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Outline. Introduction The ICES framework CGE modelling of impact assessment Main results ( ClimateCost , EUAdaptStrat ) Conclusion and proposals for discussion. Economic Assessment: methodologies. Framing the issue …. different economic assessment perspectives

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  1. Outline Introduction The ICES framework CGE modelling of impact assessment Mainresults (ClimateCost, EUAdaptStrat) Conclusion and proposals for discussion 1

  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 2

  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 3

  4. The ICES model GTAP (Hertel, 1997) GTAP-E (Burniaux and Troung, 2002) ICES (Eboli, Parradoand Roson, 2010) 4

  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) 5

  6. The ICES model AIM => Quantify the economicrelevance of possible future “changes” triggered by specificclimatechangeimpacts or policies Main model features • Intertemporal Computable Equilibrium System • Dynamic-recursive multi-region and multi-sectorcomputable general equilibrium model for the world economy • Interactionbetweenexogenous and endogenousdynamics • 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) 6

  7. The ICES model AIM => Quantify the economicrelevance of possible future “changes” triggered by specificclimatechangeimpacts or policies Main model features • Markets’ behaviour: Allmarkets (primaryfactors and commodities) work under perfectcompetitionhypothesis (supply-demandalwaysmatching => prices’ adjustment) • Relative price matters (market-driven adaptation) • Macro-economics: domestic and internationalmarketsfullyinterconnectedInteractionbetweensectors (I-O relationships) and regions (internationaltrade) • Mainoutputs: changes in GDP, national and sectoral production, prices, import/exports • Policy-relevantvariables: GHGs, AEZ, RES, Climate Policy set (BTA, AUCT vs GDFR, sectoral ETS, CO2 vs multi-GHGs) 7

  8. Climate Change Impact Assessment: overview 8

  9. Climate Change Impacts: main sources 9

  10. Climate Change Impact Assessment: rationale Socio-economicScenarios ClimateChange Drivers GHG Emissions ClimateModels ClimateVariables Physical Impact Models (bottom-up) Physical Impact Assessment Economic Impact Models (top-down) CGE Models (ICES) Macro-economic Impact Assessment 10

  11. Climate Change Impact Assessment: channels Agriculture Change in landproductivity/fertility (also water scarcitydriven) Ecosystems Loss in physical capital stock Energy Demand Change in residential demand of oil, gas, electricity Change in stock/productivityin the fishingsector Fishery Change in stock/nppin the forestsector Forestry Changes in labourproductivity(morbidity/mortality or job-on-performance) Health Agriculture : Loss in land stock Othersectors: Change in capital productivity Populationaffected: Change in labourproductivity River Floods Loss in land and physical capital stock Sea Level Rise Tourism Changes in households’ demand in the market services sector; Changes in regional income 11

  12. Impact Assessment: ICES mainresults Impact on GDP (% wrt «no climatechange scenario»): A1b SRES Source: ClimateCostproject 12

  13. Impact Assessment: ICES mainresults Impact on GDP (% wrt «no climatechange scenario») => decomposition by impact for the World … … and for Macro-Regions Source: ClimateCostproject 13

  14. Impact Assessment: comparing with B-U Whoprovideshigherimpactsbetween T-D and B-U? => CGE involve alleconomicsectorsbut market-drivenadaptation Sea Level Rise 14 Source: ClimateCostproject

  15. Impact Assessment: snapshot on EU Impact on GDP (% wrt «no climatechange scenario») => different temperature increase -0.16% (World: -0.7%) -0.74% (World: -1.8%) 15 Source: EUAdaptStratproject

  16. Impact Assessment: snapshot on EU Impact on GDP (% wrt «no climatechange scenario») => decomposition by impact for different temperature increase 2°C 4°C 16 Source: EUAdaptStratproject

  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) 17

  18. Challenges/Currentlimitations • Extension of time horizon …. • …. uncertaintycascade on impacts(functionalformswrt temperature increase and otherclimatic drivers) • …. aswellasbaseline/reference scenario (SSPs vs RCPs, GDP and Pop, energyprices, energy mix => emissions, technical progress) => harmonization of climate drivers for impact models • Extreme and Catastrophicevents(tippingpoints) • Adaptation (Cost-Benefit analysis => Investment vs avoideddamages) 18

  19. Thanks a lot! fabio.eboli@feem.it http://www.feem-web.it/ices/ 19

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

  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 => quadraticregion-specificrelationship to compute feedback on GDP) 22

  23. Impacts for Damage Function 23

  24. Damage function calibration Averagevalues => sensitivityanalysisperformedmainly for agriculture in case of > 2 degrees temperature increasewrtpre-industrial level 24

  25. Mitigation Policy Costs Consideringclimatechangeavoideddamagesreducesmitigationcosts (cumulative GWP) from 2.86% (1.97%) to 2.24% (1.66%) at 3% (5%) annual discount rate 25

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