Abstract
Willingness to pay (WTP) for a health care program can be estimated in contingent valuation (CV) studies by a nonparametric approach. The nonparametric approach is free from distributional assumptions, which is a strength compared with parametric regression-based approaches. However, using a nonparametric approach it is not clear how to obtain confidence statements for WTP estimates, for example, when testing hypotheses regarding differences in mean WTP for different subsamples. The authors propose a procedure that allows statistical testing and confidence interval estimation by employing bootstrap techniques. The method is easy to implement and has low computational costs with modern personal computers. The method is applied to data from a CV study where the WTP for hormone replacement therapy was investigated. The mean WTP was estimated for the full sample and separately for women with mild and severe menopausal symptoms. Using the proposed method, the mean WTP was significantly higher in the group with severe symptoms.
Published Version
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