8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
1/38
Assessing Optimal Mitigation Policieswith a Game Theoretic, Optimal Growth Model:
WITCH
Massimo Tavoni: CMCC, FEEM and Princeton University
Asian Development Bank, Kuala Lumpur, January 2011
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
2/38
Basic Facts of the Climate Change Problem
Key issues of the Climate Change problem:
Global dimension: GHG emissions are a perfect global externality Emissions originate from a wide range of countries, activities and
sources
Long-term dimension: Large inertia of climate system Large inertia of energy systems
Strategic incentives to free-ride on: Emissions
Technology Use of fossil fuels
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
3/38
The WITCH Model: An overview
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
4/38
Background info
World Induced Technical Change Hybrid model:
Developed at FEEM in 2004, from a previous model that wasutilized at FEEM since the mid 90s.
Employed in several projects (>20), commissioned by EuropeanCommission, International Organizations (OECD, EBRD),
Private Sector (Deutsche Bank), Governmental (Italian Ministryof Environment,UK DECC) and NGOs (WWF)
Member of international modeling fora (Energy ModelingForum, Asian Modeling Exercise, IPCC related ones)
Led to extensive reporting and publication in the peerreviewed literature
More info at www.witchmodel.org
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
5/38
WITCH as an Integrated Assessment Model
Socio-Economic System
Environmental system
Adaptation
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
6/38
STRATEGIC INTERACTIONS IN WITCH
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
7/38
Regional disaggregation
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
8/38
Mitigation options in each region
7
- Essential mitigation options for energy related CO2 (about 15
technologies), which is hard linked in the model
- Reduced Deforestation and Land Degradation (REDD),afforestation, use of residue biomass for land use relatedCO2, using marginal abatement costs
- Non-CO2 Kyoto gases (methane, N2O, fluorinated gases),using marginal abatement costs
- Technological change, both via diffusion (e.g. learning bydoing) and innovation (e.g. R&D), subject to internationalspillovers
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
9/38
Modeling capacity and output
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
10/38
Potential use
The model features are ideal for analyzing:
- The investment dynamics of low carbon strategies
- Second best policies under multiple externalities
- Technological innovation and policies
- Uncertainty
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
11/38
Mitigation strategies
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
12/38
-20%
0%
20%
40%
60%
80%
100%
0% 20% 40% 60% 80% 100%
Energy Intensity Improvement
Decarbonization
450550
BAU
past 30 yrs
Changes in Energy and Carbon Intensities
Energy savings and efficiency should be pursued vigorously in the short term, but
decarbonisation is essential from 2030 onwards already.
2030
20502100
2030
2050
2100
2100
2050
2030
550650
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
13/38
Broad mitigation portfolio is needed
0
2000
4000
6000
8000
10000
12000
14000
16000
S1 S2 S3 S4 S5 S6 S7 S8 S9
Cumulatve
PrimaryEnergy(EJ)
BIOMASS
ADVANCED FUELS
WIND+SOLAR
COAL w CCS
NUCLEAR
ENERGY CONSUMPTION
REDUCTION
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
14/38
Mitigation costs strongly depend on climate target
S1
S2S3
S5
S6
S7
S8
S9
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
1.501.701.902.102.302.502.702.903.103.303.50
GDPlo
ssesinNPV(at5%d.r.)
Temperature rise in 2100 (C)
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
15/38
.. and on the availability of mitigation options
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
16/38
Innovation
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
17/38
Copenhagen (and Cancun) pledges
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
18/38
Investing in clean energy R&D
0.00%
0.02%
0.04%
0.06%
0.08%
0.10%
0.12%
0.14%
1970 1980 1990 2000 2010 2020 2030 2040 2050
E.E. R&D
Total Energy R&D
BAU
Historical Public Energy R&D
Advanced Techs R&D
Energy Intensity R&D
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
19/38
Mitigation Costs with and wout breakthrough innovation
-8.0
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
2007 2012 2017 2022 2027 2032 2037 2042 2047 2052 2057 2062 2067 2072 2077 2082
%c
ha
ngeinGDPwithrespecttoba
seline
550ppm w ith backstops
550ppm
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
20/38
Forestry
U i b k t t t t i l d f t ti
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
21/38
Forestry Emissions
-0.5
0
0.5
1
1.5
2
2005
2015
2025
2035
2045
2055
2065
2075
2085
2095
GtC
Using carbon markets to stop tropical deforestation
Forest Carbon Seq estration
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
22/38
Forest Carbon Sequestration
Table 1: Regional Forest Carbon Sequestration, 2025, 2055, 2095
2022 2052 2092
MtC/yr
OECD
USA 42 144 193
OLDEURO 37 82 132
NEWEURO 8 18 29
CAJANZ 31 115 125
Total OECD 118 360 479
NON OECD
KOSAU 25 27 36TE 179 117 134
MENA 73 49 31
SSA 270 175 106
SASIA 34 57 32
CHINA 109 155 431
EASIA 451 481 371
LACA 391 326 330
Total Non-OECD 1649 1746 1950Total Global 1766 2105 2429
C Price $57 $113 $271
Forest Carbon Sequestration
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
23/38
Forest Carbon Sequestration
Table 3: Change in Forestland area and Change in annual timber harvests compared to the baseline.
2022 2052 2092 2022 2052 2092
Million Hectares % Change in Ann. Harvest
OECD
USA 1.5 23.1 94.2 1.2% -9.0% 48.5%
OLDEURO 11.5 34.9 51.9 -5.3% 12.1% 0.3%
NEWEURO 2.6 7.8 11.6 -5.3% 12.1% 0.3%
CAJANZ -4.0 24.5 99.0 -3.8% -3.3% 167.3%
Total OECD 11.6 90.3 256.7 -3.3% 3.0% 54.1%
NON OECD
KOSAU 5.1 17.7 49.1 11.3% 34.5% 42.1%
TE 19.0 52.2 102.7 -20.8% 8.9% -26.1%MENA 10.3 24.9 38.4 -63.9% -45.9% -6.7%
SSA 37.2 90.7 137.0 -70.1% -52.9% -9.0%
SASIA 5.2 18.8 32.3 -3.7% -3.9% 13.0%
CHINA 8.6 41.9 115.4 -20.1% 0.0% -98.8%
EASIA 25.6 66.0 111.9 -63.3% -57.2% -48.9%
LACA 42.9 129.3 262.4 -24.8% -7.1% 15.5%
Total Non OECD 153.8 441.5 849.2 -31.9% -15.4% -14.9%
Total 165.4 531.8 1105.9 -14.5% -3.3% 25.9%
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
24/38
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
25/38
Uncertainty
What should we do if we are uncertain about future policies?
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
26/38
0
2
4
6
8
10
12
14
16
18
20
2005
2015
2025
2035
2045
2055
2065
2075
2085
2095
GtC
no tgt
550
optimal
450
What should we do if we are uncertain about future policies?
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
27/38
Planning and resources
Building future commitments into current planning
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
28/38
Building future commitments into current planning
Emissions in China for a carbon tax from 2030
onwards.Anticipating future commitments allows to save25% of the costs
0
2
4
6
8
10
12
14
2000 2010 2020 2030
BillionTonsCO2
No policy
Future
commitments
beginning in
2030
Financial transfers in an international carbon market
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
29/38
2
8
Financial transfers in an international carbon market
A limit to the use of emission trading to 10% of totalabatement would keep the amount of transferredresources around 100 USD Billion
Financial transfers from OECD
0
100
200
300
400
500
600
700
2020 2025 2030 2035 2040
USDBillion
Full trade v20% v15% v10%
CurrentOECDGasImports
Current OECD OImports @
70$/bblCurrent
OECD OImports@ 50$/b
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
30/38
Mitigation vs Adaptation
Timing of adaptation and mitigation
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
31/38
3
0
Timing of adaptation and mitigation
0
500
1000
1500
2000
2500
3000
3500
4000
4500
2010
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
2065
2070
2075
2080
2085
2090
2095
2100
U
S$Billion
Residual Damage Adaptation Mitigation
Reactive and Proactive Regional Adaptation
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
32/38
eact e a d oact e eg o a daptat o
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
33/38
What to expect from this model
What WITCH is best at:
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
34/38
What WITCH is best at:
Long term dynamics of mitigation strategies
International climate negotiations
Regional strategic incentives
Deal with uncertainty
Innovation mechanisms and policies
Mitigation and adaptation interplay
What WITCH is not best at:
Country level analysis
Detailed technology roadmaps
Sectoral implications and feedbacks
Short term
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
35/38
Thanks!
2030: number of people who emit > 10tCO2/capita
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
36/38
p p p
0.0
50.0
100.0
150.0
200.0
250.0
300.0
350.0
400.0
Co-benefits of mitigation
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
37/38
g
Energy security
Local pollution
Biodiversity and ecosystems
Co-damages of mitigation
Land competition (also with food) from renewablesand biofuels
Nuclear proliferation
CCS inefficiency and coal mining
Potentially regressive distributive impacts
8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch
38/38
Thanks!
Top Related