0,0207SE_G 0,0242SE_D -0,0126DE_G 0,0329DE_G 0,0318DE_G 0,025DE_G 0,0319
IT_G 0,0527PT_D 0,0565DE_G 0,0423DE_G 0,0418SE_G 0,0395IT_D 0,0315SE_G 0,0125IT_G 0,0393GR_D 0,0339IT_G 0,0323IT_G 0,0348
SE_G 0,0782SE_G 0,0763IT_D 0,0426PT_G 0,0651DE_G 0,0427DE_G 0,0325FI_G 0,0326GR_D 0,0437IT_G 0,0435GR_D 0,0445PT_G 0,0506
DE_D 0,0997DE_D 0,0917DE_D 0,0591SE_G 0,0661DE_D 0,0813DE_D 0,0515DE_D 0,0393IT_D 0,0812DE_D 0,0661IT_D 0,0728DE_D 0,0577
PT_G 0,1235PT_G 0,0978SE_G 0,0614DE_D 0,0825GR_G 0,1155FI_G 0,0682IT_D 0,0485DE_D 0,0998IT_D 0,0743DE_D 0,0893IT_D 0,0685
FI_G 0,1907FI_G 0,1731FI_G 0,1074FI_G 0,1803FI_G 0,1475GR_G 0,1575GR_G 0,1652GR_G 0,2374GR_G 0,2359GR_G 0,2318GR_G 0,2175
DEA allows each country to freely choose the criterion weights that will place it in a
better ranking order
DE and GR with a bad/very bad performance for gasoline and IT
with a bad performance for diesel with both methods
Illustrative results: Electre Tri - Model Effectiveness
Classification
Very Bad Bad Fair Good Very Good
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
PT Gasoline
PT Diesel
UK Gasoline
UK Diesel
DK Gasoline
DK Diesel
DE Gasoline
DE Diesel
IT Gasoline
IT Diesel
GR Gasoline
GR Diesel
SE Gasoline
SE Diesel
FI Gasoline
FI Diesel
No countries classified with a very good performance
and the situation gets worse in terms of classification
UK with bad and PT, IT and FI with a
very bad performance for
dieselDK, IT with bad and DE, FI , GR with vey bad
performance for gasoline
SE with fair performance
both for gasoline and
diesel
UK with good performance for
gasoline
Illustrative results: Electre Tri + DEA – Model
Effectiveness
Classification
Very Bad Bad Fair Good Very Good
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
DK_D -0,2588DK_D -0,2588DK_D -0,2357DK_D -0,2701DK_D -0,2408DK_D -0,2357DK_D -0,238DK_D -0,238DK_D -0,238DK_D -0,2380 DK_D -0,2681
DK_G -0,2132DK_G -0,2085GR_D -0,2093DK_G -0,2262GR_D -0,1904PT_D -0,2056GR_D -0,1425GR_D -0,128PT_D -0,2054PT_D -0,1939 DK_G -0,209
GR_D -0,2037GR_D -0,1975DK_G -0,1522GR_D -0,1936DK_G -0,1696GR_D -0,1283UK_D -0,0826FI_G -0,0965GR_D -0,1334DK_G -0,1588 GR_D -0,1349
UK_D -0,0826UK_D -0,0826UK_D -0,0826UK_D -0,0826PT_D -0,0912DK_G -0,0963DK_G -0,0825PT_D -0,0959DK_G -0,107GR_D -0,1332 UK_G -0,0887
UK_G -0,0013UK_G -0,0164PT_D -0,08PT_D -0,0822UK_D -0,0826UK_D -0,0826UK_G -0,0787DK_G -0,0904UK_G -0,0916 UK_G -0,0869 UK_D -0,0839
FI_D 0,0212GR_G 0,0054FI_D -0,0282UK_G -0,0311UK_G -0,0414UK_G -0,0612PT_D -0,0672UK_G -0,0853UK_D -0,0826UK_D -0,0833 PT_D -0,0763
PT_D 0,0214FI_D 0,0125UK_G -0,0254IT_G 0,0028IT_G -0,0173IT_G -0,052IT_G -0,0291UK_D -0,0826FI_G -0,0646SE_D -0,0293 SE_D -0,0185
GR_G 0,0232PT_D 0,0238IT_G -0,0198FI_D 0,0151SE_D 0,0248PT_G -0,016SE_D -0,0008SE_D -0,073IT_G -0,0212IT_G -0,0202 IT_G -0,0127
SE_D 0,0373IT_G 0,0295PT_G 0,0097DE_D 0,0401FI_D 0,0462FI_D 0,0014PT_G 0,0054SE_G -0,0295PT_G -0,0004FI_G -0,0170 FI_G -0,0033
DE_D 0,0442DE_D 0,04DE_D 0,0288GR_G 0,0436DE_D 0,0471SE_D 0,0185DE_G 0,0101IT_G -0,0223SE_D 0,0109SE_G -0,0027 SE_G -0,0006
IT_G 0,06DE_G 0,052SE_D 0,03SE_D 0,0487PT_G 0,048SE_G 0,0324FI_D 0,0146PT_G 0,0102DE_D 0,0126DE_D 0,0178 DE_D 0,0102
DE_G 0,0773SE_D 0,0775GR_G 0,036DE_G 0,088IT_D 0,0591DE_D 0,0334SE_G 0,0298DE_D 0,02SE_G 0,0183PT_G 0,0204 FI_D 0,0262
IT_D 0,1142PT_G 0,1038DE_G 0,0611PT_G 0,0933SE_G 0,0597IT_D 0,0427DE_D 0,0386DE_G 0,0551FI_D 0,0335DE_G 0,0566 DE_G 0,063
PT_G 0,1147FI_G 0,1131FI_G 0,0865IT_D 0,103DE_G 0,0793DE_G 0,0528IT_D 0,0541FI_D 0,0986DE_G 0,0541FI_D 0,0616 PT_G 0,0665
SE_G 0,117IT_D 0,1233SE_G 0,1031SE_G 0,1118GR_G 0,1087FI_G 0,0774FI_G 0,0565GR_G 0,1093IT_D 0,0907IT_D 0,0959 IT_D 0,0782
FI_G 0,1258SE_G 0,1482IT_D 0,1033FI_G 0,1128FI_G 0,1218GR_G 0,1093GR_G 0,1078IT_D 0,1356GR_G 0,1074GR_G 0,1047 GR_G 0,1032
DE_G, FI_D, IT_D and GR_G with very bad performance with both
methods
Illustrative results: Electre Tri + DEA
Classification
Very Bad Bad Fair Good Very Good
Effectiveness Economic Efficiency
2015 2015
DK_D -0,2380 FI_D -0,3
PT_D -0,1939 DK_D -0,238
DK_G -0,1588 PT_D -0,1959
GR_D -0,1332 DK_G -0,1588
UK_G -0,0869 UK_G -0,0917
UK_D -0,0833 UK_D -0,0411
SE_D -0,0293 SE_D -0,0392
IT_G -0,0202 FI_G -0,017
FI_G -0,0170 PT_G -0,009
SE_G -0,0027 SE_G -0,0014
DE_D 0,0178 DE_G 0,025
PT_G 0,0204 IT_G 0,0323
DE_G 0,0566 GR_D 0,0445
FI_D 0,0616 IT_D 0,0728
IT_D 0,0959 DE_D 0,0893
GR_G 0,1047 GR_G 0,2318
With a higher weight on feasibility the
classification is good.
With a higher weight on feasibility the
classification is good.
With a higher weight on feasibility the
classification is good.
Illustrative results: Electre Tri
IRIS – Classification proposed with the imposition of a higher weight on economic efficiency (2015)
IRIS – Classification proposed with the imposition of a higher weight on effectiveness (2015)
High fuel taxes do not appear to drive the market towards lower CO₂
emissions
Illustrative results: DEA - What can be done to improve?
Economic Efficiency
DMUs Tax burden Share of tax on energy
prices
Absolute value of median
price elasticity of energy demand
Price advantage of
diesel
Income elasticity of
energy demand
Maturity Peers Lambdas
DE_G 0 -3,43% -0,030 -1,96% 0 10 PT_G;FI_G;FI_D 0,144;0,633;0,233
DE_D 0 -5,6% -0,105 0 0,084 7 PT_D;DK_G;SE_D 0,699;0,172;0,129
IT_G 0 -6,70% -0,070 0 0,231 6 PT_D;DK_G;SE_D 0,699;0,172;0,129
IT_D -0,51% -8,20% -0,027 0 0,498 2 DK_D;SE_D 0,468;0,532
GR_G -1,82% -15,15% -0,130 -5,46% 0,940 5 DK_D 1
GR_D -0,27% 0,000 -0,380 -5,01% 0,953 4,5 PT_D;DK_D 0,114;0,886
DE: reduce the price advantage of diesel; induce changes to price elasticity (e.g. incentives for electric vehicles, use of public transportation, increase of other complementary taxes, exemptions from circulation tax for very low-
CO2 vehicles, …)
Illustrative results: DEA - What can be done to
improve?
DMUs Tax burden Share of tax on
energy prices
Absolute value of median price
elasticity of energy demand
Price advantage of diesel
Income elasticity of
energy demandMaturity peers lambdas
PT_G 0 -6,44% -0,051 -1,97% 0,462 1 DK_G;DK_D 0,306;0,694
DE_G 0 0 -0,091 -1,57% 0,520 4 DK_D;IT_G;FI_G 0,104;0,886;0,010
DE_D 0 0 -0,03 0 0,704 1,5 UK_D;DK_G;DK_D;GR_D 0,333;0,130;0,06;0,472
IT_D -0,47% 0 -0,102 -4,72% 0,313 4,5 PT_D;UK_G 0,243;0,757
GR_G -1,36% -1,586% -0,015 0 0,020 4,5 DK_D;GR_D 0,105;0,895
FI_D -0,426% 0 -0,053 -2,3% 0,190 10 PT_D;UK_G 0,453;0,547
Effectiveness
Conclusions/Policy implications
• High fuel taxes do not appear to drive the market towards lower CO₂ emissions.
• In some countries the revenue raising appears to be a significant priority.
• The environmental and other externalities associated with gasoline and diesel use do not support the
lower tax rates that currently apply to diesel.
• Using taxation to lower the relative price for diesel may lead to a rebound effect by encouraging car
owners to drive more or to purchase a larger vehicle
• Fuel should be taxed on the basis of its energy content with similar rates of excise duty applied to gasoline
and diesel fuels to avoid market distortions leading to dieselisation.
• Policymakers have to consider other instruments (based in CO2 emissions) alongside tax changes to
encourage fuel efficient lower-carbon vehicles → such as vehicle registration tax, circulation tax, company
car taxation, etc.
• Member States should coordinate their fuel taxation policies.
Future work
• Consider different metrics based on surveys conducted with the stakeholders involved;
• Extend the analysis to other complementary measures to encourage fuel efficient lower-carbon vehicles;
• Explore distributional effects of fuel policies, eventually considering the impacts of revenue recycling;
• Further extend the analysis to other countries within the EU, explicitly considering the problem of “fuel
tourism".