Predicting versus testing: a conditional cross-forecasting accuracy measure for hypothetical bias
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A measure of hypothetical bias, or the divergence between stated and revealed preferences,
based on conditional cross-forecasting accuracy is suggested, based on out-ofsample
prediction accuracy when estimates from stated preference data are used in
place of those from actual choices, and vice versa. We describe an application of this
measure to assess hypothetical bias in the context of an inquiry into people’s willingness
to pay to avoid canola oil produced from genetically modified plants. The analysis
suggests the presence of groupwise hypothetical bias in these choice data.