The incorporation of subjective risks into choice experiments to test scenario adjustment
AbstractIn choice experiment (CE) applications, subjects are typically assumed to fully accept information given in the status quo (SQ) alternative, however, subjects might adjust such information on the basis of their subjective beliefs. This phenomenon is known as scenario adjustment. By using a CE field survey, we investigate whether subjects adjust risks portrayed in the SQ using their subjective estimates via a two-stage approach. In the first stage, subjective risks are elicited using the exchangeability method. In the second stage, two treatment groups are designed. In the first group, each subject is presented with a SQ which incorporates her/his own subjective risk estimate, and, hence, no adjustment is required. In the second group, each subject faces a SQ where the presented risk is not consistent with her/his own estimate, and, hence, a mental adjustment to the scenario might take place. Our modeling results suggest that subjects who are provided with a SQ in which the risk is lower than their own subjective estimates have a higher maximum willingness to pay (WTP) for a risk reduction than subjects provided with a SQ where the risk is consistent with their perceptions. Hence, in this case the scenario adjustment takes place. In contrast, subjects who are presented with a SQ where the risk is higher than their subjective estimates, overreact to the risk information, and have a higher WTP for the risk reduction than subjects who face a SQ where the presented risk is consistent with their perceived risks. Hence, in this case they appear to go along with the information in the SQ and abandon their subjective estimate
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Bibliographic InfoPaper provided by Italian Association of Agricultural and Applied Economics (AIEAA) in its series 2013 Second Congress, June 6-7, 2013, Parma, Italy with number 149894.
Date of creation: Jun 2013
Date of revision:
subjective risks; risk information; scenario adjustment; choice experiment; best-worst pivot design; Consumer/Household Economics; Demand and Price Analysis; C83; C93; D81; Q18;
Find related papers by JEL classification:
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
- C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy
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