A learning design for reducing hypothetical bias in the contingent valuation method

Over the last few years a great deal of research has focussed on hypothetical bias in value estimates obtained with the contingent valuation (CV) method and on means for ameliorating if not eliminating such bias. To date, efforts to eliminate hypothetical bias have relied on calibration techniques or on word-smithing of one kind or another to induce subjects to provide responses to hypothetical questions that mimic responses made by subjects facing actual payments in the valuation experiment. This paper introduces a different approach for eliminating hypothetical bias. A design for a CV survey format is presented which provides subjects with the opportunity to `learn' how the CV institution works. Sequential referenda are conducted where respondents gain experience in CV settings by participating in both hypothetical and real referenda. The logic of this Learning Design is a straightforward application of the trials process used in experimental economics. We demonstrate that the Learning Design is effective in eliminating hypothetical bias in surveys concerning donations to two different public goods.; Over the last few years a great deal of research has focussed on hypothetical bias in value estimates obtained with the contingent valuation (CV) method and on means for ameliorating if not eliminating such bias. To date, efforts to eliminate hypothetical bias have relied on calibration techniques or on word-smithing of one kind or another to induce subjects to provide responses to hypothetical questions that mimic responses made by subjects facing actual payments in the valuation experiment. This paper introduces a different approach for eliminating hypothetical bias. A design for a CV survey format is presented which provides subjects with the opportunity to 'learn' how the CV institution works. Sequential referenda are conducted where respondents gain experience in CV settings by participating in both hypothetical and real referends. The logic of this Learning Design is a straightforward application of the trials process used in experimental economics. We demonstrate that the Learning Design is effective in eliminating hypothetical bias in surveys concerning donations to two different public goods.