How to evaluate applicability and efficiency?
evaluation of the various approaches: A concept which concentrates on the reduction of risk may
lead to an increase in ignorance, and, while an economic concept may be efficient in the context
of risk, it can be inefficient when ignorance exists. In addition, it can be shown that the application
possibilities of the three concepts differ signifi- cantly. Combining the results of the efficiency and
applicability analysis, a trade-off can be derived between the possibility to precisely state whether
an economic concept is efficient and the scope of its applicability.
The taxonomy of environmental uncertainty is developed in Section 2.1, and what efficiency
means in the context of risk and ignorance is defined in Section 2.2. The following section pre-
sents the three different approaches and their assessment with respect to applicability and effi-
ciency. The final section summarises the main results and combines the analysis of efficiency and
applicability.
2. How to evaluate applicability and efficiency?
2
.
1
. A taxonomy of en6ironmental uncertainty The purpose of the taxonomy developed below
is to provide an assessment tool for the applicabil- ity of economic concepts that are targeted to-
wards environmental
uncertainty. For
other purposes, a taxonomy might well appear different,
such as the taxonomies in Siebert 1987, Faber and Proops 1993 and Faucheux and Froger
1995. In the taxonomy developed here, environ- mental uncertainty is classified according to three
different criteria.
The first criterion is the behaviour of emissions in the natural environment see also Siebert,
1987. Emissions may accumulate in the environ- ment before their damaging impact becomes visi-
ble. Environmental uncertainty which exists in combination with the accumulation of emissions
can be called ‘accumulation uncertainty’. Some emissions diffuse in the environment for a long
time before they unleash their harmful conse- quences. Environmental uncertainty that is com-
bined with diffusion over time can be called ‘diffusion uncertainty over time’. Environmental
uncertainty can also arise in connection with the diffusion of emissions over long distances. This
can be called ‘diffusion uncertainty in space’. It is also possible that none of these particularities
arises, but that uncertainty still exists about the causal relationship between an emission and the
damage it causes. This uncertainty can be called ‘damage uncertainty’. Even if the damage func-
tion of a certain emission is known, there might be uncertainty about its effects in combination
with other emissions on ecosystems, plants, ani- mals or human beings. This uncertainty can be
called ‘synergy uncertainty’.
The criterion for the second category of envi- ronmental uncertainty is the extent of knowledge
on the consequences of human intervention in nature see also Faber and Proops, 1993. Risk
exists when it is possible to attribute probabilities to various environmental damages that might oc-
cur. In a situation of ignorance, however, this is not possible. Consequently, an emission might be
unknown to be harmful. For example, ignorance existed with regard to CFC before it was discov-
ered that CFC destroys the ozone layer. The example of CFC shows that mankind can never
foresee all the damaging effects of an emission. In other words, ignorance exists in all human inter-
ventions in nature. Obviously, the division into ignorance and risk is too strict to allow all rele-
vant cases in the real world to be attributed to one of these subdivisions. The example of CFC
represents the extreme limit of a continuum be- tween ignorance and risk; it is more likely that
scientific knowledge will allow some speculation concerning the ways in which an emission might
be dangerous, and thus provide a starting point for scientific research. With the results of this
research, it might be possible to assign subjective probabilities to the different damage that may be
caused by the emission. Further research may lead to an increase in confidence in this estimation of
probabilities, i.e. expressed in the words of Ells- berg 1961 to a reduction in ‘ambiguity’. This
would suggest that a shift from ignorance to risk often takes place. Despite these qualifications, the
categories of risk and ignorance seem to offer a useful basis for the evaluation of different nuances
of environmental uncertainty that exist in reality.
Table 1 Types of environmental uncertainty
Classification criteria Different types of environmental uncertainty
Behaviour of emissions in the Damage uncer- Diffusion uncer-
Synergy uncer- Diffusion uncer-
Accumulation tainty in space
tainty uncertainty
tainty over time environment
tainty Risk
Extent of knowledge Ignorance
Uncertainty caused by the emissions Uncertainty caused by the emissions of a few polluters Number of polluters
of many polluters
The third category of environmental uncer- tainty is orientated towards the number of pol-
luters. In some cases, a high number of polluters contributes to an emission which has uncertain
effects on the environment. This uncertainty can be called ‘uncertainty caused by many polluters’.
In other cases, the emission stems only from one or a few polluters and can be termed ‘uncertainty
caused by a few polluters’. Table 1 contains an overview of the various types of environmental
uncertainty.
It should be noted that different forms of un- certainty can coexist. For example, a certain emis-
sion has damaging effects which are not yet known; the place of the emission and the place of
the damage are far apart, damage only occurs when the emission interacts with another emission
and the emission stems from many polluters. Thus we have ignorance, diffusion uncertainty in space,
synergy uncertainty and uncertainty caused by many polluters simultaneously.
2
.
2
. What abatement acti6ities are efficient in the context of en6ironmental uncertainty
?
The efficiency analysis focuses on the least cost implementation of abatement activities to comply
with a given emission standard Baumol and Oates, 1971. The standard setting-process itself is
therefore irrelevant in the context of this paper for different aspects of decision-making in a
world of environmental uncertainty, see Perrings, 1991; Drepper and Ma˚nsson, 1993; O’Hara, 1996;
Woodward and Bishop, 1997; Faucheux et al., 1998; Froger and Munda, 1998. It is assumed
that environmental uncertainty exists with respect not to the effects of the emission regulated by the
standard but to other emissions. Other emissions are important because a policy addressing one
emission often leads to the substitution of this emission by other emissions or, less frequently, to
the reduction of other emissions as well. The difference between settings of certainty, risk and
ignorance is that the policy-maker knows the harmful effects of these emissions in a world of
certainty, is informed about the probability distri- butions of their damage in a world of risk, and is
unaware of their harmful effects in a world of ignorance. In order to ascertain what constitutes
efficient abatement activities in the contexts of environmental certainty, risk and ignorance, the
conditions for the efficient abatement activities of polluters in the various contexts must be defined.
In a world of certainty, the efficient allocation of abatement activities is achieved when the net
marginal cost of reducing an emission is equalised across all activities see for this result any text-
book e.g. Baumol and Oates, 1988. It is impor- tant to note that we need not be concerned when
a polluter substitutes regulated emissions by other emissions which are not regulated. The policy-
maker is informed about the damage from all emissions and can regulate emissions, and thus
restrict substitution options, if he wishes to do so.
The situation is similar in a world of risk. Environmental policy should concentrate on emis-
sions whose probability of causing damage is known to be greater than zero. The reduction of
other emissions is undesirable, having no positive effects and perhaps causing additional expendi-
ture. The efficient allocation of abatement activi- ties is also achieved when the net marginal cost of
reducing an emission is equalised across all activi- ties. A possible substitution by the polluter of
regulated emissions by other emissions is again of no importance for the efficient allocation of
abatement activities. The policy-maker is in- formed about the probability distribution of dam-
age from all emissions and can regulate emissions accordingly.
The situation is different in a world of igno- rance. Here, we do not know whether emissions
are harmful, nor are we informed about the prob- ability distributions of damage. Therefore, envi-
ronmental policy should take all emissions into account as every emission has an unknown poten-
tial to cause harm. If environmental policy con- siders all potentially harmful emissions, two
questions arise: What potentially harmful emis- sions should preferably be reduced to decrease the
danger of environmental damage most effectively? And secondly, can the increase in one potentially
harmful emission be offset by reducing another potentially harmful emission? Unfortunately, no
satisfactory answer exists to the first question as there is no measurement which allows the danger
of two potentially harmful emissions in a world of ignorance to be compared. This makes it impossi-
ble to recommend the order in which different emissions should be reduced. The lack of mea-
surement also makes it impossible to assess whether the reduction of one emission can be
offset by increasing another. All we can say in a world of ignorance is that the danger of environ-
mental damage decreases when at least one emis- sion is reduced and no other emissions increase.
5
In a world of ignorance, the fact that every emission has an unknown potential to cause harm
is important for the efficiency analysis. However, it is impossible for a policy-maker to be able to
regulate all existing emissions. Therefore, by con- trast to the efficiency analysis in the world of
certainty and risk, it has to be taken into account that regulating one emission might have an im-
pact on the level of other emissions. More pre- cisely, it must be considered that a standard
governing an emission might lead to the substitu- tion of this emission by other potentially harmful
emissions — or, more favourably, to the reduc- tion of other emissions as well.
In order to see that these effects influence the efficiency of abatement activities, let us assume
for a moment that the marginal damage costs of potentially harmful emissions are known and can
be expressed in monetary terms. Then, the effi- ciency analysis must not only consider the differ-
ent marginal abatement costs to reduce the targeted emission, but also the marginal increases
or reductions in the damage costs caused by changes of other emissions. The least cost imple-
mentation of abatement activities is then achieved when the marginal costs of reducing the targeted
emission plus the additional marginal damage costs and the additional costs saving are equalised
across all activities. However, in a world of igno- rance, the different marginal damage costs of
potentially harmful emissions are unknown, and so we cannot tell whether abatement activities are
efficient. Yet the above reflections make clear that abatement activities that are efficient in a world of
certainty or risk might be inefficient in a world of ignorance.