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Testing Hurwicz Expected Utility
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DOI：10.3982/ECTA19221.png)
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Gul and Pesendorfer (2015) propose a promising theory of decision under uncertainty, they dub Hurwicz expected utility (HEU). HEU is a special case of & alpha;-maxmin EU that allows for preferences over sources of uncertainty. It is consistent with most of the available empirical evidence on decision under risk and uncertainty. We show that HEU is also tractable and can readily be measured and tested. We do this by deriving a new two-parameter functional form for the probability weighting function, which fits our data well and which offers a clean separation between ambiguity perception and ambiguity aversion. In two experiments, we find support for HEU's predictions that ambiguity aversion is constant across sources of uncertainty and that ambiguity aversion and first order risk aversion are positively correlated.
Keyword:
Hurwicz expected utility
probability weighting functions
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