8.2 Impacts of Domestic Policies
Evaluation of the economic impacts of domestic mitigation policies can no longer
be made independently of the linkages between these policies and the international
framework. However, it is important to disentangle the mechanisms that are themselves
independent of the international regimes from those specifically driven by the
interplay between these regimes and domestic policies. In addition, the existence
of an international framework does not rule out the importance of domestic policies
for addressing the specific problems of each country.
This section basically relies on national studies, including integrated economic
regions such as the European Union (EU), but it also reports the results of
multiregional studies for the concerned countries or region.
Table 8.1: List of the models referred
to in this chapter |
|
Model |
Region
|
Reference
|
|
ABARE-GTEM |
USA/EU/Japan/CANZ
|
In Weyant, 1999
|
ADAM |
Denmark
|
Andersen et al., 1998
|
AIM |
USA/EU/Japan/CANZ
|
in: Weyant, 1999
|
Japan
|
Kainuma et al., 1999; Kainuma et al., 2000
|
China
|
Jiang et al., 1998
|
CETA |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
E3-ME |
UK/EU/World
|
Barker 1997, 1998a, 1998b, 1998c, 1999
|
ELEPHANT |
Denmark
|
Danish Economic Council, 1997; Hauch, 1999
|
ECOSMEC |
Denmark
|
Gørtz et al., 1999
|
ERIS |
|
Kypreos et al, 2000
|
G-Cubed |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
GEM-E3 |
EU
|
Capros et al., 1999cvv
|
GEM-E3 |
Sweden
|
Nilsson, 1999
|
GemWTrap |
France/World
|
Bernard and Vielle, 1999a, 1999b, 1999c
|
GESMEC |
Denmark
|
Frandsen et al., 1995
|
GRAPE |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
IMACLIM |
France
|
Hourcade et al., 2000a
|
IPSEP |
EU
|
Krause et al., 1999
|
ISTUM |
Canada
|
Jaccard et al., 1996; Bailie et al.,
1998
|
MARKAL |
World
|
Kypreos and Barreto, 1999
|
Canada
|
Loulou and Kanudia, 1998, 1999a and 1999b; Loulou
et al., 2000
|
Ontario (Canada)
|
Loulou and Lavigne, 1996
|
Quebec, Ontario, Alberta
|
Kanudia and Loulou, 1998b; Kanudia and Loulou, 1998a;
Loulou et al., 1998
|
Canada, USA, India
|
Kanudia and Loulou, 1998b
|
EU
|
Gielen, 1999; Seebregts et al., 1999a, 1999b;
Ybema et al., 1999
|
Italy
|
Contaldi and Tosato, 1999
|
Japan
|
Sato et al., 1999
|
India
|
Shukla, 1996
|
MARKAL-MACRO |
World
|
Kypreos, 1998
|
USA
|
Interagency Analytical Team, 1997
|
MARKAL-MATTER |
EU
|
Gielen et al., 1999b, 1999c
|
MARKAL and EFOM |
EU
|
Gielen et al., 1999a; Kram, 1999a. 1999b
|
Belgium, Germany, Netherlands, Switzerland
|
Bahn et al., 1998
|
Switzerland, Colombia
|
Bahn et al., 1999a
|
Denmark, Norway, Sweden
|
Larsson et al., 1998
|
Denmark, Norway, Sweden, Finland
|
Unger and Alm, 1999
|
MARKAL Stochastic |
Quebec
|
Kanudia and Loulou, 1998a
|
Netherlands
|
Ybema et al., 1998
|
Switzerland
|
Bahn et al., 1996
|
MEGERES |
France
|
Beaumais and Schubert, 1994
|
MERGE3 |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
MESSAGE |
World
|
Messner, 1995
|
MISO and IKARUS |
Germany
|
Jochem, 1998
|
MIT-EPPA |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
MobiDK |
Denmark
|
Jensen, 1998
|
MS-MRT |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
MSG |
Norway
|
Brendemoen and Vennemo, 1994
|
MSG-EE |
Norway
|
Glomsrød et al., 1992; Alfsen et al., 1995; Aasness et al., 1996; Johnsen et al., 1996
|
MSG-6 |
Norway
|
Bye, 2000
|
MSG and MODAG |
Norway
|
Aaserud, 1996
|
NEMS + E-E |
USA
|
Brown et al., 1998; Koomey et al., 1998;
Kydes, 1999
|
Oxford |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
POLES |
USA, Canada, FSU, Japan, EU,Australia, New Zealand
|
Criqui and Kouvaritakis, 1997; Criqui et al.,
1999
|
PRIMES |
Western Europe
|
Capros et al., 1999a
|
RICE |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
SGM |
USA/EU/Japan/CANZ
|
In: Weyant, 1999v
|
SPIT |
UK
|
Symons et al., 1994
|
SPIT |
Ireland
|
ODonoghue, 1997
|
WorldScan |
USA/EU/Japan/CANZ
|
In: Weyant, 1999
|
|
8.2.1 Gross Aggregated Expenditures in Greenhouse Gas Abatements
in Technology-rich Models
In technology-rich B-U models and approaches, the cost of mitigation is constructed
from the aggregation of technological and fuel costs. These include investments,
operation and maintenance costs, and fuel procurement, but also included (and
this is a recent trend) are revenues and costs from imports and exports, and
changes in consumer surplus that result from mitigation actions. In all the
studies, it is customary to report the mitigation cost as the incremental cost
of some policy scenario relative to that of a baseline scenario. The total cost
of mitigation is usually presented as a total net present value (NPV) using
a social discount rate selected exogenously (the NPV may be further transformed
into an annualized equivalent). Many (but not all) report also the marginal
cost of GHG abatement (in US$/tonne of CO2-equivalent), which is
the cost of the last tonne of GHG reduced. Chapter 7
discusses cost concepts and discount rates in more depth.
Current B-U analysis can be grouped in three categories:
- Engineering economics calculations performed technology-by-technology (Krause,
1995; LEAP (1995), Von Hippel and Granada (1993); UNEP, 1994a; Brown et al., 1998; Conniffe et al., 1997). The costs and reductions from
the large number of actions are aggregated into whole-economy totals in these
studies. Each technology (or other action on energy demand) is assessed independently
via an accounting of its costs and savings (investment costs, operational
and maintenance cost, fuel costs or savings, and emissions savings). Once
these elements are estimated, a unit cost (per tonne of GHG reduction) is
computed for each action. The unit costs are then sorted in ascending order,
and thus the actions are ordered from least expensive to the most expensive,
per tonne of abatement, to create a cost curve. This approach requires a very
careful examination of the interactions between the various actions on the
cost curve: it is often the case that the cost and GHG reduction attached
to an action depends on those of other actions in the same economy. Although
the simpler interactions are easily accounted for by careful analysis, there
exist many other instances in which complex, multi-measure interactions are
very difficult to evaluate without the help of a more complex model that captures
the systems effects. As an example, consider simultaneously: (a) changing
the mix of electricity generation, (b) increasing interprovincial trade of
electricity, and (c) implementing actions to conserve electricity in several
end-use sectors. As each of these three actions has an impact on the desirability
and penetration of each other action, such a combination requires many iterations
that assess the three types of action separately, before an accurate assessment
of the full portfolio can be obtained.
- Integrated partial equilibrium models that facilitate the integration of
multiple GHG reduction options and the aggregation of costs. To achieve this,
the majority of B-U studies use the whole energy system (MARKAL, MARKAL-MACRO,
MARKAL-MATTER, EFOM, MESSAGE, NEMS, PRIMES1).
These models have the advantage of simultaneously computing the prices of
energy and of end-use demand as an integral part of their routine. They are
based on least-cost algorithms and/or equilibrium computation routines similar
to those used in T-D approaches. They increasingly cover both the supply and
demand sides, and include mechanisms to make economic demands responsive to
the changing prices induced by carbon policies. Furthermore, many implementations
of these models are multiregional, and represent explicitly the trading of
energy forms and of some energy intensive materials.
- Simulations models (based on models such as ISTUM) that take into account
the behaviour of economic agents when different from pure least cost. To accomplish
this, economic agents (firms, consumers) are allowed to make investment decisions
that are not guided solely by technical costs, but also by considerations
of convenience, preference, and so on. Such models deviate from least-cost
ones, and so they tend to produce larger abatement costs than least-cost models,
all things being equal otherwise.
The boundaries between these three categories is somewhat blurred. For instance,
NEMS and PRIMES do include behavioural treatment of some sectors, and MARKAL
models use special penetration constraints to limit the penetration of new technologies
in those sectors in which resistance to change has been empirically observed.
Conversely, ISTUM has recently been enhanced to allow the iterative computation
of a partial equilibrium (the new model is named CIMS).
Several studies go further: they are based on partial equilibrium models in
which energy service demands are sensitive to prices. Therefore, even the quantities
of energy services may increase or decrease in carbon scenarios, relative to
the base case. For these models report not only the direct technical costs,
but also the loss or gain in consumer surplus because of altered demands for
energy services. The results of this new generation of partial equilibrium B-U
models tend to be closer than those of other B-U models to the results of the
general equilibrium T-D models, which are also discussed in this chapter. Loulou
and Kanudia (1999) argue that, by making demands endogenous in B-U models, most
of the side-effects of policy scenarios on the economy at large are captured.
When a partial equilibrium model is used, the cost reported is the net loss
of social surplus (NLSS), defined as the sum of losses of producers and consumers
surpluses (see Chapter 7).
As is apparent from the results presented below, considerable variations exist
in the reported costs of GHG abatement. Some of these differences result from
the inclusion/exclusion of certain types of cost in the studies (e.g., hidden
costs and welfare losses), others from the methodologies used to aggregate the
costs, others from the feedback between end-use demand and prices, and still
others from genuine differences between the energy systems of the countries
under study. However, the most significant cause of cost variations seems to
lie not only (see also Chapter 9) in methodological
differences, but in the differences in assumptions. Finally, although most recent
B-U results consider the abatement of a fairly complete basket of GHG emissions
from all energy-related sources, a few essentially focus on CO2 abatement
only and/or on selected sectors, such as power generation. In this chapter,
only results are reported that have sufficient scope to qualify as GHG abatement
costs in most or all sectors of an economy.
To facilitate the exposition of the various results, the rest of this subsection
is divided into four parts, as follows:
- studies that assume a large potential for efficiency gains, even in the
absence of a carbon price;
- other B-U studies for Annex I countries or regions;
- Annex I studies that account for trade effects; and
- studies devoted to non-Annex I countries.
|