Ann likes oranges much more than apples; Bob likes apples much more than oranges. Tomorrow they will receive one fruit that will be an orange or an apple with equal probability. Giving one half to each agent is fair for each realization of the fruit. However, agreeing that whatever fruit appears will go to the agent who likes it more gives a higher expected utility to each agent and is fair in the average sense: in expectation, each agent prefers his allocation to the equal division of the fruit, i.e., he gets a fair share. We turn this familiar observation into an economic design problem: upon drawing a random object (the fruit), we learn the realized utility of each agent and can compare it to the mean of his distribution of utilities; no other statistical information about the distribution is available. We fully characterize the division rules using only this sparse information in the most efficient possible way, while giving everyone a fair share. Although the probability distribution of individual utilities is arbitrary and mostly unknown to the manager, these rules perform in the same range as the best rule when the manager has full access to this distribution.
翻译:安比苹果更喜欢橘子; 鲍伯喜欢苹果, 比橘子多得多。 明天他们会收到一种果实, 一种橙子或苹果, 其概率相同。 给每个代理商一半的水果对每个水果的实现都是公平的。 但是, 同意不管果子出现给哪个代理商, 谁更喜欢它给每个代理商带来更高的预期效用, 并且从一般意义上讲是公平的: 每个代理商都希望他分配到水果的平等部分, 也就是说, 他得到一个公平的份额。 我们把这个熟悉的观察结果变成一个经济设计问题: 在随机绘制一个对象( 水果) 时, 我们学习每个代理商已经实现的效用, 并且可以将它与公用事业分配的平均值进行比较; 没有其它关于分配的统计信息。 我们完全使用这种稀少的信息来描述分工规则, 以尽可能有效的方式向所有人提供公平的份额。 尽管单个公用事业的概率分配是任意的, 并且对于经理来说大多是未知的。 当经理完全有机会使用这种分配时, 这些规则在相同的范围内执行。