Understanding hypothetical bias: An enhanced meta-analysis

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© The Author(s) 2018. The presence of hypothetical bias (HB) associated with stated preference methods has garnered frequent attention in the broad literature trying to describe and understand human behavior, often seen in environmental valuation, marketing studies, transportation choices, medical research, and others. This study presents an updated meta-analysis to explore the source of HB and methods to mitigate it. While previous meta-analysis on this topic often involves a few dozen articles, this analysis includes 131 studies after reviewing over 500 published and unpublished articles. This enables the inclusion of several important factors that have not been investigated before. These include relatively recent willingness to pay elicitation methods such as choice experiments and the Turnbull lower bound estimator. Newly emerged HB reduction techniques such as consequentiality and certainty follow-up treatments are also included. For explanatory variables that have been examined in previous studies, this analysis does not always report consistent findings. In particular, holding everything constant and contrary to commonlyheld beliefs, the method of auction does not offer much reduction to HB compared to more conventional methods such as a referendum vote. However, choice experiment, cheap talk, consequentiality and certainty follow-up all significantly contributed to explaining and mitigating the magnitude of HB. These results help practitioners to understand HB's presence and choose appropriate methods for amelioration. The framework established through this study also enables future analyses targeted at understanding variations built upon one or multiple HB mitigation techniques.

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American Journal of Agricultural Economics

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