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arXiv 2401.06264econ.EMstat.ME
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暴露效应并非自动对政策制定有用

Exposure effects are not automatically useful for policymaking

Eric Auerbach, Jonathan Auerbach, Max Tabord-Meehan

AI总结:

本文回应 Savje(2023)关于用误设定暴露效应避免干扰强假设的建议,指出缺乏强假设时暴露效应通常无法有效评估社会政策。

摘要:

我们感谢 Savje(2023)撰写了一篇发人深省的文章,并感谢有机会以社会科学研究者的身份分享我们的观点。在其文章中,Savje 建议将误设定的暴露效应作为一种方法,以在分析实验结果时避免对干扰做出强假设。在这篇受邀讨论中,我们指出 Savje 建议的一个局限:在没有 Savje 试图避免的强假设的情况下,暴露效应通常无助于评估社会政策。

英文摘要:

We thank Savje (2023) for a thought-provoking article and appreciate the opportunity to share our perspective as social scientists. In his article, Savje recommends misspecified exposure effects as a way to avoid strong assumptions about interference when analyzing the results of an experiment. In this invited discussion, we highlight a limiation of Savje's recommendation: exposure effects are not generally useful for evaluating social policies without the strong assumptions that Savje seeks to avoid.

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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