Using respondents’ uncertainty scores to mitigate hypothetical bias in community-based health insurance studies

Community-based health insurance has been implemented in several developing countries to help the poor to gain access to adequate health-care services. Assessing what the poor are willing to pay is of paramount importance for policymaking. The contingent valuation method, which relies on a hypothetical market, is commonly used for this purpose. But the presence of the hypothetical bias that is most often inherent in this method tends to bias the estimates upward and compromises policymaking. This paper uses respondents’ uncertainty scores in an attempt to mitigate hypothetical bias in community-based health insurance in one rural setting in Cameroon. Uncertainty scores are often employed in single dichotomous choice surveys. An originality of the paper is to use such an approach in a double-bounded dichotomous choice survey. The results suggest that this instrument is effective at decreasing the mean WTP.