Academia Sinica
October 6, 2017

Outline and Description of
E3ME-Asia model
Presented by

Soocheol Lee (Meijo University, Japan)

1.Introduction to E3
modelling“Good modelling involves the combination of best
econometric practice, coherent economic theory andknowledge of data. Inevitably conflicts can arise
between these three factors, and the modeller will needto exercise judgement in the weight that is attached tothe econometric evidence, its consistency with theory
and the requirement to model properly the time series
observations”

Sean Holly (2013)

1.1 Examples of models
Equilibrium

Non-Equilibrium

General

GEM-E3*
WorldScan*

E3ME*
GINFORS*

PartialPRIMES (energy)
TIMES (energy)

ASTRA (transport)
POLES (energy)* These models cover the World1.2 Equilibrium and Non-Equilibrium• There are several different ways ofcharacterising this distinction:• supply or demand driven• long or short term
• theoretical or empirical• Not all are completely accurate, especially
now as the two approaches are coming closer
together1.3 Equilibrium and Non-Equilibrium (cont.)• In the 1960s and 1970s the macroeconometric approachdominated• Holly (2013) provides reasons for a ‘backlash’ against theapproach:• neglect of monetary influence• the Lucas Critique and rational expectations• lack of micro-foundations• inadequate treatment of error processes• failure to use insights from optimal control theory• time-inconsistency of discretionary policy• The focus of research moved to CGE approaches

1.4 Long and Short-Term Analysis?
• In conceptual terms the distinction is linked to the ‘neoclassical synthesis’:• aggregate demand may be a short-run constraint• but long-term growth rates determined by supply-side factors• Attempts have been made to create CGE models suitable forshort-term assessment (DSGE)• these are now widely used in central banks• Modern econometrics largely supports long-run analysis• CGE models, difficult to catch low carbon technology
innovation and its effective demand to influence good
impact on the economy

1.5 In a real-world policy simulation
2015 report, European Commission, DG ENER:
http://ec.europa.eu/energy/sites/ener/files/documents/CE_EE_Jobs_main%2018N
ov2015.pdf
Increasing levels of
Macro Econometric
CGE model results
ambition for energy
model results
efficiency in the EU

NB both the E3ME and GEM-E3 models have beendeveloped substantially since 2015

1.6 comparing GEM-E3(CGE) and E3ME(Macro Econometirc)

GEM-E3

E3ME• perfect competition• varying competition over sectors• constant returns to scale• varying returns to scale• equilibrium solution• product supply-demand balance• full employment• unemployment• projection based on one year's data

• projection based on 40+years' data
used for econometric estimation• guess-estimated parameters1.7 Model Linkages

Cambridge Econometrics and SERI (2011), for DG Environment

2.E3ME Description

2.1 E3ME Model(Energy-Environment-Economy
Macro Econometric Model)
Macro-Econometric Modeldeveloped by Cambridge Econometrics
Reinforced Asian sector by collaboration work with
REEPS(Research group of East Asian Environmental Policy Studies)in Japan as E3ME-Asia

・Demand driven
・No equilibrium, Non optimization
・Four East Asian regions are in the model・Based on data from past 40 years and OECD/IEA forecast

12

The E3ME model and its predecessors
have been around since 1970s and it is
one of the most well-known econometricmodels in Europe and recently globally.

2.2 History of E3ME

1975

1978 Spin-off from the
University of Cambridge
Department of Applied
Economics• Origins in the ‘Growth
Project’ led by Nobel
Laureate Prof Sir RichardStone• pioneered the developmentof detailed sectoralmodelling in an input-output
framework
1980 MDM

Early 1990s Expansion ofscope of CE’s work to• European Regional• UK Energy,
Environment andEconomy service• More tailored projectwork
Company grows from 10
to 25 staff.
1990

2000

1985

1995

Early stage of the company

Product and model developments

1980s CE’s work focuses
mainly on annual subscription
services• UK Industrial service• UK Regional service
and selected projects, notably
the EC-funded HERMES
project (in effect, apredecessor for E3ME)

It is used for official analysis for theEuropean Commission (including therecent Clean Energy Package andClimate and Energy Framework 2030).

2003 CE 25th anniversary.
Terry Barker sets up
charitable trust fund toensure CE's independence
and principles.
New Thinking in Economics:‘to advance education in thefield of economics for the
benefit of the public’
2010
2005
The move to more consultancy projects

1993 Start of part-EC
funded research project
to build E3ME

Today 40 staff based in
Cambridge.
International
reputation in theapplication of wholeeconomy, sectoralmodelling, particularly
the global E3ME model2.3 E3ME Basic Model Structures:●
・E3ME (world) models are:computer-based econometric modelsdeveloped byCambridge University and Cambridge Econometrics…covering economy, energy and emissions…
…with detailed sectors (linked by IO tables)…
…and endogenous technological progress●
・They can be used for forecasting but are typicallyused for policy analysis… sometimes at national level, usually… international

2.4 The E3ME model: Dimensions• Econometric model• cover world 59 regions, including explicit representation of all G20 countries
and all EU Member States. The model has recently been expanded to cover
many East Asia and South East Asia regions explicitly including Japan,
China, Korea, Taiwan and Indonesia. Other ASEAN countries are grouped
together.
• based on the system of national accounts• includes intermediate and all components of final demand• detailed treatment of the labor market• 22 stochastic equation sets, also covering energy and prices• large sectoral disaggregation: 42 industries, 28 consumption categories• 12 different fuel types, and 19 separate fuel user groups• 14 atmospheric emissions• long and short-term specification• annual solutions to 2050
• For more details see www.e3memodel.com

2.5 E3ME Energy-Environment-Economy interactions

2.6 E3ME Engineering-Energy-Environment-Economy interactions

FTT:
Power

FTT:
Transportation

FTT:
Industry2.7 Method of analysis :The E3ME-FTT integrated assessment model•

Environmental'policies'

Emissions*
Units:'tonnes'of'carbon/CO2''

e.g.'industrial'
emissions'of'SF6'

Energy'use'
Environmental'taxes'••

Economic'
policies'
Demographic'change'Pollu=on'abatement'
equipment'

Emissions'trading'
scheme'Economy*Energy'prices''&'costs'

Funding'R&D'

Technology*

Unit:'Euros'

Unit:'Tonnes'of'oil'equivalent'
Energy'use'

investment'

Energy*••Economic'ac=vity'&'general'prices'

Economic'ac=vity'&'general'prices'

Energy'use,'
prices'&'taxes'

Material'use,''
IO,'material'tax'

Energy'demand'Materials''
Unit:'tonnes'•

Resource'efficiency'policies'

Global'oil'price'
Energy'policies'2.8 Treatment of Technology• It is now generally accepted that technology
should be endogenous in modelling• There are two ways of doing it• explicitly (bottom-up, partial approaches)• implicitly (top-down, general approaches)• There will always be a limitation that it is notpossible to predict all future technologies

2.9 Top-down and Bottom-up Modelling• These terms mean different things in different
areas of modelling• In energy modelling:• bottom-up models are specified by technology, they
typically come from an engineering background• top-down models are based on economic
relationships• As it is not possible to define all technologies
explicitly, bottom-up models are partial2.9.1Comparison of top-down and bottom-up modelling
methodology
Classifications employed
Treatment of capital

Motive force
Perception of market
Potential efficiency
improvements

Bottom-up
Engineering-based

Top-down
Economics-based

Precise description ofcapital equipment
Discount rate employedby agents
Market imperfection andbarriers

Homogenous andabstract concept
Income and priceelasticities
Perfect market

Usually high : costless
improvement

Usually low: constraint
on economy

2.10 FTT: Power Link between E3ME and FTT
Post-Schumpeterian(evolutionary)

FTT・Fuel consumption
・Investment in
new power source
・Electricity price・Electricity demand・Fuel demand

Post-Keynesian,

E3ME・CO2 emission
・Investment spill over・GDP, Employment22

2.11 FTT Power and E3ME Model2.12 Bottom-up Schumpeterian meeting Top-down Post-Keynesian: the E3ME model

E3ME

2.13 FTT: Power (1)Probabilistic decision making
between two technologies

Probabilistic Choice Matrix:[𝐹𝑖𝑗 ]

J.-F. Mercure, Energy Policy 48, 799-811 (2012)25

2.14 FTT: Power (2)Choice probability distribution
depends on cost distribution0※Δx=xi-xj

0

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

Choice probability represents diversity of investors

26

Modelling technology substitution
Substitutions

Substitutions

Coal

Coal

Coal

CCGT

CCGT

CCGT

Hydro
Wind

éë Fij ùû

Hydro
Wind

éë Fij ùû

Hydro
Wind

PV

PV

PV

BIGCC

BIGCC

BIGCC

…

…

…

t=1

t=2

t=3

…

J.-F. Mercure, Energy Policy 48, 799-811 (2012)2.15 FTT: Power (3)Aggregate technology substitution
Substitutions
Coal

D

CCGT
Hydro
Wind

CCGT

CCGT

Hydro
Wind

[𝐹𝑖𝑗 ]

Hydro
Wind

PV

PV

BIGCC

BIGCC

BIGCC

…

…

j

Coal

…

PV

=å

Coal

t

t

J.-F. Mercure, Energy Policy 48, 799-811 (2012)28

2.16 FTT: Power (4)Technology shares determined byAggregating every choicesSi   Si S j Aij Fij  A ji F ji tj
J.-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(matrix of substitution frequencies)

Fij : Probability that technology i would be chosen between i and j(probabilistic choice matrix)t : time29

2.17 FTT: Power (5)Cost-Supply Curve= Natural resource availability

Mercure & Salas, Energy 46, 322-336 (2012)

・Cost increases as the technology diffuses
since less resource being available
・Learning effect from cumulative capacity30

2.18 Cost-supply curves for renewables

2.19 Cost-quantity curves for fossil & nuclear fuels2.20 E3ME-FTT Transport
E3ME consumption equation

car priceincomefuel pricedistance
drivencar sales

FTT-Transport

FTT transport policies*

IO feedback
average car
price

car demandby technology

road transport
fuel demandroad transport
CO2- fuel tax- carbon tax

2.21 Diffusion: technology choices
The uptake of new technology:
Innovation – Selection – Diffusionttt + ΔtJ.-F. Mercure, Energy Policy 48, 799-811 (2012)

トヨタ環境2050
https://www.toyota.co.jp/jpn/sustainability/environment/challenge2050 /2.22 The diffusion of vehicle technology
53 regions, 25 technologies
15.$UK
Prices'of'cars'(USD/km)
Std'of'price'' fuel'cost'(USD)std'fuel'cost O&M'costs'(USD)
O&M'costs'(std)'
Discount'ratelifetime energy'use'(MJ/km)
Distance'travelled'per'year'
occupancy'rate'
Capacity'factor'
C'(initial) CO2EmissionsSeats/Veh Learning'exponent
Petrol$Econ
18683.00
4396.00
0.095
0.013
0.038
0.020
15%
12
1.583
12104
0.375
4539.0 1.00744 109.732966
4 R0.0144996
Petrol$Mid
32185.00
8164.00
0.123
0.014
0.051
0.030
15%
12
2.064
12104
0.375
4539.0 0.72093 143.044759
4 R0.0144996
Petrol$Lux
99538.00 49455.00
0.202
0.057
0.064
0.030
15%
12
3.379
12104
0.375
4539.0 R0.216744 234.16231
4 R0.0144996
Advance$Petrol$Econ
18683.00
4396.00
0.076
0.013
0.038
0.020
15%
12
1.425
12104
0.375
4539.0 1.00744 98.759669
4 R0.0740006
Advance$Petrol$Mid
32185.00
8164.00
0.110
0.014
0.051
0.030
15%
12
1.858
12104
0.375
4539.0 0.72093 128.740283
4 R0.0740006
Advance$Petrol$Lux
99538.00 49455.00
0.161
0.057
0.064
0.030
15%
12
3.041
12104
0.375
4539.0 0.216744 210.746079
4 R0.0740006
Diesel$Econ
22608.00
3297.00
0.069
0.010
0.038
0.020
15%
12
1.351
12104
0.375
4539.00.3 100.104906
4 R0.0144996
Diesel$Mid$
33755.00
7065.00
0.077
0.015
0.051
0.030
15%
12
1.581
12104
0.375
4539.00 117.12274
4 R0.0144996
Diesel$Large
54793.00 14601.00
0.118
0.025
0.064
0.040
15%
12
2.104
12104
0.375
4539.0 R0.441858 155.926763
4 R0.0144996
Advance$Diesel$Econ
22608.00
3297.00
0.084
0.010
0.038
0.000
15%
12
1.216
12104
0.375
4539.00.3 90.0944151
4 R0.0740006
Advance$Diesel$Mid$
33755.00
7065.00
0.095
0.015
0.051
0.000
15%
12
1.423
12104
0.375
4539.00 105.410466
4 R0.0740006
Advance$Diesel$Large
54793.00 14601.00
0.095
0.025
0.064
0.000
15%
12
1.894
12104
0.375
4539.0 R0.441858 140.334087
4 R0.0740006
CNG$Econ21485.45
1000.00
0.048
0.055
0.039
0.020
15%
12
1.508
12104
0.375
4539.0 0.627906 84.5988
4 R0.0144996
CNG$Mid
37012.75
3000.00
0.071
0.069
0.056
0.030
15%
12
2.210
12104
0.375
4539.0 0.321858 123.981
4 R0.0144996
CNG$large
114468.70
5000.00
0.082
0.076
0.066
0.040
15%
12
2.548
12104
0.375
4539.0R0.78 142.9428
4 R0.0144996
Hybrid$Econ
29202.00
2826.00
0.084
0.003
0.039
0.030
15%
12
1.414
12104
0.375
4539.0 R0.302328 97.9758621
4 R0.1520031
Hybrid$Mid
34540.00
6594.00
0.073
0.009
0.056
0.040
15%
12
1.216
12104
0.375
4539.0R0.72 84.2592414
4 R0.1520031
Hybrid$Lux$
78343.00
9263.00
0.124
0.017
0.066
0.040
15%
12
2.078
12104
0.375
4539.0 R0.78093 144.024517
4 R0.1520031
EV$Econ10990.00
157.00
0.000
0.000
0.046
0.040
15%
12
0.210
12104
0.375
4539.0 1.32558
0
4 R0.1520031
EV$Mid44745.00
1256.00
0.000
0.000
0.065
0.050
15%
12
0.540
12104
0.375
4539.00
0
4 R0.1520031
EV$Lux89961.00
2355.00
0.000
0.000
0.080
0.060
15%
12
0.580
12104
0.375
4539.0R3
0
4 R0.1520031
2$Wheelers$Motorcycle$Econ$(<500cc)
3808.00
1326.00
0.040
0.003
0.030
0.030
15%
7
0.676
6052
0.55
3328.62.2693 46.8324621
2 R0.0144996
2$Wheelers$Motorcycle$Lux$(>500cc)
14932.00
5760.00
0.127
0.039
0.030
0.030
15%
7
2.124
6052
0.55
3328.6 0.906978 147.159745
2 R0.0144996
Adv$Mot
3808.00
1326.00
0.040
0.095
0.030
0.030
15%
7
0.676
6052
0.55
3328.62.2693 46.8324621
2 R0.0144996
Adv$Mot$
14932.00
5760.00
0.095
0.095
0.030
0.030
15%
7
2.124
6052
0.55
3328.6 0.906978 147.159745
R0.0144996
Mercure &2 Lam,
In preparation (2016)

2.23 The effectiveness of policy on consumer choices

The effectiveness of policy on consumer choices
for private road passenger transport emissions
reductions in six major economies 2015
https://www.repository.cam.ac.uk/bitstream/handle/1810/247636/WorldCarFleets_ArXiv_v3.
pdf?sequence=2

2.24 E3ME-FTT Industry• Similar concept as FTT-Power and FTT-Transport – technology
diffusions• More complex because different industries use different production
technologies
Development stage:• which industries to include?
Possible sectors: chemical, steel, petroleum, pulp and paper・defining technologies• defining policy options• data collection• link to E3ME – inputs and feedback• link to E3ME raw material demand?

2.25 The FTT family of models

2.26 The stochastic equation sets
Energy equations

Shares ofcoal, oil, gas
and electricity

Aggregate
energyTradeequations

Export andimport prices

Material use

Industrial
investment

Bilateral trade

Industrial
pricesPrice and wage equations

Aggregate
and shares ofhouseholdconsumption

NormaloutputResidual
income (nonemployment)

Industrial
averageearnings

Labour market
participation
rate

Investment indwellings

Labourmarketequations

Hours worked

Industrial
employment

2.27 Exogenous variables• Population• Natural resources (including coal, oil and natural gas,
raw commodity price)• Current and capital spending of government• Tax rates and allowances• Exchange rates• Short- and long-term interest rates• World prices of traded goods, e.g. crude oil2.28 The determination of output in E3ME

2.29 The core input-output structure Connected by I-O table+
Value Added:
wages
profits
deprecation+
Taxes andSubsides=Gross Output=

Domestic Supply=

Imports+

Total Demand+

Exports+

Change inInventories+

Fixed Investment+

Government Final
Consumption

Input-Output
Table

Household Final
Consumption

Products

Industries2.30 Energy and emission classifications in E3ME Version 6
FU:23 (fuel users)
1.

Power Generation

14. Construction2.

Own use15. Rail Transport

3.

Hydrogen production 16. Road Transport

4.

Iron & Steel5.

Non-ferrous Metals

6.

Chemicals

7.

Mineral Products

19. Households

8.

Ore-extraction

20. Agriculture, forestry, etc.

9.

Food, Drink & Tob.

21. Fishing

10. Tex., Cloth. & Foot.

11. Paper & Printing
12. Engineering etc
13. Other Industry

17. Air Transport
18. Other Transport serv.

22. Other Final Users
23. Non-energy use

J:12 (fuels)

EM:14 (air emissions)

1. Hard coal
2. Other coal etc
3. Crude oil etc
4. Heavy fuel oil
5. Middle distillates
6. Other gas
7. Natural gas
8. Electricity
9. Heat10.Combustible waste
11.Biofuels
12.Hydrogen

1. CO2
2. SO2
3. NOX
4. CO
5. Methane
6. Black smoke
7. VOC
8. Nuclear - air
9. Lead - air
10.CFCs
11.N2O (GHG)
12.HF6 (GHG)
13.PFC (GHG)
14.SF6 (GHG)2.31 Energy and emission classifications in E3ME Version 6
Road transporttechnology

Power technology
1 Nuclear
2 Oil
3 Coal
4 Coal + CCS

13 Biogas
14 Biogas + CCS

15 Tidal

5 IGCC

16 Large Hydro

6 IGCC + CCS

17 Onshore

7 CCGT

18 Offshore

8 CCGT + CCS

9 Solid Biomass

19 Solar PV

10 S Biomass CCS

20 CSP

11 BIGCC

21 Geothermal

12 BIGCC + CCS

22 Wave
23 Fuel Cells
24 CHP

1 Petrol Econ
2 Petrol Mid
3 Petrol Lux
4 Adv Petrol Econ
5 Adv Petrol Mid
6 Adv Petrol Lux
7 Diesel Econ
8 Diesel Mid
9 Diesel Lux
10 Adv Diesel
Econ
11 Adv Diesel Mid
12 Adv Diesel Lux

13 LPG Econ
14 LPG Mid
15 LPG Lux
16 Hybrid Econ
17 Hybrid Mid
18 Hybrid Lux
19 Electric Econ
20 Electric Mid
21 Electric Lux
22 motorcycles Econ
23 motorcycles Lux
24 Adv motorcycles
Econ
25 Adv motorcycles
Lux

3. How to run the E3ME
model (v6 2016)

3.1 Overall operation sequence
Pre-preparation: model
install and software
download

Sep up assumption or
scenario

Copy and paste the new‘XX.mre’ file and ‘Dan_ba.mre’
on the ‘Data folder’ in thefolder of E3ME_FE

Edit ‘Run.cmd’Wait for finishing solving andgenerating ‘XX.mre’ file atthe ‘Output folder’ in thefolder of E3ME

DoubleClick !
Front-end interface
is launched

Analyse the results

Type ‘run’ on the‘Command and Prompt’

3.2 Necessary model files to install

Install the two folders of E3ME andE3ME_FE in a local drive (C:) in yourcomputer3.3 E3ME : storing all necessary model inputs

①

②

③

3.4 In , Output, Run files
Folder or files

In

Sub-folder or sub-files

Asns

Assumptions.csv
Assumptions.idiom

You can change the assumption with this file

Scenarios

B_ETS.idiom

You can change the scenarios with this file

Enforecast.idiom

You can change the period of simulation

DAN1.idiom
DANA~E.idiom

Printing files for ‘.mre’ (results in figure)
Printing files for ‘.tab’ (results in text)

XX.idiom

OutputRUN.cmd

Explanations

XX.tabResult in text form

XX.mreResult for graph in the front-end phage

This is solution script command file. For a new
assumption or scenario, you need to makechanges on this file before running the model.

3.5 File requirements for E3ME

3.6 What are the files?

Tip

3.7 How to edit the model input
The model inputs are in text format and can be edited using OxEdit orNotepad.
• 1. Notepad
Find ‘Notepad’ under Accessories folder in the start-up menu.
• 2. OxEdit• 3.8 Assumption file: Assumptions.idiom
Percentagechange fromprevious
year

Country

Year: 2000-2050

3.9 Abbreviations
CPRICE_FOOD_FEED

Commodity Price: Food/ feed

EXRATE_LC_P_EURO

Exchange rate

CPRICE_WOOD

Commodity Price: Wood

SR_INTEREST

Interest rate: short run

CPRICE_CONS_MIN

Commodity Price: Construction minerals

LR_INTEREST

Interest rate: long run

CPRICE_IND_MIN

Commodity Price: Industrial minerals

TOT_GOV_SPENDING

Government spending

CPRICE_FER_ORES

Commodity Price: Ferrous metals

SHAR_DEFENCE

Government spending: Defence

CPRICE_NFER_ORES

Commodity Price: Non-ferrous metals

SHAR_EDUCATION

Government spending: Education

CPRICE_COAL

Commodity Price: CoalSHAR_HEALTH

Government spending: Health

CPRICE_BRENT_OIL

Commodity Price: Brent oil

TAX_INDIRECT

Tax: Indirect

CPRICE_GAS

Commodity Price: Gas

VAT_RATE

Tax: VATCPRICE_OTHERS

Global Inflation

TAX_DIRECT

Tax: Direct

BENEFIT_PAYMENT

Benefit Payment

SOCSEC_EMPLOYEES

Soc sec employees’ contributions

SOCSEC_EMPLOYERS

Soc sec employers’ contributions

SPARE1• 3.10 Scenario file: B_ETS.idiom
Editing scenario file in text editor (OxEdit)

59: number of country
50: Number of year
R: Regions
Y1: Years
RTEA: regional energy tax
as additional excise duties(euro/toe)3.11 Command prompt
Open up a solution script .cmd file to set up input files for run

One default .cmd file: Run.cmd(change name of input files if necessary)3.12 EnForecast: Run model over forecast period

3.13 Run.cmd
 The model solutions script isa ‘.cmd’ batch file.
 It is stored in C:E3ME folder.
Right click to edit the file.

 It contains information suchas location of model files
inputs, their names andnames of output file.
 If we want to set up a new
scenario different from thedefault E3ME baseline, thenwe will need to makechanges to the solution
script accordingly to refer itto the new set of model
inputs.

3.14 The model solving…
Command Prompt page3.14 .tab: results in text form
• Ex. DanA_ba.tab

3.16 xx.mre: results in graph• .mre file is a large text file which can be read in the model Front-End• To open results files in the Frone-End, copy over the large “xx.mre”
result files and paste in the ‘Data folder’• Copy and paste the output of baseline (Dan.ba.mre) for comparison
with baseline• Double click on sever.exe in E3ME_FE folder• Front-End interface is launched automatically3.17 Inspecting E3ME results

3.18 … and model outputs

3.19 Inspecting E3ME results• Inspect one file: variables, regions & sectors• Comparison between files: scenarios vsbaseline– choose any baseline to compare with– inspect results by variables, regions and sectors– level, absolute & percentage differences from baseline• Option to export to Excel

3.20 E3ME Limitations• Data– annual model– quality and availability of data

• Econometric– dealing with structural change– based on historical relationships (Lucas critique)• Complexity– complex linkages between different part of models• Treatment of financial markets

Low-carbon, Sustainable
Future in East Asia:
Improving energy systems,

taxation and policy cooperation
Edited by Soocheol Lee, Hector Pollitt and Seung-

Joon park