ICES2019 March 19
Economic and Environmental impacts ofcarbon taxes and policy mixes of other
instruments in East Asia to meet the 2050
2℃targets : An analysis using E3ME-FTT
model
SOOCHEOL LEE(Professor, Meijo University)
co-authored by•

Hector Pollitt(Cambridge Econometrics)
Unnada Chewpreecha(Cambridge Econometrics),

CONTENTS
1. Research and scenarios overview
2. Introduction to the E3ME-FTT
model
3. Model results
4. Conclusion

1. Research and Scenarios Overview

Research objective
Assess a range of climate policy
options to achieve long-term
decarbonisation targets and to showthat a combination of instruments(notjust carbon pricing only) is likely to
produce the best results for national
economies in East Asia.

Estimation of carbon cost to get 2℃ by the policy mixes target in 2050
① Carbon cost to get 2℃ target from the reference scenario by 2050
② Carbon cost to get 2 ℃ target from ②（the coal power regulation by 2050）③ Carbon cost to get 2 ℃ target from ③（②＋Energy Efficiency Policy by 2050）④ Carbon cost to get 2 ℃ target from ④（③＋Low Carbon Transport Policy by 2050）⑤ Carbon cost to get 2 ℃ target from ⑤（④＋Low Carbon Heat Policy by 2050）⑥ CO2 emission path to get 2℃ target by 2050

①②③
④⑤⑥．

Long-term decarbonisation targets
for 2050 in East Asia
2050 target vs 2015 levels

BAU in 2050(IEEJ)

China

-50

8

Japan

-80

-30

Korea

-60

3

Taiwan-70-8These targets are our own values as the countries inEast Asia do not yet have formal targets except Japanfor 2050 to be consistent with 2°C.

Policy inputs in the scenarios
CarbonTaxPowergeneration
sector policies

EnergyEfficiency inIndustries

Transportpolicies

Heatingpolicies• feed-in-tariff• renewablesubsidies• mandates toprevent newcoal power
plants beingbuilt• ambitious
taken from
IEA’s 450PPM
scenario (IEA,2016).

• fuels tax• fuels tax• registration tax • subsidies for• EV subsidies
new heating• biofueltechnologies
mandate• new heating• new vehicle
systems aretechnologies
adoptedboostedinitially inthroughpublicprocurementbuildings.

Role of carbon pricing in the scenarios• Tax rate get adjusted in each scenario so thenational emission reduction targets are met• Levied on all use of fossil fuels in relation tocarbon content• Additional to rates in the baseline• Linearly increase to 2050
• No exemptions• No revenue recycling but part of revenues getused to fund renewable subsidies and energy
efficiency investment

2. The E3ME-FTT ModelWhat is E3ME?
A computerbased global
model for theeconomy,energy andenvironment,
covering 59
regionswww.e3me.com

The model
consists ofcollections of
econometricbehavioural
equations andaccounting
identities

Based on anaccounting
framework anddesigned for
projections forbusiness andpolicy analysis

E3ME: Key characteristics• Macro-econometric model
based on a post-Keynesianframework• Optimisation not assumed• Demand = Supply… but• Demand <= Potential Supply• Under the right conditions it
is therefore possible toincrease output andemployment by demand sidestimulation

What are the key dimensions & features ofE3ME?
Detailed Coverage

Comprehensive

Highly Empirical• 59 regions (33 European, 26World)• 70/44 economic sectors and42/28 consumption
categories• 23 fuel users of 12 fuels• whole energy, environment
and economy system• two way feedback between
each module• covers many policy
instruments• 1970-2016 database• 28 econometric equations• relationships validated fromdata• econometrics allows for
short-medium and long term
analysis

Consistent

Forward Looking

Modular• based on system of national
accounting• input-output tables• bilateral trade• annual projections to 2050
• behavioural equations witheffects from previous
outcomes• ex-ante scenario analysis(ex-post is also feasible)• E3: Energy, Environment,
Economy and material
modules• power generation, transportand heat sub-modules• research can bedecentralisedwww.e3me.com

E3ME as an E3 model•

Each componentof the model isshown in its ownbox•

Exogenousfactors areshown on theoutside edge foreach component•

The linkages
between thecomponents areshown by arrows
that indicate
which values aretransmitted

GDP determination in E3MEGDPLinkage with I-O Ltable in E3ME

Which macroeconomic models to use?
Simulations(econometrics)• Facing with real world
policy options• Lack of perfectknowledge or foresight• People don’t always
behave rationally!
• Responses to policy
based on real world
behaviours• Post-Keynesian school of
economic thinking

Optimisation (computablegeneral equilibrium)• Starting from already
optimal outcome• Known-end point• Finding the least cost wayof getting there• Useful for resource
allocations• Neoclassical school of
economic thinking

Linking E3ME to technology sub-modules• Bottom-up model; econometric equations noappropriate for power generation because there istypically a small number of large plants and theeconometric approach is not well suited for thedevelopment of new renewable technologies• Current standard in energy systems modelling is bycost-optimisation/linear programminge.g. TIMES/MARKAL, MESSAGE, AIM, etc• Are optimal scenarios the answer to the question
asked?
• Is optimisation always what policy-makers finduseful?

FTT Theory• FTT:Power uses a decision-making corefor investors wanting to build newelectrical capacity, facing several
options.
• The decision-making core takes place by
pairwise levelised cost (LCOE)
comparisons, conceptually equivalent toa binary logit model, parameterised bymeasured technology cost distributions.

The FTT models of technology diffusion

Marchetti & Nakicenovic Tech. Rep. IIASA (1978)
See also Technology and Global Change by Grubler

FTT Theory (cont)• Costs include reductions originating fromlearning curves, as well as increasing marginal
costs of renewable natural resources (forrenewable technologies) using cost-supplycurves.
• Due to learning-by-doing and increasing
returns to adoption, it results in pathdependent technology scenarios that arise
from electricity sector policies.

Technology shares determined byAggregating every choicesSi   Si S j Aij Fij  Aji Fji tjJ.-F. Mercure, Energy Policy 48, 799-811 (2012)

Si : Share of technology i
Aij : Life time of technology i and lead time of technology j
Fij : Probability that technology i would be chosen between i and jt : time

Modeling technology substitution in FTT;Power

Simulates:• The future replacement and diffusion• Of power technologies• By power generation sectors worldwide(59 world regions)

Substitutions
Coal

Coal

Coal

CCGT

CCGT

CCGTHydro• Based on dynamical shares equations(the FTT method – no optimisation)Wind• Useful energy demand by country as
an exogenous driver (depending onfuture levels of construction/gereration)

Substitutions

éë Fij ùûHydroWindéë Fij ùûHydroWind

PVPV

PV

BIGCC

BIGCC

BIGCC

…

…

…
t=1

t=2

t=3

J.-F. Mercure, Energy Policy 48, 799-811 (2012)…

FTT-Power (LCOE – IEA 2016)

FTT Power

Frequency Matrix Aij = 10/lifetime*10/Build TimeModeling technology substitution in FTT;Transport
新技術の導入：イノベーション – 選択 – 拡散tt + Δt
J.-F. Mercure, Energy Policy 48, 799-811 (2012)

Modeling technology substitution in FTT;Heattt + Δt

• Households replace their heating systems in time intervals related to technical lifetimes• Choices are based on Levelised Costs of Heating (LCOH):
combined measure of investment costs, fuel costs, and maintenance costs• Calibration of these costs to observed preferences and trends:
accounts for different comfort levels, local variations, existing policies etc.

• Behavioural assumptions: no switching back to less comfortable technologies

FTT linkage with E3ME

Post-Schumpeterian(evolutionary)

FTT・Fuel/Material consumption
・Investment in
new production technology
・product price・product demand・Fuel/Material demand

Post-KeynesianE3ME

3. Modelling Results

REMINDER:
Policy inputs in the scenarios
CarbonTax

Powergeneration
sector policies

EnergyEfficiency inIndustries

Transport
policies

Heatingpolicies

1



××××

A



• feed-in-tariff• low• fuels tax• fuels tax

B• feed-in-tariff• renewablesubsidies• moderate• fuels tax• New vehicle
efficiencies• EV subsidies• fuels tax• subsidies fornew heatingtechnologiesC• feed-in-tariff• renewablesubsidies• mandates toprevent newcoal power
plants being
built• ambitious
taken from
IEA’s 450PPM
scenario (IEA,2016).

• fuels tax• fuels tax• registration tax • subsidies for• EV subsidies
new heating• biofueltechnologies
mandate• new heating• new vehicle
systems aretechnologies
adoptedboostedinitially inthroughpublicprocurementbuildings.

CO2 reduction from 2015

ChinaJapan

Korea

TaiwanTarget

-50

-80

-60

-70

Baseline(IEEJ)(2050, MCO2t)8-30

3-8(9706)

(802)

(621)

(239)

Max carbon tax rate = $1,500/tCO2

CO2 prices in each scenario, 2050
(2018 prices, $/tCO2, additional to baseline)
China

Japan

Korea Taiwan

Baseline

0000

S1 (C Tax)

1,500

1,500

1,500

1,500

S2 (+ Power)

717

1,200

1,100

1,000

S3 (+ En Eff)

300

850

500

750

S4 (+ Trans)

143

521

390

525

S5 (+ Hhold)

21293

218

220

Impacts on GDP, % from baseline in 2050
China

Japan

Korea

TaiwanS1 (C Tax)

-0.7

-4.3

-1.6

-3.9

S2 (+ Power)

-0.6

-4.1

-1.2

-1.8

S3 (+ En Eff)

-0.1

-3.2

-0.8

-1.5

S4 (+Trans)

0.3

0.8

0.8

-1.2

S5 (+ Hhold)

0.3

1.0

1.0

-1.0

Impacts on sectoral output, % from baseline
in 2050 (East Asia)
S1

S2

S3

S4S5

Agriculture

-2.0

-1.6

-1.4

-0.5

-0.3

Basic
manufacture

-1.1

-0.9

-0.1

0.5

0.5

Advancedmanufacture

-1.0

-0.8

0.2

0.9

1.0

Utilities

-6.3

-3.8

-11.2

-10.3

-10.0

Construction

0.5

-0.1

2.1

2.6

2.6

Services

-1.6

-1.3

-0.9

-0.1

0.1

4. Conclusions• Each East Asian faces different challenges todecarbonize but can meet their long-term
decarbonisation targets by carbon pricing only.
• But a broad range of policies, across all sectors isrequired• Carbon pricing is a key element of the package but
is not sufficient (at feasible prices)• All of the other policies interact with carbon pricing,allowing emissions to be cut effectively• GDP impacts will improve if other policies areimplemented – or carbon tax revenues are recycled

List of FTT References- FTT:Power: J-F Mercure, Energy Policy, 48 799-811 (2012)- FTT:Heat: Knobloch et al Energy Efficiency,
https://link.springer.com/article/10.1007/s12053-018-9710-0 (2018)- FTT:Transport: Mercure et al https://arxiv.org/abs/1702.04133 (2017)- Energy resources database: Mercure & Salas, Energy, 46 322-336(2012)- Consumption of non-renewable resources: Energy Policy, 63, 469-483(2013)- Economic impacts of decarbonisation: http://arxiv.org/abs/1310.4403- Macroeconomic impact of stranded fossil fuel assets: Mercure et al,Nature Climate Change, Volume 8, pp 588–593 (2018).