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The Missing Transfers: Estimating Misreporting in Dyadic Data

机译:丢失的传输:估计二进位数据中的错误报告

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摘要

Many studies have used self-reported dyadic data without exploiting the pattern of discordant answers. In this article we propose a maximum likelihood estimator that deals with misreporting in a systematic way. We illustrate the methodology using dyadic data on interhousehold transfers from the village of Nyakatoke in Tanzania. We show that not taking reporting bias into account leads to serious underestimation of the total amount of transfers between villagers. We also provide suggestive evidence that reporting bias can affect inference about estimated coefficients. The method introduced here is applicable whenever the researcher has two discordant measurements of the same dependent variable.
机译:许多研究使用了自我报告的二元数据,而没有利用不一致答案的模式。在本文中,我们提出了一种最大似然估计器,它以系统的方式处理错误报告。我们使用来自坦桑尼亚Nyakatoke村的家庭间转移的二元数据来说明该方法。我们表明,不考虑报告偏差会导致严重低估村民之间的转移总额。我们还提供了暗示性的证据,即报告偏差可能会影响有关估计系数的推论。只要研究人员对同一因变量进行两次不一致测量,此处介绍的方法就适用。

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