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Spatial-economic-ecological model for the assessment ofsustainability policies of Russian FederationModeling environmental dimension, policy analysis and the assessment of the model reliabilityVictoria Alexeeva-TalebiCentre for European Economic Research (ZEW), MannheimKick-off meeting CEFIR, Moscow, 11 February 2009
Agenda ZEW‘s objectives in the Sust-Rus Project Dimensions and structure of the PACE model Policy applications of the PACE model Sensitivity Analysis Outlook
1. ZEW‘s Objective within the Sust-Rus Project • To review the literature on crucial model parameters (Task 3.3) • To review the environmental indicators (Task 4.4) • To develop the environmental module (Task 5.1 and 5.2) data availability and model development • To run alternative policy scenarios (Task 9.1) definition and assessment of policy scenarios • To assess the model reliability: sensitivity analysis (Task 9.2)
Other Other regions regions Demand for goods Exports of goods Exports of Imports of goods Imports of Hous- Other Other Rest of Petro- Iron Che- Transp Elec Heat Agri. Food PPP hold ETS EII ind. leum and mical prod Steel prod. Income cycle 2. Structure: PACE core model
2. Structure: Model implementation • Highly flexible core model system • Regional/spatial resolution • N(ation): Small open economy (SOE) • E(urope): Bilateral EU-15 (SOE closure wrt ROW) • W(orld): Bilateral world trade model (up to 45 regions) • Sectoral resolution • N: Country specific (national IO), E/W: up to 50 sectors • Temporal resolution • Comparativ-static (myopic) • Dynamic-recursiv (myopic) • Intertemporal (rational expectations)
2. Structure: PACE modeling environment • Intuitive programming language GAMS • Model development and test tool MPSGE • Powerful solution algorithm PATH • Tools for automatic reporting • Transparent user interface and online-communication GAMS-X/SM • Flexibility to quickly tailor core model to specific policy issues • Flexibility to quickly link core model to complementary models
Structure: PACE-BU model • Bottom-up (BU) representation of the electricity sector • Project: Analysing the Economic Impacts of the Renewables and Climate Change Policy Implementation • For: DG Enterprise and Industry 2007, 2008 • Publications: • Neuwahl, F., Löschel, A., Ignazio, M. and L. Delgado (2006), Employment Impacts of EU Biofuels Policy: Combining Bottom-up Technology Information and Sectoral Market Simulations in an Input-Output Framework, forthcoming in Ecological Economics.
3. Policy application: The Energy package • Directive & Decision: Implementing the CO2 targets • Specifying the non-ETS targets (Decision) • Division of EU wide emission budget between ETS and non-ETS sectors • Specifying non-ETS targets for individual member states vs 2005 • Amending the ETS (Directive) • Defining overall ETS cap • Centralized allocation, mainly auction, but sector-specific • Both • Carbon: „external affairs“ (use of flex-mex) • Timeframe: 2013 to at least 2020 • Special provisions in case of international agreement
3. Policy application: The ETS targets • ETS: Target and allocation procedure • One EU wide cap (linear decrease from 2013 to 2020) • Auctioning as basic principle for allocation • Power sector: 100% auctioned from 2013 on • All others: 30% in 2013 increasing to 100% in 2020 • „Facilitating Package for energy intensive industries“: For sectors with potential leakage problems (or danger of loss of market share) free allocation of up to 100% (base: reduced ETS-cap, share based on 2005 emissions) • All allocation other than auctioning according to EU-wide harmonized rules (benchmarking suggested) No National Allocation Plans (NAPs) anymore!
3. Policy application: The policy scenarios • Evaluation of macroeconomic and environmental impacts of the EU energy package • Quantification of effects on international competitiveness, social welfare and greenhouse gas emissions • Policy scenario covering the following policy issues of the new EU 2008 energy package • Allocation rules in EU ETS + renewable certificate trading schemes • Burden sharing rules between MS in non-ETS sectors • Burden sharing rules between MS for renewable targets • Degree of flexibility for JI/CDM
140 120 100 80 60 40 20 0 France Germany Italy Spain UK Rest EU- Poland Rest EU- 15 12 3. Policy application: Carbon prices in 2020 €/tCO2
3. Policy application: Macro-economic impacts Welfare changes (in % vs BaU)
3. Policy application: Sectoral impacts in 2020 Energy intensive industries (prod. change in % vs BaU)
4. Sensitivity Analysis • Definition Sensitivity analysis is the study of how the variation in the output of a model (numerical or otherwise) can be apportioned, qualitatively or quantitatively, to different sources of variation. Sensitivity analysis serves to check the robustness of results of the simulation of an economic model. • Approaches Deterministic vs. Stochastic Approach • Publications: Claudia Hermeling and Tim Mennel (2008), Sensitivity Analysis in Economic Simulations – A Systematic Approach, ZEW Discussion Paper
5. Outlook • Modeling issues: MCP vs. MPSE • Data Modeling Policies: What issues are central for the analysis? • European Council (2007): Linking to the EU ETS? • Russia‘s Energy strategy (2003): Focus on the energy-intensive sectors (energy taxes & subsidies)? • Russia‘s Energy strategy (2003): Focus on the energy demand by the households? • EU, Russia: Energy supply issues?