Valuing Global Ecosystem Services: What Do European Experts Say? Applying the Delphi Method to Contingent Valuation of the Amazon Rainforest

Stale Navrud and Jon Strand

Environmental & Resource Economics, 2018, vol. 70, issue 1, No 11, 249-269

Abstract: Abstract Valuing global public goods like the Amazon rainforest by stated preference surveys of a representative sample of the global population would be very costly and time consuming. We explore the use of the Delphi Method in contingent valuation (CV) by asking a panel of 49 European environmental valuation experts in two rounds what they think would be the result if a European CV survey of Amazon Rainforest protection plans was conducted. The experts’ best guess for the mean willingness-to-pay (WTP) by European households for preserving the current Amazon Rainforest, and thus avoiding a predicted loss in forest area by 2050 from currently 85% to 60% of the original forest in the 1970s, was 28 € per household annually as an additional income tax. Aggregated over all European households this amounts to about 8.4 billion € annually. This preliminary estimate indicate that WTP of distant beneficiaries is substantial, and could justify preservation of global ecosystem services where aggregated benefits of the local population often do not exceed the opportunity costs of preservation in terms of lost income from commercial activities. The income elasticity of WTP with respect to per-capita income in the European countries is 0.5–0.6. Recognizing the limitations and assumptions of the Delphi CV method, it could still be a time saving and cost-effective benefit transfer tool for providing international donors with much needed order-of-magnitude estimates of the non-use value of ecosystem services of global significance.

Keywords: Delphi method; Stated preference; Contingent valuation; Global public goods; Amazon rainforest; Ecosystem services; Non-use value; Benefit transfer (search for similar items in EconPapers)
JEL-codes: Q23 Q51 Q57 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10640-017-0119-6

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