The ICES model (special focus on impacts assessment) ISI-MIP Integration Activity CGE Modellers Workshop PIK, September 2013 Fabio Eboli FEEM,CMCC

ISI-MIP Integration Activity CGE Modellers Workshop 1 Outline Introduction The ICES framework CGE modelling of impact assessment Main results (ClimateCost, EUAdaptStrat) Conclusion and proposals for discussion

ISI-MIP Integration Activity CGE Modellers Workshop 2 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

ISI-MIP Integration Activity CGE Modellers Workshop 3 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

ISI-MIP Integration Activity CGE Modellers Workshop 4 The ICES model GTAP (Hertel, 1997) GTAP-E (Burniaux and Troung, 2002) ICES (Eboli, Parrado and Roson, 2010)

ISI-MIP Integration Activity CGE Modellers Workshop 5 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)

ISI-MIP Integration Activity CGE Modellers Workshop 6 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)

ISI-MIP Integration Activity CGE Modellers Workshop 7 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, CO 2 vs multi-GHGs)

ISI-MIP Integration Activity CGE Modellers Workshop 8 Climate Change Impact Assessment: overview ProjectImpact Coverage Geographical Coverage Socio-economic and Climate Scenarios CIRCE Energy, Sea Level Rise, Tourism Mediterranean area (country level) A1B IPCC SRES scenario ClimateCost Agriculture, Energy, Forestry, Health, River Floods, Sea Level Rise, Tourism, World (macro-regional level) A1B IPCC SRES scenario ClimWatAdapt River FloodsEU (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) PESETA Coastal 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/Fishery Mediterranean and Black Sea region (country level) 3 scenarios: 1)Baseline (A1B IPCC SRES scenario); 2)Policy Targeted; 3)Deep Blue

ISI-MIP Integration Activity CGE Modellers Workshop 9 Climate Change Impacts: main sources ImpactModel Geographical Scope Reference Supply-side AgricultureClimateCropGlobalIglesias et al., 2009; Iglesias et al., 2010 Ecosystemsn.a.Global Manne et al., 2005; Warren 2006 Fisheryn.a.GlobalCheung et al., 2010 Forest net primary productivity LPJmL Dynamic Global Vegetation Model GlobalBoundeau et al., 2007; Tietjen et al., 2009 Healthn.a.Europe Kovats et al., 2006; Kjellstrom et al., 2009, Kovats and Lloyd, 2011 River floodsLISFLOODEU27Van der Knijff et al., 2009; Feyen, 2009 Sea-level rise DIVA (Dynamic Integrated Vulnerability Assessment) GlobalVafeidis et al., 2008 Demand-side Residential energy demand POLESGlobalCriqui, 2001; Criqui et al., 2009 Tourism flows HTM (Hamburg Tourism Model) GlobalBigano et al., 2007

ISI-MIP Integration Activity CGE Modellers Workshop 10 Climate Change Impact Assessment: rationale Climate Models Physical Impact Models (bottom-up) Economic Impact Models (top-down) Socio-economic Scenarios Climate Change Drivers Socio-economic Scenarios Climate Change Drivers GHG Emissions Climate Variables Physical Impact Assessment Macro-economic Impact Assessment CGE Models (ICES) CGE Models (ICES)

ISI-MIP Integration Activity CGE Modellers Workshop 11 Climate Change Impact Assessment: channels Sea Level Rise Energy Demand Tourism Fishery River Floods Health Ecosystems Loss in land and physical capital stock Change in residential demand of oil, gas, electricity Changes in households’ demand in the market services sector; Changes in regional income Agriculture : Loss in land stock Other sectors: Change in capital productivity Population affected: Change in labour productivity Agriculture : Loss in land stock Other sectors: Change in capital productivity Population affected: Change in labour productivity Changes in labour productivity (morbidity/mortality or job-on-performance) Change in stock/productivity in the fishing sector Loss in physical capital stock Agriculture Change in land productivity/fertility (also water scarcity driven) Forestry Change in stock/npp in the forest sector

ISI-MIP Integration Activity CGE Modellers Workshop 12 Impact Assessment: ICES main results Impact on GDP (% wrt «no climate change scenario»): A1b SRES Source: ClimateCost project

ISI-MIP Integration Activity CGE Modellers Workshop 13 Impact Assessment: ICES main results Impact on GDP (% wrt «no climate change scenario») => decomposition by impact for the World … … and for Macro-Regions … and for Macro-Regions Source: ClimateCost project

ISI-MIP Integration Activity CGE Modellers Workshop 14 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 Rise Source: ClimateCost project

ISI-MIP Integration Activity CGE Modellers Workshop 15 Impact Assessment: snapshot on EU Impact on GDP (% wrt «no climate change scenario») => different temperature increase Impact on GDP (% wrt «no climate change scenario») => different temperature increase Source: EUAdaptStrat project -0.16% (World: -0.7%) -0.74% (World: -1.8%)

ISI-MIP Integration Activity CGE Modellers Workshop 16 Impact Assessment: snapshot on EU Impact on GDP (% wrt «no climate change scenario») => decomposition by impact for different temperature increase Impact on GDP (% wrt «no climate change scenario») => decomposition by impact for different temperature increase Source: EUAdaptStrat project 2°C 4°C

ISI-MIP Integration Activity CGE Modellers Workshop 17 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)

ISI-MIP Integration Activity CGE Modellers Workshop 18 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)

ISI-MIP Integration Activity CGE Modellers Workshop 19 Thanks a lot!

ISI-MIP Integration Activity CGE Modellers Workshop 20

ISI-MIP Integration Activity CGE Modellers Workshop 21 The ClimateCost research structure Climatic Drivers Environm.l Impacts Socio- Economic impacts CGE-ICES Economic Top-Down Assessment Mitigation WITCH Optimal Policy Assessment Updated reduced-form damage functions WP1 WP2 WP6 WP7

ISI-MIP Integration Activity CGE Modellers Workshop 22 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)

ISI-MIP Integration Activity CGE Modellers Workshop 23 Impacts for Damage Function IMPACTMODEL Geographical Scope Reference sea-level rise DIVA (Dynamic Integrated Vulnerability Assessment) GlobalVafeidis et al., 2008 tourism flows HTM (Hamburg Tourism Model) GlobalBigano et al., 2007 crops’ productivity ClimateCropGlobal Iglesias et al., 2009; Iglesias et al., 2010 residential energy demand POLESGlobalCriqui, 2001; Criqui et al., 2009 forest net primary productivity LPJmL Dynamic Global Vegetation Model Global Boundeau et al., 2007; Tietjen et al., 2009 river floodsLISFLOODEU27 Van der Knijff et al., 2009; Feyen, 2009 job performancen.a.Europe Kjellstrom et al., 2009, Kovats and Lloyd (2011) IMPACTMODEL Geographical Scope Reference sea-level rise DIVA (Dynamic Integrated Vulnerability Assessment) GlobalVafeidis et al., 2008 tourism flows HTM (Hamburg Tourism Model) GlobalBigano et al., 2007 crops’ productivity ClimateCropGlobal Iglesias et al., 2009; Iglesias et al., 2010 residential energy demand POLESGlobalCriqui, 2001; Criqui et al., 2009 forest net primary productivity LPJmL Dynamic Global Vegetation Model Global Boundeau et al., 2007; Tietjen et al., 2009 river floodsLISFLOODEU27 Van der Knijff et al., 2009; Feyen, 2009 job performancen.a.Europe Kjellstrom et al., 2009, Kovats and Lloyd (2011) human health biodiversity catastrophic

ISI-MIP Integration Activity CGE Modellers Workshop 24 Damage function calibration Average values => sensitivity analysis performed mainly for agriculture in case of > 2 degrees temperature increase wrt pre-industrial level

ISI-MIP Integration Activity CGE Modellers Workshop 25 Mitigation Policy Costs 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