Valuation of Biodiversity Benefits (OECD)

Satellite AccountsIn addition to the types of modifications of GDP discussed above, the United NationsStatistical Division recommends the development of a system of environmental satellite accounts, tomonitor environmental change:“Satellite Accounts try to integrate environmental data sets with existing nationalaccounts information, while maintaining SNA [System of National Accounts] conceptsand principles as far as possible. Environmental costs, benefits and natural resourceassets, as well as expenditures for environmental protection, are presented in flowaccounts and balance sheets in a consistent manner. That way, the accounting identities ofthe SNA are maintained. One of the values of the SEEA [System of Integrated Economicand Environmental Accounts] framework compared to more partial approaches is that itpermits balancing, so that rough monetary estimates can be made for residual categories[Hamilton and Lutz (1996)].”However, satellite accounts (by intent) represent a disaggregation of measures ofenvironmental change, rather than an aggregation. They could serve as inputs for developingoperational indicators of environmental change, but as an independent set of indicators they wouldsuffer from the same problem as the indicators that United States Environment Protection Agency’s(EPA) Environmental Monitoring and Assessment Program (EMAP) collects. This problem revolvesaround the large number of measures, which make the examination of trade-offs and overall trendsmore difficult. This is particularly true for biodiversity, as the number of individual species totals inthe tens of millions. However, these satellite accounts could serve as a basis of an aggregate measure,in which the individual variables categorised in the satellite accounts are aggregated into a moregeneral index.Aggregate IndicesThe EPA’s EMAP represents an effort to develop indicators of environmental quality.EMAP attempts to develop overall indicators for individual ecosystems (such as forests, wetlands orestuaries). In the case of estuaries, EMAP develops a series of over twenty indicators, but creates anaggregate index by summing the indicators based on water clarity, the benthic index, and the presenceof trash [Schimmel et al. (1994)]. This is indicative of a general procedure employed by naturalscientists to create aggregate indicators by summing all individual environmental indicators anddividing by the number of indicators to create an unweighted index. This unweighted index is virtuallymeaningless, because it implicitly and arbitrarily uses equal weights for each individual indicator. Forinstance, why should a 10% increase in the benthic index and a ten percent increase in the presence oftrash receive the same weight in the index? Additionally, there is a potential problem of the level ofthe index being a function of the choice of the unit for measurement of each of the individualvariables. For example, if one variable is measured in parts per million and another is measured inparts per billion, they will have very different impacts on the index. One way to get around thismeasurement problem is to normalise each variable by dividing by its maximum level, so that all thevariables are then numbers between zero and one.While normalisation solves the unit of measurement problem, it does not solve the problemassociated with an arbitrary choice of equal weights for each variable. One way of developing moremeaningful weights is to base them on expert opinion. This could be done through a Delphi process orthrough averaging the weights that each expert has assigned. While this is certainly an improvementover the arbitrary choice of equal weights, the following section outlines a more formal procedure for102