Title:
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Probabilities, delays and social distances : decision-making in different domains
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I start the thesis with a focusing model in which increasing the range of values of an attribute makes the decision-maker place more weight on this attribute. This model explains the documented communality between risky choice and intertemporal choice, and provides a unique explanation to the common ratio, common delay, and magnitude effects. It also captures preference reversals between choice and valuation, and different forms of context dependence such as the asymmetric dominance effect. Since the model is not restricted to probabilities and temporal delays, I also apply it to allocations characterised by an amount of money and a social distance. It predicts ‘common social distance’ effects, magnitude effects in the social domain, and preference reversals between choice and valuation of allocations. I look for these social preference reversals in the second Chapter. I invite student subjects in the laboratory and isolate the effect of the social distance by comparing weak social distances, with allocations benefiting students in other Faculties, to strong social distances, where the allocations benefit widely different charities. Social distances are measured with tools developed in social psychology. I find preference reversals only with weak social distances, where subjects do not take into account social distances when they form a valuation. When social distances become stronger with the charities, subjects take social distances into account for both choice and valuation and preference reversals disappear. These results confirm that social preference reversals exist and that social distances are a relevant attribute. Finally, in the last Chapter, I test the main assumption of the model in the context of the asymmetric dominance effect. I replicate the effect but find it to be smaller than previously thought. Especially, it disappears when targeting risky low-probability, high-payoff gambles. There is also evidence of a range effect, which verifies the assumption of the model presented in the first Chapter.
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