Adjusting and Calibrating Elicited Values Based on Follow-up Certainty Questions: A Meta-analysis

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Researchers have proposed many methods to reduce hypothetical bias (HB) in stated preference studies. One of the earliest and most popular is Certainty follow-up, in which the respondent states how sure they are of their response to the valuation question they just responded to. Certainty follow-up enables the use of several cutoffs to calibrate for HB, whereas the efficacy of other popular HB mitigation methods, such as Cheap Talk, have no such flexibility. Even given a cutoff level, its ability to reduce HB may vary with characteristics of the Certainty follow-up and of the study. Using a meta-analysis, we find that Certainty follow-up is more effective than Cheap Talk at adjusting for potential HB and that value elicitation method, mode of data collection, as well as whether other HB mitigation methods are used in a study could affect Certainty follow-up efficacy. Using and recoding Certainty follow-up questions quantitatively or qualitatively can be equally effective when compared to unadjusted hypothetical values where potential HB may occur or to values elicited with real binding conditions in which the actual magnitude of the HB is known. There is strong evidence that HB can be completely calibrated for or even overcorrected, but we encourage more Certainty follow-up studies with binding elicitations to fully explore the potential of this method.

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Environmental and Resource Economics

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