RECURSIVE AMBIGUITY AND MACHINA'S EXAMPLES
Machina列举了Choquet期望效用等模型无法捕捉的模糊态度情形，本文证明Segal的递归非期望效用模型能统一处理这些涉及三个或更多结果的选择问题。
Machina ( American Economic Review 99 (2009), 385–392; American Economic Review 104 (2014), 3814–40) lists a number of situations where Choquet expected utility, as well as other known models of ambiguity aversion, cannot capture plausible features of ambiguity attitudes. Most of these problems arise in choice over prospects involving three or more outcomes. We show that the recursive nonexpected utility model of Segal ( International Economic Review 28 (1987), 175–202) is rich enough to accommodate all these situations and, moreover, that this can be done using the same functional form for all situations.