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

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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.

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Notes

  1. Kramer and Mercer (1997) refer to a 1995 working paper version of Carson (1998).

  2. Converted to 2012 PPP-€ using the standard procedure of adjusting with the US Consumer Price Index to 2012- US $ (a 64% increase) and using the purchase power parity (PPP)-corrected exchange rate between US $ and euros for the EU-28 countries in 2012 (0.756 from; http://www.oecd.org/std/purchasingpowerparitiespppsdata.htm) in order to make the results comparable to our Delphi CV survey, which was conducted in 2012.

  3. Converted to 2012 PPP-€ using the standard procedure of adjusting with the UK Consumer Price Index to UK 2012-£ (a 46% increase) and using the purchase power parity (PPP)-corrected exchange rate between UK £ and euros for the EU-28 countries in 2012 (1.087; calculated from http://www.oecd.org/std/purchasingpowerparitiespppsdata.htm) in order to make the results comparable to our Delphi CV survey, which was conducted in 2012. Note, however, that the strict assumption of this standard procedure for temporal benefit transfer, i.e. that people’s WTP for this public good has increased at the same rate as the CPI (for private goods), might not hold (Navrud and Ready 2007).

  4. Note that Horton et al. (2002, 2003) asked about WTP for preserving the Brazilian part of the Amazon only. 40% of the Amazon rainforest is found outside of Brazil, in 8 different countries.

  5. See e.g. Tol (2005, 2008) for meta-analyses of Social Costs of Carbon (SCC) estimates.

  6. See Mitchell and Carson (1989), Carson et al. (2001), and Carson (2011), for presentations of the CV method. The latter reference contains a comprehensive bibliography. See Carson (1998) for a more specific discussion of CV in the context of rainforest valuation.

  7. For representative CE studies see Adamowicz et al. (1998), Hanley et al. (1998), and Louviere et al. (2000). Among prominent, more specific and recent, applications to environmental and resource economics, are Bennett and Blamey (2001), Bateman (2002), Holmes and Adamowicz (2003), Rolfe and Bennett (2006), and Bennett and Birol (2010). Note also that Carson and Louviere (2011) in their attempt to develop a common nomenclature for SP methods argue that the distinction between CE and CV is odd as the original meaning of CV was using a survey approach to place an economic value on marginal changes in public goods, and thus encompassing what we currently term Choice Experiments.

  8. Comparative studies of internet surveys and traditional survey modes like face-to-face interviews and mail surveys indicate that internet surveys could perform just as well; especially in countries with high internet penetration and using panels of households recruited for internet surveys by professional survey firms (Lindhjem and Navrud 2011a, b). However, in countries with low internet penetration, internet surveys would have to be replaced or supplemented by the traditional surveys modes of face-to-face interviews or mail in order to secure a representative sample.

  9. For the European WTP estimate, the experts were told to assume that each European household should be given equal weight. Information of the approximate percentage of the European population in the different European countries was provided: Germany 15% , France 12%, UK 12 %, Italy 11%, Spain 9%, Poland 7%, Romania 4%, Netherlands 3%; 2% each for Austria , Belgium, Czech Republic, Greece, Hungary, Portugal and Sweden;, 1% each for Bosnia, Croatia, Denmark, Finland, Ireland, Norway, Serbia, Slovakia, Switzerland, and the Baltic states taken together (Estonia, Latvia and Lithuania). Albania, Cyprus, Iceland, Kosovo, Luxemburg, Macedonia, Malta, Montenegro, Slovenia and other countries made up the remaining 3% of the European population.

  10. The complete questionnaire for Rounds 1 and 2 can be found in Navrud and Strand (2013; Appendices 1 and 2).

  11. The same four estimates were then requested for Plan B.

  12. These differences might be due to experts being more pessimistic with respect to aggregate European WTP than to own-country WTP; but in part also follow from differences in methods of (implicit and explicit) aggregation across European countries by experts themselves; and the fact that countries with high WTP (and income) levels are likely overrepresented among experts.

  13. Eliminating one variable of every pair of variables having a higher correlation (r) than 0.3, as a rule of thumb.

  14. We also ran linear regressions, but these had in general fewer significant variables and lower explanatory power.

  15. Note that we are presenting both “raw” (with only per-capita national income included) and “corrected” calculations (which include a number of relevant background variables some of which are significant; see Table 7).

  16. See Navrud and Strand (2013; Appendix 3) for a formal presentation of this argument.

  17. Using a PPP-corrected exchange rate of 1 US $ =0.92 € (http://stats.oecd.org/Index.aspx?DataSetCode=CPL).

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Authors and Affiliations

  1. School of Economics and Business, Norwegian University of Life Sciences, P.O. Box 5003, 1432, Ås, Norway

    Ståle Navrud

  2. Development Research Group, Environment and Energy Team, The World Bank, 1818 h Street, NW Washington, DC, 20433, USA

    Jon Strand

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  1. Ståle Navrud
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  2. Jon Strand
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Correspondence to Ståle Navrud.

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Navrud, S., Strand, J. Valuing Global Ecosystem Services: What Do European Experts Say? Applying the Delphi Method to Contingent Valuation of the Amazon Rainforest. Environ Resource Econ 70, 249–269 (2018). https://doi.org/10.1007/s10640-017-0119-6

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