Climate Policies and Induced Technological Change: The Impacts of Timing of Technology Subsidies

1. Climate Policies and Induced Technological Change:The Impacts of Timing of Technology Subsidies Knut Einar Rosendahl Research Department, Statistics Norway Presentation at International Energy Workshop, Paris, June 2004 based on paper with Snorre Kverndokk and Thomas F. Rutherford

2. Introduction • Technological development • is crucial to reach long-term climate goals • is not autonomous, but partly induced by market incentives and policy measures • is characterised by market failures (spillovers) • Optimal climate policy • may involve both carrot (subsidies) and stick (taxes) • has an important time dimension • requires lots of information, e.g. about the future • Three questions: • How should the optimal technology subsidy evolve over time? • What are the costs of simpler policy rules? • Under what conditions can lock-in of the wrong technology become important?

3. Some relevant literature: • Wigley et al. (1996): Timing of abatement without ITC • Goulder and Mathai (2000); Manne and Richels (2002); Rosendahl (2004): Timing of abatement and carbon taxes with R&D or LBD • Kverndokk et al. (2004): Optimal combination of carbon taxes and subsidies within a static framework • Redding (2002): Model with endogenous innovation, path-dependence and technological lock-in • Carbon-free energy technologies • Today: • Various costly, inflexible technologies • Future: • ?? • Depends on learning potential for existing technologies • Depends on development of new technologies • Lock-in of suboptimal technologies?

4. Stylised dynamic equilibrium model • Intertemporal welfare optimisation with representative consumer • Consumes electricity and other goods • Fixed present value of income • Deterministic model – uncertainty disregarded • 3 electric energy technologies: • Defender (DEF): Fossil fuel based technology. No LBD. • Challenger (CHL): Existing carbon-free technology. High costs. LBD. • Advanced (ADV): Future carbon-free technology – available at a pre-specified year. Low costs. LBD. • Producers maximise intertemporal profits

5. Learning by doing (LBD) • Production of carbon-free energy gives experience, and reduces unit costs • LBD is assumed to be either internal or external to the firm (i.e., spillovers) • Technology constraints • Expansion and contraction constraints prevent too rapid changes in the energy mix (internalised) • Climate restriction • Affects only emissions from electricity production • Constraint on cumulative carbon emissions until 2200 • Policy measures: • Carbon taxes and subsidies on carbon-free energy

6. Alternative scenarios are simulated for various technology assumptions: • No governmental intervention (baseline) • carbon externality not internalised (no spillovers of LBD) • Optimal climate policy • all externalities are internalised – optimal subsidy rate of CHL • Suboptimal policy w.r.t. CHL (existing carbon-free energy) • constant subsidy rates over time (2000-2060) • carbon tax optimally chosen • Delayed carbon tax until 2020 • Focus on main scenario:

7. Energy supply in baseline scenario

8. Energy supply with optimal abatement

9. Unit costs with optimal abatement

10. Subsidy rates on CHL in alternative scenarios

11. Alternative technology assumptions • Introduction year of ADV • Later introduction: Same time profile of optimal CHL subsidy • Earlier introduction: Possibly no use of CHL • Unit cost of ADV • Higher initial or min. cost: Same profile of optimal CHL subsidy – possibly no use of ADV • Unit cost of CHL • Higher min. cost: Lower init. subsidy rate – falls more steeply • Lower learning exp.: Lower init. subsidy rate – falls less steeply • Tighter CO2 restriction • CHL adopted earlier – same time profile of subsidy rate • Summing up: • Optimal CHL subsidy rate should fall over time – time profile determined by learning prospects of this technology

12. Energy price impacts in alternative scenarios

13. Economic costs of alternative scenarios

14. Technological lock-in: Picking the right winner… • Can subsidies to CHL prevent introduction of ADV? • assuming spillovers but no subsidies of ADV • No need for subsidies in the main scenario for ADV to enter the market • Higher init. cost (+25%) of ADV: • Lock-in of DEF/CHL instead of ADV – small welfare costs • Higher init. cost (+50%), lower min.cost (-33%) and earlier introduction (-20 yrs) of ADV; higher min.cost (+33%) of CHL; and tighter climate restriction (-20%): • Optimal climate scenario: Wait for ADV technology • Internalisation of CHL only: Lock-in of CHL – significant welfare costs • No subsidies to either ADV nor CHL: Almost optimal solution

15. Conclusions • Learning spillovers imply that a combination of carbon taxes and subsidies is optimal • Optimal subsidy rate varies significantly over time • Highest initially • Depends mainly on learning characteristics of the technology • Constant subsidy rate increases abatement costs only slightly • Insignificant difference when subsidy rate is close to average optimal rate • Subsidies to existing technologies may lead to technological lock-in • Relevant if learning potential of new technology is large • Internalising spillovers of existing technology may be suboptimal • Uncertainty about future technological development • Stochastic framework preferable