Francesco Bosello. Assessing Climate Change Impacts and Policies With CGE Models, Methodology and Application - The ICES Model

8/7/2019 Francesco Bosello. Assessing Climate Change Impacts and Policies With CGE Models, Methodology and Application - The ICES Model

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CENTRO EURO-MEDITERRANEOPER I CAMBIAMENTI CLIMATICI

1

Regional Consultation Meeting of RDTA 7645: StrengtheningPlanning Capacity for Low Carbon Growth in Developing Asia

Kuala Lumpur, 27 Jan, 2011

Assessing climate change impacts and policies withCGE models: methodology and application. The ICES

model

Francesco BoselloCMCC, FEEM and University of Milan


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CENTRO EURO-MEDITERRANEOPER I CAMBIAMENTI CLIMATICI 2

Classifying models for policy assessment

Climate-environmental-economicsystems integration

Hard Linked Soft Linked

Time treatment Static Dynamic

Modelling of the production anddemand technology

Top-Down Bottom-Up

Modeling of market relations Partial Equilibrium General Equilibrium

Policy assessment performed Policy Evaluation Policy Optimization


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Top Down vs Bottom Up

Top-Down Models Bottom-Up Models

General approach Economic- focus on marketexchanges

Engineering focus onproduction technologies

Market view Olistic Partial

Main variables Elasticity of substitution inside theproduction or the utility function

Technical progress: oftenexogenous

Initial cost, installed capacity,residual life, penetration of different

technologies technologicaladoption/diffusion is thusendogenous

Detail Geographically/sectorally high,technologically low

Geographically high, sectorally low,technologically (energy sectors)high

Energy demand Typically endogenous Typically exhogenous

About energy

substitution and

emissions reduction

costs

Pessimistic (high costs)

Rebounds & lower cost optionsnot usually accessible

Optimistic (low costs)

No rebounds & lower cost optionsaccessible


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Growth and General Equilibrium Models

The top-down stream originated many different applied modellingapproaches. For what matters here:

One stemming from modern and new growth theory (Solow 1956,Ramsey, 1926, Aghion-Howitt 1996) Dynamic optimization models

One stemming from the neoclassical theory of general economicequilibrium (Walras, 1874; Arrow-Debreu, 1954; Negishi, 1960,Showen-Whalley, 1992) + international macroeconomic (Armington1969) Computable General Equilibrium Models

Since the 90s both have been increasingly applied to study the economicimplications of climate change and of climate change policies(effectiveness, efficiency, equity) with different perspectives though:


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Growth and General Equilibrium Models

The growth modeling approach focuses more on transitions to long-termequilibrium with this perspective it investigates: cost/benefit of

climate change policies (e.g. Nordhaus and Yang, 1995; Nordhaus andBoyer 1999, Manne and Richels 2004); strategic incentives toparticipate to international mitigation efforts (e.g. Carraro et al.2001), the relation between climate policy, R&D policies energypolicies (e.g. Bosetti et al. 2008), relation between mitigation andadaptation policies (e.g. Agrawala et al. 2010, Bosello et al. 2010)

The general equilibrium modeling approach focuses more on mid-termsectoral and competitiveness effects of mitigation policies answeringe.g. the questions: what is the overall burden of the policy? Is itefficiently distributed among countries and sectors? What are thepolicy effect on international competitiveness? Which are the sectors

at higher leakage risk? Which policy can better limit this risk? (SEC2008, SEC 2010) or on impacts assessments (Ciscar 2009, Aaheimand Wey 2010, Eboli et al. 2008)

Recently increasing focus on REDD policies by both research approaches


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Computable General Equilibrium Models

There are many countries and many sectors

Representative agents are rational (optimizing behavior by firms and

households is assumed)

Markets are perfectly competitive and in equilibrium (demand matches

supply).

All markets are also interdependent as when excess demand or supply

materialize (because of economic shocks) inputs and outputs (resourcesand demand flows) re-locate inter-nationally/sectorally responding toprice signals => international trade is explicitly modelled

These models are usually calibrated: demand and supply functionsare parameterized in order to replicate observed market exchanges in agiven reference year


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Sketching a CGE model

Consumers

(households, government)

Producers(firms, government)

Maximise welfare

from consumption

Minimise costof production

supply

demand supply

demand

Input marketsK, L, Land, NR

Income

Income

Output marketsGoods and

services

Constrainedby income

Constrained

by technology

They meet in


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The I/O (SAM) structure

S1 S2 Sn S1 S2 Sn

S1

S2

Sn

S1

S2

Sn

Country A Country B


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Strengths and weaknesses of CGE models

Pros: Market interdependence allows the description of policy transmission

mechanisms across sectors and countries i.e. policy effects on themacroeconomic context and rebounds of this. Trade effects,competitiveness effects, sectoral effects, leakages Highly flexible, they can assess the implication of everything once ithas been translated into changes into demand or supply

Cons: Difficult to be developed into fully dynamic computational difficulty

due number of countries and markets => stylized dynamics withmyopic agents problems to study transitions, endogenizetechnological progress, better for policy evaluation (cost effectiveness)

than for policy optimization (cost benefit) being calibrated good for short, mid-term analyses they are equilibrium model, market imperfections only with ad hoc

modelization data intensive


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The ICES (Intertemporal Computable EquilibriumSystem) model

Top-down, recursive-dynamic, computable general equilbriummodel for policy evaluation

Calibrated in 2004 (GTAP-7 database) 113 regions 57 sectorsamong which: Indonesia, Malaysia, Philippines, Singapore,Thailand, Vietnam

Depicts international trade with capital mobility

Growth driven by endogenous investment decisions buildingcapital stock interperiodally

Production-side detail improved including nuclear, hydro, wind,solar, (biofuel under development)

Emissions from CO2, N2O, CH4


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TOP Level

1Level

2Level

3Level

4Level

5Level

OutputOutput

V.A. + Energy Other Inputs

Domestic ForeignNaturalResources

Land LabourCapital

+Energy

Capital Energy

Non Electric Electric

NuclearNon Nuclear

Oilgas Non Oilgas

Region 1

Region ...

Region n

Representative Firm - cost minimizingLeontief

CES

VAE D

CES

KE

CES

=0.5

CES

=0.5

CES

=1

M

6Level

CoalOther fuel

CES

=1

CES

=0.5

Non Intermittent

CES

=2

Other ElyHydro

CES

=2

CES

=0.5

Solar Wind

Intermittent

GasCrude Oil BiofuelPetroleumProd7Level

CES

=1

ICES: the supply side

Representative costminimizing firm


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ICES: the demand side

Utility

PrivateConsumption

Savings

Domestic Foreign

Region 1 Region n

Region ...

Item Item mItem 1

PublicConsumption

Domestic Foreign

Region 1 Region n

Region ...

Item Item mItem 1

Representative utilitymaximizing household

Cobb-Douglas


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ICES: the standard treatment of land and the AEZapproach

Currently: Land is homogenous and imperfectly mobile across

crops responding to crops prices. Only economic factorsconsidered, not climatic and soil characteristics

No competition between forestry and agricultural land

GTAP AEZ

Introduces climate and soil characteristics making use of theFAO/IIASA agro-ecological zoning methodology.

Land is imperfectly mobile across crops responding to cropsprices within AEZ, but not between AEZ. Many land types

accounting for geographical and biochemical land characteristic. The original model may now be modified to account for land

competition between forestry and agriculture


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The 18 AEZ


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Application (1): the economic implication of the EU postKyoto mitigation policy: the20-20-20and30-20-20

The context:

In June 2009 the EU Council established as mandatory the 20-20-20Climate and Energy package for the EU.

It requires:

20% GHG emission reduction compared to 1990 levels in 202020% share of renewable energy in total final energy consumption in202020% increase in energy efficiency compared to 2020 baseline

After the exit of 2009 COP 15 Bali (and 2010 COP 16 Cancun) discussionto move forward to 30% GHG emission reduction


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The Copenhagen Pledges

Low pledges High pledges

EU27-20% GHG emissions wrt 1990 in

2020-30% GHG emissions wrt 1990 in

2020

USA-17% GHG emissions wrt 2005 in


2020

Russia-15% GHG emissions wrt 1990 in


2020

RoA1-29% GHG emissions wrt 2005 in


2020

China -40% CO2/GDP wrt BAU 2020 -45% CO2/GDP wrt BAU 2020

India -20% C/GDP wrt BAU 2020 -25% C/GDP wrt BAU 2020

Brazil -5.3% GHG emissions wrt BAU 2020

-9.4% GHG emissions wrt BAU

2020

NonA1_T -2% GHG emissions wrt 2005 in 2020-10,5% GHG emissions wrt 2005

in 2020


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Regional and sectoral detail of the exercise

Regions Sectors

EU27:Austria, Belgium, Czeck Republic,Denmark, Finlan, France,Gemany,Greece, Hungary, Ireland, Italy,Netherlands, Poland, Portugal,Spain, Sweden, UK, Rest of EU27,

+Usa,Russia,Rest of Annex1,China,India,

Brazil,Rest of NonAnnex1,Rest of the World

Agriculture,Coal,Oil,Gas,Oil Products,Nuclear,

Solar,Wind,Hydro,Other Electricity,Paper,Minerals,

Chemicals,Iron and Steel,Transportation,Other Industries,Services


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Benchmark assumptions: GDP

GDP Growth rates 2004-2020

Sources for benchmark:EC (2010): Economic ForecastsEC (2010): Ageing Report 2009WEO (2010)IMF (2010)

0

20

40

60

80

100

120

140

160

180

200

Austria

Belgium

Cz

echR

ep

Denm

ark

Finlan

d

Fran

ce

Germ

an

y

Gre

ece

Hun

gary

Irelan

d

Italy

Netherlan

ds

Polan

d

Portu

gal

Spain

Sw

eden

UnitKin

gdom

RoE

U

USA

Russia

RoA1

Chin

a

India

Brazil

NonA1

_T

RoW

%c

hange2005-2

020

ICES Benchmark


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Benchmark assumptions: fossil fuel prices

0

5

10

15

20

25

30

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

US$(2008)/boe

ICES Benc hmar k

0

20

40

60

80

100

120

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

US$

(2008)/boe

ICES Benc hmar k

0

10

20

30

40

50

60

70

80

90

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

US$(2008)/boe

ICES Benc hmar k

Coal Price

Oil Price Natural Gas Price

SEC (2008)DB (2008) SCDB (2008) CCDB (2010) CC

Source: Eurelectric (2010)


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Policy scenarios

EU27 NON EU27

20-20 20% emission reduction comparedto 1990 in 202020% renewable energy over totalfinal energy consumption

Business as Usual

30-20 30% emission reduction comparedto 1990 in 202020% renewable energy over totalfinal energy consumption

Business as Usual

20-20 Low 20% emission reduction comparedto 1990 in 202020% renewable energy over totalfinal energy consumption

Low Copenhagen pledges

30-20 Low 30% emission reduction comparedto 1990 in 2020

20% renewable energy over totalfinal energy consumption

Low Copenhagen pledges

30-20 High 30% emission reduction comparedto 1990 in 202020% renewable energy over totalfinal energy consumption

High Copenhagen pledges


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GDP impacts of the EU mitigation policy

-0.56

-1.26

0.10

-0.66

-1.89

-0.55

0.20

-2.0

-1.5

-1.0

-0.5

0.0

0.5

ICES 20-20 ICES 30-20 ICES 20-20

Low

ICES 30-20

Low

ICES 30-20

Low Gdf ETS

ICES 30-20 high ICES 30-20 full

trade

EU GDP ( % changewrt baseline in 2020)

0.090.17

-0.97-0.91 -0.89

-1.3

-0.75

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

ICES 20-20 ICES 30-20 ICES 20-20

Low

ICES 30-20

Low

ICES 30-20

Low Gdf ETS


trade

Non EU GDP ( %change wrt baseline in

2020)


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GDP impacts of the EU mitigation policy

30.2

69.957.0

102.0

205.0

110.0

40.8

0

50

100

150

200

250

ICES 20-20 ICES 30-20 ICES 20-20

Low

ICES 30-20

Low

ICES 30-20

Low Gdf ETS


trade

CO2 price (/t in 2020)


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Sectoral impacts of the EU mitigation policy

0.3

-21.7

-3.3

1.81.3

-17.5

-17.6

-0.37.7

0.2 1.21.41.72.3

0.1-0.34

.3

-44.2

-14.6

5.1

-8.5

-12.9

-12.8

4.4

16.2

4.9 5.96.06.65.74.64.2

4.7

-46.0

-18.0

9.9

-5.7 -1.8

-1.8

3.9

27.1

5.2 7.68.18.99.2

4.83.75

.4

-46.0

-20.3

10.7

-7.7

-0.4

-0.5 4.9

29.4

6.2 8.79.1 10.1

10.1

5.74.7

-50

-40

-30

-20

-10

0

10

20

30

40

Agric

ulture Co

al Oil Gas

Oil_P

ctsSo

larWi

ndHy

droOt

hEly Paper

Mine

rals

Chem

icals

Iron_

Steel

Tran

sport

Oth_

ind

Serv

ices

Var.%r.baseline

20-20

20-20 Low

30-20 Low

30-20 High

-0.3

-0.4

-1.1

-2.1

-2.0

-1.9

-0.3

-0.2

-1.2

-0.3

-0.1

2.3

-0.4

-0.3

-1.7

0.4

-1.6

-0.8

-1.4

-0.1

-2.5

-2.9

-1.9

0.1

-2.0

-0.9

-1.0

0.8

-1.5

-2.7 -

2.3

0.2

-4

-3

-2

-1

0

1

2

3

Agric

ultur

ePa

per

Mine

rals

Chemi

cals

Iron_Stee

l

Trans

port

O

th_ind

Serv

ices

Var.%r.

baselin

e

20-20

20-20 Low

30-20 Low

30-20 High

-6.7

-0.5

-10.6 -6

.1

60.3

57.5

1.2

-3.4

-35.1

-3.5

-20.0

-0.2

67.4

59.1

0.4

-3.5

-47.3

-4.7

-28.6

-8.7

45.1

45.4

3.2

-6.2

-49.9

-5.7

-30.3

-7.4

46.1

45.9

3.1

-6.1

-60

-40

-20

0

20

40

60

80

C

oal

Oil

Gas

Oil_P

cts

Solar

Wind

Hydr

o

Oth

Ely

Var.%r.

baseline 20-20

20-20 Low

30-20 Low

30-20 High

Sectoral Prices in the EU: % change wrt baseline in 2020

Sectoral Production in the EU: % change wrt baseline in 2020


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Domestic regional action vs full trade: GDP 30-20 low

Domestic action

UE27 -0.66 0.2

Italy -0.69 0.1

Germany -0.46 0.3

UK -0.17 0.4

Spain -0.75 0.16

Non UE27 -0.91 -0.75

Countries withPledges

-1.25 -0.6

USA -0.60 -0.37

Russia -2.37 -4.1

RoA1 -1.18 -0.06

China -1.62 -3.8

India 1.64 -2.2

Brazil 0.00 -0.18

NonA1_T -6.79 -1.12

RoW 2.24 1.65

Full Trade


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Application 2: CGE implication of climate change (thecost of inaction)

Impact Cathegory Status

Impact on labour quantity (change in mortality health effect

of climate change)

Impacts on labour productivity (change in morbidity health

effect of climate change)

Impacts on land quantity (land loss due to sea level rise)

Impacts on land productivity (Yield changes due totemperature and CO2 concentration changes)

Impacts on capital quantity (infrastructure vulnerability to

increase in frequency and intensity of extreme weather

events)

Impacts on water quantity (climate change driven water

scarcity)

Impacts on energy demand (change in households energy

consumption patterns for heating and cooling purposes)

Impacts on recreational services demand (change in tourism

flows induced by changes in climatic conditions)

Impacts on health care expenditure

Supply- side impacts

Demand-side impacts

Under development

Under development

+ 1.2 Ctemperature

increase in2050 wrt 2000(+1.4 C wrt 1980-

1999 average)

NEW+ 3.1 C

temperatureincrease in

2050 wrt 2000(+3.5 C wrt 1980-

1999 average)

Likelyrange

accordingto IPCC

FAR 2007


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Quantifying impacts

1.2C 3.2C 1.2C 3.2C 1.2C 3.2C 1.2C 3.2C 1.2C 3.2C 1.2C 3.2C

USA -0.06 -0.18 -0.15 -0.28 -0.02 -0.03 -5.66 -18.89 -6.19 -20.37 -8.18 -25.15Med_Europe 0.01 0.01 -0.10 -0.18 0.00 -0.01 -1.14 -8.33 -4.62 -18.94 -2.00 -11.84North_Europe 0.06 0.16 -0.35 -0.88 -0.01 -0.03 1.50 -7.74 -5.90 -26.01 50.00 107.82East_Europe 0.09 0.23 -0.47 -1.17 -0.01 -0.02 -1.13 -10.50 -2.64 -13.57 -4.60 -18.35FSU 0.11 0.28 -0.41 -1.03 -0.01 -0.03 -6.12 -21.92 -7.47 -24.64 -9.73 -30.10KOSAU -0.43 -1.14 0.57 1.62 0.04 0.11 -7.78 -17.00 -2.90 -7.41 -3.11 -7.38CAJANZ 0.09 0.22 0.03 0.24 0.00 0.00 -0.74 -12.33 -1.87 -14.31 -2.24 -15.17NAF -0.28 -0.69 2.02 4.41 0.10 0.23 -12.81 -42.14 -10.78 -41.00 -12.62 -45.97MDE -0.22 -0.34 1.34 1.81 0.10 0.14 -8.40 -32.40 -11.73 -38.52 -13.60 -43.12SSA -0.31 -0.84 0.47 1.34 0.07 0.19 -9.89 -15.02 -7.17 -7.42 -8.81 -10.59SASIA -0.11 -0.30 0.28 0.76 0.06 0.17 -2.96 -13.37 -4.89 -17.39 -6.61 -21.43CHINA 0.14 0.37 0.65 1.80 0.06 0.17 0.93 2.69 0.50 1.79 -1.42 -2.37

EASIA -0.11 -0.32 1.05 2.96 0.06 0.17 2.45 9.82 0.34 5.04 -1.15 1.93LACA -0.14 -0.39 0.68 1.98 0.07 0.19 -6.69 -68.10 -6.61 -55.65 -8.25 -76.37

Labour Product. Public Exp. Private Exp. Wheat Rice Cereal Crops

HEALTH LAND PRODUCTIVITY

1.2C 3.2C 1.2C 3.2C 1.2C 3.2C 1.2C 3.2C 1.2C 3.2C 1.2C 3.2C

USA -0.026 -0.055 -0.68 -1.76 -0.17 -0.43 -13.67 -35.31 -18.52 -47.84 0.76 1.96Med_Europe -0.007 -0.015 -1.86 -4.81 -0.40 -1.02 -12.68 -32.76 -15.84 -40.91 0.76 1.96North_Europe -0.020 -0.041 7.54 19.47 1.78 4.61 -13.75 -35.51 -15.52 -40.09 -2.20 -5.68East_Europe -0.022 -0.046 -2.46 -6.36 -0.33 -0.86 -12.93 -33.41 -17.39 -44.92 0.76 1.97FSU -0.007 -0.015 0.00 -0.01 0.00 0.00 -13.02 -33.65 -17.39 -44.92 0.75 1.94KOSAU -0.005 -0.011 -1.31 -3.39 -0.32 -0.82 nss nss -13.03 -33.66 12.31 31.81CAJANZ -0.004 -0.009 5.54 14.30 1.40 3.61 -5.05 -13.04 -12.63 -32.63 -4.80 -12.40NAF -0.017 -0.036 -2.52 -6.52 -0.24 -0.63 -8.60 -22.22 -13.25 -34.22 5.95 15.37MDE -0.004 -0.007 -4.67 -12.06 -0.91 -2.34 -13.12 -33.89 -17.39 -44.92 0.74 1.92SSA -0.066 -0.139 -4.43 -11.45 -0.37 -0.96 nss nss -6.51 -16.83 16.35 42.23SASIA -0.204 -0.427 -1.21 -3.12 -0.10 -0.25 nss nss nss nss 20.38 52.65CHINA -0.045 -0.094 -4.99 -12.89 -0.33 -0.85 nss nss nss nss 20.38 52.65

EASIA -0.316 -0.662 -4.69 -12.10 -0.53 -1.38 nss nss nss nss 20.38 52.66LACA -0.025 -0.052 -2.68 -6.91 -0.56 -1.45 nss nss nss nss 21.37 55.20

HOUSEHOLDS' ENERGY DEMAND

Natural Gas Oil Products Electricity

SEA LEV. RISE TOURISM

Land LossesMarket Serv.

DemandIncome Flows


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Climate cange impacts: the global picture (1)

CC (1.2C) vs baseline: Real GDP (% change)

-5

-4

-3

-2

-1

0

1

2

3

4

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041

2044

2047

2050

USA

Med_Europe

North_Europe

East_Europe

FSU

KOSAU

CAJANZNAF

MDE

SSA

SASIA

CHINA

EASIA

LACA

World

CC (3.1C) vs baseline: Real GDP (% change)

-5

-4

-3

-2

-1

0

1

2

3

4

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041

2044

2047

2050

USA

Med_Europe

North_Europe

East_Europe

FSU

KOSAU

CAJANZNAF

MDE

SSA

SASIA

CHINA

EASIA

LACA

World


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Climate cange impacts: the global picture (2)

Climate Change Impacts: Summary

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

1.2 C 3.1 C 1.2 C 3.1 C 1.2 C 3.1 C 1.2 C 3.1 C 1.2 C 3.1 C 1.2 C 3.1 C

Agriculture Energy

Demand

Health Sea Level

Rise

Tourism A ll Impacts

Tempe rature increase

%ofGD

P

USA

Med_Europe

North_Europe

East_Europe

FSU

KOSAU

CAJANZ

NAF

MDE

SSA

SASIA

CHINA

EASIA

LACA

World


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Effects in international markets (1)

CC (1.2C) vs Baseline: world pr ices (% Changes)

-20

-15

-10

-5

0

5

10

15

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041

2044

2047

2050

Rice

Wheat

CerCrops

VegFruits

Animals

Wood Prod

Fishing

Coal

Oil

Gas

Oil_Pcts

Electricity

Water

En_Int_ind

Oth_ind

MServ

NMServ

CC (3.1C) vs baseline: world prices (% changes)

-20

-15

-10

-5

0

5

10

15

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041

2044

2047

2050

Rice

WheatCerCrops

VegFruits

Animals

Wood Prod

FishingCoal

Oil

Gas

Oil_Pcts

ElectricityWater

En_Int_ind

Oth_ind

MServ

NMServ


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Effects in international markets (2)

CC (1.2C) vs Baseline: terms of trade (% changes)

-20

-15

-10

-5

0

5

10

15

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041

2044

2047

2050

USA

Med_Europe

North_Europe

East_Europe

FSU

KOSAU

CAJANZ

NAF

MDE

SSA

SASIA

CHINA

EASIA

LACA

CC (3.1C) vs Baseline: term s of trade (% changes)

-20

-15

-10

-5

0

5

10

15

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041

2044

2047

2050

USA

Med_Europe

North_Europe

East_Europe

FSU

KOSAU

CAJANZ

NAF

MDE

SSA

SASIA

CHINA

EASIA

LACA


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The sectoral pictureClimate change impacts on production, 3.1C, ref. Year 2050 (% change wrt base)

USA Med_Eu North_Eu East_Eu FSU KOSAU CAJANZ NAF MDE SSA SASIA CHINA EASIA LACA

Rice -3.46 3.18 1.14 0.21 -0.99 -0.55 -10.09 -9.07 6.18 -3.77 -5.39 -1.11 -1.75 2.10

Wheat -10.27 -1.12 6.28 0.85 -3.11 -0.10 3.03 -5.69 5.10 -3.57 -1.38 -0.99 0.04 -1.84

CerCrops -9.85 -1.05 48.39 -2.14 -4.53 1.61 -3.01 -7.35 -1.77 -1.60 -3.73 0.58 -1.45 -3.20

VegFruits -10.08 0.79 21.76 -0.11 -4.28 0.16 -3.14 -4.89 3.79 -0.99 -4.17 1.65 0.62 -2.76

Animals -3.96 2.56 -2.33 -0.01 -3.18 -1.19 -7.89 -5.54 3.33 -4.56 -6.14 -1.61 -1.47 1.07

Wood Products 0.71 2.16 -14.50 0.87 1.29 -0.94 -20.36 -0.05 8.29 -0.83 -4.07 -1.01 -2.86 2.72

Fishing 2.11 8.77 -8.09 1.53 1.89 2.12 -18.75 -0.99 7.54 -3.08 -4.45 -0.55 0.52 3.31Coal -0.15 0.06 -2.13 -0.69 -0.19 -0.08 -1.24 0.38 0.62 0.65 0.56 0.64 0.58 0.58

Oil -0.54 -0.61 -0.72 -0.75 -0.31 -0.55 -0.83 -0.25 -0.22 -0.25 -0.29 -0.20 -0.27 -0.30

Gas -4.93 -14.51 -13.84 -16.62 -5.84 -1.71 -3.99 -1.49 -2.43 -0.26 -0.43 2.46 0.55 2.28

Oil_Pcts -2.28 0.72 -0.77 -1.10 -7.58 -0.63 0.97 -7.13 -9.19 -6.16 1.28 3.55 6.42 4.64

Electricity -0.18 1.68 -16.16 -2.58 -1.47 3.39 -13.45 4.01 3.78 10.95 7.39 4.73 13.83 16.44

Water 0.84 5.92 -11.66 0.71 -0.64 1.51 -14.18 -0.77 2.75 -1.96 -0.79 0.30 1.21 2.84

En_Int_ind 0.10 3.54 -10.46 0.26 0.01 -1.27 -13.05 2.47 13.00 2.44 -3.52 -0.75 -2.46 4.05

Oth_ind 1.80 5.11 -12.22 2.03 -1.79 -0.14 -14.87 -4.45 9.68 -3.91 -6.22 -0.98 -1.71 2.55

MServ -0.74 -0.21 10.70 -1.83 0.33 -1.95 7.25 -2.85 -7.17 -4.56 -4.13 -4.64 -5.43 -5.82NMServ 0.36 -1.20 -2.21 -0.24 -2.20 1.31 -1.26 0.29 -2.67 -0.83 2.60 2.59 1.90 0.85

Int. Inv. Flows -0.67 0.72 6.30 -2.37 -4.87 -1.47 2.41 -4.66 -5.84 -4.93 -5.79 -4.30 -5.22 -5.28

Med_Eu North_Eu East_Eu

Rice 3.18 1.14 0.21Wheat -1.12 6.28 0.85

CerCrops -1.05 48.39 -2.14

VegFruits 0.79 21.76 -0.11

Animals 2.56 -2.33 -0.01

Wood Products 2.16 -14.50 0.87

Fishing 8.77 -8.09 1.53Coal 0.06 -2.13 -0.69

Oil -0.61 -0.72 -0.75

Gas -14.51 -13.84 -16.62

Oil_Pcts 0.72 -0.77 -1.10

Electricity 1.68 -16.16 -2.58

Water 5.92 -11.66 0.71En_Int_ind 3.54 -10.46 0.26

Oth_ind 5.11 -12.22 2.03

MServ -0.21 10.70 -1.83

NMServ -1.20 -2.21 -0.24

Int. Inv. Flows 0.72 6.30 -2.37

0.31 2.96 -1.20GDP


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Application 3: impact of opening EU mitigation policy toREDD

Addressing the role REDD may play in the European carbon market,

in the context of a mitigation policy aiming to reduce EU emissionsby 20% respect to 1990 in 2020.

Accounting for direct and indirect effects occurring both on land andtimber markets. Lower deforestation => lower land available to

agriculture and lower raw wood to timber industry

ICES Emission Trade Scheme (ETS) module (originally restricted toemission reduction from fossil fuel use) updated to account fortrading of carbon credits originated by reduced deforestationactivities.

Regions selling REDD credits can participate to the EU carbon marketeven without accepting binding reduction quota, but only on thebasis of proven reduction in deforestation activities


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REDD data

Mainly from IIASA Cluster model (Gusti et al. 2008) providing BAUdeforestation rates and regional avoided deforestation curves inresponse to CO2 prices (Below example for Latin America)

LACA IIASA

0

200

400

600

800

1000

1200

0 20 40 60 80 100

120

140

160

180

200

220

240

260

280

300

320

340

360

380

400

420

440

460

480

500

520

540

560

580

600

620

Million Tons

CarbonPrice

2010

2015

2020

2025

2030

2035

2040

2045

2050


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Results: EU GDP costs (2020)

Limits to REDD credits in the ETS market

No

REDD

5% 10% 15% 20% 25% 30% 50%

No

Limits

CO2

EU Price 46 43 40 38 35 33 31 23 8

% reduction 0% -6% -12% -17% -22% -27% -32% -50% -83%

European Policy Cost (Million US$)

115.110

101.377

76.769

19.292

0

20.000

40.000

60.000

80.000

100.000

120.000

140.000

ETS without REDD ETS with 10% REDD ETS with 30% REDD ETS with REDD


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Results: direct revenues to REDD regions (2020)

Reduction in deforestation activities 22% (on average in2020)


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Results: GDP gains for REDD regions (2020)

GDP Variation with respect to BAU (Million US$)

1.073836

2.637

361115

953

0

500

1.000

1.500

2.000

2.500

3.000

10 SSA 13 EASIA 14 LACA

ETS w/o REDD ETS withl REDD


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CENTRO EURO MEDITERRANEOPER I CAMBIAMENTI CLIMATICI 37

Results: Price effects on land (upper) and timber (lower)(2020) in REDD regions

Documents

Francesco Bosello. Assessing Climate Change Impacts and Policies With CGE Models, Methodology and Application - The ICES Model