requires that the expected value of income flows be non declining over time or in other words that
‘ expected future consumption should be at least as large as current consumption’ p. 521. If we
ignore uncertainty and use a deterministic income measure, we may make inaccurate conclusions
regarding sustainability. The reason being that there will be an inherent amount of variability in
income that results from risk.
Brekke 1997 compares the wealth-based in- come calculations described in his paper to other
approaches to measuring resource stock changes. The depreciation approach put forth by Repetto
et al. 1989 values the total change in stock in the current year at current prices. Brekke describes
why this approach is not consistent with the wealth approach. Another approach is El Serafy’s
user cost approach, which was derived to calcu- late the appropriate measure of income from non
renewable resource extraction. Brekke successfully argues that this approach is ‘a special case of the
wealth approach’ which assumes constant prices and production over time p. 523. In this paper,
we further illustrate the usefulness of the wealth approach when future risks to resource revenues
are significant. We also show how the deprecia- tion approach inadequately accounts for these
risks.
3. Importance of risk and uncertainty to forest income flows
Uncertainty and risk are associated with future income flows from forest resources. The uncer-
tainties associated with income generated from timber harvesting stem from uncertainty regard-
ing both future environmental and market condi- tions. Changes in environmental conditions can
alter the growth and characteristics of the timber stock and thereby influence commercial forestry,
recreational activity, biodiversity and other forest services. For example, the weather can influence
harvest costs and the amount harvested in a given year. Market conditions can also influence future
income flows from the forest. Timber flow and stock values can change in response to output
price fluctuations stimulated by factors such as consumer preferences, development of substitutes
and technological advancements. Many aspects of future conditions cannot be
anticipated, however, there are some parameters for which an equation or probability distribution
could be used to characterize movements over time. Fire risk, an environmental risk, and price
risk, a market-related risk, are examples. A num- ber of different fire risk models can be used to
attach a probability to the likelihood of a fire occurring in an area. It is expected that incorpo-
rating the distribution of fires over time in forest resource accounts will influence the volume of
timber harvested and the size of the timber stock in future periods, thereby affecting the value of
net income in future periods. The historical vari- ability in market prices, pulp and lumber prices in
this case, can also be used to obtain a reasonable estimate of the distribution that future prices are
likely to follow.
4. Case study
Haener and Adamowicz 1999 describe the development of a resource accounting framework
and the estimation of annual net income 1996 for a region of public forestland in northern Al-
berta. Rights to all deciduous and some conifer- ous
timber in
the region
are held
by Alberta-Pacific Forest Products, which produces
hardwood and softwood bleached kraft pulp. Rights to the coniferous timber in the region are
also held by several quotaholders and most of their harvest is distributed to sawmills in the
region for the production of lumber. The resource account concentrates on the forest goods and
services of most significance to the region. The resulting estimate of forest net income includes
the value of commercial forestry pulp and lumber production, produced capital depreciation and
timber capital appreciation, commercial fishing and trapping, recreational use camping, hunting,
fishing, traditional aboriginal land use, biodiver- sity maintenance and carbon sequestration. Using
the depreciation approach to calculate the value of timber stock changes in 1996, the study esti-
mates net income to be about 232 million in
1996. Commercial forestry comprises : 62 of the total. Refer to Haener and Adamowicz
1999 for a brief description of the region and discussion of the methods used to estimate net
income.
Haener and Adamowicz 1999 apply the ‘Green NNP’ approach but they do not consider
the influence of uncertainty on the measurement of regional net income. Fire and price risks were
identified as potentially important forms of risk in the case study region. If these forms of risk
are significant, the literature discussed in the pre- vious section suggests that the net income mea-
sure for the region should account for the influence of these forms of risk on future rev-
enue flows. Without these adjustments, the in- come measure will be inaccurate and use of the
index to assess sustainability may be inappropri- ate.
Formally adjusting the net income measure for the region requires re-formulating the model of
the economy to account for stochasticity. A stochastic differential equation, which character-
izes the influence of risk on future revenue flows, would have to be added to the problem. How-
ever, a number of other complicating factors would also have to be considered. Hartwick
1990 and Ma¨ler 1995 explain that only unan- ticipated or partially anticipated shocks to the
economy are relevant to current measures of wellbeing. Correctly anticipated changes have ‘al-
ready been capitalized in other prices and there- fore, already been included in the net national
income concept’ Ma¨ler, 1991, p. 13. Estimating contingent shadow prices could be complicated,
since it may be difficult to determine the degree to which current prices already reflect risk.
The practical question that must be addressed is whether it is enough to simply qualify our
interpretations of net income or whether the net income measure for the region should be for-
mally adjusted to account for risk. Simulation exercises such as the one carried out in this pa-
per, provide a practical alternative to re-formula- tion
of deterministic
welfare indices.
The simulation allows the significance of risk and its
expected influence on sustainable income to be assessed.
5. Simulations
