Agenda

1. 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

2. 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

3. 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)

4. 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

5. 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)

6. 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

7. 2. Structure: PACE model extensions

8. 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.

9. 2. PACE: Structure of BU-TD model

10. 2. PACE: Structure of BU-TD model

11. 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

12. 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!

13. 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

14. 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

15. 3. Policy application: Macro-economic impacts Welfare changes (in % vs BaU)

16. 3. Policy application: Sectoral impacts in 2020 Energy intensive industries (prod. change in % vs BaU)

17. 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

18. 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?