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We demonstrate that the set of cost distributions under which the optimal strategy for maximizing compliance (or more generally, effort) in a binary choice environment is identical to the optimal strategy for maximizing the accuracy of the reward (minimizing Type-I and Type-II errors) is finitely shy (Anderson and Zame (2001) in the space of all smooth parameterized real-valued distributions possessing full support on the real line. In words, this implies that maximizing compliance and maximizing accuracy “almost always” call for different incentive schemes.

生成讲解博客的中文版本

生成AI智能校验的中文版本