In the contingent valuation literature, both anchoring and acquiescence biases pose problems when using an iterative bidding game to infer willingness to pay. Anchoring bias occurs when the willingness to pay estimate is sensitive to the initially presented starting value. Acquiescence bias occurs when survey respondents exhibit a tendency to answer 'yes' to questions, regardless of their true preferences. More generally, whenever a survey format is used and not all of those contacted participate, selection bias raises concerns about the representativeness of the sample. In this paper, we estimate students' willingness to pay for student health care at Stanford University while accounting for all of these biases. As there is no cost sharing for students, we assess willingness to pay by having a random sample of students play an online iterative bidding game. Our main results are that (1) demand for student health care is elastic by conventional standards; (2) ignoring anchoring bias would lead to a substantially biased measure of the demand elasticity; (3) there is evidence for acquiescence bias in student answers to the opening question of the iterative bidding game and failure to address this leads to the biased conclusion that demand is inelastic; and (4) standard selection correction methods indicate no bias from selective non-response and newer bounding methods support this conclusion of elastic demand.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
13865.
Length: Date of creation: Mar 2008 Date of revision: Handle: RePEc:nbr:nberwo:13865
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Find related papers by JEL classification: C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data C9 - Mathematical and Quantitative Methods - - Design of Experiments I1 - Health, Education, and Welfare - - Health
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