Exchanging Ideas on Climate
National Round Table on the Environment and the Economy
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Economic Instruments for Long-term Reductions in Energy-based Carbon Emissions

8. Case Study Scope, Boundaries and Methodologies

Several aspects of the scoping and boundary decisions made within the case studies were contentious:
  • Members of the EFR and Energy Task Force emphasized that the case studies are intended to portray an illustrative sequencing of technologies, not a comprehensive energy strategy. The technologies are understood to be part of a broader mix of supply sources and demand sectors, now and in the future. Other energy sources - nuclear energy and large-scale hydroelectricity, in particular - represent a substantial share of low-carbon energy sources, and fossil fuels will likely remain a significant source of primary energy into the foreseeable future.

  • Some participants were concerned that the use of the EcoLogo certification criteria in the emerging technologies case study would send the wrong signal regarding the renewability of large-scale hydro:

    - The EcoLogo criteria focus on "low impact" renewable energy, excluding most large-scale hydroelectricity, although this is a renewable energy source. "Low impact" hydro is defined by a number of criteria based on protection of indigenous species and habitat, requirements for head-pond water levels, water flows, water quality and several other factors. Theoretically, an installation of any size could meet this requirement, although the general threshold is approximately 10 to 20 MW. As well, the length of time that water is retained upstream from the installation should generally be less than 48 hours. (Note: the EcoLogo criteria also screen out some biomass facilities. For more detail, see Appendix B.)

    - Some hydroelectric utilities consider the EcoLogo exclusion of larger installations to be confusing and misleading. Moreover, it was pointed out that the federal government defines large-scale hydro as a renewable energy source.64 Fiscal instruments for emerging renewable power sources should therefore be complemented by other measures designed to support renewable sources at more mature stages of development, most notably large-scale hydro. Failure to do so would eliminate 90 percent of the current renewable electricity supply in Canada, as well as risking less displacement of fossil-fuel generation.

    - A related concern was that the EcoLogo, a voluntary ecolabelling program, is a marketing tool, not a regulatory standard; as such, it should not be used as the basis for fiscal instruments.

There was widespread agreement that large-scale hydro is complementary to many emerging renewable energies. Apart from geothermal energy, these resources are intermittent and require backup energy production capacity, such as that from hydroelectric reservoirs.

  • The solar industry and Natural Resources Canada originally wanted the emerging renewable electricity case study to include off-grid applications (e.g., ground-source heat pumps, solar hot water heaters and passive solar), which hold considerable promise in mitigating long-term carbon emissions. These technologies could not be addressed in the computer model that was used and, for that reason only, were excluded. Although certain modelling programs do exist for such technologies (i.e., the Renewable Energy Deployment Initiative, REDI), these technologies do not lend themselves to production-related fiscal measures. Off-grid technologies can contribute more to the displacement of existing generation (in ways that are sometimes difficult to measure) than to the actual generation of electricity.

  • One participant questioned the exclusive focus on hydrogen as an emerging fuel source for transportation. This person would have liked to have seen electric vehicles studied as well. The technology for electric vehicles was thought to be more commercially advanced than that for hydrogen vehicles and, in some regions of the country, to have a better energy balance.


The three case studies shared a similar analytical framework:

  • define a business-as-usual (BAU) evolution assuming no government intervention;

  • identify elements that offer an opportunity to alter development either in time or intensity;

  • identify barriers that prevent opportunities from being achieved;

  • define instruments that could overcome the barriers;

  • assess the economic and environmental efficiency and effectiveness of the potential instruments; and

  • have policy and technical experts review these modelling results, as well as validate and shape recommendations for economic instruments specific to each technology.

The hydrogen and renewable energy case studies model the period from 2010 to 2030. The energy efficiency case study models a slightly longer period from 2005 to 2030. It must be emphasized that this time horizon introduced sizable uncertainties into the technology development pathway and commodity prices, influencing the reliability of the results.

The work of the Analysis and Modelling Group of Canada's National Climate Change Process was used as a common baseline for calibrating assumptions to ensure consistency and comparability of results.65 The BAU scenarios used in these studies do not include any of the measures committed to under Action Plan 2000.

Each case study uses a different model to evaluate the possible impact of fiscal instruments on greenhouse gas emissions in the target sectors. The case studies also differ in terms of definitions of costs, levels of regional and sectoral detail, and the scope of feedback included in the analysis. For example, in evaluating the impact of different fiscal instruments, the energy efficiency case study considers non-price factors affecting the adoption of energy efficiency technologies. In contrast, the renewable energy case study assumes the penetration of renewable energy is related primarily to relative prices only (except in the case of a renewable portfolio standard, or RPS, which mandates a minimum level of production from renewables). Similarly, the energy efficiency case study includes limited assumptions about induced technological change (primarily in the form of a decline in technology costs with increasing market share), whereas the renewable energy case study includes the effects of policies on R&D decisions, and the effects of both R&D investments and cumulative experience on future renewable energy costs. For this reason, comparisons of per-tonne emission reduction costs between one study and another are not possible.

None of the case studies includes feedback from changes in aggregate demand, including trade impact, or structural changes in the national economy.

Table 1 provides a summary of key assumptions and outputs for each case study. Direct comparison was not easy because each study team reported inputs and outputs in very different ways (e.g., present values vs. annual averages; aggregate impacts vs. sectoral or regional impacts). This table represents a best interpretation of the results of each case study.

Table 1: Case Study Assumptions and Results

Hydrogen energy

(A) Fiscal instruments considered:
Only subsidies are considered. Two alternative fiscal packages are examined with different levels of subsidy in each:
- Producer tax credits or grants to lower the cost of hydrogen production by 10% or 25%
- Producer incentives as above together with consumer incentives to reduce the price of hydrogen vehicles and stationary fuel cells by 10% or 25%

(B) Estimated emission impacts (excluding macroeconomic feedbacks):
From an increase of 0.3 to a decrease of 1.2 Mt/year by 2030 (Note 1)

(C) Marginal cost of emission reductions in 2030:
~$800 to >$2,000/tonne (depending upon sub-sector)

(D) Total direct costs of instrument (excluding other feedbacks):
No estimate of total costs is provided but, assuming average reduction costs of $1,400/tonne, an estimated ~$1.6 billion in government subsidies per year will be required by 2030

(E) Price impact of instruments:
Use of subsidies results in no price increases for non-participants (Note 3)

(F) Consideration of non-price factors in the analysis:
Modelling framework considers non-price factors in estimating impact of subsidies on producer and consumer decisions

(G) Effects included:
Hydrogen production costs
Equipment purchases by producers and consumers
Hydrogen demand

(H) Effects excluded:
Incremental effects of policies on R&D activity
Effect of incremental R&D and/or penetration on rate of technology change
Indirect costs of government funds for subsidies
Possible changes in prices of fossil fuel generation (through technological change and changes in fossil fuel prices)

(I) Sectors directly affected:
Transportation, residential and commercial

(J) Regional impact:
Impacts modelled by region
Uptake is largest in Alberta, Ontario, B.C. and Saskatchewan

(K) Technology impact:
50% increase in hydrogen demand for transportation (43 to 67% increase in hydrogen-related vehicles) by 2030
472% increase in hydrogen demand for stationary fuel cells (230% increase in number of installed fuel cells)

Renewable energy

(A) Fiscal instruments considered:
Five alternative packages to achieve a 12%
reduction in emissions:
- Renewable portfolio standard (24%)
- Emission pricing ($10/tonne)
- Renewable subsidy ($0.006/kWh)
- R&D subsidy (61% of forecast base case R&D)
- Combined renewables and R&D subsidies

(B) Estimated emission impacts (excluding macroeconomic feedbacks):
Decrease of 9 to 24 Mt/year by 2030

(C) Marginal cost of emission reductions in 2030:
~$10 to $40/tonne (Note 2)

(D) Total direct costs of instrument (excluding other feedbacks):
Case study estimates net levelized welfare costs of $68 to $270 million/year, calculated as changes in consumer costs + changes in producer profits + changes in net government revenues. In the case of emission pricing, government revenues would equal ~$1 billion per year. In the case of subsidies, government expenditures would be $125 to $460 million/year.

(E) Price impact of instruments:
No price increases with subsidies.
Under emission pricing and RPS, national average electricity prices (delivered) increase 4.0 to 5.4% in 2015. Impact of RPS declines to 1.0% beyond 2015 as a result of R&D investments. (Note 4)

(F) Consideration of non-price factors in the analysis:
Modelling framework assumes all technologies/options are perfect substitutes with decisions based entirely on relative prices

(G) Effects included:
Uptake of renewables
In the case of emission pricing, fuel switching (coal to natural gas) is included
Demand feedbacks based on electricity price increases (aggregate elasticities)
R&D investment and subsequent reduction in technology costs
Reduction in technology costs associated with increased

(H) Effects excluded:
Electricity trade
Downstream impacts on output for individual sectors
Aggregate demand feedbacks
Indirect costs of government funds for subsidies and indirect benefits from revenue recycling of taxes

(I) Sectors directly affected:

(J) Regional impact:
Impacts modelled using aggregate national parameters

(K) Technology impact:
8 to 80% increase in renewable production
$22 to $172 million increase in annual R&D spending
13 to 26% reduction in renewable cost

Energy efficiency

(A) Fiscal instruments considered:
Three alternative instruments with two levels
of shadow cost ($15 and $30/tonne):
- Greenhouse gas tax
- Tradable permits (auctioned)
- Subsidies (grants, loans and tax incentives)

(B) Estimated emission impacts (excluding macroeconomic feedbacks):
Decrease of 46 to 58 Mt/year by 2030

(C) Marginal cost of emission reductions in 2030:
~$15 to $30/tonne

(D) Total direct costs of instrument (excluding other feedbacks):
In the case of emission taxes, government would raise $5 to $10 billion/year (after changes in greenhouse intensity). In the case of subsidies, government would spend $0.2 to $0.5 billion per year. This estimate assumes no free riders, which could increase costs as much as 85%. In both cases, these costs represent the cost of inducing changes in industry based on price and non-price considerations. In terms of real financial costs, industry will also save $1.9 to $2.7 billion per year in energy costs (net of capital investment).

(E) Price impact of instruments:
In case of subsidies, combined effects of subsidies and energy savings could actually lower prices in some sectors (by 0.1 to 9.0% depending upon the reduction scenario and sector). In the case of carbon taxes, prices could decline in some sectors (energy savings exceed cost of compliance) and increase in other sectors. Largest price impact occurs in industrial minerals, where additional costs exceed 5% of total value of output. The impact could be mitigated in part through revenue-recycling mechanisms.

(F) Consideration of non-price factors in the analysis:
Modelling framework considers non-price factors in estimating impact of instruments on producer decisions

(G) Effects included:
Investments in energy efficiency equipment in target sectors as well as reductions in upstream electricity emissions (through cogeneration)
Some reduction in technology costs incorporated with increased market shares

(H) Effects excluded:
Effects of policies on R&D activity
Effect of cumulative experience on technology costs
Sectoral demand feedbacks
Aggregate demand feedbacks
Indirect costs of government funds for subsidies and indirect benefits from revenue recycling of taxes

(I) Sectors directly affected:
Mining and manufacturing (indirect impacts on electricity sector through fuel substitution and cogeneration)

(J) Regional impact:
Impacts modelled by region but sub-regional impacts not reported separately

(K) Technology impact:
Encompasses a wide variety of technologies and processes; impact is diffus


1. Emissions may increase depending upon the source of hydrogen (e.g., SMR vs. electrolytic production).

2. The price instrument has the lowest unit cost. The other instruments are more costly on a unit cost basis. The higher value reflects the approximate cost of reductions under R&D subsidies.

3. For participants, the cost of hydrogen still exceeds the cost of gasoline and electricity. Uptake is driven by non-financial considerations. In theory, reduced demand for conventional fuels from participants could lower prices of conventional fuels for non-participants.

4. It is not entirely clear from the case study why the cost of electricity does not also decline under emission pricing with increased R&D expenditure.

Source: Trent Berry, "Macroeconomic Impacts of Fiscal Policy Promoting Long-term Decarbonization in Canada," Working paper prepared for the National Round Table on the Environment and the Economy (Vancouver: Compass Resource Management Ltd., August 2004).

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