Update on Market Simulation Group Modeling September 24, 2012 1
Forecasted BAU GHG Emissions Compared to the Allowance Cap Covered Entities Only 2013 - 2020 450 394.5 382.4 400 370.4 358.3 346.3 334.2 350 300 Millions CO2e 250 200 162.8 159.7 150 100 50 0 2013 2014 2015 2016 2017 2018 2019 2020 BAU Forecast (Phase 1&2 entities) BAU Forecast (Phase1 entities) AB32 Cap 2
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Supply of Abatement with Containment Reserve Allowance Price 50 40 Electricity Dispatch Changes; Industrial Processes Changes; Fuels Consumption Changes Offsets Costly Complementary Costless Reshuffling Measures Reshuffling 0 GHG Reductions
Factors in BAU modeling • Macroeconomic growth and fluctuations • Energy intensity trends and fluctuations • Complimentary policies – SB1368, LCFS, RPS, CAFE, Fed Policies/Incentives • Supply shocks: hydro-electricity, fuels, natural gas, OTC retirements 5
Electricity Sector • Reshuffling • Relabeling • Scope for dispatch changes 6
Industrial Sector • Output incentives under output-based updating – Removes elasticity that the sector would otherwise contribute to the abatement supply • Production efficiency incentives under output- based updating • Changes between compliance periods • Border adjustments instead of output-based updating? 7
Non-Industrial Natural Gas • Level and form of free allocation (fixed or indexed to something) to local distribution companies • Passthrough from LDCs to customers • Elasticity of demand (and cross-elasticity with other energy) 8
Tailpipe Emissions • Elasticity of personal and commercial transport with respect to fuel prices • Medium-run versus long-run elasticities 9
Offsets • Offset supply curve • Exogenous uncertainties on offset availability • Regulatory uncertainties on offset qualification 10
Other Modeling Issues • Intertemporal arbitrage over 8 years and 3 compliance periods • Discrete investments • Endgame issue in 2020 11
“Soft” Uncertainties may drive results • Willingness of importers to reshuffle • Offset protocols and barriers • Willingness to hold allowances for future – Confidence in the program – Incentives of regulated utilities • Regulatory incentives for GHG reduction – Eg, tariff design 12
Outcomes • Competitive market expected outcome and volatility – Scenarios with price near floor – Scenarios with price near $40 or higher • Potential for market power • Potential for market manipulation 13
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