The Missing Transfers: Estimating Misreporting in Dyadic Data
提出一种最大似然估计方法，系统处理二元数据中的误报问题。利用坦桑尼亚村庄的家庭间转移数据，发现忽视报告偏差会严重低估转移总额，并可能影响系数推断。
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.