The ICES model (special focus on impacts assessment) ISI-MIP Integration Activity CGE Modellers...

The ICES model (special focus on impacts assessment)

ISI-MIP Integration Activity

CGE Modellers Workshop

PIK, 18-19 September 2013

Fabio Eboli

FEEM,CMCC



2

Outline

• Introduction

• The ICES framework

• CGE modelling of impact assessment

• Main results (ClimateCost, EUAdaptStrat)

• Conclusion and proposals for discussion



3

Economic Assessment: methodologies

Framing the issue …. different economic assessment perspectives

Bottom-Up => deep analysis on specific impact/region/sector (first-order or partial equilibrium or direct effects)

Top-Down => economy-wide analysis, beyond the initial shock => propagation throughout the rest of the economic system (higher-order or general equilibrium or indirect effects) => CGE models



4

CGE modelling framework

• Main scope: assessing higher-order (general) effects on the whole economic system assuming localized shocks within it

• Applications: International trade, taxation, agricultural policy => recent development on environmental economics (impacts and policies assessment, mainly climate change and other transboundary issues)

• Main results: impacts on GDP, sectoral output and prices, international trade when considering market-driven (autonomous) adaptation of economic agents => scenario analysis



5

The ICES model

GTAP (Hertel, 1997)

GTAP-E (Burniaux and Troung, 2002)

ICES (Eboli, Parrado and Roson, 2010)



6

Social Accounting Matrix

• GTAP7 database (Narayanan and Walmsley, 2008) => now GTAP8 database available

Content: all economic - and energy - flows in Input-Output (SAM) matrix format

National statistics balancement + International Trade Baseyear: 2004 (GTAP8: 2007) Geographic coverage: world (113 countries/regions)

(GTAP8: 129) Sector coverage: the whole economic system (split in 57

sectors)



7

The ICES model

AIM => Quantify the economic relevance of possible future

“changes” triggered by specific climate change impacts or policies

Main model features

Intertemporal Computable Equilibrium System Dynamic-recursive multi-region and multi-sector computable general

equilibrium model for the world economy Interaction between exogenous and endogenous dynamics Geographical detail: country/macroregion (bundles of countries) One-year time steps Micro-economic perspective (agents’ behaviour): economic agents

perfectly clever (households and firms utility and profit maximizers, respectively) but not looking forward (vs fully dynamic CGE models; vs optimization model, e.g. REMIND, WITCH)



8

The ICES model

AIM => Quantify the economic relevance of possible future

“changes” triggered by specific climate change impacts or policies

Main model features

Markets’ behaviour: All markets (primary factors and commodities) work under perfect competition hypothesis (supply-demand always matching => prices’ adjustment)

Relative price matters (market-driven adaptation) Macro-economics: domestic and international markets fully

interconnected Interaction between sectors (I-O relationships) and regions (international trade)

Main outputs: changes in GDP, national and sectoral production, prices, import/exports

Policy-relevant variables: GHGs, AEZ, RES, Climate Policy set (BTA, AUCT vs GDFR, sectoral ETS, CO2 vs multi-GHGs)



9

Climate Change Impact Assessment: overview

Project Impact CoverageGeographical Coverage

Socio-economic and Climate Scenarios

CIRCE Energy, Sea Level Rise, Tourism

Mediterranean area (country level)

A1B IPCC SRES scenario

ClimateCostAgriculture, Energy, Forestry, Health, River Floods, Sea Level Rise, Tourism,

World (macro-regional level)

A1B IPCC SRES scenario

ClimWatAdapt River Floods EU (country level) 4 SCENES FP7 project scenarios

EUAdaptStrat

Agriculture, Ecosytems, Energy, Fishery, Forestry, Health, River Floods, Sea Level Rise, Tourism,

EU (country level) 2012 Ageing Report(2°C and 4°C)

PESETACoastal systems, Human health, Agriculture, Tourism, River Floods

EU (5 macro-regions)

A2 (high emissions) & B2 (low emissions) IPCC climate scenario:•2020s only one climate scenario; •2080s four alternative climate futures: 2.5°C, 3.9°C, 4.1°C and 5.4°C

SESAME Marine Ecosystems/FisheryMediterranean and Black Sea region (country level)

3 scenarios: 1)Baseline (A1B IPCC SRES scenario); 2)Policy Targeted; 3)Deep Blue



10

Climate Change Impacts: main sources

Impact ModelGeographical Scope

Reference

Supply-side

Agriculture ClimateCrop Global Iglesias et al., 2009; Iglesias et al., 2010

Ecosystems n.a. Global Manne et al., 2005; Warren 2006

Fishery n.a. Global Cheung et al., 2010

Forest net primary productivity

LPJmL Dynamic Global Vegetation Model

Global Boundeau et al., 2007; Tietjen et al., 2009

Health n.a. EuropeKovats et al., 2006; Kjellstrom et al., 2009, Kovats and Lloyd, 2011

River floods LISFLOOD EU27 Van der Knijff et al., 2009; Feyen, 2009

Sea-level riseDIVA (Dynamic Integrated Vulnerability Assessment)

Global Vafeidis et al., 2008

Demand-side

Residential energy demand

POLES Global Criqui, 2001; Criqui et al., 2009

Tourism flowsHTM (Hamburg Tourism Model)

Global Bigano et al., 2007



11

Climate Change Impact Assessment: rationale

Climate ModelsClimate Models

Physical Impact Models (bottom-up)

Physical Impact Models (bottom-up)

Economic Impact Models (top-down)Economic Impact

Models (top-down)

Socio-economic Scenarios

Climate Change Drivers

Socio-economic Scenarios

Climate Change Drivers

GHG EmissionsGHG Emissions

Climate VariablesClimate Variables

Physical Impact AssessmentPhysical Impact Assessment

Macro-economic Impact AssessmentMacro-economic Impact Assessment

CGE Models

(ICES)

CGE Models

(ICES)



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Climate Change Impact Assessment: channels

Sea Level RiseSea Level Rise

Energy DemandEnergy Demand

TourismTourism

FisheryFishery

River FloodsRiver Floods

HealthHealth

EcosystemsEcosystems

Loss in land and physical capital stockLoss in land and physical capital stock

Change in residential demand of oil, gas, electricityChange in residential demand of oil, gas, electricity

Changes in households’ demand in the market services sector; Changes in regional incomeChanges in households’ demand in the market services sector; Changes in regional income

Agriculture : Loss in land stock Other sectors: Change in capital productivityPopulation affected: Change in labour productivity

Agriculture : Loss in land stock Other sectors: Change in capital productivityPopulation affected: Change in labour productivity

Changes in labour productivity (morbidity/mortality or job-on-performance)Changes in labour productivity (morbidity/mortality or job-on-performance)

Change in stock/productivity in the fishing sectorChange in stock/productivity in the fishing sector

Loss in physical capital stockLoss in physical capital stock

AgricultureAgriculture Change in land productivity/fertility (also water scarcity driven)Change in land productivity/fertility (also water scarcity driven)

ForestryForestry Change in stock/npp in the forest sectorChange in stock/npp in the forest sector



13

Impact Assessment: ICES main results

Impact on GDP (% wrt «no climate change scenario»): A1b SRESImpact on GDP (% wrt «no climate change scenario»): A1b SRES

Source: ClimateCost projectSource: ClimateCost project



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Impact Assessment: ICES main results

Impact on GDP (% wrt «no climate change scenario»)

=> decomposition by impact for the World …

Impact on GDP (% wrt «no climate change scenario»)

=> decomposition by impact for the World …

… and for

Macro-Regions

… and for

Macro-Regions




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Impact Assessment: comparing with B-U

Who provides higher impacts between T-D and B-U?

=> CGE involve all economic sectors but market-driven adaptation

Who provides higher impacts between T-D and B-U?

=> CGE involve all economic sectors but market-driven adaptation

Sea Level RiseSea Level Rise




16

Impact Assessment: snapshot on EU

Impact on GDP (% wrt «no climate change scenario») =>

different temperature increase


different temperature increase

Source: EUAdaptStrat projectSource: EUAdaptStrat project

-0.16%

(World: -0.7%)

-0.74%

(World: -1.8%)



17

Impact Assessment: snapshot on EU


decomposition by impact for different temperature increase


decomposition by impact for different temperature increase

Source: EUAdaptStrat projectSource: EUAdaptStrat project

-8

-6

-4

-2

0

2

4

6

%

Agriculture Tourism Energy Sea Level Rise Ecosystems Floodings Human Health Fishery-8

-6

-4

-2

0

2

4

6

%

Agriculture Tourism Energy Sea Level Rise Ecosystems Floodings Human Health Fishery

2°C4°C



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Conclusions

• Economic assessment of climate change does not show – not surprisignly - a huge loss in terms of aggregate welfare/GDP

• Nevertheless, impact distribution across regions and countries quite relevant

• The poorer the more vulnerable (also in EU – Southern suffers more)

• Changes in crop productivity, tourism flows and ecosystem services predominant

• Currently, acceptable coverage in terms of impacts• Possible extension to damage function calibration in

optimization model (e.g. Witch in ClimateCost)



19

Challenges/Current limitations

Extension of time horizon ….…. uncertainty cascade on impacts (functional forms

wrt temperature increase and other climatic drivers) …. as well as baseline/reference scenario (SSPs vs

RCPs, GDP and Pop, energy prices, energy mix => emissions, technical progress) => harmonization of climate drivers for impact models

Extreme and Catastrophic events (tipping points)

Adaptation (Cost-Benefit analysis => Investment vs avoided damages)



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Thanks a lot!

[email protected]

http://www.feem-web.it/ices/



21



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The ClimateCost research structure

ClimaticDrivers

Environm.lImpacts

Socio-Economicimpacts

CGE-ICESEconomicTop-Down

Assessment

Mitigation

WITCHOptimalPolicy

Assessment

Updated

reduced-form

damage

functions

WP1 WP2 WP6

WP7



23

Damage Function in IAM-WITCH

The analysis performed through the CGE-ICES model is used to update the reduced-form damage function for the IAM-WITCH model - based on Nordhaus (2007)

Nordhaus still used to quantify impacts categories not covered by the ICES impact assessment (non-market impacts)

Damage function allows computing SCC (Social Cost of Carbon) (damages caused by one extra ton on carbon in atmosphere) => useful criterion to assist policymakers on climate policy

(emissions => radiative forcing => temperature => quadratic region-specific relationship to compute feedback on GDP)

(emissions => radiative forcing => temperature => quadratic region-specific relationship to compute feedback on GDP)



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Impacts for Damage Function

IMPACT MODELGeographical Scope

Reference

sea-level riseDIVA (Dynamic Integrated Vulnerability Assessment)


tourism flowsHTM (Hamburg Tourism Model)


crops’ productivity

ClimateCrop GlobalIglesias et al., 2009; Iglesias et al., 2010

residential energy demand


forest net primary productivity


GlobalBoundeau et al., 2007; Tietjen et al., 2009

river floods LISFLOOD EU27Van der Knijff et al., 2009; Feyen, 2009

job performance

n.a. EuropeKjellstrom et al., 2009, Kovats and Lloyd (2011)

IMPACT MODELGeographical Scope

Reference

sea-level riseDIVA (Dynamic Integrated Vulnerability Assessment)


tourism flowsHTM (Hamburg Tourism Model)


crops’ productivity

ClimateCrop GlobalIglesias et al., 2009; Iglesias et al., 2010

residential energy demand


forest net primary productivity


GlobalBoundeau et al., 2007; Tietjen et al., 2009

river floods LISFLOOD EU27Van der Knijff et al., 2009; Feyen, 2009

job performance n.a. EuropeKjellstrom et al., 2009, Kovats and Lloyd (2011)

human health

biodiversity

catastrophic



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Damage function calibration

-20.0

-15.0

-10.0

-5.0

0.0

5.0

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50

Pe

rce

nta

ge

GD

P lo

ss

Degree Celsius above pre-industrial levels

USA

OLDEURO

NEWEURO

KOSAU

CAJAZ

TE

MENA

SSA

SASIA

CHINA

EASIA

LACA

Average values => sensitivity analysis performed mainly for agriculture in case of > 2 degrees temperature increase

wrt pre-industrial level

Average values => sensitivity analysis performed mainly for agriculture in case of > 2 degrees temperature increase

wrt pre-industrial level



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Mitigation Policy Costs

-20

-15

-10

-5

0

5

10

15

2005 2015 2025 2035 2045 2055 2065 2075 2085 2095

US$

20

05

Tri

llio

ns

Policy costs net of avoided damages

Policy costs gross of avoided damages

Climate change benefits (avoided damages)

Considering climate change avoided damages reduces mitigation costs (cumulative GWP) from 2.86% (1.97%) to 2.24% (1.66%) at

3% (5%) annual discount rate

Considering climate change avoided damages reduces mitigation costs (cumulative GWP) from 2.86% (1.97%) to 2.24% (1.66%) at

3% (5%) annual discount rate

The ICES model (special focus on impacts assessment) ISI-MIP Integration Activity CGE Modellers...

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