Poorly designed stated preference (SP) studies are subject to a number of well-known biases, but many of these biases can be minimized when they are anticipated ex ante and accommodated in the studyfs design or during data analysis. We identify another source of potential bias, which we call scenario adjustment. where respondents assume that the substantive alternative(s) in an SP choice set, in their own particular case, will be different from what the survey instrument describes. We use an existing survey, developed to ascertain willingness to pay for private health-risk reduction programs, to demonstrate a strategy to control and correct for scenario adjustment in the estimation of willingness to pay. This strategy involves data from carefully worded follow-up questions, and ex post econometric controls, for each respondent's subjective departures from the intended choice scenario. Our research has important implications for the design of future SP surveys.
scenario adjustment scenario rejection stated preferences value of a statistical life mortality and morbidity risks microrisk reductions willingness to pay