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我们应该如何对幸福水平和差异进行人际比较?福利经济学的一个分支避免进行这种比较,因为这种比较被认为是不可能的或不可知的;规范性评价基于帕累托或卡尔多-希克斯效率等标准,不需要人际间的可比性。福利经济学的另一个分支,例如最优税收理论,使用“社会福利函数”(SWFs)来比较社会状态和政府政策。个人间可比较的效用数字为主权财富基金提供了输入。但这种学术传统从来没有充分解释这些数字的基础。约翰·海萨尼在他关于所谓的“扩展偏好”的研究中提出了一个富有成果的观点。普通偏好是对结果的排序,而“扩展偏好”是对个人历史的排序。假设个体k对历史(x;I) / (y;j)的意思是:k倾向于在结果x中拥有个体i的属性,而不是在结果y中拥有个体j的属性。Harsanyi的建议是赋予个体“扩展偏好”;使用“扩展”效用函数来表示这些偏好;反过来,利用这些功能,作为幸福感水平和差异的人际比较的基础。然而,哈萨尼的分析存在各种差距和缺陷。在这篇文章中,我诊断了这些困难,并展示了如何补救它们——产生了一个可行的人际比较的描述,一个足以满足主权财富基金方法需求的描述。
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Harsanyi 2.0
How should we make interpersonal comparisons of well-being levels and differences? One branch of welfare economics eschews such comparisons, which are seen as impossible or unknowable; normative evaluation is based upon criteria such as Pareto or Kaldor-Hicks efficiency that require no interpersonal comparability. A different branch of welfare economics, for example optimal tax theory, uses “social welfare functions” (SWFs) to compare social states and governmental policies. Interpersonally comparable utility numbers provide the input for SWFs. But this scholarly tradition has never adequately explained the basis for these numbers.John Harsanyi, in his work on so-called “extended preferences,” advanced a fruitful idea. While an ordinary preference is a ranking of outcomes, an “extended preference” is a ranking of individual histories. To say that individual k has an extended preference for history (x; i) over (y; j) means something like the following: k prefers to have the attributes of individual i in outcome x, as opposed to having the attributes of individual j in outcome y. Harsanyi’s proposal was to endow individuals with “extended preferences”; to represent such preferences using “extended” utility functions; and to employ such functions, in turn, as the basis for interpersonal comparisons of well-being levels and differences.Harsanyi’s analysis, however, had various gaps and flaws. In this Article, I both diagnose these difficulties, and show how they can be remedied - yielding a viable account of interpersonal comparisons, one sufficient for the needs of the SWF approach.
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