Value transfer in ecosystem accounting applications

Ecosystem accounting is a statistical framework that aims to track the state of ecosystems and ecosystem services, with periodic updates. This framework follows the statistical standard of the System of Environmental Economic Accounting Ecosystem Accounting (SEEA EA). SEEA EA is composed of physical ecosystem extent, condition and ecosystem service supply-use accounts and monetary ecosystem service and asset accounts. This paper focuses on the potential use of the “Value Transfer” (VT) valuation method to produce the monetary ecosystem service accounts, taking advantage of experience with rigorous benefit transfer methods that have been developed and tested over many years in environmental economics. Although benefit transfer methods have been developed primarily for welfare analysis, the underlying techniques and advantages are directly applicable to monetary exchange values required for ecosystem accounting. The compilation of regular accounts is about to become a key area of work for the National Statistical Offices worldwide as well as for the EU Member States in particular, due to the anticipated amendment to regulation on European environmental economic accounts introducing ecosystem accounts. On this basis, accounting practitioners have voiced their concerns in a global consultation during SEEA EA revision, about three issues in particular: the lack of resources, the need for guidelines and the challenge of periodically updating the accounts. We argue that VT can facilitate empirical applications that assess ecosystem services in monetary terms, especially at national scales and in situations with limited expertise and resources available. VT is a low-cost valuation approach in line with SEEA EA requirements able to provide periodic, rigorous and consistent estimates for use in accounts. While some methodological challenges remain, it is likely that VT can help to implement SEEA EA at scale and in time to respond to the pressing need to incorporate nature into mainstream decision-making processes