Contingent Valuation Design and Data Treatment: If You Can't Shoot the Messenger, Change the Message

The contingent valuation method has become an established and major part of the toolbox used to produce monetary values for evaluating environmental changes. It has been used to inform everything from the value of ecosystem services to cultural heritage to loss of life. The method has been highly controversial at various stages but despite this, or perhaps due to the publicity, it has grown in scope and scale. Numerous occurrences of ‘bias’ and ‘anomalies’ in results have been addressed by improved design, so providing guidance on perfected approaches to making sure respondents reveal preferences in accord with theoretical expectations. That respondents may not wish to and often fail to conform is seen as a challenge for the design team to be more ingenious with their incentive mechanisms which get respondents to act ‘rationally’. Failing this, data can be classified and treated to derive ‘conservative’ results. I document in this paper how whole areas of evidence from contingent valuation have been removed from consideration by design, with respondents expected to conform to an idealised rational agent model or to suffer branding and exclusion as having the ‘wrong motives’. While the method is then susceptible to manipulation (eg to meet sponsors' requirements), if used more scientifically it also holds the potential to reveal fundamental flaws in economic theory and ways to advance that same theory.