Modeling the Reference and Alternative Scenarios

1. Modeling the Reference and Alternative Scenarios 11-12 September 2007, Prince Hotel and Residence Kuala Lumpur E.Barcelona The Institute of Energy Economics, Japan(IEEJ)

2. Projection Outline • Projection Period：2005～2030 • Methodology：Final Energy Demand: estimated using econometrics Electricity generation: based on generation mix submitted by individual countries; For countries with no projected mix: based on econometrics and other relevant information • Scenarios: • Reference - Reference scenario anticipates probable assumptions based on current political situations and the economic growth targets of each EAS countries which yields future evolution of energy demand and supply • Alternative Policy Scenario This scenario develops future picture, in which Asian countries successfully implement their energy saving goals and action plans. For countries with no numerical targets, no APS is made hoping that new information would be provided during this meeting. In cases where both primary energy intensity targets and energy savings goals are provided, the latter are used.

3. Model Structure Economic Growth Targets GDP, Crude oil price, Exchange rate, Population, Power generation outlook, thermal efficiencies, etc. Industry Transport Other For APS, Primary energy intensity targets or detailed sectoral energy saving goals, thermal efficiences and use of biof-uels Final Consumption Power generation Oil Refinery Coal Products Primary Energy

4. Incorporating energy conservations assumptions Energy Policy etc Efficiency Industrial Sector By Energy By Industry Main Production of Industry(Steel, Cement etc) Coal Transformation Efficiency Fuel Prices GDP Population Residential Sector By Energy Oil Refinery Efficiency Final Consumption Transformation (Fuel Input) Primary Energy Consumer Spending Household Commercial Sector By Energy Gas Processing Efficiency Power Generation(kWh) Nuclear 33% Hydro 100% Geothermal 10% Car Hold Transport Sector By Energy By Mode Nuclear Hydro Geothermal etc Other Activity Thermal Efficiency Fossil fuel Power

5. Incorporating energy conservations assumptions 【Final Consumption Sector】 Energy=f(GDP, Trend, Price)・・・・BAU Energy= f(GDP, Trend, Price)*(1-s）・・・・APS s: energy saving target ratio 【Transformation Sector】 Gross Electricity Generation = FEC + Loss & Own Use GEG by fossil fuel = GEG * Share of fossil fuel Fossil fuel input=GEG by fossil fuel/Efficiency・・・BAU Fossil fuel input= GEG by fossil fuel/(Efficiency*(1+e))・・・APS e: thermal efficiency improvement ratio

6. Application of the Assumptions • Result are calculated using the submitted assumptions • Missing assumptions are supplemented by the IEEJ. • Exceptions • Results for Australia are from ABARE’s outlook (2006). • Results for Japan are based on IEEJ’s outlook (2006), not by the government for the time being.

7. Economic and Energy Data • Energy Data: “Energy Balances” of the IEA • “Combustible Renewables and Waste” of the Non-OECD countries are not included • “Feedstock Use in Petrochemical Industry” is included in industry sector, not non-energy use sector. • Economic Data: “World Development Indicators” by the World Bank, etc.

8. Model • IEEJ Model • Applied to 12 countries: Econometric type models built by the IEEJ except for Australia, Cambodia, Lao PDR and Myanmar • Not Modeled • Australia: IEEJ used ABARE projections • LEAP Model: • Applied to Cambodia, Lao PDR and Myanmar • Regression software used to forecast final energy consumption

9. Definition of BAU and APS • BAU: • Natural trend: no assumption of additional efficiency improvement • The future intensity data submitted by the countries are not applied. • Future intensities are derived from model results. • APS: Depends on the submitted assumptions • If both BAU and APS intensities are submitted, the relative improvement from BAU to APS is applied • e.g. Korea submission: BAU 237 toe/million USD; APS 200 toe/million USD (16% decrease) • IEEJ result: BAU 222 toe/million USD; APS 187 toe/million USD (16% decrease)

10. TPES/GDP Intensity in 2030

11. Modeling CLM • Final Energy Consumption • Cambodia – trend extrapolation • Lao PDR and Myanmar – regression analysis • Major Variables: GDP, sectoral GDP, population and urbanization • Supply of Petroleum Products • Cambodia and Lao PDR: continue to import oil products • Myanmar: Refining capacity to increase in proportion to demand • Power Generation • Cambodia and Lao PDR – future power plants will be coal and hydro • Myanmar – exogenous hydro and the balance will be supplied by coal

12. Modeling CLM • LEAP Model • Accounting model – • With given demand equationsand exogenous variables, demand is estimated by the model • Sectoral energy saving goals entered as multipliers • Information on transformation processes are supplied which include configuration of electricity generation system and oil refining plants • Energy reserves are also supplied to the model if available • Produces energy balances as primary output • Other results such as electricity generation input and output, CO2 emissions, etc could also be extracted

13. Summary of ResultsEnergy Intensity vs GDP per Capita

14. Energy Intensity vs. GDP per CapitaLower Income Countries Thank you for your attention