Predicting versus testing: A conditional cross-forecasting accuracy measure for hypothetical bias

Abstract

A measure of hypothetical bias, or the divergence between stated and revealed preferences, based on conditional cross-forecasting accuracy is suggested, based on out-of-sample 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. © 2011 The Authors. AJARE © 2011 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd.