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

Hermann Donfouet, University of Rennes I
Pierre-Alexandre Mahieu, University of Nantes
Eric Malin, University of Rennes I

Community-based health insurance is being considered as an effective way to reach the poor people to access adequate health care services in developing countries. Assessing what the poor are willing to pay is of paramount importance for policy-making. The contingent valuation method, which relies on a hypothetical market, is commonly used for this purpose. But the presence of the hypothetical bias which is most often inherent in this method tends to bias the estimates upward, and compromises policy-making. This paper uses respondent 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 approach in a double-bounded dichotomous choice survey. The results suggest that this instrument is effective at decreasing the mean WTP.