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In this paper the authors examine the performance of theories of decision making under uncertainty/ambiguity from the perspective of their descriptive and predictive power, taking into account the relative parsimony of the various theories. To this end, they employ an innovative experimental design which enables one to reproduces ambiguity in the laboratory in a transparent and non-probabilistic way. They find that judging theories on the basis of their theoretical appeal, or on their ability to do well in testing contexts, is not the same as judging them on the basis of their explanatory and predictive power. They also find that the more elegant theoretical models do not perform as well as simple rules of thumb.
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