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arXiv 2103.00734econ.GNecon.THq-fin.EC
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福利与同意:论骚扰的最优惩罚

Welfare v. Consent: On the Optimal Penalty for Harassment

Ratul Das Chaudhury, Birendra Rai, Liang Choon Wang, Dyuti Banerjee

AI总结:

本文提出以促进合意、威慑非合意互动的同意方法替代社会福利最大化来确定骚扰的最优惩罚,并通过#MeToo启发模型表明其惩罚不可能为零。

摘要:

确定最优法律政策的经济学方法涉及最大化社会福利函数。我们提出一种替代方案:同意方法,旨在促进合意互动并威慑非合意互动。该同意方法不依赖于人际效用比较或关于偏好的价值判断。与福利方法相比,它不需要任何额外信息。我们利用一个受骚扰标志性案件和#MeToo运动启发的程式化模型,强调福利方法与同意方法之间的差异。在我们的模型中,福利方法下使社会福利最大化的骚扰惩罚可能为零,但在同意方法下则不可能为零。

英文摘要:

The economic approach to determine optimal legal policies involves maximizing a social welfare function. We propose an alternative: a consent-approach that seeks to promote consensual interactions and deter non-consensual interactions. The consent-approach does not rest upon inter-personal utility comparisons or value judgments about preferences. It does not require any additional information relative to the welfare-approach. We highlight the contrast between the welfare-approach and the consent-approach using a stylized model inspired by seminal cases of harassment and the #MeToo movement. The social welfare maximizing penalty for harassment in our model can be zero under the welfare-approach but not under the consent-approach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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